Distribution of Registered Nurses in Alberta Health Services

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1 Distribution of Registered Nurses in Alberta Health Services 2017 This study examined how Registered Nurses are staffed in Rural and Remote Emergency Departments, Mental Health Units, and Home Care settings. Results indicated there is considerable variability across zones that is not fully accounted for by patient acuity. Health Systems Evaluation and Evidence Innovation and Research Management, Research, Innovation and Analytics Alberta Health Services Edmonton: Aberhart Centre Red Deer: rd Street Calgary: Southport IV

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3 Acknowledgements iii ACKNOWLEDGEMENTS This research was made possible by a financial contribution by the College and Association of Registered Nurses of Alberta. This report was prepared on behalf of The College and Association of Registered Nurses of Alberta for: Margaret Ward Jack Senior Advisor, Public Affairs College and Association of Registered Nurses of Alberta Edmonton, AB This report was prepared by: Stephanie Hastings Senior Consultant Health Systems Evaluation & Evidence Innovation & Research Management Alberta Health Services stephanie.hastings@ahs.ca Hue Quan Senior Analyst Health Systems Evaluation & Evidence Innovation & Research Management Alberta Health Services hue.quan@ahs.ca Ameera Memon Research & Evaluation Coordinator Health Systems Evaluation & Evidence Innovation & Research Management Alberta Health Services ameera.memon@ahs.ca This work is owned and copyrighted by Alberta Health Services (AHS). It may be reproduced in whole or in part for internal AHS use. For any use external to AHS, this work may be produced, reproduced and published in its entirety only, and in any form including electronic form solely for educational and noncommercial purposes without requiring consent or permission of AHS and the author. Any such reproduction must include the following citation: Hastings, S.E., Quan, H., & Memon, A. (2017). Distribution of Registered Nurses in Alberta Health Services. Calgary, AB: Health Systems Evaluation & Evidence, Alberta Health Services.

4 iv Distribution of Registered Nurses in Alberta Health Services TABLE OF CONTENTS Acknowledgements... iii Executive Summary... v Introduction... 1 Methods... 2 Data... 2 Analysis... 3 Results... 4 Rural and Remote Emergency Departments... 4 Mental Health Units... 7 Home Care Discussion Limitations Conclusion Appendix: Guiding Principles for Evaluation... 19

5 Executive Summary v EXECUTIVE SUMMARY Background Upcoming changes to regulations for Registered Nurses (RNs) in Alberta may have significant impact on how they are distributed and used across the province. Given this, the College and Association of Registered Nurses of Alberta sought to understand how RNs are currently staffed in settings providing care to vulnerable populations to facilitate future evaluation of the impact of these regulatory changes. Alberta Health Services (AHS) Rural and Remote Emergency Departments (RREDs), Mental Health (MH) units, and Home Care (HC) programs were selected for examination. The research questions were: 1. How are RNs distributed in rural and remote emergency departments, mental health units, and home care programs across AHS? 2. Are there differences in how RNs are distributed across zones, unit/facility types, and remote settings? 3. How do patient characteristics differ according to RN distribution across units, departments, and programs? Method We used staff and patient data from a number of AHS administrative data systems. We did descriptive analyses of the data to examine how RNs are mixed with other staff and distributed around the five AHS zones. We also examined the distribution of RNs in relation to relevant measures of patient volume and workload as a proxy for acuity. Findings RREDs RNs comprised the bulk of the RRED workforce in the province as a whole (61%) The North Zone had the lowest percentage of RNs (50%) compared to the other zones and the Central Zone had the highest (78%). Licensed Practical Nurses (LPNs) were the second most commonly staffed RRED provider in all zones. There was some variability across the province in terms of how many RNs were available relative to the workload; we found the South Zone had the most RN Full Time Equivalent () for every 1000 patient days at 29.4 whereas the Central Zone had MH Units RNs made up a much smaller proportion of the staff in MH units, with only 27.2% province wide. Registered Psychiatric Nurses (RPNs) accounted for a further 18.3%.

6 vi Distribution of Registered Nurses in Alberta Health Services Interestingly, Allied Health professionals (e.g., counsellors, occupational therapists) made up more than 30% of MH staff in the province. This was driven primarily by the Central Zone, where RNs were only 9.1% of staff and Allied Health were 51%. Staffing relative to patient length of stay and acuity was much more variable in MH units. The Calgary Zone had far higher RN s per 1000 patients days (27.9) than all other units; the next highest was the Edmonton Zone with 9.3. HC Teams There was significantly less variability in home care compared to the other two care settings. RNs made up 87% of the HC workforce provincially, and at least 80% in each of the zones. There was variability in the amount of Allied Health vs. LPN support across zones. There was also less variability in the amount of RN staffing relative to patient workload. All zones had between 4.7 and 7.3 RN s per 1000 patient days. Conclusions The results suggest that planning for RN staffing is not consistent across AHS zones or care settings. This is particularly true for Mental Health units, where we saw substantial variability in how units are staffed. HC teams tended to be more similar compared to RREDs and MH units. We also saw that patient workload and acuity were not consistently related to RN staffing. Future research should examine the reasons for these differences.

7 Introduction 1 Distribution of Registered Nurses in Alberta Health Services INTRODUCTION Proposed changes to regulations for Registered Nurses (RNs) in Alberta, such as adding the ability to prescribe certain medications and order diagnostics tests, may change how RNs are used and distributed across the province. The College and Association of Registered Nurses of Alberta (CARNA) is particularly interested in how these upcoming changes will affect RNs ability to care for vulnerable populations. Given this, CARNA sought to understand how RNs are currently distributed across rural and remote emergency departments, mental health units, and in home care programs. Health Systems Evaluation and Evidence, Alberta Health Services (AHS), was contracted to develop staffing profiles for these three care areas to examine how RNs are mixed with other regulated and unregulated care providers and distributed across different types of units, facilities, and geographic zones. This study examined the following research questions: 1. How are RNs distributed in rural and remote emergency departments, mental health units, and home care programs across AHS? 2. Are there differences in how RNs are distributed across zones, unit/facility types, and remote settings? 3. How do patient characteristics differ according to RN distribution across units, departments, and programs? The answers to these questions will facilitate future research into how regulatory changes have impacted RN staffing and distribution in these care areas.

8 2 Distribution of Registered Nurses in Alberta Health Services METHODS Ethical approval for this project was obtained through the Conjoint Health Research Ethics Board at the University of Calgary. Data disclosure agreements and research agreements were obtained through the AHS Research Administration team. DATA We used staff and patient data from various systems within AHS. Staffing data, including full time head counts and provider type by unit and facility, was obtained from the AHS emanager database. Data on home care patients was obtained from the PARIS (Community Health Programs CCIS) system and Meditech. Data on mental health patients and most emergency department patients was obtained from the Discharge Abstract Database, Admission Discharge Transfer database, and the National Ambulatory Care Reporting System; some data for the Calgary Zone emergency patients was obtained via CDR9 Betach. These databases were used to obtain patient volume and severity indexes. Patient and staffing data were extracted and aggregated at a unit level and then linked using facility and unit names. We used job family descriptions to identify different provider types and, in a few cases, reclassified them into broader categories. The provider types examined were: Registered Nurses (RNs) Licensed Practical Nurses (LPNs) Health Care Aides (HCAs) Registered Psychiatric Nurses (RPNs) Nursing + (clinical nurse specialists, graduate nurses, nurse clinicians, nurse practitioners) Allied Health (e.g., Occupational Therapists, Mental Health Aides, Psychologists) Service workers Unit clerks Managers

9 Methods 3 ANALYSIS We used the staffing data to find out staffing levels of all of these providers on all rural and remote emergency departments (RREDs), mental health (MH) units, and home care (HC) services for a three month period (January March, 2017). We used patient data to calculate length of stay (LOS), Resource Intensity Weight (RIW) for mental health patients, the Canadian Triage and Acuity Scale (CTAS) score for emergency department visitors, and Resource Utilization Groups (RUG) for home care patients. RIW is a predictor of overall resource use by patients including the number of days in the hospital and is based on information such as diagnosis, age, and health status and is standardized such that a patient using average resources receives a score of 1.0. CTAS represents the level of urgency of a case based on presenting problems, with one being the most urgent and five the least. The RUG categorizes home care patients into one of seven major categories based on diagnosis. We used Poss et al. s (2008) 1 breakdown of RUG categories to convert these into Case Mix Index (CMI) scores that predict resource use (standardized to 1.0 similar to the RIW). We did descriptive analyses of the data to examine how RNs are mixed with other staff and distributed across different unit types, facilities, and AHS zones. We also examined the distribution of RNs in relation to patient volume (using a standardized value of RN s per 1000 patient days to allow comparisons across zones) and workload (using a standardized value of RN s per 1000 RIW or CMI). Each patient is assigned an RIW or CMI score; using a denominator of 1000 RIW or CMI allowed us to examine how many RN s are available relative to the overall effort or workload required to treat patients. We also classified units or facilities with and without designated RNs and split average unit/program RIW, RUG, and CTAS classifications into high and low scores to examine whether staffing varied based on patient intensity or acuity. 1 Poss, J.W., Hirdes, J.P., Fries, B.E., McKillop, I., & Chase, M. (2008). Validation of Resource Utilization Groups Version III for Home Care (RUG III/HC): Evidence from a Canadian home care jurisdiction. Medical Care, 46(4),

10 4 Distribution of Registered Nurses in Alberta Health Services RESULTS RURAL AND REMOTE EMERGENCY DEPARTMENTS Data were collected from 60 RREDs. No emergency departments in the Edmonton Zone are classified as Rural or Remote so Edmonton Zone data are not shown here. RNs worked in all of the RREDs but while some units had full time, dedicated RRED staff, others had only part time and casual staff who are assigned to work in other areas of the hospital and called into the RRED as necessary. We included only units with dedicated full time RN staff for most analyses. However, we did include the units with and without dedicated full time RNs in a comparative analysis to examine whether there are differences in patient acuity across the two staffing models. Figure 1 shows the distribution of staff in RREDs across the province. RNs made up the bulk of the workforce provincially, comprising 61% of the total s. LPNs were the next most common provider, at 18%. Figure 1. Provincial distribution of staff in RREDs (% of total ) 5% 2% 2% 12% Registered Nurse Licensed Practical Nurse Nursing+ Manager 18% 61% Service Worker Unit Clerk Table 1 shows the distribution of RNs in RREDs across the province, broken down by zone. The emanager database showed that Calgary Zone RREDs did not have any dedicated full time RN staff so this zone is not included in the table. The North Zone has a considerably lower

11 Results 5 proportion of RN staff (49.9%) relative to the others, and a higher proportion of LPNs (22.3%). Central Zone has the highest proportion of RN staff, with nearly 80% of dedicated staff members being RNs. Just over two thirds of RRED staff in the South Zone were RNs. Table 1. RN as a percentage of total RRED staffing Overall North Central South Providers % of total % of total % of total % of total RN LPN Nursing Manager Unit clerk Service worker Both RIW and CTAS scores were available to rate the resource intensity and acuity of patients in RREDs. The CTAS score represents the patient s acuity while in the emergency department. The RIW is a patient intensity score based on the entire hospital stay. Although the CTAS is a more accurate score for emergency departments, the RIW was also included here to allow a rough comparison of s across other types of units based on resource intensity. Table 2 and Figure 2 show the number of dedicated RN s per 1000 patient days and per 1000 RIW to provide an estimate of the workload covered by RNs. There was some variability across the province; South Zone had the highest RN s per 1000 patient days at 29.4 whereas Central Zone had half that number (14.9%). South Zone also had the highest RN per 1000 RIW at 56.4; North and Central Zone figures were more similar at 42.4 and 36.2 s per 1000 RIW, respectively. This suggests that in the South Zone, more RNs are available relative to the workload than in other zones. The average patient days and average RIW were also much lower in the South Zone than elsewhere.

12 6 Distribution of Registered Nurses in Alberta Health Services Table 2. RN per 1000 patient days and 1000 RIW for RREDs Zone # of Units Average patient days Average RN per 1000 patient days Average RIW per 1000 RIW Overall Central North South Figure 2. RN per 1000 patient days and 1000 RIW for RREDs per 1000 patient days per 1000 RIW Central North South Overall Next, we split the sites with and without dedicated RNs to examine RN staffing models in relation to CTAS scores (Table 3). In the North Zone, sites with and without dedicated full time RNs were fairly similar in their breakdown of CTAS scores; 78.6% of sites without dedicated RNs had low average CTAS scores compared to 71.4% of units with dedicated RNs. The same was true in the Central Zone, where 50% of units without dedicated RNs had high average CTAS

13 Results 7 scores compared to 53.8% of sites with dedicated RNs. Interestingly, in the Calgary Zone, which had no units with dedicated full time RNs, 75% of units had higher urgency patients. Table 3. Percentage of RREDs with high and low CTAS scores with and without dedicated RNs Zone No dedicated RNS Low CTAS 4 5 (%) High CTAS 1 3 (%) Low CTAS 4 5 (%) Dedicated RNs High CTAS 1 3 (%) Calgary Central North South MENTAL HEALTH UNITS Data were collected from 55 MH units. RNs worked in all of the MH units; only six of the 55 units did not have full time, dedicated RNs. We have included the 49 units with dedicated full time RN staff in our analyses. Figure 3 shows the distribution of staff in MH units across the province. RNs make up about 27.2% and RPNs make up about 18.3% of the total dedicated s in MH units provincially. Interestingly, Allied Health staff have the highest overall distribution across the MH units in the province. Over 30% of MH staff across the province are included in the Allied Health job family. These staff may include addiction counsellors, family counsellors, mental health therapists, mental health workers, occupational therapists, therapy assistants, psychologists, psychometricians, rehabilitation workers, social workers, recreation therapists, recreation aides, and speech language pathologists.

14 8 Distribution of Registered Nurses in Alberta Health Services Figure 3. Provincial distribution of staff in MH units (% of total ) 1% 1% 2% 9% 7% 18% 5% 30% 27% Registered Nurse Allied Health RPN LPN HCA Nursing+ Clerk/Secretary Manager Service Worker Table 4 shows the distribution of RNs in MH units across the province, broken down by zone. All zones had dedicated RNs in MH units, so all zones were included in this analysis. The data showed that North Zone has the highest proportion of RN staff at 46%, with South Zone (44%) and Calgary Zone (39%) close behind. Central Zone had a far lower proportion of RNs than did the other zones, with only 9%. There, the proportion of Allied Health staffing (51%) was substantially higher than elsewhere. Specific to staff distribution across the zones, it is important to note that zones with MH units who had greater proportions of allied health professionals had lower proportions of RN, RPN, and Nursing+ staff. For example, half of Central Zone MH staff were part of Allied Health, but RNs made up less than 10%. In contrast, North Zone Allied Health made up only 6.1 % of staff but RNs were 45.5% of the North Zone s. Similarly, the data suggests that RPN representation is elevated in MH units that have lower percentages of RN s.

15 Results 9 Table 4. RN as a percentage of total MH staffing across zones Overall North Central Edmonton Calgary South Providers % of total % of total % of total % of total % of total % of total Allied Health RN RPN LPN HCA Nursing Manager Clerk/Secretary Service Workers Table 5 and Figures 4 and 5 show the number of dedicated RN s per 1000 patient days and per 1000 RIW in MH units to provide an estimate of the workload covered by RNs across the province. Calgary Zone had far higher RN s per 1000 patient days than all other zones at Edmonton Zone had approximately a third of that number (9.3%), and Central and South Zones were far lower at 0.4 and 0.8 RNs per 1000 patient days, respectively. Similarly, Calgary Zone had the highest RN s per 1000 RIW at 146.7; Edmonton had approximately half of that at 78.7 RN s per 1000 RIW. Central and South Zones both had fewer than 10 s per 1000 RIW. It is important to note than Edmonton, North, and South Zones have fewer MH units than do the Calgary and Central Zones.

16 10 Distribution of Registered Nurses in Alberta Health Services Table 5. RN per 1000 patient days and 1000 RIW for MH units # of Units Average patient days Average RN per 1000 patient days Average RIW per 1000 RIW Overall Calgary Central Edmonton North South Figure 4. RN per 1000 patient days in MH units across zones per 1000 patient days Calgary Central Edmonton North South Overall

17 Results 11 Figure 5. RN per 1000 RIW in MH units across zones per 1000 RIW Calgary Central Edmonton North South Overall Finally, as we did with the other areas of service delivery, we split the sites with and without dedicated full time RNs to examine RN staffing models in relation to RIW scores (Table 6). It is important to point out that there were only six units throughout the province that did not have dedicated RN s in MH units. The RIWs from these MH units may not be generalizable to the greater population and overall staffing differences across the province. In addition, a comparative analysis was not possible for North and South Zones because there were no units without dedicated RN s. Interestingly, all units without dedicated full time RNs had high average RIW scores. Most of the sites with dedicated full time RNs were also on the higher side of acuity; only one unit in the Calgary Zone and one in the North Zone had lower average RIW.

18 12 Distribution of Registered Nurses in Alberta Health Services Table 6. Percentage of MH units with high and low average RIW scores with and without dedicated RNs No Dedicated RNs Dedicated RNs Zone Low RIW (<1) High RIW ( 1) Low RIW (<1) High RIW ( 1) Calgary Central Edmonton North South HOME CARE Data were collected from 422 HC teams as identified by office site. Due to limitations in the HC staffing data, we were only able to include full time staff in our analyses. Figure 6 shows the distribution of staff in home care for the province as a whole. Overall, RNs make up the vast majority of providers at 87%. Allied Health staff, including occupational therapists and physiotherapists, were the second most common provider at 9%. Figure 6. Provincial distribution of staff in HC programs (% of total ) 0% 4% 9% Registered Nurse RPN LPN Allied Health 87%

19 Results 13 Table 7 shows the breakdown of HC providers by zone. There is less staffing variability in HC programs compared to the other care settings examined; in all zones, RNs comprised at least 80% of s. Central Zone was the only area with RPNs on staff, and Calgary Zone was the only area without full time LPNs. Interestingly, Calgary had the highest proportion of Allied Health providers at 16.5%. South Zone had few Allied Health providers but the greatest percentage of LPNs at 15.2%; the next highest zone for LPN staffing was the North Zone at 6.7%. Table 7. RN as a percentage of total HC staffing across zones Overall North Central Edmonton Calgary South Providers % of total % of total % of total % of total % of total % of total RN Allied Health RPN LPN Table 8 and Figures 7 and 8 show the RN per 1000 patient days and 1000 CMI. Again, there is lower variability in HC programs than in the other two care settings. All zones had between 4.7 and 7.3 RN s per 1000 patient days. per 1000 CMI was slightly more variable, as average CMI was quite different across the zones. South Zone s average CMI score for the period under study was 263.8, whereas Edmonton had a more resource intensive patient load at When standardized by the Edmonton and Calgary zones had lower RN per 1000 CMI compared to the relatively less resource intensive South Zone.

20 14 Distribution of Registered Nurses in Alberta Health Services Table 8. RN per 1000 patient days and 1000 CMI for HC programs # of Programs Average patient days Average RN per 1000 patient days Average CMI per 1000 CMI Overall Calgary Central Edmonton North South Figure 7. RN per 1000 patient days in HC programs across zones per 1000 patient days Calgary Central Edmonton North South Overall

21 Results 15 Figure 8. RN per 1000 CMI in HC programs across zones per 1000 CMI Calgary Central Edmonton North South Overall Finally, we split home care RNs into full time and part time to examine their average RUG categories. In both categories, average RUG categories were similar; all tended to have more patients on the lower side of resource utilization (i.e., RUGs between 5 and 7). Table 9. Percentage of HC RNs with high and low average RUG categories in full and parttime positions Part Time RNs Full Time RNs Zone Low RUG (5 7) High RUG (1 4) Low RUG (5 7) High RUG (1 4) Calgary Central Edmonton North South

22 16 Distribution of Registered Nurses in Alberta Health Services DISCUSSION The goal of this research was to examine the following research questions: 1. How are RNs distributed in rural and remote emergency departments, mental health units, and home care programs across AHS? 2. Are there differences in how RNs are distributed across zones, unit/facility types, and remote settings? 3. How do patient characteristics differ according to RN distribution across units, departments, and programs? Our results showed that RNs are present in all of these care settings, but in varying proportions. For instance, in RREDs, RNs made up only 50% of the staff in the North Zone but almost 80% in the Central Zone. Given that RNs make up 61% of RRED staff in the province as a whole, the variability across zones is substantial. In MH units, these differences are even more pronounced: RNs make up only 27% of staff provincially but 46% in the North Zone and 9% in the Central Zone. In HC programs, where RNs make up the vast majority of the workforce, we saw far less variability across zones. Interestingly, the differences in distribution across zones also cut across service types. As noted above, RNs make up most of the RRED staff in Central Zone but are a minority in MH units there. In MH units, RPNs and Allied Health staff made up a substantial proportion of s. In RREDs, LPNs tended to be the second most common provider. In HC, RNs were always the most common provider by far, followed by either Allied Health or LPN staff. Patient characteristics did not seem to greatly affect RN staffing in a systematic way. The per 1000 patient days and per 1000 RIW (or CMI) showed some variability in all settings except home care, where staffing seemed to be slightly more predictable by the workload. We saw variability in both patient volume and patient acuity across unit types and the different zones. Interestingly, the RN per 1000 RIW was higher in Calgary Zone MH units than for any other zone or unit type. It was also interesting that the Calgary Zone patient volume scores were the highest for the MH units and second highest across the zone and unit types, however

23 Discussion 17 the MH units also showed some of the lowest patient volume scores. This wide range of patient volume and acuity scores across unit types and zones show that there were no consistent patterns for how RNs are being staffed on these types of units across the province. LIMITATIONS There are some limitations to the administrative data results. First, staffing data is based on s assigned to the units or programs. Some staff are attached to the units/programs whereas others may work as casuals or are drawn from the general hospital pool (e.g., physiotherapy staff are often linked with an Allied Health program rather than a specific unit). As such, we cannot say conclusively that we have included every staff member who works on a unit. Furthermore, limitations in the HC staffing data meant that we could only include full time staff, meaning that those working part time were not captured in the analysis. RIW, CMI, and CTAS scores have limitations in their ability to determine workload. RIW and CMI scores are predictors of overall resource use by patients during the course of care. CTAS represents the level of acuity of a case. None of these is a perfect representation of acuity. Further, our CMI scores were from published Canadian scores, as recommended by the Canadian Institute for Health Information 2, rather than specific to Alberta due to data limitations. CONCLUSION The results suggest that planning for RN staffing is not consistent across AHS zones. There is considerable variability in staffing, particularly in mental health units. Some might expect that RNs would be the most common provider across any unit type, particularly at higher acuity levels, but our data show that this is not always the case. RIW, CMI, and CTAS scores, used here as proxies for patient acuity, were not consistently related to RN staffing. In summary, we found that there is room for improvement in standardizing and optimizing the use of RNs in these three care settings. Future research could examine whether there are reasons for the differences we found (e.g., lower availability of RNs in some zones relative to other providers) 2 Personal communication, 2017

24 18 Distribution of Registered Nurses in Alberta Health Services or whether the differences are based on legacy hiring practices that should be updated to better respond to patient needs.

25 Appendix: Guiding Principles for Evaluation 19 APPENDIX: GUIDING PRINCIPLES FOR EVALUATION Through evaluation excellence, healthcare practitioners are guided to do their best work and optimize the delivery of healthcare services. As part of Alberta Health Services, Evaluation Services is a professional practice that offers specialized expertise and experience in the field of health care related evaluation. As an external model of evaluation, our team has rights, responsibilities and duties to ensure reliable and useable results. Our practice is guided by the following principles: integrity, collaboration and ethical oversight. Integrity An external model of evaluation can help to enhance objectively by offering an outside perspective. Not having a vesting interest in the initiative helps to reduce the risk of conflict of interest. Any possible conflict of interest will be declared. While the interpretation of evaluation results by stakeholders is critical to providing context and a deeper understanding, Evaluation Services will only report on what the data presents and will not entertain requests to exclude or adjust findings unless there is evidence that the request is valid. This helps to safeguard the integrity of the evaluation results. Our practice is governed by a professional code set by the Canadian Evaluation Society, our own Survey and Evaluation Services Standards of Practice (2011) and provincial legislations 3. We will not engage in inappropriate requests that may violate those standards and the integrity and reputation of the evaluator and the evaluation. Collaboration We recognize that active stakeholder involvement in evaluation planning and decisionmaking is essential to success. Collaboration helps to ensure that: evaluation results are useful; decision making is evidence informed; there is good stewardship of resources; and through stakeholder engagement, a culture of evaluation evolves within your organization. Ethical Oversight Evaluation Services is committed to employing a systematic approach for ethical oversight in all projects. We work to ensure sound methodology and ethical practice at all stages of the evaluation. Ethical oversight is essential to reducing risk to human participants and by protecting the personal and health information collected and stored for evaluation purposes. 3 Governing provincial legislations include: Health Information Act (HIA), Freedom of Information and Protection of Privacy (FOIP) and the Alberta Evidence Act (AEA)

26 20 Distribution of Registered Nurses in Alberta Health Services References Alberta Health Services. (2013). Code of Conduct. Retrieved April 2014 from code of conduct.pdf Canadian Evaluation Society. (2012). Program Evaluation Standards. Retrieved April 2014 from Province of Alberta. (2003). Health Information Act (HIA). Edmonton: Alberta Queen s Printers. Retrieved April 2014 from Province of Alberta (2013a). Alberta Evidence Act. Retrieved April 2014 from Province of Alberta. (2013b). Freedom of Information and Protection of Privacy. Retrieved April 2014 from Survey and Evaluation Services. (2011). Survey and Evaluation Services Standards of Practice. Alberta Health Services. Retrieved April 2014 from ses standards of practice for survey andevaluation services.pdf

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