Sub-Region Population Health Profiles

Transcription

1 Sub-Region Population Health Profiles Technical Report October 2017 (Last update: April 2018) 1 P a g e

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3 Acknowledgements This report is the product of a collaboration among the LHIN (1), Public Health (2), Ontario Health Unit (3), The Hospital (4), The Royal (5), Renfrew County and District Health Unit (6), Lanark, Leeds and Grenville Health Unit (7), Parent Resource Centre, (8), and Cancer Care Ontario (9). The following people contributed substantially to the development of this report (in alphabetical order): Amira Ali (2), Juhee Anderson (1), Kevin Barclay (1), Leah Bartlett (1), Andrew Bonner (4), Kelly Bradley (1), Mitsi Cardinal (5), John Cunningham (7), James Fahey (1), Amber Kayed (1), Allison Lampi (1), Bruce Libman (1), Cameron McDermaid (2), Catherine Millar (8), Peggy Patterson (6), Karen Patzer (1), Katherine Russell (2), Brian Schnarch (1), Darlene Rose (1), Dr. Frank Shi (3), Louise Simmons (3), Dara Spatz Friedman (2), and Jamie Stevens (1). 3 P a g e

4 Updates and Corrections Date Change Section Nov 24, 2017 Nov 24, 2017 Updated % of population 19 and under and % of population 65 and over by sub-region, replacing 2011 with 2016 data. Corrected rates of readmissions for certain conditions by neighbourhood socioeconomic and social support quintiles. Feb 28, 2018 Updated historical population growth rates, replacing to-2011 with 2011-to-2016 data. Feb 28, 2018 Feb 28, 2018 Apr 24, 2018 Minor corrections to estimated number of people with mental health and addictions conditions in Central and Corrected rates of Emergency Department Visits for Opioid Related Harm for all sub-regions, added value for Ontario Corrected rates of Hospitalizations for Intentional Self- Harm. Table 2.1 and Appendix B Figure 5.5 Table 2.1 and appendix B. Table Table 3.27 and appendix B Table 3.26 and appendix B 4 P a g e

5 Table of Contents Executive Summary 6 Abbreviations 11 Glossary Introduction Population Characteristics Population Health Status 31 General Health 31 Risk Factors 32 Chronic Disease in the Sub Regions 36 Cancer Rates 44 Infectious Diseases 46 Injury 48 Mortality 50 Mental Health and Addictions Health Service Provider Distribution and Capacity System Performance LHIN 68 Primary Care System Performance 68 Hospital and Cross-Sector System Performance 75 Home and Community Care System Performance 80 Mental Health and Addictions 85 5 P a g e

6 References 86 Appendix A: Sub-Region Summaries 94 Appendix B: At a Glance Comparison of Sub-Regions vs. Average 100 Executive Summary On December 7, 2016, the Patient s First Act was legislated by the Ontario Government. The Ontario government and the LHIN are committed to working with stakeholders to transform our health care system into one that puts the needs of patients at its centre. Our mission to build a coordinated, integrated, and accountable health system for people where and when they need it requires an approach that reflects the needs of local residents. The establishment of five sub-regions by the LHIN will serve as the foundation for future health system improvement. A They are areas that will serve as the focal point for local health system planning, as well as strengthening service integration and coordination in the region. Sub-regions will not create barriers to where people access care. They are, simply, a better way to plan and improve health services by increasing the focus on local strengths, needs, and challenges. A sub-region approach is expected to help improve health equity, patient experience, and overall quality. The benefits to the development of sub-regions for integrated planning and delivery include: Focusing on population health needs to address health equity; Enhancing coordination of services; Leveraging local community resources and knowledge; Engaging patients/clients and caregivers to ensure that the work of each sub-region meets the needs of its population; Enhancing local accountability for population health and performance along the continuum of care; and Increasing the value of our health system. The region consists of the following sub-regions: A A detailed account of the process to establish their boundaries is available in the sub-regions section of the LHIN website. 6 P a g e

7 , the most western and rural sub-region, has a population of 154,575 people including the Pikwàkanagàn First Nation, as well as Arnprior, Carleton Place, Kemptville, Pembroke, and Petawawa. is the fastest growing sub-region in and has 303,274 people. includes Kinburn, Carp, Kanata, Stittsville, Barrhaven, and Manotick. Central is the most culturally diverse, urban sub-region, and includes the areas of Bayshore, Nepean, Downtown, Vanier, and Riverside South. With 416,202 people, it is the most populated of the five sub-regions. sub-region extends around the city from Cumberland to Osgoode. About half of its 213,413 people live in Orléans, and 1 in 3 people speak French as their mother tongue. is the easternmost part of Ontario. It includes Akwesasne, the second most populous First Nation community in Canada, as well as Alexandria, Casselman, Hawkesbury, Rockland, Winchester, and the City of Cornwall. More than 40% of its residents speak French as their mother tongue. The dimensions of health and well-being are complex and multifaceted. This report provides a snapshot of population characteristics, population health status, health service provider distribution and capacity, and system performance. It was developed to provide baseline information on each sub-region in order to identify strengths, challenges, and needs, and to support priority setting and planning. At times, the report goes beyond sub-regions providing data, where available, for specific sub-groups such as immigrants, Francophones, and Indigenous people. The impact of social determinants of health is also examined. Population Characteristics Of the 1.3 million people in about two out of three people live in, one of six in smaller cities and towns and one of five in rural areas. The population is forecasted to grow, on average, by 1.1% per year over the next 10 years ( ). Those aged 65 and older comprise 16.7% of the population and those aged 19 and younger make up 22.5%. and experienced the highest population growth in between 2011 and and have the largest proportion of people over 65 years of age. The LHIN, compared to Ontario, has a much higher proportion of Francophones, particularly in the sub-regions. Central is the most culturally diverse area. It has the highest proportion of visible minorities, immigrants, same sex couples, and people with a mother tongue other than English and French. and have proportionately fewer visible minorities and immigrants. 7 P a g e

8 and have lower levels of education while Central has the highest proportion below the low income cut-off, a difference that is more pronounced among seniors who live alone. Socioeconomic status measures are generally most favourable in and. Across overall, Indigenous people have, on average, lower education and higher rates of unemployment and low income. Recent immigrants tend to have higher education but also higher rates of unemployment and low income. Those with French as their mother tongue are, on average, older than those with English mother tongue, but socioeconomic indicators are similar. Population Health Status In the region, 60.7 % of the population, aged 12 and over, rate their health as very good or excellent, and 70.6 % report very good/excellent mental health. and sub-regions report higher rates of very good/excellent general health than the other subregions at 64.3% and 64.5%, respectively. Over a third of residents (age 12+) self-report having a chronic condition, with 15% reporting multiple conditions. Chronic disease rates overall in are comparable to the provincial averages, with rates generally lower in the three sub-regions and higher in and. The incidence of chronic obstructive pulmonary disease (COPD) also shows wide variance across the region, with the highest rates in the Counties and, in particular, around the Cornwall area. Hospitalization rates for COPD and for ischemic heart disease (which includes heart attacks, atherosclerosis, and chest pain) were much higher in and compared to the sub-regions. The rates are influenced by the burden of disease in the community and factors related to health service organization and access. Chronic disease hospitalization rates, overall, were higher among people from more socio-economically disadvantaged areas. The rate of 30-day hospital readmissions for certain chronic conditions, a key LHIN indicator, is highest in and Central. Life expectancy at birth in is slightly better than for Ontario overall. Within, it is highest in and and lowest in and. Female life expectancy is longer in all sub-regions, by three to five years. The top three causes of death in and Ontario are ischemic heart disease, dementia, and lung cancer. Ischemic heart disease is responsible for between 15% ( and Central ) and 20% ( ) of deaths across the sub-regions. In, dementia is the top cause of death, at 16.8%. Among youth (15-24) the leading causes of death are related to transport incidents (including accidents), intentional self-harm and accidental poisoning. 8 P a g e

9 The estimated proportion of people with a mental health/addictions condition was similar across sub-regions, ranging from 18.6% in to 21.0% in and Central. The rates of hospitalization due to self-harm, however, were over 50% higher in and compared with the sub-regions. Health Service Provider Distribution and Capacity In general, health care services are clustered in Central. Most of the Central providers, however, serve large numbers of clients and patients from other areas. has the fewest general and family practitioners on a per capita basis, followed by. has the highest proportion of people seeking primary care in other sub-regions. The number of long term care beds relative to the population over age 75 varies across sub-regions. has the highest ratio and Central has the lowest. Looking across capacity measures for long-term care, home care, community support services, and community mental health and addictions, tends to have lower service rates. Although per capita and per client measures don t tell the whole story of supply and demand, they do suggest that there may be some inequity in the distribution of services in the sub-regions. System Performance High rates of people waiting for an alternate (more appropriate) level of care (ALC) can be a reflection of insufficient service capacity or poor integration across sectors. Rates are also impacted by hospital discharge planning and practices. In , on average, more than one out of every 8 (12.9%) acute care hospital beds in was occupied by people waiting for an alternate level of care. Patients from the Central sub-region had the highest rate, while and had the lowest. The rate of readmission within 30 days for certain chronic conditions is impacted by a patient s health, the quality of hospital care, discharge planning, the effectiveness of handoffs between hospitals and primary care, and the accessibility and quality of supports in the community., as a whole, performs better than Ontario. The best performing sub-regions are and. High-performing primary care is associated with improved equity, better health outcomes, lower mortality and a lower overall cost of health care. Most people in have a regular primary care provider, ranging from 91.2% of those surveyed in Central to 98.0% in. and had higher percentages of people reporting difficulty accessing after-hours care without going to an emergency department, and significantly higher rates of emergency visits for conditions that could be best managed elsewhere. has significantly higher rates of hospitalization for ambulatory 9 P a g e

10 care sensitive conditions (ACSCs) than all other sub-regions. ACSCs are chronic conditions that require fewer hospitalizations when well managed in the community. The rate of palliative care patients who were discharged home from hospital with home supports is a proxy measure of how well end-of-life patients are cared for. Overall, performs better than Ontario. Performance was best in and. At the end of life, it is particularly important to receive care in the place where you are most comfortable. Palliative home care patients from Central were more likely to have died in their preferred location than those from the other sub-regions. Central residents were also more likely to have died in residential hospice. A very small proportion of palliative home care patients from (3%) and (1%) died in residential hospice. There is minimal variation in home and community care wait times across s subregions however people with mother tongues other than English or French tend to wait longer. Conclusion The intent of this report is to provide baseline information to guide health system priority setting and planning in each sub-region. This report is a result of an unprecedented collaboration of key stakeholders across various sectors of the health system including local public health units, community-based providers, hospitals and the LHIN. Thanks to this strong collaboration, the scope of this report is broad. However, additional information and further interpretation is needed to assess opportunities and challenges. The data in this report should be considered alongside other information relevant to each sub-region and interpreted with input from stakeholders who have a good understanding of each respective sub-region. Engagement will continue with stakeholders, including patients and caregivers, to gain local knowledge that will help set priorities and inform planning. Health system planners and providers in each sub-region can use this information to help identify opportunities for equity, improved access to, and effective integration of health services. We look forward to collaborating with community members to make optimal use of the health resources within our region and reduce inequities. 10 P a g e

11 Abbreviations ACSC ALC BME BORN CCHS CCO CHC CHF CI CIHI CKD COPD ED EDI FP GP HCES ICES INSPQ iphis LHIN MOHLTC Ambulatory Care Sensitive Conditions Alternative Level of Care Best Managed Elsewhere Better Outcomes Registry & Network Canadian Community Health Survey Cancer Care Ontario Community Health Centre Congestive Heart Failure Confidence Interval Canadian Institute for Health Information Chronic Kidney Disease Chronic Obstructive Pulmonary Disease Emergency Department Early Development Instrument Family Practitioner General Practitioner Health Care Experience Survey Institute for Clinical Evaluative Sciences Institut national de santé publique du Québec Integrated Public Health Information System Local Health Integration Network Ministry of Health and Long-term Care 11 P a g e

12 MT PYLL WHO Glossary Mother tongue Potential Years of Life Lost World Health Organization Confidence interval Early Development Instrument Health Links Infant mortality rate Life expectancy Mother tongue New immigrant Potential years of life lost Sub-sub region A measure of how precise a result is. A population-based measure of children s developmental health at school entry; identifies children who face a greater likelihood of challenges in school learning. A strategy that coordinates health care services (hospitals, family physicians, long-term care, community support services) so that a patient with complex needs receives efficient and effective care. The number of infant deaths under one year of age per 1,000 live births in the same year. The hypothetical average number of years that an individual would live if subjected to the age-specific mortality rates of the specified population and time. The first language learned at home in childhood and still understood by an individual at the time of collection. Someone who has immigrated to Canada in the past 10 years. A measure of the total number of years of life lost due to premature death before age 75. The difference between age 75 and age at time of death. A smaller geographic area that rests within a larger sub-region. There are 34 sub-sub regions nestled into the 5 larger sub-regions of. 12 P a g e

13 1. Introduction Region 13 P a g e

14 Why sub-regions? The region is vast. Each sub-region is unique, as are the many communities and neighbourhoods within them. Moving the planning lens closer to the community level makes good sense. Of the 1.3 million people in about two out of three people live in, one of six in smaller cities and towns and one of five in rural areas. From Akwesasne to Hawkesbury, to Vanier, to Barrhaven, and to Petawawa, life can be very different. Health needs and determinants can vary from one community to another and the best ways to address them also depend on where you live. s five sub-regions are local planning areas that will serve as the focal point for health system planning, strengthening service integration and coordination. A sub-region approach will help improve health equity, patient experience and overall quality. Local planning and engagement has always made sense. The Local Health Integration Network (LHIN) has had smaller planning regions within area in the past. The difference now is that they are being formalized as part of the implementation of the Patients First legislation. At the LHIN, there will be a dedicated administrative lead and a clinical lead (a regulated professional with a practice in the area) who will focus on the needs of each sub-region. People who live and work in a community understand the local needs best. Through a sub-region approach, the LHIN will support and leverage local expertise and knowledge. Sub-regions will not restrict access to care; the aim is to connect patients to the right service at the right time without limiting choice. Sub-regions are, simply, a better way to plan and improve health services by increasing the focus on local strengths, needs, and challenges. Why these particular sub-regions? In anticipation of the Patients First legislation, five initial sub-regions were proposed by the LHIN. The initial proposal was based on extensive data analysis and four key criteria (critical mass, population characteristics, existing Health Links Areas, and local knowledge). In August and September 2016, the LHIN held six face-to-face public consultations across the region and distributed an online survey. There were 224 people who attended sessions and more than 130 completed the survey. The feedback was rich and complex, and resulted in numerous changes to the initial draft sub-region boundaries. A detailed account of the process is available in the sub-regions section of the LHIN website. 14 P a g e

15 is the most western and rural subregion, with a population of 154,575 people. The region includes the Pikwàkanagàn First Nation, as well as Arnprior, Carleton Place, Kemptville, Pembroke, and Petawawa. One in five people are over 65 years old. is the fastest growing sub-region in and has 303,274 people. includes Kinburn, Carp, Kanata, Stittsville, Barrhaven, and Manotick. 15 P a g e

16 Central is the most culturally diverse, urban sub-region, and includes the areas of Bayshore, Nepean, Downtown, Vanier, and Riverside South. With 416,202 people, it is the most populated of the five sub-regions. extends around the city from Cumberland to Osgoode. About half of its 213,413 people live in Orléans, and one in three people speak French as their mother tongue. This sub-region has the highest proportion of self-reported very good or excellent health. 16 P a g e

17 spans the rural area east of and borders both the US and Quebec. More than 40% of its 201,975 people speak French as their mother tongue. This region also includes Akwesasne, the second most populous First Nation community in Canada. Why this report? Good planning requires good data. Good sub-region planning requires good sub-region data. This report was developed to provide a baseline of information about the population, health, and health services in each sub-region. It is intended to help those living and working in the subregions to identify key areas of challenge and opportunity. In combination with local knowledge, LHIN and provincial priorities and other considerations, the data provided in this document can help guide strategy development and priority setting. To meet the requirements of different users, the data is presented in three ways: 1. Detailed chapters including context, interpretation and data limitations, organized into four main themes: population characteristics, population health, health system performance and health system capacity (pages 12 to 85) 2. An appendix containing summaries of key findings for each sub-region (pages 93-98) 3. An appendix with an at-a-glance data only view. (pages ) In the detailed chapters, data is provided for each sub-region, for as a whole, and where available, for Ontario. For some indicators even more granular or sub-sub region data is provided in the form of colour-coded and scaled bubble maps. has 34 sub-sub-regions 17 P a g e

18 that nest precisely into its sub-regions. Intended for analytical purposes, these were identified by the LHIN based on similar criteria that developed the sub-regions. The sub-sub-region data reveals important variations even within sub-regions. Figure 1.1: Sub-sub Regions An interactive map is available online, here. You can use this map to zoom in, search for addresses or postal codes and turn different layers on or off, including sub-sub-regions, counties, health units and the location of health service providers. There are over 120 indicators in this report compiled from a variety of data sources, including: Statistics Canada (Census, National Household Survey, Canadian Community Health Survey) Ontario Ministry of Finance (population projections) Intellihealth Ontario (Discharge Abstracts Database, National Ambulatory Care Reporting System, OHIP Billing database, Mortality records) Internal LHIN and Community Care Access Centre data BORN (Better Outcomes and Registry Network) Information System 18 P a g e

19 Cancer Care Ontario (New Cancer diagnoses) Parent Resource Centre (Early Development Instrument) Ontario Health Care Experiences Survey For certain indicators, the report goes beyond a geographic analysis to look at differences based on residents social determinants of health, including: Age Gender Language Immigrant status Indigenous status Socioeconomic factors Social support factors Although this report is focused on sub-regions, the characteristics above were included in the data because they are at least as important to health planning as where a person lives. For most indicators, direct measures of socioeconomic status and social support were not available typically because people are not asked those questions when receiving care. Instead, we used two neighbourhood-level indices based on patient postal codes. The indices were developed by R. Pampalon at the Institut national de santé publique du Québec (INSPQ) and are based on composite scores for certain questions in Statistics Canada s Census 1 : Socioeconomic (or material ) Proportion of people without a high school diploma Average personal income Ratio of employment to population Social support Proportion of people separated, divorced or widowed Proportion of single-parent families Proportion of people living alone Based on their postal code, each person was assigned to the quintile associated with the corresponding Statistics Canada dissemination area (dissemination areas typically include 400 to 700 people) or neighbourhood. Quintile 1 represents those living in the most advantaged (e.g. higher socioeconomic status) neighbourhoods and quintile 5 representing the least advantaged. This neighbourhood or ecological approach is not perfect because individuals characteristics differ from the neighbourhood averages. The approach, however, is widely used and provides useful proxies where individual-level data is not otherwise available. Statistical testing for differences between sub-regions or confidence intervals are provided for some indicators, but not all. Where not specified, the differences between sub-regions (or compared to or Ontario) may or may not be significant and should be interpreted cautiously. 19 P a g e

20 2. Population Characteristics This chapter includes the population demographic, sociocultural, and socio-economic profiles. An understanding of the sub-region population characteristics is important for planning services and initiatives for their specific needs. At a basic level, knowing how many people, where they live, their age, gender, the language(s) they speak and their health issues, can help us plan which services to provide, how many, where they are located, and in what language they need to be provided. Socioeconomic differences in a population are associated with risk factors, overall health outcomes, and access to and utilization of health care services. Health Quality Ontario recently compiled Ontario academic and non-academic literature that demonstrates differences in life expectancy, self-rated health, low birth weight, diabetes, length of stay in hospital and rate of avoidable hospitalizations for characteristics such as age, race, immigration status, language, homelessness, income and socioeconomic status 2. Our education, income, environment, social supports, and other social determinants of health, impact our opportunities for well-being, to make healthy choices, to avoid illness and its complications, and to access care when we need it. To improve health and reduce costs, we can work across sectors (housing, employment, education, municipal government, public health, health care, etc.) to create better opportunities for health such as access to affordable education, safe employment, a living wage, accessible recreation, a clean environment, and affordable healthy food, to name a few. We can also create more accessible health care in terms of cost, proximity, culture and language. Though the health care system is just one of the factors affecting our health, a system that thoughtfully considers the social determinants of health and provides equitable person-centred high-quality care can help to mitigate the social and economic factors that may be affecting the health of the people, or their access to care, in the sub-regions. Population Demographic Profile Approximately 9.5% of Ontarians or 1,289,440 people live in the region. 3 The population is forecast to grow, on average, by 1.1% per year over the next 10 years ( ). In the LHIN, those aged 65 and older comprise 16.7% of the population and those aged 19 and younger make up 22.5%, both similar to Ontario. Between 2013 and 2015, there was an average of 13,490 births per year resulting in a birth rate of 10.3 births per 1,000 population. The birth rate was similar across all sub-regions, except for, which had a slightly higher birth rate (Table 2.1). Table 2.1 shows how the population is distributed across the region. About one third of the population in the region lives within Central (34.1%), the dense urban 20 P a g e

21 core. Among sub-regions, Central has the lowest proportion of children (aged 19 and younger) at 19.2%. The population of is concentrated in Kanata-Stittsville and Barrhaven, and the population of is concentrated in Orléans (Figure 2.1). Typical of suburban areas, both and have relatively fewer seniors and relatively more children. Both areas experienced the highest population growth in between 2011 and 2016, with 2.1% for and 1.7% for. The population of and is partly concentrated in towns on the edges of, including Arnprior (10,099), Carleton Place (10,013), Rockland (11,099), and Embrun (6,380) as well as in other cities and towns, including Pembroke (16,146), Cornwall (49,243) and Hawkesbury (12,267). Both and also include large rural areas and many smaller villages. These two rural sub-regions have the largest proportion of people over 65 years of age. In all but one sub-region, females make up a little more than half of the population. This is also true for Ontario overall, since women tend to outlive men. In, however, only 49.9% of the population are female (approximately 75,200 females and 75,500 males). This is explained by the fact that Petawawa has almost 1,300 more males than females, or is only 45% female. Data in this section are primarily derived from the Census and National Household Survey. Most of the information is from 2011, as only partial information from the 2016 Census was available at the time this report was prepared. 21 P a g e

22 Table 2.1: Population Demographic Profile 4, 5, 6, 7 Central Ontario Total Population (2016) 4 154, , , , ,975 1,289,440 13,448,505 Total Population (2011) 5 150, , , , ,545 1,230,655 12,860,341 % Population (2016) % 22.5% 34.1% 16.2% 15.5% 9.5% % Population (2011) % 22.2% 33.6% 16.0% 16.0% 9.6% Population Density Persons per square km (2011) 5 Average # of births per year ( ) 6, a Birth rate(births per 1,000 population) ( ) , ,557 3,048 4,426 2,117 2,048 13,490 a 138, % Age 19 and Younger (2016) % 26.4% 19.2% 24.9% 21.7% 22.5% 22.4% % Age 65 and Older (2016) % 13.5% 17.4% 14.4% 19.7% 16.7% 16.7% % Female (2015) 49.9% 51.1% 51.1% 51.1% 50.4% 50.8% 50.9% % annual growth historic ( ) 5 0.5% 2.1% 0.1% 1.7% 0.5% 0.9% 0.9% % projected annual growth ( ) % +1.4% +0.4% +1.1% +1.1% -For 65+ population +3.8% +4.4% +4.2% +4.3% +4.2% -For population under age % +0.9% -0.6% +0.5% +0.5% a Total may not add up to the total of the sub-regions due to missing geographic identifier and hence some births in the region could not be assigned to a sub-region. 22 P a g e

23 Figure 2.1: Population Density by Census Tract () and Census Sub-Division (Outside of ), Sociocultural Profile The LHIN, compared to Ontario, has a much higher proportion of Francophones, particularly in the sub-regions (Table 2.2). It also has a slightly higher proportion of Indigenous people. B, however, has proportionately fewer visible minorities and immigrants. B The term Indigenous is used in this report. In this section, it includes the Aboriginal identity population defined by Statistics Canada as well as members of Akwesasne First Nation (which does not participate in the Census). 23 P a g e

24 5, 8, 9 Table 2.2: Sociocultural Profile, Central % who identify as Indigenous a 6.7% 1.4% 1.5% 1.7% 8.0% 3.1% 2.4% Ontario % who are immigrants b 5.8% 21.9% 26.9% 17.8% 6.0% 18.4% 28.6% % who are recent immigrants (arrived within ) c 0.4% 2.1% 4.6% 2.0% 0.5% 2.5% 3.8% % visible minority d 1.9% 21.4% 27.1% 19.1% 3.0% 17.6% 25.9% % of couples that are same sex e 0.4% 0.5% 1.4% 0.4% 0.5% 0.8% % who include French as mother tongue f % who include English as mother tongue f % who include other mother tongues f 0.8% (Canada) 5.4% 7.3% 15.3% 29.3% 41.8% 18.8% 4.4% 91.1% 74.2% 62.1% 58.4% 56.0% 66.8% 70.3% 3.5% 18.5% 22.6% 12.3% 2.2% 14.4% 25.3% a % who identify as Aboriginal as defined by Statistics Canada plus Akwesasne registered on-reserve population reported by Aboriginal Affairs and Northern Development Canada (Indigenous and Northern Affairs Canada). Akwesasne did not participate in the 2011 Census. 9 b % of total population in private households by citizenship and who identified their immigration status in NHS c % of total population in private households by citizenship and who identified their immigration status in NHS 2011 and in NHS d % of total population identified their minority status in NHS e % of total people in same sex couples divided by the number of people in couples. f % of total population who identified their mother tongue in Census is relatively homogeneous socio-culturally compared to. It has the lowest proportion of minorities, immigrants, and same sex couples. The vast majority (91.1%) of the population report English as a mother tongue and only 5.4% report it to be French. The sub-region has, however, the second highest proportion of people with Indigenous identity. includes the Algonquins of Pikwàkanagàn First Nation in the Golden Lake area. The proportion of the population who are Indigenous is highest in, primarily because the area includes Akwesasne, the 2 nd most populous First Nation community in Canada (see Figure 2.2). 24 P a g e

25 Figure 2.2: Number and Percent of the Population Identifying as Indigenous by Sub Sub- Regions, Central is the most culturally diverse area, similar to urban centres elsewhere. It has the highest proportion of visible minorities, immigrants, same sex couples and people with mother tongues other than English and French. Figure 2.3 shows the distribution of new immigrants in the region and the sub sub-regions. and have proportionately fewer immigrants and visible minorities than Central but more than in the rural sub-regions. 25 P a g e

26 Figure 2.3: Number and Percent of the Population who are New Immigrants by Sub Sub- Regions, has the second highest proportion with French as a mother tongue (29.3%) while has the second lowest (7.3%). The proportion with French as mother tongue tends to be lowest in the South and West of the region and highest to the North and East. has the largest proportion of people with French as a mother tongue. Prescott-Russell, the northern part of the sub-region, is predominantly Francophone. Over 70% of the population in the Hawkesbury, Alfred-Plantagenet, the Nation and Casselman areas report French as their mother tongue followed by Clarence-Rockland at 66% (Figure 2.4). 26 P a g e

27 Figure 2.4: Proportion of the Population with French as Mother Tongue by Census Tract () and Census Sub-Division (Outside of ), Socio-economic Status Profile Socio-economic status, including income, unemployment and education, is better in than the Ontario average. The proportion of people age 25 to 64 who have not completed high school, for example, is 8.8% in compared with 11.1% in the rest of Ontario. (Table 2.3) Similar to other urban centres, Central has the highest proportion below the low income cut-off and the highest proportion of single parent households. The proportion of seniors living alone with low income is three to five times higher in Central (10.4%) than in other subregions (2.0% to 3.7%). The proportion with low income and the unemployment rates in are higher than the regional average. Unemployment is also higher in. Education levels in the more rural sub-regions are the lowest. For example, the proportion of people aged 25 to P a g e

28 years old, with post-secondary education is 58.1% in, 54.4% in compared with 73.0%-77.0% in the sub-regions. and have the lowest proportions of people with low income. The two sub-regions have the lowest proportions of seniors living alone with low income. Education levels were highest in. Table 2.3: Socioeconomic Profile, , 8 Central a Of total population age 15 and over living in private households in NHS b Low income based on the low-income measure after-tax (LIM-AT): Fixed percentage (50%) of median adjusted after-tax income of households observed at the person level, where adjusted indicates that a household s needs are taken into account. c Of total population age years by higher education certificate, diploma, or degree in NHS d Of total number of families with children in Census e Of total population age 65 and over living in private households in NHS f Of the total number of seniors (age 65+) Populations: Immigrants, Indigenous People, and Language Groups Of the population of, 16.1% (198,380) report French as a mother tongue. One in % or 199,240) of the population report a mother tongue other than English or French. The immigrant population in the region is 18.1% (222,585). New immigrants (62,375 people who immigrated between 2001 and 2011) make up over a quarter (28%) of the total immigrant population. (Table 2.4) The Indigenous population has the lowest proportion of people with completed post-secondary education (49%) and the highest proportion without a certificate, diploma or degree (24%). Indigenous people are more likely than residents in general to be unemployed (11% compared to 7% in ) and have low income (17% vs. 12%). Estimates are limited to the Indigenous people who were surveyed and self-identified as Indigenous during the 2011 Census and National Household Survey. The population of Akwesasne, which did not participate in the surveys, and an unknown number of other people are excluded. Ontario % Low Income (after tax) a, b 10.8% 5.9% 17.9% 5.8% 13.4% 11.7% 13.8% % Unemployed a 4.6% 3.8% 4.5% 3.3% 4.4% 4.2% 5.2% % who have not completed high school c % with completed post-secondary education c % Lone-Parent Families (among census families) d 11.7% 4.8% 9.0% 5.6% 15.0% 8.8% 11.1% 58.1% 77.0% 73.8% 73.0% 54.4% 69.5% 64.8% 24.5% 19.4% 34.5% 21.7% 26.1% 25.8% 26.4% % of seniors living alone e 26.4% 17.2% 33.5% 16.6% 26.4% 26.1% 24.4% % of seniors living alone with low income f 2.2% 2.0% 10.4% 2.6% 3.7% 5.5% N/A 28 P a g e

29 People who immigrated to Canada are more likely to have a post-secondary education (68% for all immigrants and 67% for recent immigrants vs. 59% for non-immigrants). However, despite the higher education levels, recent immigrants are more likely to be unemployed (13% vs. 7%). The recent immigrant population in is much more likely to have low income (28% vs. 11% for non-immigrants), especially among people under 20 years of age (36% vs. 13%). Mother tongue refers to the first language learned at home in childhood and still understood by an individual. In Table 2.4, only those reporting one mother tongue are presented. The most common languages of mother tongue, other than English or French, were Arabic, Chinese (not otherwise specified), Spanish, Italian, and German. Almost 30,000 people spoke Arabic, 26,500 spoke Chinese, and 11,000 spoke Spanish as their mother tongue. An additional 31,000 people responded that they had multiple mother tongues. Of those reporting more than one mother tongue, 47% spoke English and French, 38% spoke English and another non-official language, 10% spoke French and another non-official language, and a small proportion (5%) spoke English, French and another language as their mother tongue. People with a mother tongue other than English and French were more likely to have a postsecondary education (65%, compared to 59% of English and 55% of French mother tongue), but had slightly higher rates of unemployment (9% compared to 7% English and 5% French), and much higher prevalence (20% vs. 10% and 10%) of low income. A larger proportion of people with French as a mother tongue are 65 years of age and older (16% compared with 12% for English). Those reporting French as a mother tongue are less likely to have a post-secondary degree (55%) than those reporting English as a mother tongue (59%) and are less likely to be unemployed (5% compared vs. 7%). The proportion of people with low income is identical among those reporting French or English as a mother tongue (10%) except among people over 65 (9% among those with French mother tongue vs 7% English). 29 P a g e

30 Table 2.4: Regional Socio-Economic Indicators by Sub-Population, Sociocultural Profile All Indigenous Identity a All Immigrants Recent Immigrants b Non- Immigrants French MT c English MT c Other MT c Total population 32, ,585 62, , , , ,240 1,230,655 % of aged 19 or younger 30% 9% 26% 27% 20% 25% 18% 23% % of aged 65 and older 6% 20% 5% 12% 16% 12% 15% 13% Social Economic Profile % without certificate, diploma or degree % with completed postsecondary education % with Bachelor degree or higher % in labour force who are unemployed Prevalence of low income in 2010 based on after-tax lowincome measure (%) 24% 13% 14% 16% 18% 15% 15% 15% 49% 68% 67% 57% 55% 59% 65% 59% 14% 40% 44% 26% 23% 28% 39% 29% 11% 8% 13% 7% 5% 7% 9% 7% 17% 16% 28% 11% 10% 10% 20% 12% Less than 18 years % 18% 33% 36% 13% 12% 12% 32% 14% 18 to 64 years % 18% 17% 26% 11% 10% 10% 19% 12% 65 years and over % 15% 8% 20% 8% 9% 7% 10% 8% a Data from Statistics Canada. Akwesasne, which did not participate in Census, is excluded. In addition, the count of Indigenous people outside of Akwesasne, is considered to be underestimated. b Recent Immigrants: immigrated c MT: Mother Tongue According to Statistics Canada and Indigenous and Northern Affairs Canada data, there are 42,593 Indigenous people in (Table 2.5). More than three-quarters (77%) live off reserve. About two-thirds (67%) are First Nations, one quarter Métis (27%), 2% Inuit and 4% have other or multiple Indigenous identities (e.g. both First Nations and Métis). The numbers are considered to be underestimated, excluding people who were not surveyed for various reasons, those who didn t self-identify and many transient residents (e.g. Inuit living temporarily in to attend school or access services). Table 2.5: Indigenous Populations and Place of Residence, 2011 a bb First Nations Inuit Metis Others Total Living On Reserve Lands 9,818 b 9,818 Living Off Reserve 18, ,485 1,650 32,775 Total 28, ,485 1,650 42,593 a b Source: Statistics Canada National Household Survey, 2011 and First Nations population on-reserve based on Registered Indigenous population on-reserve reported by Indigenous and Northern Affairs Canada as of Aug, 2017, Includes Akwesasne and Pikwàkanagàn 30 P a g e

31 3. Population Health Status General Health Self-reported health measures give useful high-level insights into a population s perception of health status. This perceived health status can guide further investigation into service utilization and helps inform the resources required to support the population in leading healthy and active lives. Self-reported health can help guide health service planning conversations and examining regional disparities can help identify if geography is a meaningful context in which to consider service allocation. The Canadian Community Health Survey is a cross-sectional data survey that provides a means to estimate a variety of self-rated health measures and health-related behaviours. 10 Four years of data collected for the region from 2011 through 2014 was combined to obtain adequate statistical power to provide the following age-standardized estimates. 11 Persons living on reserve are excluded from the survey's coverage. Self-reported health measures In the region, 60.7 % of the population aged 12 and over rate their health as very good or excellent. and sub-regions report higher rates of very good/excellent general health than the other sub-regions at 64.3% and 64.5% respectively. In the region, 70.6 % of the population report very good/excellent mental health. There are no significant differences for reporting very good or excellent mental health between sub-regions. The percent of the population requiring help with at least one activity of daily living is lower in (8.7%) compared to all sub-regions. (9.0%) is lower compared to (13.3%). Table 3.1: Self-rated General and Mental Health and Help with One Activity of Daily Living, age 12 and over (Percent and 95% Confidence Intervals), 2011/2014 combined sample. 11 Central Self-rated general health as very good/excellent 57.6 (±3.4) 64.3 (±3.5) 59.4 (±3.5) 64.5 (±4.3) 56.9 (±3.8) 60.7 (±1.8) Self-rated mental health as very good/excellent 68.4 (±3.6) 72.7 (±4.3) 68.2 (±3.4) 72.9 (±4.2) 71.2 (±3.3) 70.6 (±1.9) Requires help with at least one activity of daily living 11.9 (±2.2) 8.7 (±1.8) 11.0 (±2.2) 9.0 (±2.4) 13.3 (±2.2) 10.6 (±1.0) 31 P a g e

32 Risk Factors Factors that can influence health include individual choices; the accessibility and use of primary care services; and the settings in which we live, learn, work and play. Regional information about individual risk factors helps guide resource allocation and informs interventions that support healthy choices. Regional differences in individual risk factors are one important component in the decision framework for resource allocation. Infant Feeding on Discharge from Hospital To achieve optimal growth, development and health, the World Health Organization (WHO) and Health Canada recommend that mothers exclusively breastfeed infants from births to six months of age. 12, 13, 14 Table 3.2 shows the percentage of babies who were exclusively breastfed or have had any breastfeeding upon discharge from hospital or within three days of birth in midwifery care. From , 62.8% of babies were exclusively breastfed upon discharge from hospital or midwifery care in. The highest rate of exclusive breastfeeding was in (68.1%) while the lowest rate was in Central (60.1%). In the region, 90.1% of babies had received breastfeeding (exclusively or in combination with formula milk) upon discharge from hospital or within three days of birth in midwifery care. The percentage of babies who received any breastfeeding (exclusively or in combination with formula milk) was lower in (86.1%) and (81.2%) in comparison to the three sub-regions. Table 3.2: Breastfeeding on Discharge from Hospital or within Three Days of Birth in Midwifery Care, Central Exclusive breastfeeding 68.1% 64.4% 60.1% 62.9% 62.8% 62.8% Any breastfeeding (either exclusively or in combination with formula milk) Utilization and Access to Health Care 86.1% 93.9% 93.1% 91.7% 81.2% 90.1% Table 3.3 shows the percentage of the population aged 12 and over who state they have a regular family doctor and the percentage that report having had a flu shot in the past two years. 88% of residents in the region aged 12 and up report having a regular family doctor. Central has the lowest rate among the sub-regions at 82.6%. has the highest rate at 94.2%. 32 P a g e

33 Self-report of a flu shot in the past two years was 50% or lower for all regions with no statistically significant differences between sub-regions. Table 3.3: Self-Reported Regular Family Doctor and Flu Shot in the Past Two Years, Age 12 and Over (percent estimates and 95% confidence interval), 2011/2014 combined sample. 11 Central Regular medical doctor 91.5 (2.1) 90.9 (2.4) 82.6 (3.0) 94.2 (2.3) 88.1 (2.9) 88.0 (1.3) Flu shot in the past two years 42.7 (3.6) 50.6 (3.8) 48.0 (2.7) 50.1 (4.5) 41.2 (2.9) 47.1 (1.6) Healthy Eating and Active Living Table 3.4 shows the percent of the population aged 12 and over who report being inactive during leisure time and who report consuming five or more fruits or vegetables daily. Overall, 40.3% of the population in the region are inactive during leisure time. s population reports being the least inactive during leisure time among the subregions at 30.7%. reports the highest levels of inactivity at 46.3%. Consumption of fruits and vegetables five or more times daily is lower in and compared to and Central. In the region, 36.6% self-report eating fruits or vegetables five or more times daily. No other comparisons are statistically significant. Table 3.4: Self-Reported Inactivity During Leisure Time and Consumption of Fruits/Vegetables Five or More Times Daily, Age 12 and over (percent estimates and 95% CI), 2011/2014 combined sample. 11 Central Inactive during leisure time 43.1 (±4.7) 40.7 (±4.5) 40.5 (±3.2) 30.7 (±4.0) 46.3 (±4.0) 40.3 (±1.9) Consumption of fruits or vegetables five or more times daily 33.4 (±4.4) 36.0 (±4.5) 39.1 (±3.3) 39.6 (±4.7) 34.1 (±3.0) 36.6 (±1.9) Healthy Weights Self-reported height and weight is used to estimate being overweight or obese among adults aged 20 years and over (Table 3.5). In the region, 50% of the population aged 20 years and over are estimated as being overweight or obese using this measure. (58.4%) and (57.7%) have higher rates of overweight/obesity than all other subregions. Central (44.7%) and (46.9%) have the lowest percentage of adults estimated as overweight/obese compared to the other sub-regions. No other comparisons were statistically significant. 33 P a g e

34 Table 3.5: Overweight or Obese Based on Self-Reported Height and Weight, Age 20 and Over (percent estimates and 95% CI), 2011/2014 combined sample, 2011/2014 combined sample. 11 Central Overweight or obese based on selfreported height and weight 57.7 (±4.1) 46.9 (±4.0) 44.7 (±3.7) 52.0 (±5.8) 58.4 (±3.9) 50.1 (±1.9) Tobacco and Alcohol Use Table 3.6 shows the percent of the population aged 20 and over who report being current smokers, who report exceeding the Canada Low Risk Drinking Guidelines 16 and who report engaging in heavy drinking. and had higher rates of current smokers than the other sub-regions at 26.4% and 26.1% respectively. There were no statistically significant differences within the sub-regions. The Low-Risk Alcohol Drinking Guidelines pertain to reducing the immediate and long-term health risks of alcohol. To meet these guidelines, men should not exceed fifteen drinks per week and women should not exceed ten drinks per week. In addition, on most days, men should have fewer than three drinks a day and women fewer than two drinks per day. Both men and women should have at least two non-drinking days per week. 16 has a higher rate of exceeding the Canada Low-Risk Alcohol Drinking Guidelines (33.8%) compared to (26.6%) but no other differences between sub-regions are significant. In the region, 20% of adults engage in heavy drinking: meaning having five or more drinks on one occasion once a month or more. There are no significant differences in selfreported heavy drinking between sub-regions. Table 3.6: Self-Reported Current Smoking, Exceeding Canadian Low Risk Drinking Guidelines and Heavy drinking, age 20 and over (percent estimates and 95% CI), 2011/2014 combined sample. 11 Central Current smoker Exceed Canada Low Risk Drinking Guidelines 26.4 (±4.5) 30.2 (±3.5) 15.0 (±3.6) 27.1 (±4.1) 18.2 (±2.6) 29.4 (±3.2) 14.6 (±3.8) 33.8 (±5.5) 26.1 (±3.8) 26.6 (±3.1) 18.9 (±1.6) 29.4 (±1.8) Heavy drinking 18.3 (±2.9) 17.1 (±3.8) 19.2 (±2.7) 25.0 (±5.0) 20.2 (±2.9) 20.0 (±1.6) 34 P a g e

35 Vulnerability at School Entry The Early Development Instrument (EDI) is a population-based measure of children s developmental health at school entry and identifies children who face greater likelihood of challenges in school learning. 17 The EDI is one of the indicators of children s health in a community and is an important source of data for local health and social program planning. Overall, EDI vulnerability rates in the region are similar to the provincial results for Ontario (Table 3.7). has the highest percentage of vulnerable children compared to all other sub-regions, while Central has the largest population of vulnerable children. and have the lowest percentage of vulnerable children as compared to the other sub-regions and these percentages are substantially lower than the provincial results. Although EDI vulnerability rates are low in, this subregion has the second largest population of vulnerable children in. Table 3.7: Number and Percent of Kindergarten Children Vulnerable in One or More Early Development Instrument (EDI) Domains, 2014 to 2015 (Cycle 4). 18 Central Ontario Number and Percentage of Children Vulnerable in One or More Domains 278 (28.8%) 813 (23.5%) 993 (30.5%) 532 (23.7%) 689 (32.8%) 3305 (27.5%) 36,994 (29.4%) Preterm birth Preterm births are defined as live births with a gestational age at birth of less than 37 completed weeks and attribution to the LHIN sub-regions is based on the mothers residential address. The preterm birth rate is expressed as a percentage of all live births. Among industrialized countries, preterm birth is the leading cause of neonatal and infant mortality and accounts for a substantial portion of neonatal morbidity. 19 Between 2013 and 2015, 8.1% of births to residents were preterm. (8.9%) had the highest rate of preterm birth and had the lowest rate (7.3%). (Table 3.8) Table 3.8: Percentage of Preterm Births, Central Ontario % of preterm births 7.9% 8.9% 8.1% 7.6% 7.3% 8.1% 8.0% 35 P a g e

36 Chronic Disease in the Sub Regions Over a third of residents (age 12+) self-report having a chronic condition, with 15% reporting multiple conditions. 21 Living with a chronic disease impacts people s daily lives, but their experience and outcomes are improved with coordinated care between hospitals and community services. 22 The LHIN continues to support many aspects of chronic disease management, at the system level (electronic consultation with specialists, the Health Links approach), program-level (new services, centralized intake) and to the client (online selfmanagement support, self-referral options, peer support groups). Over the past few years, the LHIN has made targeted investments to improve chronic disease care in the community, including establishment of the Community Health Centre lung health programs and the community stroke outreach program; expansion of tele-cardiac rehabilitation in rural communities; and streamlined access to diabetes education programs (e.g. centralized intake). Research demonstrates that pulmonary rehabilitation, cardiac rehabilitation, stroke rehabilitation and diabetes education programs reduce emergency department visits, hospitalization and readmissions for people living with chronic conditions. 23, 24, 25 More and more, our local hospitals are partnering with these community providers and programs to provide better continuity of service, as evidence-based management of chronic disease in hospitals encourages a coordinated hand-off for support in the community sector. 26 Overall the prevalence and incidence rates of chronic disease in are comparable to the provincial average, though they vary across geographies with generally lower rates in the sub-regions. The reported prevalence of diabetes is 11.1%, which is slightly lower than the provincial rate of 12.4%. 29 Previous analysis of prevalence has shown the highest rates in the and Renfrew County, which is part of ). 31, 32 Previous analysis also showed wide variation in the incidence of Chronic Obstructive Pulmonary Disease (COPD) across the region, with the highest rates in the Counties and in particular around the Cornwall area. 27 Some key prevalence and incidence rates are summarized in Table 3.9. Table 3.9: Prevalence and Incidence of Selected Chronic Conditions. 27, 28, 29, 30 Chronic Condition Chronic Obstructive Pulmonary Disease (COPD) Incidence: 918 cases per 100,000 population 27 Stroke 1.2 inpatient admissions for stroke/transient ischemic attack (TIA) (per 1,000 population) 28 Diabetes Prevalence: 11.1% (118,244 adults) 29 Hypertension Self-reported prevalence: 152 per Heart Disease Self-reported prevalence: 46 per Asthma Self-reported prevalence: 94 per Arthritis Self-reported prevalence: 163 per P a g e

37 New analysis of chronic disease prevalence estimates is provided in Table The estimates include people with a minimum number of hospital admissions and/or physician visits for the specific condition over a specified period. Central had rates below the average for the four conditions evaluated and was above for all four. For asthma, diabetes and high blood pressure prevalence rates in the sub-regions differed from s by no more than 20%. Chronic obstructive pulmonary disease rates, however, were 26% higher in and 62% higher in. Table 3.10: Prevalence Estimates of Select Chronic Diseases (Age-standardized), (percent and 95% CI), a Asthma (Age 20 and up) Chronic Obstructive Pulmonary Disease (Age 35 and up) Diabetes (Age 20 and up) High blood pressure (Age 20 and up) a b c 15.7 (±0.2) 13.5 c (±0.2) 10.7 (±0.2) 26.4 c ±(0.3) 15.6 (±0.2) 7.3 b (±0.2) 9.5 b (±0.2) 23.1 b (±0.2) Central 14.7 b (±0.2) 9.6 b (±0.2) 10.2 b (±0.1) 22.4 b (±0.1) 15.9 c (±0.2) 8.3 b (±0.2) 10.8 c (±0.2) 24.1 (±0.3) 17.2 c (±0.2) 17.3 c (±0.2) 12.6 c (±0.1) 26.1 c (±0.2) Source: Institute Clinical Evaluative Sciences 2017 Project No Technical definitions, along with information about sensitivity and specificity of the algorithms, are included in 2016 Health Quality Ontario Primary Care Practice Report, Technical Appendix. Chances are at least 19 times in 20 that the rate is statistically lower than the rate (p<0.05). Chances are at least 19 times in 20 that the rate is statistically higher than the rate (p<0.05). The next section presents the picture of chronic disease in sub-regions, focussing on emergency department visits, hospitalizations, and 30-day hospital readmissions. Chronic Disease: Emergency Department Visits The number of visits to emergency departments for chronic conditions continue to climb, and for many of these visits, the symptoms and conditions could be better managed in the community with primary care. 33 In, there is significant variation in emergency department (ED) visits related to chronic diseases across the sub-regions (Table 3.11) (±0.1) 10.7 (±0.7) 10.6 (±0.1) 24.0 (±0.1) 37 P a g e

38 Table 3.11: Emergency Department Visit Rate (Age Standardized) per 100,000 for Select Conditions, FY 2015/16. Central ED visits for COPD a Ontario ED visits for hyper/hypo-glycaemia for adults living with diabetes b a b ED visit rates for COPD are age and sex standardized. ED visit rate for hyper/hypoglycemia are for the cohort of adults with diabetes. The emergency department visit rates for hyper/hypo-glycaemia among adults living with diabetes is higher in and than in the sub-regions (Table 3.11, Figure 3.1). Common underlying causes of visits to the ED for hyper/hypoglycaemia are related to medication (e.g. insulin), infections, having multiple medical comorbidities (e.g. Congestive Heart Failure (CHF), Chronic Kidney Disease (CKD)) and difficulty accessing primary care. 34, 35, 36 Emergency department visits for hyper/hypo-glycaemia is used as a measure of the overall performance of diabetes management in outpatient and primary care settings. Figure 3.1: Emergency Department Visit Rate per 100,000 for Hyper/Hypo-Glycaemia Among Adults Age 18 and Over with Diabetes, FY 2015/ P a g e

39 Emergency department visit rates for Chronic Obstructive Pulmonary Disease (COPD) in and are more than triple that of the central sub-regions (Table 3.11, Figure 3.2). and also have the highest smoking rates (see Risk Factors). Frequent emergency department visits for COPD exacerbations are related to medication use, previous hospitalizations, and reduced access to primary care. 37 The exacerbations of COPD are not just an outcome of the disease but they also cause the disease itself to worsen and further damage the lungs, leading to a decrease in quality of life and an increase in hospital visits for the client. 38 More generally, patients in and tend to access a larger portion of their primary and other health care services from hospitals than patients in. In smaller cities, services tend to be relatively concentrated in hospitals. This results in higher emergency department use rates overall. Figure 3.2: Emergency Department Visits per 100,000 for COPD, FY 2015/ P a g e

40 Chronic Disease: Hospitalizations Hospitalizations for chronic diseases account for a large proportion of health care resources. Potentially preventable hospitalizations point to a failure to provide adequate disease management support prior to admission. 39 In search of a hospital admission risk prediction tool, Health Quality Ontario found that hospital admissions could be predicted by a patient s age, geographic location to where the patient had been discharged, having a chronic condition, number of previous emergency department visits and number of previous hospital admissions. 40 In, the hospitalization rates for some chronic conditions vary across sub-regions, but not for all conditions. For example, the rates of hospitalization for cancer, arthritis, and stroke are fairly consistent across sub-region geographies (Table 3.12). In contrast, hospitalization rates for ischemic heart disease, which includes heart attacks, atherosclerosis and chest pain, was nearly twice as high in and compared to the sub-regions (Figure 3.3, Table 3.12). 41 Figure 3.3: Hospitalization Rate per 100,000 for Ischemic Heart Disease, FY 2015/ P a g e

41 The hospitalization rate for COPD in is three times the provincial average and much higher than the sub regions. also had a higher rate of COPD hospitalizations, at double the provincial average (Table 3.12). Hospitalizations for diabetes are also much higher outside of. Diabetes, though, like hypertension is underrepresented overall as it those conditions are often comorbidities or complications rather than the main diagnoses attributed to a hospitalization. Table 3.12: Hospitalizations for Common Chronic Conditions per 100,000, FY 2015/16. Chronic Condition Central Diabetes Ischemic heart disease Hypertension Congestive heart failure (CHF) Arthritis Asthma Cancer Stroke Chronic obstructive pulmonary disease Total Ontario (±50) (±24) (±17) (±29) (±49) (±12) The rate of hospitalization for common chronic diseases were also calculated based on patients neighbourhood socioeconomic status using method described on page As shown in Figure 3.4, chronic disease hospitalization rates are higher among people from more socio-economically deprived areas. The trend across quintiles is consistent, with the most deprived quintile showing nearly double the rate of those in the most advantaged quintile. These findings mirror the analysis by the Canadian Institute of Health Information, demonstrating higher rates of hospitalization with decreased socio-economic status. In their analysis the differences were especially pronounced for males P a g e

42 Select Chronic Conditions Hospitalization Rate (per 100,000) Figure 3.4: Hospitalization Rate per 100,000 for Select Chronic Conditions by Neighbourhood Socioeconomic Status, FY 2015/ Q1 - most advantaged Q2 Q3 Q4 Q5 - most disadvantaged Neighbourhood Socioeconomic Quintile Additionally, Health Quality Ontario found a higher likelihood of having multiple chronic conditions in populations with lower incomes compared to their wealthier counterparts. 43 In contrast, increasing levels of social deprivation (measured by family status and household composition) did not show a linear increase in the number of chronic disease hospitalizations. Chronic Disease: Hospital Readmissions The LHIN and local hospitals have a shared provincial performance indicator of the 30-day readmission rate for certain chronic conditions (includes stroke, COPD, CHF, diabetes and others). The regional target is 15.5% for 30-day hospital readmissions, but there is significant variation across hospitals. From previous analysis, the highest rates of readmissions are with the clinical cohorts of congestive heart failure, COPD, and acute myocardial infarction. 44 Additionally, analysis demonstrated the cohort of patients with the highest needs accounted for 87% of all 30-day hospital readmissions in the region, highlighting the importance of the Health Links approach. Focusing in on the sub-regions, the 30-day hospital readmissions for select chronic conditions are highest in (16.4%) and Central (15.4%) (Table 3.13). The lowest rates are in (12.7%) and (12.2%), both below the LHIN average. Predictors of hospital readmissions include rural residence, neighbourhood income, comorbidities and clinical conditions, older age, male gender, very long or very short length of stays, and availability of post-acute care P a g e

43 Table 3.13: 30-Day Readmissions for Certain Chronic Conditions, FY 2016/17 Q2. Central 30-Day Readmissions for Certain Chronic Conditions 16.4% 12.7% 15.4% 12.2% 14.6% 14.7% 43 P a g e

44 Cancer Rates Cancer Rate Profile According to Cancer Care Ontario, Cancer includes more than 200 different diseases that are characterized by abnormal cells in the body that divide and spread without control. In 2012, 30.2% of all deaths in Ontario were attributable to cancer, making it the leading cause of death in this province. 46 Cancer Care Ontario (CCO) has reported that the number of new cancer cases diagnosed each year in Ontario has increased since This increase has been largely attributed to the aging of the population and population growth rather than to changes in cancer risk or cancer control practices. The majority of new cancer cases in Ontario were diagnosed in people 50 years of age and older in The greatest proportion of cases were diagnosed in people between the ages of 60 and 69 (26.6% of new cases) and 70 and 79 (24.1%). Cancer was rare among children and adolescents, with less than 1% of all new cases diagnosed in people under the age of The incidence of cancer is influenced by socio-demographic factors, the availability of early detection and screening, and the prevalence of risk factors. Risk factors can include: 46 unhealthy behaviours (i.e.: smoking, poor diet, alcohol consumption and physical inactivity), non-modifiable risk factors (i.e.: age at menarche and menopause), lifestyle factors (i.e.: oral contraceptive or hormone replacement therapy use), exposure to certain environmental and occupational carcinogens (i.e.: radon, certain viral infections and air pollution), and genetic predispositions (i.e.; BRCA1 and CRCA2 gene mutations) Table 3.14 shows cancer incidence rates for the most prevalent types of cancer. In the region, the highest rates of all cancers occur in followed by. The rates of all cancers fall below the Ontario rate; however, the rates of colon and rectum cancer and lung and bronchus cancer are higher in the region than in Ontario. Of all cancers, the most prevalent in the region is lung and bronchus. The highest rates of lung and bronchus cancers are found in, followed by. The rates of lung and bronchus cancers in, and Central are higher than the Ontario rate. 44 P a g e

45 Colon and rectum cancers are also highest in followed by. When compared with Ontario, rates of colon and rectum cancer are higher in,,, and. Prostate cancer rates are highest in followed by. The rate of prostate cancer is higher in than in Ontario. The female breast cancer rate is highest in. Female breast cancer rates in and Central are higher than the provincial rate. Table 3.14: Age-Adjusted Cancer Rates per 100,000, Adults 20+ Years, Central All Cancers Lung and Bronchus Breast (Female) Colon and Rectum Prostate a b Ontario Number of new cases is based on the NCI SEER standards for counting multiple primary cancers, which were adopted by the Ontario Cancer Registry (OCR) for cases diagnosed in Counts produced for this analysis may differ from counts produced using CCO SEER*Stat Package Release 10 OCR (August 2015) 45 P a g e

46 Infectious Diseases Chlamydia and Hepatitis C Incidence Rates and Influenza/Pneumonia Hospitalization In accordance with the Health Protection and Promotion Act in Ontario, over 70 diseases are reportable to the local Medical Officer of Health. Chlamydia and Hepatitis C are two of these diseases. Chlamydia is the most frequently reported infectious disease in Ontario. 48 Hepatitis C is the most burdensome infectious disease in Ontario based on measures of mortality and morbidity. 49 The incidence rates in this report do not represent the true incidence because diagnosis can be impacted by the delay or absence of symptoms, the individual s access to care and health seeking behaviours. Table 3.15 shows incidence rates for Hepatitis C and Chlamydia based on data from 2013 to The incidence rate of Hepatitis C is age-standardized and the Chlamydia rate is age specific for ages 15 to 24 years. The Chlamydia incidence rate is highest in Central followed by, and, with having the lowest incidence rate. In, the most common risk factors for Chlamydia infection are not using condoms and having a new sexual partner in the past two months. 50 Central has the highest Hepatitis C incidence rate, followed by. There are no differences between the rates in the other 3 sub-regions. In, the most common risk factor for Hepatitis C infection is injection drug use. 51 In, there is significant variation in emergency department (ED) visits related to pneumonia/flu across the sub-regions. The ED visit rate due to pneumonia/flu in and is more than double that of the three sub-regions. ED visit rates in rural areas tend to be higher in general as hospitals play a larger role in primary care. The rate overall, is higher in compared to the provincial average ( 850 visits per 100,000 vs. Ontario 694 visits per 100,000). There is less variation for hospitalizations due to flu or pneumonia. s hospitalization rate was higher than the rate and much higher than the other sub-regions at 232 per 100,000 population. Administration of the flu vaccine has been shown to reduce flu-associated hospitalizations and visits to the emergency 52, 53 department. 46 P a g e

47 Table 3.15: Age-Standardized Incidence of Hepatitis C, Age-Specific Incidence of Chlamydia and Hospitalization for Influenza or Pneumonia (rate per 100,000 population and 95% 54, 55, 56 confidence intervals). Chlamydia incidence rate, age ( ) 54 Hepatitis C age-standardized incidence rate ( ) 54 ED visits for flu or pneumonia (2015/2016) 55 Hospitalization for flu/ pneumonia ( ) ( ) 17.6 ( ) ( ) 13.3 ( ) Central ( ) 32.5 ( ) ( ) 16.1 ( ) ( ) 24.4 ( ) ( ) 22.1 ( ) Ontario 1, , P a g e

48 Injury Fall-related emergency department visits for seniors is an important indicator of the health status of seniors across the sub-regions. For seniors, injuries from falls contribute to about half of the deaths due to injury. Most falls are preventable. Public health interventions should focus on addressing risk factors associated with falls such as: 57 i) Safe use of prescription and over the counter medication ii) Importance of nutrition, calcium and vitamin D intake, and exercise to prevent falls and delay onset of osteoporosis iii) Identification of hazards in the built environment which increase the risk of falls in homes and in the community, as a whole, does not perform as well as Ontario on this indicator, however there is significant variation among the sub-regions (Table 3.16). Central has the lowest fallrelated ED visit rate among the five sub-regions while s rate is 125% higher. This variation across may partly reflect rural ED use patterns. Table 3.16: Fall-related ED Visit Rates among Seniors per 100,000 Population, FY 2014/2015 FY 2015/2016. Central Ontario Fall-Related ED Visit Rates Among Seniors Rate from 4 th Quarter FY 2015/2016 Rates of fall-related ED visits among seniors were compared based on neighbourhood characteristics using methods described on page 14. Rates were high among those in the most socioeconomically disadvantaged neighbourhoods (Figure 3.5). 1 This trend is almost reversed when looking at social support. Seniors fall-related ED visit rates were highest in neighbourhoods with higher social support levels (based on household/family structure and living alone measures). Central, however differed, with similar rates across the social support quintiles. 48 P a g e

49 Fall-Related ED Visit Rate among Seniors, Age 65+ (per 1000,000) Figure 3.5: Fall-Related ED Visit Rates among Seniors age 65+ years (per 100,000 Population) by Neighbourhood Socioeconomic and Social Support Quintiles, FY 2014/2015 FY 2015/ ,500 2,000 1,500 1, , , , , , , , , , , Q1 Most advantaged Q2 Q3 Q4 Q5 Q1 Most Most Advantaged Disadvantaged Neighbourhood Socioeconomic Quintile Q2 Q3 Q4 Q5 Most Disadvantaged Neighbourhood Social Support Quintile 49 P a g e

50 Mortality According to the World Health Organization, measuring how many people die each year and why they died is one of the most important means along with gauging how diseases and injuries are affecting people for assessing the effectiveness of a [health system]. 58 Causes of death can point to where we should focus our efforts and resources for primary and secondary prevention. Looking at cause of death in sub-regions encourages us to think about the different health and life circumstances between the regions and to plan for how we might focus our prevention and treatment efforts. In this chapter, we will review mortality rates, life expectancy, premature mortality, leading causes of death, and preventable mortality in the region and sub-regions. Mortality rates Table 3.17 shows the crude and age-adjusted rates of mortality (male, female and combined) and infant mortality between sub-regions. C Crude rates give the best picture of the mortality rate in the sub-regions. However, when comparing sub-regions, the age-adjusted rates should be used as adjusting for age removes the influence of the differences in the population by age between regions. The age-adjusted mortality rate for both sexes combined in the region is much lower than the Ontario rate, signaling a relatively healthier population. Overall, age-adjusted mortality rates are higher in and sub-regions (though still lower than the Ontario average) and lowest in and sub-regions. The lowest ageadjusted mortality rate is in, significantly lower than Central, and, and Ontario mortality rates, but not significantly lower than. age-adjusted mortality is lower than and. The patterns for men and women are similar to what is seen for the combined population. While the highest age-adjusted mortality rate for women and men is in, the rate in is only high for men. The difference in mortality is not seen as strongly among women in compared with others. The infant mortality rate (the number of infant deaths under one year of age per 1,000 live births in the same year) is also highest in and, and in, but the confidence intervals are wide and the differences between the sub-regions are not significant. 59 C Age adjustments compared with 2011 Canadian population. 50 P a g e

51 Table 3.17: Mortality Rates (rates per 100,000 and 95% confidence intervals), Central Ontario Mortality Crude Rate per 100,000 Male Female Combined 810 (±81) 853 (±65) 995 (±54) 407 (±32) 446 (±35) 437 (±34) 669 (±37) 754 (±37) 732 (±26) 442 (±41) 430 (±41) 448 (±30) 770 (±54) 761 (±54) 764 (±37) 630 (±20) 632 (±19) 631 (±14) 647 (±6) 625 (±6) 646 (±4) Age- Adjusted Mortality Rate per 100,000 Male Female Combined 846 (±66) 620 (±47) 719 (±39) 671 (±55) 486 (±38) 560 (±32) 764 (±40) 558 (±28) 646 (±23) 709 (±66) 536 (±50) 619 (±41) 897 (±60) 592 (±42) 725 (±35) 769 (±24) 547 (±17) 642 (±14) 794 (±8) 543 (± 5) 652 (±4) Infant Mortality Rate per 1,000 Combined 5.3 (±3.7) 4.3 (±2.4) 3.6 (±1.8) 3.8 (±2.4) 5.4 (±3.3) 4.2 (±1.1) 4.9 (±0.4) Life Expectancy Life expectancy is the average number of years that a person can be expected to live, assuming that age-specific mortality levels remain constant, and is influenced by increases or decreases in premature death (due to chronic illness, war, epidemics, accidents, etc.). As such, increases in life expectancy are indicators of better living conditions and effective prevention and treatment of health issues. Table 3.18 shows the life expectancy at birth in the sub-regions, Ontario, and the region. Statistically significant differences in life expectancy exist between subregions. People in the sub-region have the longest male (82.5 years) and female (86.6 years) life expectancy. People in and have significantly longer life expectancy than in and. People in also have a longer life expectancy than Central. The differences between sub-regions exist for male, female, and combined life expectancy. As expected, female life expectancy is significantly longer in all regions, by three to five years. life expectancy at birth for males (81 years) is longer than for males in Ontario (80.1 years) by almost one year. The difference in female life expectancy between and Ontario is not statistically significant (Table 3.18). 51 P a g e

52 Table 3.18: Life Expectancy at Birth (Years and 95% Confidence Intervals), Life Expectancy at birth (years) Male Female 79.7 (±1.0) 83.7 (±1.0) 82.5 (±0.8) 86.6 (±0.7) Central 80.9 (±0.6) 85.1 (±0.6) 82.1 (±0.9) 85.6 (±0.8) 79.0 (±0.9) 84.1 (±0.8) 81.0 (±0.1) 85.3 (±0.4) Ontario 80.1 (±0.1) 84.5 (±0.1) Combined 81.8 (±0.7) 84.7 (±0.5) 83.1 (±0.4) 83.9 (±0.6) 81.6 (±0.6) 83.2 (±0.2) 82.4 (±0.1) Premature Mortality Potential years of life lost (PYLL) is a measure of the total number of years of life lost due to premature death (the sum of the years between death and life expectancy across the population). In this section, we count the number of years lost before age 75. The region as a whole had fewer potential years of life lost per 100,000 population than Ontario. and, and Central lost more years of potential life per 100,000 than in and, and in the region as a whole (Table 3.19). The range of years lost per 100,000 is wide from approximately 2800 in to 4800 in, a 70% difference. These rates are not age-adjusted, so differences in the age distribution of the sub-regions may affect the overall number of potential years of life lost in the sub-regions. Table 3.19: Age-Adjusted Potential Years of Life Lost (Rate per 100,000 and 95% Confidence Intervals), Central Ontario Age-adjusted Potential Years of Life Lost 4812 (±108) 2814 (±63) 4437 (±65) 2979 (±76) 4778 (±93) 3877 (±34) 3987 (±11) Leading Cause of Mortality Overall, the top causes of potential years of life lost in Ontario and are the same: ischemic heart disease, lung cancer and intentional self-harm. Between the sub-regions, the top causes of PYLL are slightly different (Table 3.20). Ischemic heart disease is the leading cause in, and Central. Lung cancer is the top cause of PYLL in, with 640 years/100,000 population compared with the region (407 years/100,000). Lung cancer does not appear at all in the top three causes for. The number of potential years of life lost for intentional self-harm 492 years/100,000 in is higher than all other subregions. In the rural sub-regions of and, transport incidents 52 P a g e

53 (including accidents) are the third largest cause of PYLL. In the and sub-regions, perinatal conditions enter the top three causes of years of PYLL, and are the top cause of PYLL in. Table 3.20: Top Causes of Potential Years of Life Lost. Top causes of Potential Years of Life Lost (PYLL) Per 100,000 population a Ischemic heart disease (620) Intentional self-harm (492) Transport incidents (433) Ischemic heart disease (253) Perinatal conditions (231) Lung cancer (205) Central Ischemic heart disease (419) Intentional self-harm (323) Lung cancer (318) Perinatal conditions (319) Lung cancer (270) Ischemic heart disease (255) Lung cancer (640) Ischemic heart disease (593) Transport incidents (495) Ischemic heart disease (407) Lung cancer (348) Intentional self-harm (288) The term transport incidents is used rather than transport accidents to reflect the fact that not all deaths involving transport are accidental. Transport incidents involves all vehicles that are used for conveying persons or goods, including, but not limited to, automobiles, bicycles, trains, transport trucks, and airplanes. Overall, the top age-adjusted causes of death (Table 3.21) include heart disease, dementia, stroke, cancers, respiratory disease, diabetes, and diseases of the urinary system. The top three causes of death in and Ontario are ischemic heart disease, dementia, and lung cancer. Ischemic heart disease is responsible for between 15% ( and Central ) and 20% ( ) of deaths across the sub-regions. In, dementia is the top cause of death, at 16.8%, while the proportion of deaths due to dementia is between 10-13% in other regions. Lung cancer is consistently the third cause of death in all sub-regions. Age-adjusted death rates for the top ten causes vary a fair amount between the sub-regions. Table 3.21 shows the top ten causes of death in the region with age-adjusted rates of death, for each cause, per 100,000 population. People in have significantly higher rates of death for ischemic heart disease than other sub-regions. has a significantly higher rate of death for dementia than other sub-regions, which is higher than the rate by 35%. Ontario Ischemic heart disease (384) Lung cancer (311) Intentional self-harm (260) 53 P a g e

54 Table 3.21: Top Ten Causes of Death (age-adjusted rate per 100,000 and 95% Confidence Intervals), Rank Central Ontario 1 Ischemic heart disease 2 Dementia/ Alzheimer s (±13.9) 47.2 (±9.4) 75.5 (±11.7) 72.9 (±11.8) 84.3 (±8.3) 53.0 (±6.2) 86.2 (±15.5) 51.0 (±12.8) (±12.8) 46.9 (±8.5) 88.5 (± 5.1) 54.0 (±4.0) 94.5 (±1.7) 50.7 (±1.2) 3 Lung cancer 4 Cerebrovascular/ Stroke 51.1 (±10.0) 33.0 (±7.9) 38.6 (±8.3) 29.6 (±7.4) 51.7 (±6.7) 35.1 (±5.3) 47.6 (±10.7) 44.4 (±11.6) 57.1 (±9.3) 30.0 (±6.8) 49.6 (±3.9) 33.2 (±3.1) 48.1 (±1.2) 35.7 (±1.0) 5 Chronic lower respiratory/ COPD 6 Colon, rectum and anus cancer 7 Lymph, blood and related cancer 33.6 (±8.0) 30.0 (±7.7) 17.5 (±5.8) 25.2 (±6.9) 28.6 (±7.1 ) 22.8 (±6.3) 24.5 (±4.4) 27.2 (±4.8) 23.5 (±4.5) 26.2 (±8.6) 21.3 (±7.3) 25.9 (±8.3) 36.9 (±7.5) 25.2 (±6.3) 18.2 (±5.2) 28.5 (±2.9) 26.8 (±2.8) 21.5 (±2.5) 27.9 (±0.9) 23.6 (±0.8) 19.4 (±0.8) 8 Diabetes 9 Breast cancer 26.3 (±7.2) 15.2 (±5.5) 15.2 (±5.3) 12.9 (±4.7) 17.7 (±3.9) 15.3 (±3.7) 14.0 (±6.3) 15.7 (±6.1) 27.2 (±6.5) 12.3 (±4.4) 19.7 (±2.4) 14.1 (±2.1) 20.8 (±0.8) 14.1 (±0.6) 10 Urinary diseases 7.5 (±3.8) 7.9 (±3.9) 11.7 (±3.0) 8.4 (±5.0) 13.2 (±4.5) 10.4 (±1.8) 12.5 (±0.6) The top causes of death are different between age groups (Table 3.22). Top causes of death for children under 14 in are not shown due to small numbers. For youth 15-24, they are transport incidents, intentional self-harm and accidental poisoning; for adults 25-64, heart disease, lung cancer and colon cancer; for seniors 65-84, heart disease, lung cancer and dementia; and for older seniors 85+, they are dementia, heart disease, and cerebrovascular disease (stroke). 54 P a g e

55 Rank Table 3.22: Top Causes of Death by Age Group (% of total), Infants 0-1 yr 1 Perinatal conditions (68%) 2 Congenital malformations (25%) Children 1-14 yrs Youth yrs Transport incidents (34%) Intentional selfharm (24%) 3 Accidental poisoning (8%) a b Adults yrs Ischemic heart disease (12%) Lung cancer (11%) Colon cancer (6%) Seniors yrs Ischemic heart disease (14%) Lung cancer (11%) Dementia/ Alzheimer disease (6%) Older seniors 85+ yrs Ischemic heart disease (17%) Dementia/ Alzheimer disease (16%) Cerebrovascular/ Stroke (8%) Greyed out areas indicate a suppression of data due to a small number of cases. The term transport incidents is used rather than transport accidents to reflect the fact that not all deaths involving transport are accidental. Transport incidents involves all vehicles that are used for conveying persons or goods, including, but not limited to, automobiles, bicycles, trains, transport trucks, and airplanes. Preventable Mortality Of the top causes of death listed above, efforts to reduce mortality and potential years of life lost and to increase life expectancy could make a difference if targeted towards preventable D and/or treatable E causes of death. According to a Canadian Institute for Health Information (CIHI) report in 2012, Mortality from preventable causes (or preventable mortality) includes deaths from diseases with well-established and significant modifiable risk factors. In the World Health Organization s report Global Health Risks, the leading risk factors for mortality in higher-income countries, including Canada, were tobacco use and high blood pressure, followed by overweight and obesity, physical inactivity, high blood glucose, high cholesterol, low fruit and vegetable intake, exposure to urban air pollution, alcohol use and occupational risk factors. Among high-income countries, it has been estimated that, in 2004, these 10 risk factors accounted for 28% of deaths or 3.3 years of life-expectancy lost. 61 Table 3.23 below shows age-adjusted rates of preventable mortality by sub-region. The preventable mortality rate is highest for people in, which is almost twice the rate of the and Sub-Regions and significantly higher than the D Preventable causes could be avoided by reducing the number of initial cases of the condition/illness. Examples are enteritis, vaccine-preventable diseases, sexually transmitted diseases, hepatitis, HIV, some cancers, heart disease (50% considered preventable), aneurysm, COPD, lung disease, injuries (unintentional and intentional), alcohol related, drug use related, nutritional deficiency, diabetes (50%), adverse effects of medical care. 61 E Treatable causes of death could be avoided by reducing the number of people who die once they have a condition. Examples of conditions considered treatable are tuberculosis, bacterial infections, sepsis, malaria, meningitis, cellulitis, pneumonia, some cancers (colorectal, breast, cervical, testicular, uterus, bladder, thyroid, Hodgkin s, leukemia), 50% of heart and cerebrovascular disease, asthma, most respiratory conditions P a g e

56 average. The preventable mortality rate in and sub-regions is very low compared to the rates in all other sub-regions and in. Table 3.23: Age-adjusted Rates of Preventable Mortality (Rates per 100,000 and 95% confidence intervals), Central Age-adjusted Rates of Preventable Mortality 137 (+/-18) 72 (+/-11) 120 (+/-11) 88 (+/-13) 151 (+/-16) 120 (+/-6) The most common preventable causes of death based on crude rates in the region are lung cancer, ischemic heart disease, and intentional self-harm, followed by chronic lower respiratory disease, and liver disease. (Table 3.24) The top two most common causes of preventable mortality are lung cancer and ischemic heart disease in all sub-regions. The rates of lung cancer are much higher in (52.7) and (37.5) than the other sub-regions (range of ). The rate of chronic lower respiratory conditions is very high for people living in and is the third most common preventable cause of death of people living in and. People living in and, and Central have the highest rates of death from intentional selfharm with 15.2, 13.2, and 10.3 deaths per 100,000 people, respectively. Table 3.24: Top Preventable Causes of Death (Age-Adjusted Rate per 100,000), Rank a Lung cancer (37.5) Ischemic heart disease (24.9) Intentional self-harm (15.2) Chronic lower respiratory/ COPD (13.0) Transport incidents (10.8) Central Lung cancer (17.3) Ischemic heart disease (8.3) Intentional selfharm (5.8) Cirrhosis/ liver disease (5.8) Chronic lower respiratory/ COPD (4.6) Lung cancer (29.8) Ischemic heart disease (17.8) Intentional selfharm (10.3) Chronic lower respiratory/ COPD (6.9) Accidental poisoning (6.6) Lung cancer (25.5) Ischemic heart disease (10.1) Chronic lower respiratory/ COPD (6.4) Intentional selfharm (5.8) Transport incidents (5.8) Lung cancer (52.7) Ischemic heart disease (23.3) Chronic lower respiratory/ COPD (19.2) Intentional selfharm (13.2) Transport incidents (12.1) Lung cancer (30.8) Ischemic heart disease (16.1) Intentional self-harm (9.6) Chronic lower respiratory/ COPD (9.0) Cirrhosis/ liver disease (6.1) The term transport incidents is used rather than transport accidents to reflect the fact that not all deaths involving transport are accidental. Transport incidents involves all vehicles that are used for conveying persons or goods, including, but not limited to, automobiles, bicycles, trains, transport trucks, and airplanes. 56 P a g e

57 Mental Health and Addictions From the Mental Health Commission of Canada: 62 In any given year, one in five people in Canada experience a mental health problem or illness, with a cost to the economy of well in excess of $50 billion. Only one in three people who experience a mental health problem or illness and as few as one in four children or youth report that they have sought and received services and treatment. Of the 4,000 Canadians who die every year as a result of suicide, most were confronting a mental health problem or illness. Using OHIP physician visits data, the Institute for Clinical Evaluative Sciences (ICES) has developed an algorithm that allows the LHIN to estimate the number of individuals in each sub-region who experience a mental illness in a given year (Table 3.25). 63 Accordingly, approximately 232,000 people in the region are affected by a mental health/addictions condition; translating to a slightly higher proportion of residents (20.0%), as compared to Ontario (18.5%). The sub sub-regions with the highest proportion of residents affected by a mental health/addictions condition include Overbrook-Vanier- Beechwood, Nation-Alfred-Plantagenet, and the sub sub-region west of downtown (Figure 3.6). It is important to recognize that mental health is a particular concern within Indigenous communities. Although local Indigenous data is not available, suicide rates across the country are much higher within Indigenous groups and mental health issues are often a precursor to suicide. 62 Mental health problems strongly correlate with socio-economic factors such as employment and housing. A significant number of people living in homeless shelters have mental illness and addictions problems; and the majority of individuals with severe mental illness are unemployed. 62 Table 3.25: Prevalence Estimates for Mental Health/Addictions Condition, FY 2014/ Est. # persons with a mental health/addictions condition 2014/15 Est. % persons with a mental health/addictions condition 2014/15 a Central Ontario 26,647 49,883 80, ,075 35, ,659 2,322, % 19.0% 21.0% 21.0% 18.6% 20.0% 18.5% Indicator provided by the Institute for Clinical Evaluative Sciences, based on OHIP physician billings with codes specific to mental health and addictions diagnoses and care utilization, during fiscal year P a g e

58 Figure 3.6: Population Living with a Mental Health/Addictions Condition, FY 2014/ a Indicator provided by the Institute for Clinical Evaluative Sciences, based on OHIP physician billings with codes specific to mental health and addictions diagnoses and care utilization, during fiscal year Intentional Self-harm Approximately 1.4% of all deaths in Ontario are caused by intentional self- harm. 64 Most individuals who die through intentional self-harm were confronting a mental health problem or illness. Often, death by self-harm is preceded by attempts at self-harm that lead to the use of hospital services. In, there were 2059 emergency department visits for self-harm and hospitalizations for self-harm during 2015/16. Age adjusted rates per 100,000 for these hospital visits are provided in Table 3.26 below. The rate of emergency department visits for self-harm is almost double the Ontario average, perhaps due in part to emergency department use patterns overall. Hospitalization rates related to intentional self-harm were highest in Central and lowest in East and West. 58 P a g e

59 Table 3.26: Emergency Department Visits and Hospitalizations Related to Intentional Self- Harm, Age-adjusted Rates. Emergency Department Visits for Intentional Self-Harm per 100, 000 per fiscal year quarter (2014/ /16) Hospitalizations for Intentional Self- Harm per 100,000 per fiscal year (2012/ /17) Central Ontario Average rates per fiscal year quarter, calculated over several fiscal years; Akwesasne and out of LHIN postal codes are not included. Opioids Use and misuse of opioids is a significant health and policy issue in Ontario. 65 Opioids include prescription drugs, illicit street drugs, and counterfeit drugs that may contain powerful synthetic opioids such as fentanyl. Canada has one of the highest prescription rates for opioids in the world and prescription opioid use and misuse spans across all socio-demographic [groups]. 66 Ontario s dispensing levels per capita are five times higher than those in the U.K. and four times higher than those in Germany. 66 Traditionally, opioids were derived from naturally occurring substances. More recently, powerful synthetic opioids have been manufactured for specific medicinal uses (such as fentanyl patches). Synthetic opioids have now been found in illicit drugs in, including in counterfeit prescription pills with variable and sometimes lethal levels of the opioid. In, there were 709 emergency department visits associated with opioid related harm between and Age-adjusted rates for sub-regions are found in Table Generally, hospital emergency department use is higher in the more rural sub-regions of West and East, as compared to the sub-regions. Emergency department visits for opioid related harm follow a similar pattern as hospital use for intentional self-harm: higher rates in rural areas. Table 3.27: Emergency Department Visits for Opioid Related Harm, Age-adjusted Rates, FY 2012/2013 FY 2015/2016. Emergency department Visits for Opioid Related Harm per 100,000, per fiscal year quarter Central Ontario Average rates per fiscal year quarter, calculated over several fiscal years; Akwesasne and out of LHIN postal codes are not included. 59 P a g e

60 4. Health Service Provider Distribution and Capacity This chapter provides an overview of the distribution of health services across sub-regions, focusing on those funded by the LHIN and family/general practitioners. Per capita and per client service levels for select services help identify which sub-regions are relatively less well served. Provider Counts Table 4.1 provides basic counts of health service providers by sub-region. LHIN-funded services, Family Health Teams (one type of primary care arrangement) and the total number of family or general practitioners are listed. In general, health care, like many other services, is clustered in Central. Most of the Central providers, however, serve large numbers of clients and patients from other areas. A higher number of agencies does not necessarily translate to a higher volume of service, as the size of each operation varies. The following section more directly addresses the supply or level of services available relative to the population or to estimates of need. Table 4.1: Service Provider Counts by Sub-Region, 2017 LHIN records. Central Hospital sites a Community Health Centre Locations, including satellite sites a Assisted living services for high risk seniors spaces Mental Health and Addictions Agencies a Long Term Care Homes a Long Term Care Home Beds 1,177 1,281 2, ,582 7,569 Community Support Service Agencies a Home Care Service Provider Organizations c c Family Health Team locations a Family practitioners/general practitioners b a b c Counts of service locations. The size of each operation and the extent to which they provide service to people from other sub-regions varies. Emergency doctors without primary care practices and specialists are excluded. Home care service provider organizations (SPOs) are contracted by the LHIN to provide direct home care services. The total is less than the sum of the sub-region counts because some agencies are represented in multiple sub-regions. 60 P a g e

61 Capacity Relative to Population and Need Primary Care On an unadjusted per capita basis, Central has the highest concentration of general and family practitioners (GP/FPs) (Table 4.2). GP/FPs in that area, however, serve a disproportionate number of patients from other sub-regions. Central is the only sub-region with a higher number of patients coming in from other sub-regions than it has going out (Table 4.3). Within Central, per capita GP/FP ratios are highest in the downtown core, followed by an area in the east end (bounded approximately by the Aviation Parkway, Canotek Road, Regional Road 174 and the River). One notable exception in Central is the Bayshore area, with relatively few GPs/FPs per capita (Figure 4.1). has the fewest GP/FPs on a per capita basis, followed by. Those sub-regions, however, have the highest rates of primary care retention (i.e. patients visiting doctors in the same sub-region). is the most self-contained, with 72% of physician visits occurring within the sub-region followed by at 68%. This is likely because both areas include population centres far from (Cornwall and Hawkesbury in the East and Pembroke and Petawawa in the West). has the highest proportion of people seeking care in other sub-regions. Almost half (48%) of primary care visits by residents take place outside the sub-region. Of those who access services outside of the sub-region, almost two-thirds go to Central (Table 4.3). While there is much criss-crossing of sub-regions to access primary care, the region as a whole is largely self-contained, with people receiving their care within the LHIN. is the LHIN with the highest level of primary care retention: 93% of visits by residents take place within. The average for other LHINs is 80%. The high rate in is also true of other services. This is a reflection of s geography which borders Quebec to the North and East. The population is also concentrated far enough away from the region s boundaries. 61 P a g e

62 Table 4.2: Primary Care Capacity and Retention. # General/family practice physicians and nurse practitioners per 100,000 population (2017 LHIN records) a Primary Care retention: Proportion of primary care visits patients made to doctors in the same sub-region ( ) b, 67 a b c Central % 58% 63% 52% 72% 93% c Emergency doctors without primary care practices and specialists excluded. Based on the number of general practitioner/family practitioner visits in Excludes CHC physicians. Physician locations are based on their billing addresses, which sometimes differ from where services are provided (e.g. for physicians who work in multiple locations) 93% of primary care visits by patients took place within. Figure 4.1: Number of Family Practitioners/General Practitioners and Nurse Practitioners by Sub-Regions and Sub Sub-Regions, a Based on number of GPs/FPs and the population of each sub-sub-region, irrespective of where people actually access care. Emergency doctors without primary care practices and specialists excluded. 62 P a g e

63 Table 4.3: Sub-region of Patient Residence vs. Sub-Region of Primary Care Physician Visited ( residents only), Location of Physician Visited Central Other LHINs Total 683,801 (68%) 76,155 (8%) 70,932 (7%) 19,006 (2%) 6,941 (1%) 152,672 (15%) 1,009,507 (100%) Patient residence Central 76,239 (5%) 26,933 (1%) 13,928 (1%) 956,471 (58%) 337,586 (14%) 87,107 (7%) 452,302 (27%) 1,581,528 (63%) 388,010 (31%) 54,351 (3%) 290,191 (12%) 650,362 (52%) 21,716 (1%) 44,551 (2%) 46,510 (4%) 93,526 (6%) 211,135 (8%) 65,644 (5%) 1,654,605 (100%) 2,491,924 (100%) 1,251,561 (100%) a 12,490 (1%) 24,047 (2%) 97,375 (7%) 101,719 (8%) 958,703 (72%) 131,563 (10%) Based on the number of general practitioner/family practitioner visits in Excludes CHC physicians. Percentages may not sum to 100% due to rounding. Physician locations are based on their billing addresses, which sometimes differ from where services are provided (e.g. for physicians who work in multiple locations) Long Term Care Homes The number of long term care beds relative to the population over age 75 varies by about 30% across sub-regions. As shown in Table 4.4, has the highest level (100.1 per 1,000 people aged 75+) and Central has the lowest (72.2). Although it is useful as a measure of relative capacity to compare sub-regions, there are limitations. The measure does not quantify the level of need for long term care spaces. There were, for example, approximately 3,500 people on wait list for long term care beds through 2016 and occupancy hovered near 100% at all times. Also, it does not take into account sub-region variations for other factors that influence need, such as socioeconomic status, availability of related services (e.g. assisted living services for high risk seniors) and client preference for homes not in their own sub-regions. Table 4.4: Long Term Care Capacity, Long-term care beds per 1,000 population 75 years+ a a Central 1,325,897 (100%) Ontario Not adjusted (e.g. for socioeconomic status, population health or availability of other services) and does not take into account the inflow/outflow of residents originally from other sub-regions. 63 P a g e

64 Home Care Home care costs were calculated for clients whose services were coordinated by the Community Care Access Centre in These services are now managed by the LHIN as of Home care services include in-home personal support services (helping with activities of daily living), specialized therapy (such as speech language therapy and physiotherapy) and nursing care. After adjusting for client complexity and neighbourhood social and economic factors, there was a 16% difference between the highest ( : $3,514) and the lowest ( : $3,031) average cost per client (Table 4.5). Additional costs associated with driving to rural homes may be a partial explanation, however that does not explain why costs were slightly higher in Central than in. Sub-region patterns for seniors and adults were similar to the all-age totals. For paediatric clients, s costs were lowest. Differences in costs may reflect differences in the availability of certain services or professionals. Home care costs were also compared based on client mother tongue. The costs for clients whose mother tongue was neither English nor French was about 20% higher than for people whose mother tongue was either English or French. This held generally true across sub-regions. The reasons are unclear. We do know, however, that those with other mother tongues also tend to wait longer to receive their first home care service (see Table 5.11). Table 4.5: Home Care Capacity, Home Care service costs per client a Central $3,255 $3,180 $3,393 $3,031 $3,514 $3,343 Seniors (65+) $3,415 $3,403 $3,493 $3,116 $3,524 $3,471 Adults (18-64) $3,271 $3,057 $3,387 $2,982 $3,594 $3,320 Children (0-17) $2,481 $2,743 $2,766 $2,826 $3,170 $2,815 English mother tongue clients $3,260 $3,143 $3,319 $3,009 $3,577 $3,316 French mother tongue clients $3,042 $3,111 $3,274 $2,813 $3,339 $3,219 Other mother tongue clients $3,164 $3,662 $4,025 $4,048 $4,056 $3,939 a Based on the volume of services multiplied by reference costs for those services. Includes core services (personal support, nursing and specialized therapies, such as speech language therapy, physiotherapy, occupational therapy, social work, physiotherapy and others), but excludes case management, equipment and supplies and administration. Costs are adjusted based on the complexity of clients (using standardized assessments) and their neighbourhood socioeconomic and social status, based on postal code. Community Support Services 64 P a g e

65 The number of people within each sub-region who received Community Support Services were tabulated based on client postal code. Rates were calculated based on the number of people aged 75 and older, reflecting the primary target population for the four services assessed (Table 4.6). Adult Day Programs involve supervised programming in a group setting for people who require close monitoring and assistance with personal activities. The service helps participants achieve and maintain their maximum level of functioning, prevents or delays institutionalization and provides respite and information to caregivers. has the highest level of Adult Day Program services (27.8 per 1,000 people aged 75+), approximately double the services that are available in (12.3) and Central (14.5). Home Making Services include help with shopping, light housekeeping, paying bills, caring for children, laundry and training the client to perform these activities. Central has a level of Home Making Services (38.9 per 1,000 people 75+) that is about triple the rates in (14.6) and (11.8). Transportation Services involve driving people to medical appointments, shopping, various social activities and programs. The level of service is much higher in (181.0 clients per 1,000 population 75+) and in (226.1) than in the subregions (range ). Services tend to be farther from home in the rural areas and transportation alternatives that might be appropriate for some people (e.g. taxis and public transit) tend to be less available or more expensive. Assisted Living Services for High Risk Seniors are accessible on a 24-hour basis for people living either in a supportive housing setting or in their own residence. Services include homemaking and personal support. has the highest level (15.2 clients per 1,000 people 75+) and the lowest (4.4), nearly a fourfold difference. The level in Central is also relatively low (5.6). Table 4.6: Community Support Services Capacity, Adult day programs: clients per 1,000 population 75 years+ a Home Making services: clients per 1,000 population 75 years+ a Transportation services: clients per 1,000 population 75 years+ a Assisted Living Services for High Risk Seniors: clients per 1,000 pop 75 years+ a a Central Based on the number of services delivered by Community Service Agencies to clients within those sub-regions, irrespective of the locations of the agencies. Rates are not adjusted (e.g. for client complexity or area socioeconomic status). 65 P a g e

66 Community Mental Health and Addiction Services Expenses related to providing community mental health and addictions services within each subregion were estimated by distributing expenses at each agency across its service area. Sub-region expenses were then divided by the estimated number of people living with a mental health condition or addiction to create a ratio reflecting relative levels of service. Although Central is home to almost two-thirds of the mental health and addictions agencies (Table 4.1), it has the second lowest service level ($395) (Table 4.7). The other parts of were also low ($373 in and $411 in ) relative to the more rural areas ($453 in and $579 in ). Table 4.7: Community Mental Health and Addictions Services, Ratio of expenses for community mental health and addictions services to the number of people living with mental health conditions and/or addictions a a Central $453 $411 $395 $373 $579 $430 Based on LHIN-funded services in , including those based outside of the region that serve residents. Includes total costs for community mental health and addictions services/functional centres (fund type 1 and 2). Expenses were pro-rated to reflect agency service catchment areas, (e.g. The Royal s Assertive Community Treatment Teams cover all three sub-regions). The methodology to estimate the number of people living with mental health conditions and/or addictions is described in Chapter 3 (Population Health Status: Mental Health and Addictions). Hospitals A per capita hospital bed measure is not included here because some hospitals, particularly the tertiary and specialty centres in Central serve patients from all parts of and beyond. Instead, acute care bed occupancy summed across hospitals in each sub-region is provided as a rough proxy for capacity relative to need. hospitals have the lowest occupancy at 74% (Table 4.8). The other sub-regions range from 89%-95%. These are averages. On any given day and at any specific hospital, the rates can be much higher or lower. Table 4.8: Acute Care Hospital Occupancy, April-December Average occupancy of acute care hospital beds for hospitals within the sub-region a Central 74% 89% 95% 89% 91% 91% Weighted average of hospital reported occupied beds and beds in operation. and are based on one hospital each (Queensway-Carleton and Hôpital Montfort, respectively). Health Services Overview Excluding hospitals, looking across all long-term care, home care, community support service and community mental health and addictions measures reviewed, tends to have 66 P a g e

67 lower service rates. It was lowest on four of eight measures and not the highest on any of the eight. and tend to have higher service rates, even when transportation is excluded. Although per capita and per client measures don t tell the whole story of supply relative to need they do suggest that there may be inequity in the distribution of services. Historical growth in services has not always been equitable and has not always moved in lockstep with the growth and aging of populations. The data here will help to ensure more equitable service distribution moving forward. 67 P a g e

68 5. System Performance LHIN Primary Care System Performance For most people, primary care is the entry point to the health care system. Primary care provides health system navigation, illness prevention, health promotion, diagnosis and treatment, rehabilitation and counselling all as close to home as possible. In short, primary care helps people maintain their health, prevent problems, manage or treat health problems as they arise, and provide linkage and access to appropriate services throughout the health system. In this chapter, a snapshot of the performance of some of the elements of the primary health care system F will be provided. High-performing primary care is associated with improved equity, better health outcomes, lower mortality and a lower overall cost of health care. 70 Primary care performs best when it is accessible, coordinated, patient-centred, safe, effective, equitable, efficient and oriented to population health; 70 when residents have a regular primary care provider; when they can access that provider when they are sick; and when they have effective communication with their provider. Primary care is most effective when residents go to their doctor for preventative screening and health advice and their illnesses and chronic conditions are well managed. When the primary care system is not performing as well, we may expect to see less desirable outcomes, such as increased visits to the emergency department for issues that are best managed elsewhere, increased hospitalization for issues that could have been prevented or managed outside of the hospital, and increased hospitalization for chronic conditions. These indicators may also be related to the social and economic circumstances within the subregions. Studies show that people with lower income, lower education, and higher social isolation have higher rates of unhealthy behaviours and circumstances such as smoking and inadequate nutrition; have higher rates of chronic illness; and have poorer health outcomes overall. 70 So, if a sub-region has different socioeconomic circumstances than others, we can expect it also to have different rates and patterns of health care utilization. This chapter will provide a summary of a sub-set of possible measures of primary care performance in and each of the sub-regions, compared to the Ontario average, using the Ontario Health Care Experience Survey (HCES) data (collected between January 2013 and September 2016), as well as emergency room and inpatient hospital data (for ) extracted from Intellihealth databases. It is important to note that with both data sources, when we look at sub-region level and/or social and economic factors, sometimes have widely distributed F The primary health care system is broader than primary care and includes family physician offices/clinics, nurse practitioner-led clinics, interprofessional primary health care organizations, walk-in clinics, public health units, urgent care centres, emergency departments (particularly in rural areas), community care access centres, Telehealth Ontario, mental health and addictions agencies, midwives and so on. 68 P a g e

69 confidence levels resulting from data or from sampling smaller populations. Therefore, at times, estimates of results could have a fairly wide range. For the HCES, which was conducted by telephone in English and French, respondents had to be over 16 years of age (respondents were asked to respond on behalf of children living in the household), have a phone (landline or mobile) and a valid health card to respond. Some people such as newcomers, or those with unstable housing or very low income, may not have had the opportunity to provide their feedback. In addition, we are not able to reliably use language and Indigenous status data for these measures at a sub-region level. Instead, we will add some previously reported data from the 2016 LHIN Environmental Scan. Accessibility In, 95% of the residents who responded to the HCES in 2015 said they have a regular primary care provider (Table 5.1). The highest percentage of residents who reported having a regular provider was in (98%), and lowest was in Central (91.2%). Almost one in ten people in Central do not have a regular provider but would like one. Indigenous people, particularly in urban areas, and immigrants, particularly in rural areas, may be G less likely to have a regular primary care provider than the rest of the population. 71 Francophones were about as likely as Anglophones to have a regular primary care provider. 72 Ideally, residents are able to see their primary care provider on the same day or next day when they are sick. Of those who have a regular provider, 43.7% of residents said they are able to get an appointment on the same day or next day when they are sick (Table 5.1). The rate is about the same as the provincial average. The percent of residents that could get a same day or next day appointment ranged from 34.9% in to 47.5% in but none are significantly different from each other. However, the percentage of residents who said they waited more than 7 days for an appointment when they were sick was higher in (17.4%) than in (6.8%). The two sub-regions of and had higher percentages of people who have difficulty accessing after-hours care without going to an emergency department (72.7% and 68.4% respectively) than any of the other sub-regions, (as a whole) and Ontario (Table 5.1). G Differences were not statistically significant due to small sample size for sub-populations. 69 P a g e

70 Table 5.1: Access to Primary Care in Sub-regions (percentage and 95% confidence limit), January 2013 September Central Ontario Has a PC provider for checkups, when sick, etc. a 96.5% (±1.9%) 94.3% (±2.5%) 91.2% (±2.3%) 98.0% (±1.3%) 97.6% (±1.9%) 95.0% (±1.0%) 95.5% (±0.50%) Access to same day/next day appointment when they are sick 34.9% (±7.8%) 47.5% (±6.2%) 46.9% (±5.4%) 42.8% (±6.5%) 39.4% (±7.6%) 43.7% (±2.9%) 44.7% (±1.3%) Residents having difficulty accessing after-hours care without going to an emergency department 68.4% (±6.1%) 46.4% (±5.5%) 49.6% (±5.2%) 53.6% (±5.7%) 72.7% (±5.4%) 56.2% (±2.5%) 53.1% (±1.1%) a Excludes residents who said they did not want a regular provider Continuity of Care Table 5.2, below, shows the percentage of residents who said they saw their own provider (rather than someone else) when they were sick, one measure of the continuity of primary care. Approximately 78% of residents, slightly lower than the Ontario average, saw their own provider the last time they were sick. The range was between 76% and 80% in the subregions but there were no significant differences between the sub-regions on this indicator. Table 5.2: Residents Who Saw their Own Primary Care Provider the Last Time They Were Sick (percentage and 95% confidence limit), January 2013 September Central Ontario Percent who saw own provider (when sick) 78.9% (±6.5%) 75.8% (±5.1%) 78.2% (±4.6%) 79.9% (±5.2%) 75.7% (±6.4%) 77.7% (±2.4%) 81.3% (±0.7%) Patient Engagement The quality of the interaction with the provider can impact the effectiveness of the primary care service. In, 85.8% of residents said their primary care provider spent enough time with them, 88.2% agreed that their provider always or often involved them in decisions about their care, and 87.1% agreed that their provider gave them an opportunity to ask questions about the recommended treatment. Results for all three indicators were higher than the provincial average. Table 5.3 shows the results for the sub-regions,, and Ontario, which were not significantly different from each other. 70 P a g e

71 Table 5.3: Patient Engagement/Patient-centred Care (percentage and 95% confidence limit), January 2013 September Central Ontario Provider always or often involves them in decisions about their care Provider spends enough time 86.5% (±4.1%) 87.1% (±3.9%) 88.2% (±3.2%) 87.8% (±3.1%) 88.3% (±2.7%) 87.4% (±2.8%) 89.4% (±3.3%) 83.1% (±4.0%) 87.8% (±3.5%) 83.1% (±3.9%) 88.2% (±1.5%) 85.8% (±1.6%) 86.0% (±0.7%) 82.0% (±0.9%) Opportunity to ask questions 86.0% (±4.1%) 85.7% (±3.5%) 88.0% (±2.7%) 87.8% (±3.5%) 87.5% (±3.2%) 87.1% (±1.5%) 84.9% (±0.7%) System Indicators As mentioned previously, the primary care system can impact the performance of the health system in terms of emergency room use and hospitalization for certain conditions (Table 5.4). On the whole, with respect to emergency department visits for conditions best managed elsewhere H, the region has the same rate (6 per 1,000) as the Ontario average. The more rural sub-regions of and have significantly higher rates of emergency visits for conditions best managed elsewhere at 14 and 29 per 1,000 visits respectively; while the more central sub-regions are significantly lower at 2 per 1,000 visits. The higher rate in aligns with the Health Care Experience Survey result related to residents indicating that they had difficulty accessing medical care after hours without going to the emergency department. While emergency department visits for conditions best managed elsewhere could be an indicator of poor primary care access, rural areas may be the exception to this idea. Often, residents in rural areas may intentionally access their family doctor at the emergency department and the emergency department may be considered part of the primary care system. Emergency department data does not reliably indicate whether or not the visit was scheduled. While the sub-region has a significantly higher rate of emergency visits for conditions best managed elsewhere, has significantly higher rates of hospitalization for all chronic conditions I and ambulatory care sensitive conditions (ACSCs) J H Conditions designated as best managed elsewhere include: conjunctivitis, cystitis, otitis media, and upper respiratory infections (e.g., common cold, acute or chronic sinusitis and tonsillitis, acute pharyngitis, laryngitis or tracheitis, and others. I Conditions include diabetes, COPD, asthma, cancer, cardiovascular and cerebrovascular disease, arthritis, and Alzheimer s disease. J Conditions such as grand mal status and other epileptic convulsions, chronic obstructive pulmonary disease, asthma, heart failure and pulmonary edema, hypertension, angina, diabetes. 71 P a g e

72 than all other sub-regions. ACSCs are conditions that are considered to be usually prevented or managed in primary care. 74, 75 Table 5.4: Age-adjusted Health System Indicators (95% confidence limit), Central Ontario Emergency Department visits for conditions best managed elsewhere (rate per 1,000) (±1) 2.4 (±0.2) 1.9 (±0.1) 1.9 (±0.1) 14.0 (±2) 6.0 (±0.2) 6.0 Hospitalization for ambulatory care sensitive conditions (rate per 100,000) (±24) 52 (±8) 70 (±8) 61 (±11) 223 (±27) 93 (±6) 84 Hospitalization for select common chronic conditions (rate per 100,000) (±50) 377 (±24) 324 (±17) 411 (±29) 777 (±49) 442 (±12) 397 Socioeconomic Status and Social Support Factors The same three system indicators were looked at in relation to socioeconomic status (based on income, employment and education measures) and social support levels (based on household/ family structure and living alone measures) using the neighbourhood approach described on page Figures show the patterns for for emergency visits for conditions best managed elsewhere, hospitalizations for ambulatory care sensitive conditions, and hospitalizations for chronic conditions. All rates increase consistently as socioeconomic disadvantage increases. In simple terms, the poorest neighbourhoods have the highest rates. Considering neighbourhood social support, the gradient is not evident for emergency visits for conditions best managed elsewhere (5.1). The rate of hospitalizations for ambulatory care sensitive conditions is highest in the two most social-support disadvantaged quintiles (Figure 5.2), but the gradient for the rate of hospitalizations for select chronic conditions is the opposite of what might be expected (Figure 5.3). 72 P a g e

73 Rate per 1,000 Rate per 1,000 Figure 5.1: Age-adjusted Emergency Visits for Conditions Best Managed Elsewhere by Neighbourhood Socioeconomic and Social Support Quintiles in, Q1 Most advantaged Error bars are 95% confidence intervals Q2 Q3 Q4 Q5 Most Q1 Most Advantaged Disadvantaged Neighbourhood Socioeconomic Quintile Q2 Q3 Q4 Q5 Most Disadvantaged Neighbourhood Social Support Quintile Figure 5.2: Age-adjusted Hospitalization Rate for Ambulatory Care Sensitive Conditions by Neighbourhood Socioeconomic and Social Support Quintiles in, Q1 Most advantaged Error bars are 95% confidence intervals Q2 Q3 Q4 Q5 Most Q1 Most Advantaged Disadvantaged Neighbourhood Socioeconomic Quintile Q2 Q3 Q4 Q5 Most Disadvantaged Neighbourhood Social Support Quintile 73 P a g e

74 Rate per 100,000 Figure 5.3: Age-adjusted Hospitalization Rate for All Chronic Conditions by Neighbourhood Socioeconomic and Social Support Quintiles in, Q1 Most advantaged Error bars are 95% confidence intervals Q2 Q3 Q4 Q5 Most Q1 Most Advantaged Disadvantaged Neighbourhood Socioeconomic Quintile Q2 Q3 Q4 Q5 Most Disadvantaged Neighbourhood Social Support Quintile 74 P a g e

75 Hospital and Cross-Sector System Performance In this section we examine s performance on metrics that cut across two or more sectors of the health care system. For example, the data for the percentage people in hospital awaiting an alternative level of care is counted in the hospitals, but dependent mostly on resources available outside of the hospital sector (e.g. community support services). Cross-sector measures of performance are instrumental to understanding how well the LHIN is functioning in its integration role. Health Link Areas were established across all LHINs in the province to provide coordinated care for people living with multiple chronic conditions and complex needs. Health Links is a patientcentered approach of coordinated care across primary care, community care, and hospital providers. In the region, implementation of the Health Links approach to coordinated care began in November As of March 2017, Health Links are operational across all geographic areas of the region. As of the end of February 2017, over 1,000 patients with complex needs have a coordinated care plan. Table 5.5 shows the proportion of people with coordinated care plans by sub-region and the sub-regional variation reflecting when the different Health Links Areas began operation. In , on average, more than one of every 8 (12.9%) acute care hospital beds in the area were occupied by people waiting for an alternate (more appropriate) level of care. High rates of people awaiting alternative levels of care (ALC) can be a reflection of inadequate capacity or integration with community-based services, complex continuing care, rehabilitation services and long-term care beds. The rates are also impacted by hospital discharge planning and practices. The 2015/16 rate (12.9%) was slightly better than the Ontario rate of 14.5% (Table 5.5). Patients from the Central sub-region had the highest rate (15.9%) while (10.8%) and (10.0%) had the lowest. These rates are reported based on the sub-region of patient residence irrespective of where patients were hospitalized. As reported in Table 3.12, the rate of readmissions within 30 days for certain chronic conditions is impacted by the patients health, the quality of hospital care, discharge planning, the effectiveness of handoffs between hospitals and primary care, and the accessibility and quality of supports in the community., as a whole, performs better than Ontario (14.7% vs. 16.5%). The best performing sub-regions are (12.2%) and (12.7%). 75 P a g e

76 ALC Days (%) Table 5.5: Measures of Cross-Sectoral Performance. 76, 77 Central Ontario Percentage of high needs patients with a coordinated care plan (January 2017) a, 77 Percentage of Alternate Level of Care Days (% ALC)( 2015/16) day hospital readmission rate for selected chronic conditions (2016/17 Q2) 78 5% 3% 1% 1% 7% 5% 12.5% 12.1% 15.9% 10.0% 10.8% 12.9% 14.5% 16.4% 12.7% 15.3% 12.2% 14.6% 14.7% 16.5% a Patient sub-region is based on postal code. Where postal code was not available, patients were allocated based on their Health Link s geographic catchment(s). 76 Socioeconomic Status and Social Support Factors The readmissions and alternate level of care measures were also analyzed in relation to socioeconomic status (based on income, employment and education measures) and social support levels (based on household/ family structure and living alone measures) using the neighbourhood approach described on page 14. The proportion of patients awaiting alternate level of care was highest in neighbourhood with less social support. Specifically, the rate was 1.6 times higher among those in Q5, the quintile with the least social support, compared with those in Q1. (Figure 5.4). The pattern in relation to neighbourhood socioeconomic status was less clear. Figure 5.4: Figure 5.5: Percentage of Alternative Level of Care (ALC) Days by Neighbourhood 1, 77 Socioeconomic and Social Support Quintiles in, % 16% 14% 12% 10% 8% 6% 4% 2% 0% 12.9% 12.8% 12.3% Q1 Most advantaged 11.1% 12.4% 9.8% Q2 Q3 Q4 Q5 Most Q1 Most Advantaged Disadvantaged Neighbourhood Socioeconomic Quintile 10.6% 11.8% 13.2% 15.7% Q2 Q3 Q4 Q5 Most Disadvantaged Neighbourhood Social Support Quintile 76 P a g e

77 30-Day Readmission for Certain Chronic Conditions (%) The most disadvantaged neighbourhoods in terms of social supports had higher rates of readmissions within 30 days for select conditions (Figure 5.5). The rates were also somewhat higher in both the most and least socioeconomically disadvantaged neighbourhoods. The overall numbers of admissions and readmissions per capita, however, are both considerably higher in the more disadvantaged neighbourhoods. Figure 5.5: 30 Day Readmission for Certain Chronic Conditions by Neighbourhood 1, 77 Socioeconomic and Social Support Quintiles in, % 16% 14% 12% 10% 8% 6% 4% 2% 0% 15.2% Q1 Most advantaged 12.4% 13.1% 14.6% 15.6% Q2 Q3 Q4 Q5 Most Q1 Most Advantaged Disadvantaged Neighbourhood Socioeconomic Quintile 14.1% 14.2% 13.5% 14.3% 16.0% Q2 Q3 Q4 Q5 Most Disadvantaged Neighbourhood Social Support Quintile The proportion awaiting alternate level of care was also compared based on patient mother tongue (Table 5.6). Those with French as a mother tongue had a higher proportion of ALC days (19%) than those with English mother tongue (16%) or those with Other mother tongues (12%), although the results are based on very preliminary and limited data. About half of the July-September 2016 records included mother tongue information and one hospital contributed a disproportionate number of records. Further analysis and more data is needed to disentangle the role of patient language from the hospital-specific rates. Readmission rates were similar between those whose mother tongue was English or French. People with Other mother tongues had the highest readmission rates (Table 5.6). Again, results are preliminary, based on limited data. 77 P a g e

78 Table 5.6: Cross Tabulation of Percent ALC Days and 30 Day Readmission for Certain Chronic Conditions by Mother Tongue. 77 Mother Tongue a Percent ALC days (2015/16) Percent Number of discharges Percent 30-Day Readmissions for Certain Chronic Conditions (2016/17 Q2) b Number of readmissions English 16% 6,212 11% 112 French 19% 1,961 12% 45 Other 12% 94 14% 41 Not recorded 18% 0% a b c See Chapter 2 (Population Demographics: Sub-Populations: Immigrants, Aboriginal, and Language) for a description of how the language variable was derived. Q2 2016/17 data only. No repeat visits past the last day of the time period examined. Rate of repeats will be lower than expected. Language data collected from the Discharge Abstract Database as part of a special project number 631 at hospitals. The rate of hospital discharges on the weekend is, in part, a reflection of health system provider coordination and access to support services in the community. It is also a measure of how efficiently hospital beds are managed. On weekends, hospitals and community support services typically have less staff, which can delay patient discharges and transfers until the following week. While weekends represent 28.6% of days in each week (2/7), across, only 22.8% of patients are discharged over the weekend. Patients from and have higher rates of weekend discharges, while patients from Central, and have lower rates of weekend discharges. (Table 5.7) Fridays have the highest number of hospital discharges (18%) and Mondays the lowest (13%). K The proportion of people who had an emergency department visit in their last two weeks of life reflects, in part, the availability of community supports for end-of-life care. The rates were similar across the sub-regions except in. The rate in was higher than all the others (43.7% vs. 35.7%-38.7%) (Table 5.7). The rate of palliative care patients who were discharged from hospital with home supports is another proxy measure of how well end-of-life patients are cared for. Overall, (88%) performs better than Ontario (84%). Performance was best in (93%) and (90%). s value (82%) was the lowest among sub-regions (Table 5.7). K Data retrieved from the Discharge Abstract Database, unpublished results. 78 P a g e

79 Table 5.7: Hospital Discharges on the Weekend and End of Life Care, , 79 Central Ontario Percent of discharges on the Weekend ( ) Percent of palliative care patients discharged home from hospital with home supports a, b, 79, 80 Decedents with emergency department visit in last 2 weeks of life ( ) a, 79, % 24.1% 22.0% 23.4% 22.8% 22.8% 82% 90% 85% 93% 87% 88% 84% 35.7% 38.7% 36.6% 36.6% 43.7% 38.2% a Matching records from the NACRS and Deaths databases. 72, 78 b Results differ from (and should not be directly compared) with those reported by the Ontario Palliative Care Network due to differences in methodology. Table 5.8 provides responses from the Ministry of Health and Long-Term Care s Health Care Experience Survey regarding individual s overall satisfaction with health care in their community. 73 The LHIN has a significantly higher rate (89%) compared to Ontario (87%), but this was not the case for all sub-regions (Table 5.8). and had lower overall satisfaction (87%) compared to the sub-regions (89.3%- 90.5%). However, these differences were not statistically significantly. Table 5.8: Overall Satisfaction with Care in the Community (95% confidence intervals), January 2013 September Central Ontario Overall satisfaction with health care in the community (Jan 2013-Sep 2016) 87.1% ( ) 90.4% ( ) 89.3% ( ) 90.5% ( ) 87.2% ( ) 89.1% ( ) 86.9% ( ) 79 P a g e

80 Home and Community Care System Performance Home and community care supports people who need health care services in their home, at school, and in the community. The provider formerly known as the Community Care Access Centre (CCAC), now the LHIN, plays a key role in home and community care by linking clients to public and private services. In May 2017, the LHIN assumed the home care mandate when the CCAC merged with the LHIN. Home and community care consists of various direct and non-direct services. Non-direct services include case management, home care assessment, health service management, and long-term care placement management. Direct services include rapid response nurses, mental health and addictions nurses, hospice palliative care nurse practitioners, and geriatric assessment services. Other health services, such as nursing, personal support, are delivered to patients by contracted health service providers. Therapy services, such as physiotherapy, occupational therapy and speech language therapy are delivered both directly and by contracted providers. Home care performs best when services are timely and equitably distributed based on patient needs. High performance in home care results in patients staying healthier in their homes longer and reducing or avoiding time in hospitals and long-term care homes. Wait times There is not much variation in wait times across s sub-regions. All sub-regions are close to meeting the target of 95% for receiving a nursing visit within five days of authorization. Sub-regions are not meeting the target (95%) for the five-day service wait time for personal support services. (Table 5.9). Figure 5.6 explains why personal support services were delivered to patients after 5 days. The reasons are grouped into four categories: resource constraints, pre-planned care plans, patient availability, and service provider delays. 80 P a g e

81 Figure 5.6: Description of Target Met & Target Not Met for PSS Five-Day Service Wait Time, FY 2015/ CCAC Resource Constraints, 13.8% Service Received within 5 days, 74.6% Pre-Planned, 8.4% Patient Not Available, 1.1% Service Provider Delay, 2.1% CCAC Resource constraints: The service start date was delayed beyond 5 days due to CCAC budget limitations. Pre-Planned: The service start date was delayed more than 5 days based on patient needs. Patient availability: The patient was not available for some reason (e.g. not home when worker arrived). Service Provider delay: The contracted service provider organization was unable to meet the 5 day requirement (e.g. due to staffing challenges). All sub-regions met the LHIN target for the 90 th percentile wait time of 21 days for patients referred from hospital to first Home Care service. Patients referred from the community waited longer than the target of 21 days, ranging from 47 days in to 60 days in Central. All figures are based on fiscal year , however it is important to note that wait times have varied considerably over time. 81 P a g e

82 80, 81 Table 5.9: Home Care Service Wait Time, FY 2015/2016. % Home Care Patients who received their Nursing Visit within 5 days of the date they were authorized for Nursing Services a % Home Care Patients who received their Personal Support Services within 5 days of the date they were authorized for PSS Services a 90th Percentile Wait Time from community for Home Care In-Home Services: Application from Community setting to first Home Care service b 90th Percentile Wait Time from community for Home Care In-Home Services: Application from Hospital setting to first Home Care service b a b Central 93.9% 92.8% 92.7% 93% 93.6% 93.1% 73.6% 72.3% 74.2% 77.8% 75.4% 74.5% 52 days 47 days 60 days 57 days 52 days 55 days 14 days 17 days 19 days 17 days 13 days 16 days Five day wait time metrics reflect the time from when the service was authorized to when it was received. The nursing visits indicator includes all clients 19 and older. The Personal Support Services indicator includes adults with complex care needs. The LHIN target for both indicators is to that 95% of clients receive service within 5 days. 81 The 90th percentile metrics identify the maximum number of days that 90% of patients wait. 10% of patients wait longer. The number of days is calculated from the time of referral until a direct care service is received. Patients receiving Case Management services only, long-term care placement assistance, or waiting for a service for more than one year are excluded. The LHIN 90 th percentile target is 21 days. Beyond sub-regions, we also looked at how wait times differed based on socioeconomic status and patient mother tongue. Socioeconomic status is based on where patients live using the method described on page Across the four wait time metrics, people living in the most socioeconomically disadvantaged neighbourhoods (bottom 20%) had shorter wait times than those in the most advantaged neighbourhoods (Table 5.10). Differences were generally modest and the trends across all economic quintiles, from 1 to 5, were not consistent. The longer wait for home care in more advantaged neighbourhoods may reflect less urgent needs (i.e. less complex care requirements), more supports or more ability to pay for private services. It may also be related to the prioritization process for home care services. Services are prioritized based on formal assessments, including patients resources and available supports from other health services, caregivers, and informal sources. 82 P a g e

83 Table 5.10: Home Care Service Wait Time by Neighbourhood Socioeconomic Quintile, , Wait Time Indicator Quintile 1 most advantaged Quintile 2 Quintile 3 Quintile 4 Quintile 5 most disadvantaged % Home Care Patients who received their Nursing Visit within 5 days of the date they were authorized for Nursing Services % Home Care Patients who received their Personal Support Services within 5 days of the date they were authorized for PSS Services 90th Percentile Wait Time from community for Home Care In- Home Services: Application from Community setting to first Home Care service 90th Percentile Wait Time from community for Home Care In- Home Services: Application from Hospital setting to first Home Care service 92.6% 93% 93% 93.3% 93.8% 93.1% 73.9% 70.9% 74.8% 73.3% 77.7% 74.5% 60 days 54 days 50 days 50 days 53 days 55 days 18 days 17 days 15 days 15 days 15 days 16 days Wait times among those with English and French as a mother tongue were fairly similar across all four metrics (Table 5.11). Those whose first language was neither English nor French, however, waited longer. This held true across all measures but was most pronounced 40% higher among those awaiting home care service from within a hospital (21 days vs. 15 days for those with English and French as a mother tongue). Table 5.11: Home Care Service Wait Time by Patient Mother Tongue, English French Other % Home Care Patients who received their Nursing Visit within 5 days of the date they were authorized for Nursing Services % Home Care Patients who received their Personal Support Services within 5 days of the date they were authorized for PSS Services 90th Percentile Wait Time from community for Home Care In-Home Services: Application from Community setting to first Home Care service 90th Percentile Wait Time from community for Home Care In-Home Services: Application from Hospital setting to first Home Care service 93.2% 93.2% 91.8% 93.1% 74.8% 75.2% 71.2% 74.5% 53 days 57 days 62 days 55 days 15 days 15 days 21 days 16 days 83 P a g e

84 Palliative Care At the end of life, it is particularly important to receive care in the place where you are most comfortable. Home care clients are asked about their preferred location and this can be compared with where they actually spend their last days. Overall, most (90%) of palliative home care patients died in their preferred location (Table 5.12). The proportion was highest in Central (93%) and lowest in (85%). Almost everyone who indicated a preference to die in hospital (96%) did die there. The proportion who preferred to die at home or in residential hospice who actually did die there was slightly lower (90% and 89%). The true picture can vary as some people s preferences change without being updated on their file. Table 5.12: Proportion Who Died in Their Preferred Location, Palliative Home Care Patients, 80, a, b Central Home 86% 89% 92% 93% 87% 90% Hospital 97% 98% 94% 96% Residential Hospice 92% 92% 91% 89% Total c 90% 85% 93% 89% 90% 90% a Based on dividing the number of people who preferred to die in that location and did die in that location by all who preferred to die in that location. Excludes client for whom a preferred location was not recorded. b Greyed out areas represent numbers that were suppressed due to counts below 50. c The total also includes people who preferred to die in other locations (e.g. long term care home or nursing home) Where people actually died varied more (Table 5.13). Palliative home care patients in and were more likely to die at home than those in the other sub-regions but less likely to die in residential hospice. People in were most likely to die in hospital. Table 5.13: Actual Place of Death, Palliative Home Care Patients, , a Actual Place of Death Central Home 43% 65% 37% 69% 40% 45% Hospital 35% 30% 25% 26% 26% 27% Residential Hospice 22% 1% 37% 3% 33% 27% Other Location 0% 3% 1% 3% 1% 1% Total 100% 100% 100% 100% 100% 100% a Other location includes long term care homes and nursing homes. 84 P a g e

85 Mental Health and Addictions Two indicators have been defined within the Ministry LHIN Accountability Agreement to monitor performance of mental health and addictions services: emergency department re-visits for substance use, and emergency department re-visits for mental health problems. The rationale behind these indicators is that, if a person needs mental health or addictions care, they should be able to access that care quickly. The emergency department may be an appropriate place to access care in a crisis and, in a high performing system, the individual should be promptly followed by other care alternatives within the community or hospital. If effective, these care alternatives should reduce the need for another emergency department visit. The indicators are calculated as a ratio of emergency department re-visits within 30 days following the initial visit, divided by the total number of visits. The initial visit may be a visit with the principle presenting problem as either a substance abuse issue or a mental health issue. The principle problem on the re-visit determines if it is categorized as a substance abuse re-visit or a mental health re-visit. During the last reported quarter (Q3 2016/17): 554 individuals re-visited emergency departments for a mental health problem, and 191 individuals re-visited emergency departments for a substance abuse problem. Central residents revisit the emergency department for a mental health or substance abuse problem at a higher rate than all other sub-regions (Table 5.14). Contributing factors may include increased severity of mental health and addictions problems co-occurring with lower socio-economic status indicators. There may also be different care seeking patterns within the Central sub-region. The LHIN has explored in greater detail the relationship between these performance indicators and measures of income and social support. 82 Subpopulations residing in local areas across that have the lowest income and social support also tended to have highest mental health and substance abuse emergency department revisit rates. Table 5.14: Age-adjusted 30-Day Repeat Emergency visits for Mental Health or Substance Use related problems, Q2 2016/ Day Repeat Emergency Department Visits for Mental Health (%) 30-Day Repeat Emergency Department Visits for Substance Abuse (%) Central P a g e

86 Conclusion The intent of this report is to provide baseline information to guide health system priority setting and planning in each sub-region. This report is a result of an unprecedented collaboration of key stakeholders across various sectors of the health system including local public health units, community-based providers, hospitals and the LHIN. Thanks to this strong collaboration, the scope of this report is broad. However, additional information and further interpretation is needed to assess opportunities and challenges. The data in this report should be considered alongside other sources of information relevant to each sub-region and interpreted with input from stakeholders who have a good understanding of each respective sub-region. Engagement will continue with stakeholders, including patients and caregivers, to gain local knowledge that will help set priorities and inform planning. Health system planners and providers in each subregion can use this information to help identify opportunities for equity, improved access to, and effective integration of health services. We look forward to collaborating with community members to make optimal use of the health resources within our region and reduce inequities. 86 P a g e

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93 78. Ministry of Health and Long-Term Care. National Ambulatory Care Reporting System Database. IntelliHealth ONTARIO Ministry of Health and Long-Term Care. Deaths Database. IntelliHealth ONTARIO Community Care Access Centre ( Local Health Integration Network). Client Health and Related Information System (CHRIS). FY Community Care Access Center ( Local Health Integration Network). Client Care Model: Board Meeting, April 25, PowerPoint presentation (available at 25%20CCM%20presentation%20Final.pdf). 82. Local Health Integration Network. Measuring Performance: LHIN 2016/17 Second Quarter Report. January 2017 (available at 93 P a g e

94 Appendix A: Sub-Region Summaries 94 P a g e

95 (WC) has the smallest population and the lowest population density. The population is concentrated in towns on the edge of, including Arnprior, Carleton Place, and Kemptville and in other cities and towns, including Pembroke and Petawawa (a Canadian Forces Base). It also includes large rural areas and many smaller villages. WC has the largest proportion of their population over 65 at 20.2%. Over the next 10 years, the 65+ populations will grow 3.8% per year while the population under 65 decreases by 0.5% a year. Relatively homogeneous socio-culturally; WC has the lowest proportion of minorities, immigrants, and same sex couples, but the second highest proportion of people with Indigenous identity (6.7%). 91.2% of the population speaks English as a mother tongue. WC includes Algonquins of Pikwàkanagàn First Nation in the Golden Lake area. Indigenous health services include a family health team, community support, assisted living, and mental health services. Overall, social economic indicators are lower than other sub-regions; the unemployment rate is the highest and education levels are the 2nd lowest among sub-regions. General health measures are poorer than the average. The percent of the population with risk factors such as consuming less than 5 fruits and vegetables a day, physical inactivity, exceeding low-risk drinking guidelines and smoking are high relative to other sub-regions. The percentage of the people who have a regular primary care provider is highest among sub-regions. WC has the second highest rate of acute care hospitalizations for chronic conditions and the second highest rate of cancer among sub-regions. WC had the highest rate of ED visits for opioid-related harm and also for intentional self-harm. 8 hospitals are located in. WC has the 2nd highest count of many other health service providers including Community Health Centre locations, Assisted Living Services space for high risk seniors, Mental Health and Addictions agencies, Community Support Service Agencies, and Family Health Team locations. 95 P a g e

96 (WO) has the 2nd largest population among subregions. The population is concentrated in the Kanata-Stittsville and Barrhaven. It has relatively few seniors and relatively more children. WO experienced the highest population growth in between 2006 and 2011 and had a slightly higher birth rate between 2013 and WO has proportionately fewer immigrants and visible minorities than Central but more than in the rural areas. has the 2nd lowest (7.3%) proportion of the population who speak French as their mother tongue. WO has the lowest proportion of people with low income as well as the lowest proportion of seniors living alone with low income. Education levels were highest. WO reports higher rates of very good/excellent general health than the other sub-regions. The percent of the population requiring help with at least one activity of daily living (8.7%) is relatively low. WO had the highest rate of flu vaccination and the lowest rate (17%) of people classified as heavy drinkers. WO had the second lowest rate of acute care hospitalizations for common chronic conditions. The second lowest percent of the population categorized as patients with high need based on Health Link definition. WO had the second lowest proportion of people with mental health/additions condition and the second lowest intentional self-harm rate. WO has generally fewer HSPs compared to Central and the rural sub-regions. The Queensway Carleton Hospital is the only hospital located in WO. There are also 2 Mental Health and Addictions agencies, 7 Long Term Care Homes, 2 Community Support Service Agencies, and 3 Family Health Team locations. 96 P a g e

97 Central About one third of the population in the LHIN lives within Central (34.1%), the dense urban core. Central is the most culturally diverse area, similar to urban centres elsewhere. It has the highest proportion of visible minorities, immigrants, same sex couples and people with mother tongues other than English or French. Central has the highest proportion below the low income cut-off and the highest proportion of single parent households. The proportion of seniors living alone with low income (10.4%) in Central is 3 to 5 times higher than other sub-regions (range: 2.0% to 3.7%). It has the lowest proportion of children (age 19 and younger), at 19.2% Central has the lowest infant mortality rate at 3.6 per However, other general health measures are placed in the middle of the 5 sub-regions. Similarly, the rates of risk factors are in the middle, except for the proportion of people with a regular primary care provider, which is lowest. CO has the lowest rates of acute care hospitalizations for common chronic conditions. CO has the lowest rate of fall-related ED visits among seniors. CO has one of the highest proportions of people with mental health or addictions conditions. Within CO, at the more local level, rates were highest in West Central (23%) and Overbook-Vanier- Beechwood (24%) areas. ED visit rates for intentional self-harm were about average. Central has 7 hospitals and 7 CHCs. It also has the highest counts of all HSPs, many of which provide service to large numbers from other sub-regions and beyond. Indigenous health services in CO include Wabano Centre for Aboriginal Health, focusing on providing health care services to the urban Indigenous population, and Akausivik Inuit Family Health Team. 97 P a g e

98 EO s population is concentrated in Orléans. The sub-region experienced the 2nd highest population growth among sub-regions between 2006 and 2011 at 2.6%. EO has a relatively low proportion of seniors (14.4% aged 65 and older), and a high proportion of children (24.9% age 19 and younger). EO has proportionately fewer immigrants and visible minorities than Central but more than in the rural areas. EO has the 2 nd highest proportion with French as a mother tongue (27.6%). The social economic status of EO is similar to and both are better overall than other sub-regions. EO is tied with for the lowest proportions of people with low income, and EO has the lowest rates of unemployment. Education indicators are 2 nd best. EO has the highest rates of self-reported very good/excellent general health and very good/excellent mental health. It also has a lower proportion of the population requiring help with at least one activity of daily living. EO residents are more likely than residents of other sub-regions to have a regular primary care provider. They have relatively high levels of physical activity but relatively high rates of people classified as heavy drinkers and overweight/obese. EO has the highest case rates for arthritis-related hospitalizations and new cases of female breast cancer. EO has the lowest rate of ED visits for falls among seniors. EO has a relatively high percent of people living with a mental health or addictions condition, but it has low rates of ED visits for intentional self-harm. Similar to, EO has relatively few health service providers/locations. Montfort is the only hospital. EO has 3 Mental Health and Addictions agencies, 7 Long Term Care Homes, and 8 Family Health Teams. 98 P a g e

99 The population of (EC) is concentrated in towns on the edge of, including Rockland, Embrun and in Cornwall and Hawkesbury. EC also includes large rural areas and many smaller villages. EC has the 2 nd largest proportion of their population over 65 at 19.7%. Between 2017 and 2026, the population over 65 is projected to grow 4.2% annually and the number under age 65 will decrease 0.6% annually. EC has the highest proportion of people with French as a mother tongue at 41.8% (the next highest is 27.6%) and relatively low percentages of immigrants, visible minorities, and same sex couples. The proportion who are Indigenous is highest in EC, primarily because it includes Akwesasne, the 2 nd most populous First Nation community in Canada. Akwesasne contains an Aboriginal Health Access Centre, as well as community support services and a long-term care home. The proportion with low income and the unemployment rates in EC are below the regional average. Among the proportion of people 25 year to 64 years old, 54.4% have post-secondary education in EC compared with 72.6%-77.0% in the sub-regions. General health status measures in EC are generally worse than other sub-regions. The proportion of people with self-rated general health as very good/excellent is the lowest. The proportion of people requiring help with at least one activity of daily living was highest as was the infant mortality rate. The EC population also has a higher proportion of people with certain risk factors, including a low proportion who consume 5+ fruit or vegetables daily, a low flu vaccination rate, a high percent of people who are inactive during leisure time and high smoking rate. EC had the highest rates for acute care hospitalization for common conditions including the highest hospitalization rates for diabetes, ischemic heart disease, heart failure, COPD and cancer and 2 nd highest for arthritis, asthma, cancer and stroke. EC has the 2nd highest rate of seniors fall-related ED visits. Although EC has a relatively low proportion living with a mental health or addictions conditions, it has high rates of ED visits for opioid-related harm and intentional self-harm. There are 5 hospitals are located in EC and the EC sub-region has the most Long Term Care homes with 18. EC has 6 Community Health Centre locations and 5 Mental Health and Addictions agencies. 99 P a g e

100 Appendix B: At a Glance Comparison of Sub-Regions vs. Average Indicator Central POPULATION CHARACTERISTICS % Higher or Lower (relative difference ƚ ) than Overall Left is lower; Right is higher Region Average Population Density Persons per square km (2011) Birth rate (births per 1,000 population) ( ) % Age 19 and Younger (2016) % Age 65 and Older (2016) % Female (2015) % annual historic growth ( ) % projected annual growth ( ) % projected annual growth ( ), for 65+ population % projected annual growth ( ), for population under age 65 % who identify as Indigenous % population who are immigrants % of population who are recent immigrants (arrived within ) % visible minority % of people in same sex couples % who include French as mother tongue % who include English as mother tongue % who include other mother tongues 78.3% 137.7% % 136.2% 46.4% % 1.9% 2.9% 1.9% 1.9% % 17.2% 14.8% 10.6% 3.3% 22% 21.2% 19.1% 4.3% 13.6% 18.3% 17% 1.8% 0.6% 0.6% 0.6% 0.8% % 133.3% 88.9% 88.9% 44.4% 0.9% 63.6% 27.3% 27.3% 27.3% 63.6% 1.1% 11.6% 2.3% 2.3% 2.3% 2.3% 4.3% 200.0% 80.0% 80.0% 80.0% 220.0% 0.5% 116.1% 54.8% 51.6% 45.2% 158.1% 3.1% 68.5% 19.0% 46.2% 3.3% 67.4% 18% 84.0% 16.0% 84.0% 20.0% 80.0% 2.5% 89.2% 21.6% 54.0% 8.5% 83.0% 18% 50.0% 37.5% 75.0% 50.0% 37.5% 0.8% 71.3% 61.2% 18.6% 55.9% 122.3% 19% 36.4% 11.1% 7.0% 12.6% 16.2% 67% 75.7% 28.5% 56.9% 14.6% 84.7% 14% ƚ Bars are based on the relative percent difference between sub region value (e.g. 10% of people having an illness is 100% worse than 5%) and the average. Bar lengths are scaled using the percent differences for all indicators in this section (up to +/ 100%), so the longest bars represent the biggest differences. For actual statistics and other information, see the relevant chapter in this report. a Tested for significant difference between each sub region and (p<0.05) * Significant difference between sub region and 100 P a g e

101 Appendix B: At a Glance Comparison of Sub-Regions vs. Average % Low income (after tax) % Unemployed Indicator Central POPULATION CHARACTERISTICS % who have not completed high school % completed post secondary education % Lone parent familities (among census families) % of seniors living alone % of seniors living alone with low income GENERAL HEALTH % Better or Worse (relative difference ƚ ) than overall Left/Red is WORSE; Right/Green is BETTER Region Average 7.7% 49.6% 53.0% 50.4% 14.5% 12% 9.5% 9.5% 7.1% 21.4% 4.8% 4.2% 33.0% 45.5% 2.3% 36.4% 70.5% 8.8% 16.4% 10.8% 6.2% 5.0% 21.7% 70% 5.0% 24.8% 33.7% 15.9% 1.2% 26% 1.1% 34.1% 28.4% 36.4% 1.1% 26% 60.0% 63.6% 89.1% 52.7% 32.7% 6% Requires help with at least one activity of daily living a 12.3% 17.9% 3.8% 15.1% 25.5% 11% Self rated general health as very good/excellent a 5.1% 5.9% 2.1% 6.3% 6.3% 61% Self rated mental health as very good/excellent a 3.1% 3.0% 3.4% 3.3% 0.8% 71% RISK FACTORS Breastfeeding on discharge from hospital or within 3 days of birth in midwifery care, Exclusive breastfeeding 8.4% 2.5% 4.3% 0.2% 0.0% 63% Breastfeeding on discharge from hospital or within 3 days of birth in midwifery care, Any breastfeeding 4.4% 4.2% 3.3% 1.8% 9.9% 90% Flu shot in the past 2 years a 9.3% 7.4% 1.9% 6.4% 12.5%* 47% Current smoker a 39.7%* 20.6% 3.7% 22.8% 38.1%* 19% Exceeds Canada Low Risk Drinking Guidelines a 2.7% 7.8% 0.0% 15.0% 9.5% 29% Heavy Drinking a 8.5% 14.5% 4.0% 25.0% 1.0% 20% Consumption of fruits or vegetables five or more times daily a 8.7% 1.6% 6.8% 8.2% 6.8% 37% Regular medical doctor a 4.0%* 3.3% 6.1%* 7.0%* 0.1% 88% % of children at risk (vulnerable) at time of school entry in 1+ Early Development Instrument (EDI) domains 4.7% 14.5% 10.9% 13.8% 19.3% 28% % of pre term births ( ) 2.5% 9.9% 0.0% 6.2% 9.9% 8.1% Inactive during leisure time a * 6.9% 1.0% 0.5% 23.8%* 14.9% 40% Overweight or obese based on self reported height and weight a 15.2%* 6.4% 10.8% 3.8% 16.6%* 50% ƚ Red/green bars are based on the relative percent difference between sub region value (e.g. 10% of people having an illness is 100% worse than 5%) and the average. Values are adjusted so that left/red is always worse. Bar lengths are scaled using the percent differences for all indicators in this section (up to +/ 100%), so the longest bars represent the biggest differences. For actual statistics and other information, see the relevant chapter in this report. a Tested for significant difference between each sub region and (p<0.05) * Significant difference between sub region and 101 P a g e

102 Appendix B: At a Glance Comparison of Sub-Regions vs. Average Indicator Central % Better or Worse (relative difference ƚ ) than overall CHRONIC CONDITIONS Left/Red is WORSE; Right/Green is BETTER Region Average Hospitalization for common chronic conditions a 54.8%* 14.9% 26.7% 7.0% 75.6%* day readmissions for certain chronic conditions Hospitalization for chronic obstructive pulmonary disease ED visit rate per 100,000 for COPD 11.6% 13.6% 4.8% 17.0% 0.7% 15% 69.4% 28.2% 3.4% 8.2% 161.8% % 46.6% 33.0% 50.4% 88.1% Hospitalization for diabetes 36.5% 39.2% 9.4% 27.9% 70.4% ED visit rate per 100,000 for hyper/hypo glycaemia for adults living with diabetes 49.1% 10.4% 15.5% 32.3% 26.4% Hospitalization for congestive heart failure (CHF) Hospitalization for hypertension Hospitalization for ischaemic heart disease Hospitalization for stroke Hospitalization for arthritis Hospitalization for asthma Hospitalization for cancer Prevalence estimate of Asthma (age 20+) Prevalence estimate of Chronic Obstructive Pulmonary Disease (Age 35+) Prevalence estimate of Diabetes (Age 20+) Prevalence estimate of high blood pressure (age 20+) CANCER 27.9% 26.7% 18.8% 7.9% 42.1% % 47.9% 28.6% 27.1% 12.1% % 24.7% 25.9% 8.2% 46.1% % 9.5% 18.6% 3.4% 18.0% % 4.1% 13.9% 8.8% 10.7% % 34.5% 1.9% 8.0% 73.5% % 8.8% 10.8% 6.0% 11.2% % 0.0% 5.8% 1.9% 10.3% % 31.8% 10.3% 22.4% 61.7% % 10.4% 3.8% 1.9% 18.9% % 3.7% 6.7% 0.4% 8.8% 24.0 Age adjusted cancer rates for adults 20+, All cancers Age adjusted cancer rates for adults 20+, Lung and Bronchus Age adjusted cancer rates for adults 20+, Breast (female) Age adjusted cancer rates for adults 20+, Colon and rectum Age adjusted cancer rates for adults 20+, prostate 3.8% 5.9% 1.9% 1.3% 7.1% % 23.0% 1.4% 10.8% 28.3% % 2.7% 1.9% 7.9% 0.2% % 1.9% 6.1% 0.2% 11.8% % 1.2% 7.6% 22.2% 6.3% ƚ Red/green bars are based on the relative percent difference between sub region value (e.g. 10% of people having an illness is 100% worse than 5%) and the average. Values are adjusted so that left/red is always worse. Bar lengths are scaled using the percent differences for all indicators in this section (up to +/ 100%), so the longest bars represent the biggest differences. For actual statistics and other information, see the relevant chapter in this report. a Tested for significant difference between each sub region and (p<0.05) * Significant difference between sub region and 102 P a g e

103 Appendix B: At a Glance Comparison of Sub-Regions vs. Average Indicator Central INFECTIOUS DISEASE AND INJURY % Better or Worse (relative difference ƚ ) than overall Left/Red is WORSE; Right/Green is BETTER Region Average Chlamydia incidence rate, age a 1.4% 29.3% 60.5%* 16.7%* 38.9%* Hepatitis C age standardized incidence rate a 20.4% 39.8%* 47.1%* 27.1% 10.4% 22.1 ED visits for flu or pneumonia Hospitalization for flu/pneumonia 62.5% 40.5% 40.9% 40.2% 60.2% % 31.4% 23.4% 3.6% 42.2% Fall related ED visit rates among seniors a 70.0%* 3.9% 24.9%* 20.9%* 52.3%* MORTALITY Mortality rate per 100,000 (not adjusted), Male a 28.6%* 35.4%* 6.2% 29.8%* 22.2%* Mortality rate per 100,000 (not adjusted), Female a 35.0%* 29.4%* 19.3%* 32.0%* 20.4%* Mortality rate per 100,000 (not adjusted), Combined a 57.7%* 30.7%* 16.0%* 29.0%* 21.1%* Age Adjusted mortality rate per 100,000, Male a 10.0% 12.7%* 0.7% 7.8% 16.6%* Age Adjusted mortality rate per 100,000, Female a 13.3%* 11.2%* 2.0% 2.0% 8.2% Age Adjusted mortality rate per 100,000, Combined a 12.0%* 12.8%* 0.6% 3.6% 12.9%* Infant Mortality Rate per 1,000, Combined a 26.2% 2.4% 14.3% 9.5% 28.6% 4.2 LIFE EXPECTANCY Life expectancy at birth, Male a 1.6%* 1.9%* 0.1% 1.4%* 2.5%* 81.0 Life expectancy at birth, Female a 1.9%* 1.5%* 0.2% 0.4% 1.4%* 85.3 Life expectancy at birth, Combined a 1.7%* 1.8%* 0.1% 0.8% 1.9%* 83.2 PREMATURE MORTALITY (PYLL) Age adjusted potential years of life lost (per 100,000) Causes of PYLL per 100,000 Ischaemic Heart Disease Causes of PYLL per 100,000 Intentional self harm Causes of PYLL per 100,000 Transport accidents Causes of PYLL per 100,000 Perinatal conditions Causes of PYLL per 100,000 Lung Cancer 24.1% 27.4% 14.4% 23.2% 23.2% % 37.8% 2.9% 37.3% 45.7% % 35.8% 12.2% 40.6% 14.6% % 52.1% 56.7% 16.3% 130.2% % 5.2% 28.2% 28.6% 0.4% % 41.1% 8.6% 22.4% 83.9% ƚ Red/green bars are based on the relative percent difference between sub region value (e.g. 10% of people having an illness is 100% worse than 5%) and the average. Values are adjusted so that left/red is always worse. Bar lengths are scaled using the percent differences for all indicators in this section (up to +/ 100%), so the longest bars represent the biggest differences. For actual statistics and other information, see the relevant chapter in this report. a Tested for significant difference between each sub region and (p<0.05) * Significant difference between sub region and 103 P a g e

104 Appendix B: At a Glance Comparison of Sub-Regions vs. Average Indicator Central CAUSE OF DEATH Top 10 causes of death (Rate per 100,000), Ischaemic heart disease Top 10 causes of death (Rate per 100,000), Dementia/Alzheimers Top 10 causes of death (Rate per 100,000), Lung cancer Top 10 causes of death (Rate per 100,000), Cerebro vascular stroke Top 10 causes of death (Rate per 100,000), Chronic lower respiratory/copd Top 10 causes of death (Rate per 100,000),Colon cancer Top 10 causes of death (Rate per 100,000), Lymph/blood cancer Top 10 causes of death (Rate per 100,000), Diabetes Top 10 causes of death (Rate per 100,000), Breast cancer Top 10 causes of death (Rate per 100,000), Urinary diseases PREVENTABLE MORTALITY % Better or Worse (relative difference ƚ ) than overall Left/Red is WORSE; Right/Green is BETTER Region Average 13.3% 14.7% 4.7% 2.5% 20.5% % 35.0% 1.7% 5.5% 13.1% % 22.2% 4.2% 4.0% 15.0% % 10.8% 5.6% 33.5% 9.7% % 11.4% 14.0% 8.0% 29.8% % 6.6% 1.5% 20.5% 6.0% % 6.1% 9.2% 20.7% 15.5% % 22.6% 9.9% 29.0% 38.0% % 8.7% 8.3% 11.1% 13.0% % 24.4% 12.4% 19.3% 26.7% 10.4 Age adjusted rates of preventable mortality 14.2% 40.0% 0.0% 26.7% 25.8% Top preventable causes of death (Rate per 100,000), Lung cancer a 21.8% 43.8%* 3.2% 17.2% 71.1%* 30.8 Top preventable causes of death(rate per 100,000), Ischaemic heart disease a 54.7% 48.4%* 10.6% 37.3% 44.7% 16.1 Top preventable causes of death(rate per 100,000), Intentional self harm a 58.3% 39.6% 7.3% 39.6% 37.5% 9.6 Top preventable causes of death (Rate per 100,000) Transport accidents a 92.9% 51.8% 57.1%* 3.6% 116.1%* 5.6 Top preventable causes of death (Rate per 100,000), Diabetes a 102.6% 51.3% 2.6% 59.0% 48.7% 3.9 Top preventable causes of death(rate per 100,000), Cirrhosis/liver disease a 29.5% 4.9% 3.3% 55.7% 34.4% 6.1 Top preventable causes of death (Rate per 100,000), Chronic lower respiratory/ COPD a 44.4% 48.9%* 23.3% 28.9% 113.3%* 9.0 Top preventable causes of death (Rate per 100,000), Accidental poisoning a 10.0% 42.5% 65.0% 32.5% 32.5% 4.0 MENTAL HEALTH Estimated % persons with mental health/addictions condition Emergency dept visits for opioid related harm per 100, % 5.0% 5.0% 5.0% 7.0% 20% 15.6% 27.8% 7.8% 0.0% 7.8% 9.0 Emergency dept visits for intentional self harm per 100,000 a 25.5% 7.5% 1.8% 26.8%* 37.2%* 65.0 Hospitalizations for intentional self harm per 100,000 a 12.5%* 17.0% 26.0% 23.5% 3.2%* 40.0 ƚ Red/green bars are based on the relative percent difference between sub region value (e.g. 10% of people having an illness is 100% worse than 5%) and the average. Values are adjusted so that left/red is always worse. Bar lengths are scaled using the percent differences for all indicators in this section (up to +/ 100%), so the longest bars represent the biggest differences. For actual statistics and other information, see the relevant chapter in this report. a Tested for significant difference between each sub region and (p<0.05) * Significant difference between sub region and 104 P a g e

105 Appendix B: At a Glance Comparison of Sub-Regions vs. Average Indicator Central HEALTH SERVICE PROVIDER DISTRIBUTION AND CAPACITY Primary Care retention: proportion of primary care visits patients made to General/family practice physicians and nurse practitioners per 100,000 Long term care beds per 1,000 population 75 years+ Home Care Service costs per client Home Care Service costs per client, Seniors (65+) Home Care Service costs per client, Adults (18 64) Home Care Service costs per client, Children (0 17) Home Care Service costs per client, English mother tongue clients Home Care Service costs per client, French mother tongue clients Home Care Service costs per client, Other mother tongue clients Region Average 40.7% 19.5% 40.7% 8.8% 21.2% % 2.9% 15.0% 17.9% 14.7% % 4.9% 1.5% 9.3% 5.1% % 2.0% 0.6% 10.2% 1.5% % 7.9% 2.0% 10.2% 8.3% % 2.6% 1.7% 0.4% 12.6% % 5.2% 0.1% 9.3% 7.9% % 3.4% 1.7% 12.6% 3.7% % 7.0% 2.2% 2.8% 3.0% CSS Capacity, Adult day programs: clients per 1,000 population 75 years+ 24.6% 32.8% 20.8% 8.7% 51.9% 18.3 CSS Capacity, Home Making Services: clients per 1,000 population 75 years+ 39.9% 23.5% 60.1% 51.4% 49.0% 24.3 CSS Capacity, Transportation services: clients per 1,000 population 75 years+ 68.8% 67.5% 39.5% 32.3% 110.9% CSS Capacity, Assisted Living Services for High Risk Seniors: clients per 1,000 pop 75 years+ 50.6% 42.9% 27.3% 97.4% 1.3% 7.7 Ratio of expenses for community MHA services to the number of people living with MH and/or Addictions 5.3% 4.4% 8.1% 13.3% 34.7% Average occupancy of acute care hospital beds for hospitals within the subregion 18.7% 2.2% 4.4% 2.2% 0.0% 91% PRIMARY CARE SYSTEM PERFORMANCE % Better or Worse (relative difference ƚ ) than overall Left/Red is WORSE; Right/Green is BETTER ER visits for conditions best managed elsewhere (rate per 1,000) a 383.3%* 60.0%* 68.3%* 68.3%* 133.3%* 6.0 % Adults who report that their provider always or often involves them in decisions about their care a 1.9% 0.0% 1.4% 1.4% 0.5% 88% Rate of hospitalization for ambulatory care sensitive conditions (rate per 100,000) a 62.4%* 44.1%* 24.7%* 34.4%* 139.8%* 93.0 % of patients who reported that their providers spends enough time with them a 1.5% 2.3% 1.9% 3.1% 3.1% 86% % of patients who reported that their provider always gives patients the opportunity to ask questions a 1.3% 1.6% 1.0% 0.8% 0.5% 87% Residents having difficulty accessing after hours care without going to an emergency department a 21.7%* 17.4%* 11.7% 4.6% 29.4%* 56% Access to same day/next day appointment when sick a 20.1% 8.7% 7.3% 2.1% 9.8% 44% % of 2 year olds with an 18m well baby visit 20.0% 11.7% 1.7% 11.7% 10.0% 60% Has a PC provider for check ups, when sick, etc. a 1.6% 0.7% 4.0%* 3.2%* 2.7%* 95% Hospitalization for all chronic conditions (rate per 100,000) a 55.0%* 14.7%* 26.7%* 7.0% 75.8%* ƚ Red/green bars are based on the relative percent difference between sub region value (e.g. 10% of people having an illness is 100% worse than 5%) and the average. Values are adjusted so that left/red is always worse. Bar lengths are scaled using the percent differences for all indicators in this section (up to +/ 100%), so the longest bars represent the biggest differences. For actual statistics and other information, see the relevant chapter in this report. a Tested for significant difference between each sub region and (p<0.05) * Significant difference between sub region and 105 P a g e

106 Appendix B: At a Glance Comparison of Sub-Regions vs. Average Indicator Central HOSPITAL AND CROSS SECTOR SYSTEM PERFORMANCE % of high needs patients with a coordinated care plan 0.0% 40.0% 80.0% 80.0% 40.0% 5% % of palliative care patients dischared home from hospital with home supports 6.8% 2.3% 3.4% 5.7% 0.0% 88% % of Alternate Level of Care days (%ALC) % of discharges on the weekend 30 day hospital readmission rate for selected chronic conditions Decedents with emergency department visit in last 2 weeks of life Overall satisfaction with health a care in the community HOME AND COMMUNITY CARE SYSTEM PERFORMANCE Region Average 3.1% 6.2% 23.3% 22.5% 16.3% 13% 3.5% 5.7% 3.5% 2.6% 0.0% 23% 11.6% 13.6% 4.1% 17.0% 0.7% 15% 6.5% 1.3% 4.2% 4.2% 14.4% 38% 2.2% 1.5% 0.2% 1.6% 2.1% 89% % Home Care Clients who received their Nursing Visit within 5 days 0.9% 0.3% 0.4% 0.1% 0.5% 93% % Home Care clients with complex needs who received their Personal Support Visit within 5 days 1.2% 3.0% 0.4% 4.4% 1.2% 75% 90th percentile Wait Time from community for In Home Services: from community to first service (days) 5.5% 14.5% 9.1% 3.6% 5.5% 55 90th Percentile Wait Time from community for In Home Services: from hospital setting to first service (days) 12.5% 6.3% 18.8% 6.3% 18.8% 16 % Palliative clients who have died in their preferred place of death MENTAL HEALTH SYSTEM PERFORMANCE % Better or Worse (relative difference ƚ ) than overall Left/Red is WORSE; Right/Green is BETTER 10.1% 6.7% 9.8% 5.4% 8.0% 79% % Repeat 30 day ED visit for Mental Health a 12.2%* 25.6%* 12.8%* 22.6%* 12.2%* 16% % Repeat 30 day ED visit for Substance Abuse a 37.7%* 3.8%* 18.9%* 38.7%* 39.2%* 21% ƚ Red/green bars are based on the relative percent difference between sub region value (e.g. 10% of people having an illness is 100% worse than 5%) and the average. Values are adjusted so that left/red is always worse. Bar lengths are scaled using the percent differences for all indicators in this section (up to +/ 100%), so the longest bars represent the biggest differences. For actual statistics and other information, see the relevant chapter in this report. a Tested for significant difference between each sub region and (p<0.05) * Significant difference between sub region and 106 P a g e

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