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Quality Ambition: Safe NHS Lanarkshire aims to be the safest health and care system in Scotland with no avoidable deaths, reduction in avoidable harm, a sustainable infrastructure for patient safety and improvement, a sustainable safety culture, and safe, reliable and person centred care. Safe: Percent Unadjusted Inpatient Mortality (NHSL Acute Hospitals) Percent Unadjusted Inpatient Mortality (NHSL Acute Hospitals) Total number of in-hospital deaths Total number of deaths (TD) + live discharges (LD) No shift or trend in the data is noted at present. With effect from May 215, Mental Health deaths and admissions in the three acute sites are now included in this measure. This is as a result of these locations now being recorded via TrakCare Patient Management System. Safe: Percent Unadjusted Inpatient Mortality (Hairmyres) Percent Unadjusted Inpatient Mortality (Hairmyres) Total number of in-hospital deaths Total number of deaths (TD) + live discharges (LD) No shift or trend in the data is noted at present. January saw the highest reported % in the two year reporting period (3.52%). Review of case listings for this period identified a high % of frail elderly patients and patients with cancer diagnosis, many of whom had died after 3 days in hospital and were part of the high numbers of delayed discharges on the site that are now much reduced. With effect from May 215, Mental Health deaths and admissions in the three acute sites are now included in this measure. This is as a result of these locations now being recorded via TrakCare Patient Management System. UIM_NHSL Unadjusted Inpatient Mortality - NHSL UIM_HM Unadjusted Inpatient Mortality - Hairmyres 4. 4. 3.5 3.5 3. 3. 2.5 2.5 % 2. % 2. 1.5 1.5 1. 1..5.5. Aug-15. Aug-15 % Median % Median Median: The median enables run chart rules to be applied to identify if there has been a non-random change. (Please see page 17) The baseline median is calculated using 28 unadjusted mortality. Description: Unadjusted mortality is a complementary measure to HSMR. This provides an indicator of trend. The trend should be decreasing and under the median line. Median: The median enables run chart rules to be applied to identify if there has been a non-random change. (Please see page 17) The baseline median is calculated using 28 unadjusted mortality. Description: Unadjusted mortality is a complementary measure to HSMR. This provides an indicator of trend. The trend should be decreasing and under the median line. Page 3 of 22 Print :15/1/215
Safe: Percent Unadjusted Inpatient Mortality (Monklands) Percent Unadjusted Inpatient Mortality (Monklands) Total number of in-hospital deaths Total number of deaths (TD) + live discharges (LD) No shift or trend in the data is noted at present. The % dropped in March 215 ending the previously noted upward trend in the data. With effect from May 215, Mental Health deaths and admissions in the three acute sites are now included in this measure. This is as a result of these locations now being recorded via TrakCare Patient Management System. Safe: Percent Unadjusted Inpatient Mortality (Wishaw) Percent Unadjusted Inpatient Mortality (Wishaw) Total number of in-hospital deaths Total number of deaths (TD) + live discharges (LD) The Wishaw data is once again displaying a downward shift with 7 consecutive points below the median line. With effect from May 215, Mental Health deaths and admissions in the three acute sites are now included in this measure. This is as a result of these locations now being recorded via TrakCare Patient Management System. UIM_MK Unadjusted Inpatient Mortality - Monklands UIM_WG Unadjusted Inpatient Mortality - Wishaw 4. 4. 3.5 3.5 3. 3. 2.5 2.5 % 2. % 2. 1.5 1.5 1. 1..5.5. Aug-15. Aug-15 % Median % Median Median: The median enables run chart rules to be applied to identify if there has been a non-random change. (Please see page 17) The baseline median is calculated using 28 unadjusted mortality. Description: Unadjusted mortality is a complementary measure to HSMR. This provides an indicator of trend. The trend should be decreasing and under the median line. Median: The median enables run chart rules to be applied to identify if there has been a non-random change. (Please see page 17) The baseline median is calculated using 28 unadjusted mortality. Description: Unadjusted mortality is a complementary measure to HSMR. This provides an indicator of trend. The trend should be decreasing and under the median line. Page 4 of 22 Print :15/1/215
Safe: Hospital Standardised Mortality Ratio (HSMR) - Hairmyres Number of Observed Deaths versus Predicted Deaths (3 days) -Hairmyres Number of Observed deaths and Number of Predicted deaths Not Applicable The number of observed deaths has increased at Hairmyres in comparison to the previous quarter and is parallel with predicted deaths which have also increased. This is reflected in the HSMR figure for this quarter. Hospital Standardised Mortality Ratio - Hairmyres Number of Observed deaths Number of Predicted deaths The last 9 data points (quarterly) have remained below the median (and below 1.) which is indicative of a downward shift in the data (six or more consecutive points below the median line). PREDD_HM OBSD_HM Observed Deaths versus Predicted Deaths - Hairmyres HSMRM_HM HSMR - Hairmyres 32 1.2 28 1. 24 2.8 Number 16 12 Rate.6.4 8 4.2 Apr-1 Jul-1 Oct-1 Jan-11 Apr-11 Jul-11 Oct-11 Jan-12 Apr-12 Jul-12 Oct-12 Jan-13 Apr-13 Jul-13. Jul-9 Oct-9 Jan-1 Apr-1 Jul-1 Oct-1 Jan-11 Apr-11 Jul-11 Oct-11 Jan-12 Apr-12 Jul-12 Oct-12 Jan-13 Apr-13 Jul-13 Observed Deaths Predicted Deaths Median HSMR Description: Predicted probability of death is calculated based on primary diagnosis; specialty; age; sex; where admitted from; number and severity of prior morbidities; number of emergency admissions in previous 12 months; whether admitted as an inpatient or day case and type of admission (elective / non-elective). Data reliability = Very High (see appendix c) Median: The median enables run chart rules to be applied to identify if there has been a non-random change. (Please see page 17) The median is calculated in line with the ISD HSMR Dashboard. Description: HSMR is calculated as: Observed Deaths within 3 Days / Predicted Deaths Within 3 Days and is calculated for all acute inpatient and day case patients admitted to all specialties. Data reliability = Very High (see appendix c) Page 5 of 22 Print :15/1/215
Safe: Hospital Standardised Mortality Ratio (HSMR) - Monklands Number of Observed Deaths versus Predicted Deaths (3 days) -Monklands Number of Observed deaths and Number of Predicted deaths Not Applicable The number of both observed and predicted deaths has increased at Monklands in comparison to the previous quarter. This is reflected in the HSMR figure for this quarter. Hospital Standardised Mortality Ratio - Monklands Number of Observed deaths Number of Predicted deaths This is the 5th consecutive quarter where the HSMR for Monklands has been less than 1. PREDD_MK OBSD_MK Observed Deaths versus Predicted Deaths - Monklands HSMRM_MK HSMR - Monklands 32 1.2 28 24 1. 2.8 Number 16 12 8 Rate.6.4 4.2 Apr-1 Jul-1 Oct-1 Jan-11 Apr-11 Jul-11 Oct-11 Jan-12 Apr-12 Jul-12 Oct-12 Jan-13 Apr-13 Jul-13. Jul-9 Oct-9 Jan-1 Apr-1 Jul-1 Oct-1 Jan-11 Apr-11 Jul-11 Oct-11 Jan-12 Apr-12 Jul-12 Oct-12 Jan-13 Apr-13 Jul-13 Observed Deaths Predicted Deaths Median HSMR Description: Predicted probability of death is calculated based on primary diagnosis; specialty; age; sex; where admitted from; number and severity of prior morbidities; number of emergency admissions in previous 12 months; whether admitted as an inpatient or day case and type of admission (elective / non-elective). Data reliability = Very High (see appendix c) Median: The median enables run chart rules to be applied to identify if there has been a non-random change. (Please see page 17) The median is calculated in line with the ISD HSMR Dashboard. Description: HSMR is calculated as: Observed Deaths within 3 Days / Predicted Deaths Within 3 Days and is calculated for all acute inpatient and day case patients admitted to all specialties. Data reliability = Very High (see appendix c) Page 6 of 22 Print :15/1/215
Safe: Hospital Standardised Mortality Ratio (HSMR) - Wishaw Number of Observed Deaths versus Predicted Deaths (3 days) - Wishaw Number of Observed deaths and Number of Predicted deaths Not Applicable The number of observed deaths has decreased while the number of predicted deaths has decreased only slightly at Wishaw in comparison to the previous quarter, with less observed deaths than predicted. This is reflected in the HSMR figure for this quarter. Hospital Standardised Mortality Ratio - Wishaw Number of Observed deaths Number of Predicted deaths The Q1 215 HSMR for Wishaw has decreased to below the median line (Q1 215 -.98, Q4 214-1.6). A casenote review of the Q4 214 cases has been completed to establish any learning. This data point is the subject of increased scrutiny and a separate report has been considered by HQAIC. In addition, a review of surgical deaths that quarter is taking place.the Board has met with colleagues from HIS and Public Health Intelligence to further review the data to better understand HSMR related analyses including the relationship with unadjusted mortality, and has also shared the findings from the casenote review at that meeting. PREDD_WG OBSD_WG Observed Deaths versus Predicted Deaths - Wishaw HSMRM_WG HSMR - Wishaw 32 1.2 28 1. 24 2.8 Number 16 12 Rate.6.4 8 4.2 Apr-1 Jul-1 Oct-1 Jan-11 Apr-11 Jul-11 Oct-11 Jan-12 Apr-12 Jul-12 Oct-12 Jan-13 Apr-13 Jul-13. Jul-9 Oct-9 Jan-1 Apr-1 Jul-1 Oct-1 Jan-11 Apr-11 Jul-11 Oct-11 Jan-12 Apr-12 Jul-12 Oct-12 Jan-13 Apr-13 Jul-13 Observed Deaths Predicted Deaths Median HSMR Description: Predicted probability of death is calculated based on primary diagnosis; specialty; age; sex; where admitted from; number and severity of prior morbidities; number of emergency admissions in previous 12 months; whether admitted as an inpatient or day case and type of admission (elective / non-elective). Data reliability = Very High (see appendix c) Median: The median enables run chart rules to be applied to identify if there has been a non-random change. (Please see page 17) The median is calculated in line with the ISD HSMR Dashboard. Description: HSMR is calculated as: Observed Deaths within 3 Days / Predicted Deaths Within 3 Days and is calculated for all acute inpatient and day case patients admitted to all specialties. Data reliability = Very High (see appendix c) Page 7 of 22 Print :15/1/215
Safe: Coding Completeness - NHSL Discharges coded within 6 weeks in NHSL Lanarkshire Total number submitted within 6 week target Total number of discharges expected to be submitted The technical issue that prevented SMR data being extracted on time for the February target date was resolved in March allowing NHSL to submit on time. The July 215 figure for NHS Lanarkshire has demonstrated a 1% increase from the previous month to 86%. A more detailed paper will be provided to the next HQAIC. Safe: Coding Completeness - Per Site Discharges coded within 6 weeks in NHSL Lanarkshire Total number submitted within 6 week target Total number of discharges expected to be submitted All three hospitals continue to strive towards achieving the 95% target for discharges coded within 6 weeks of patients being discharged. Both Monklands and Wishaw have shown an increase in July compared to the previous month; Monklands by 3% and Wishaw by 1%. Hairmyres has decreased by 2%. Figures for July are as follows: Hairmyres 83%, Monklands 84%, Wishaw 91%. Process Measure Process Measure DISCH_NHSL % Discharges coded within 6 weeks in NHS Lanarkshire DISCH_NHSL % Discharges coded within 6 weeks - All Hospitals in NHS Lanarkshire 1 1 8 8 6 6 % % 4 4 2 2 Aug-13 Aug-13 % Median Goal % Hairmyres % Monklands % Wishaw Goal Median: The median enables run chart rules to be applied to identify if there has been a non-random change. (Please see page 17) The baseline median was calculated using Jan-Dec 212 data. Following a shift the median has been recalculated from Dec 213. Description: The Scottish Government target for SMR submission to ISD is 6 weeks (42 days) following discharge/transfer/death. ISD calculates timeliness as data received 6 weeks following the end of month of discharge/transfer/death e.g:. all SMR1 records with a March 214 date of discharge/transfer/death would be expected to be submitted to ISD by 12th May 214. The data on the chart above demonstrates the number of SMR1 records submitted by the target date of 6 weeks following the end of the month of discharge. Data reliability = High (see appendix c) Description: The Scottish Government target for SMR submission to ISD is 6 weeks (42 days) following discharge/transfer/death. ISD calculates timeliness as data received 6 weeks following the end of month of discharge/transfer/death e.g:. all SMR1 records with a March 214 date of discharge/transfer/death would be expected to be submitted to ISD by 12th May 214. The data on the chart above demonstrates the number of SMR1 records submitted by the target date of 6 weeks following the end of the month of discharge. Data reliability = High (see appendix c) Page 8 of 22 Print :15/1/215
Safe: Rate of Harms (NHSL) Rate of Harms (NHSL) per 1 total deaths and live discharges Total number of Falls resulting in injury from DATIX, Pressure Ulcers reported on DATIX and Cardiac Arrests (CA audit data) Total number of deaths & live discharges for the same period The chart is based on 3 of the 4 harms across NHS Lanarkshire and work is still in progress to obtain organisation level CAUTI data to incorporate it into this measure. Reducing harm collaborative pilot teams are working on aims to reduce harm in these areas and testing and implementing evidence based changes and achieving reliability of key processes. ROH_NHSL 14 Rate of Harms (NHSL) 12 1 Rate 8 6 4 2 Jul-13 Aug-13 Rate Median Median: The median enables run chart rules to be applied to identify if there has been a non-random change. (Please see page 17) The baseline median is calculated using Aug 12-Jul 13 data points. Description: As part of the Boards Prioritised patient safety plan measuring the number of harms and achieving 95 % harm free care are both strategic aims locally. These measures are key drivers of the National Scottish Patient Safety Programme Phase 2 Page 9 of 22 Print :15/1/215
Safe: Cardiac Arrest Rate - NHSL Cardiac Arrest Rate (True cardiac +/- respiratory arrests) per 1 total deaths and live discharges (NHSL) Total number of true cardiac +/- respiratory arrests Total number of deaths & live discharges for the same period To date there is no statistically significant improvement or reduction in Cardiac Arrests evident. Pilot teams are testing and implementing changes to increase the reliability of key processes that are recognised to impact on and achieve a reduction in Cardiac Arrests. Learning from a previous cardiac arrest casenote review highlighted the following areas for improvement: Reliability of observations, robust DNACPR, End of Life Care and Ceiling of Treatment processes and reliable recognition and response. The reporting of MEWS whilst an important and ongoing component of the work; has been replaced to represent the current focus of improvement work which is ensuring reliability of clinical observations which in turn will increase the reliability of MEWS as part of the recognition and response processes. Aligning the work of DNACPR and associated measures has been identified as an additional area of benefit in progressing this agenda. Safe: Cardiac Arrest Rate - Hairmyres Cardiac Arrest Rate (True cardiac +/- respiratory arrests) per 1 total deaths and live discharges (Hairmyres) Total number of true cardiac +/- respiratory arrests Total number of deaths & live discharges for the same period Whilst the rate of cardiac arrests at Hairmyres appears to be showing less variation overall, there is no statistically significant improvement applying SPC chart rules. This chart show normal variation. Page 1 of 22 Print :15/1/215
Safe: Cardiac Arrest Rate - Monklands Cardiac Arrest Rate (True cardiac +/- respiratory arrests) per 1 total deaths and live discharges (Monklands) Total number of true cardiac +/- respiratory arrests Total number of deaths & live discharges for the same period Safe: Cardiac Arrest Rate - Wishaw Cardiac Arrest Rate (True cardiac +/- respiratory arrests) per 1 total deaths and live discharges (Wishaw) Total number of true cardiac +/- respiratory arrests Total number of deaths & live discharges for the same period This chart show normal variation. This chart currently displays normal variation. The Jan 215 data point was previously reported as breaching the upper control limit. A review of the Cardiac arrests for this period took place and findings have been presented to the patient safety strategic steering group. On review, one data point was not a true cardiac arrest and was removed from the data. This brings the Jan 215 data point back within the control limits. Page 11 of 22 Print :15/1/215
Safe: Number of Patient Safety Leadership Walkrounds - NHSL Number of Patient Safety Leadership Walkrounds (NHSL) The number of Patient Safety Leadership Walkrounds taking place Not applicable Patient safety walkrounds are recognised as a useful activity that demonstrates an organisations commitment to making patient safety a priority. Through the process safety issues raised are turned into key actions with associated timescales to ensure these are progressed in a timely and appropriate manner. NHS Lanarkshire aim to complete 1 patient safety leadership walkround per week and this is being achieved. Process Measure Safe: Patient Safety Leadership Walkrounds - Action Status - NHSL Patient Safety Leadership Walkrounds - Action Status (NHSL) Total Number of Actions Total Number of Actions Closed / Closed with monitoring / Open (overdue) / Open (within target) There has been a significant increase in the closing of actions since the start of the reporting period and as a result the organisation has a deeper understanding of overdue actions. Site based reports are shared with local site teams to enable them to see progress and follow up outstanding actions to achieve closure, where possible. Several actions currently outstanding and have breached relate to environmental issues, site teams are reviewing to see what can be closed off from a walkround perspective or if not resolved added to site risk register. Process Measure WALK_NHSL Number of Patient Safety Leadership Walkrounds 8 7 6 Number 5 4 3 2 1 Aug-15 Number Goal: The goal is for a minimum of 1 Patient Safety Leadership Walkround to take place per week Description: This is a cumulated count of the number of Patient Safety Leadership Walkrounds that occur every month. Senior leaders are encouraged to use Patient Safety Leadership Walkrounds to demonstrate their organisation's commitment to building a culture of safety. Page 12 of 22 Print :15/1/215
Safe: Closure of Category 1 rated incidents in Datix Safe: Closure of Category 2 rated incidents in Datix Closure of Category 1 rated incidents in Datix within agreed timescales Closure of Category 2 rated incidents in Datix within agreed timescales Total Category 1 rated incidents closed in Datix within 9 days Total Category 2 rated incidents closed in Datix within 3 days Total number of incidents in DATIX graded as Category 1 rated incidents Total number of incidents in DATIX graded as Category 2 rated incidents There were 12 verified Category 1 incidents (2 SAER s have been commissioned, 1 complete <9 day timescale; 1 overdue - due to delayed decision from the commissioner, this was confirmed 8/215, report scheduled for sign-off on 16/1/215. There are 3 Category 1 incidents where a Suicide Review has been commissioned. From the 3 Category 1 incidents not closed <9 days, 1 had initial delay in commissioning, 2 had no SAER commissioned, but will be reviewed through M&M site meetings. Both incidents occurred in MDGH, with no retrospective update and closure. The following chart sets out NHSL performance against category 2 incidents and timescales for closure of incidents. For incidents exceeding the agreed timescale there is an escalation process involving operational Site Risk Management Facilitators and Senior Management teams. RSKH_NHSL % of Category 1 rated incidents in Datix closed within 9 days RSKM_NHSL % of Category 2 rated incidents in Datix closed within 3 days % of Cat 1 incidents closed within 9 days 1 8 6 4 2 % of Cat 2 incidents closed within 3 days 1 8 6 4 2 % breaches Median % breaches Median Description: The risk management steering group set performance indicators (KPIs) The KPIs inform the board on the effectiveness of incident management. The board should look for performance to be improving. Description: The risk management steering group set performance indicators (KPIs) The KPIs inform the board on the effectiveness of incident management. The board should look for performance to be improving. Page 13 of 22 Print :15/1/215
Safe: Compliance with Hospital Length of Stay Average Hospital Length of Stay: Surgical Total bed days used for patients discharged from a Surgical specialty Number of hospital discharges, for patients discharged from a Surgical specialty The ALOS (Surgical) chart has been updated with refreshed data from MiLAN and is now displaying normal variation for the May period. The average Hospital Length of Stay (surgical) for August 215 has decreased in comparison to the previous month and is displaying normal variation. Dec 214 data presented a special cause data point; poor flow and an increase in delayed discharges was noted in Dec 14 for NHSL. Further review of the data at hospital level indicates that the Surgical ALOS was particularly high for Hairmyres Hospital in Dec 214. Average Hospital Length of Stay: Medical Total bed days used for patients discharged from a Medical specialty Number of hospital discharges, for patients discharged from a Medical specialty The ALOS (Medical) chart has been updated with refreshed data from MiLAN. The August 215 data has dropped below the lower control limits and is displaying special cause variation. Description: Reducing Length of Stay releases capacity in the system, including beds and staff time. This increase in capacity will help to minimise waiting times, maximise productivity and improve the patient experience. However, if patients are discharged too early this could lead to readmissions. Work is underway to identify a suitable benchmark as the overall Scottish average rate is not comparable. This will be incorporated at a future date. Description: Reducing Length of Stay releases capacity in the system, including beds and staff time. This increase in capacity will help to minimise waiting times, maximise productivity and improve the patient experience. However, if patients are discharged too early this could lead to readmissions. Work is underway to identify a suitable benchmark as the overall Scottish average rate is not comparable. This will be incorporated at a future date. Page 14 of 22 Print :15/1/215
Safe: Compliance with Emergency Medical Readmissions Rate of Emergency Medical Readmissions within 7 days (per 1 discharges) Number of emergency readmissions to any medical specialty within 7 days of discharge for patients initially admitted to a medical specialty Number of hospital discharges, for patients admitted to a medical specialty The data is displaying normal variation. The increased rate of Medical Readmissions (Dec - Mar) has been driven by readmissions through Monklands Hospital and reflects changes to classification of admission type in the Monklands site. The Medical Ambulatory Emergency Care (AEC) unit commenced 24th November 214 in Monklands Hospital. AEC patients were coded as admissions from this point onwards and AEC returns were initially coded as admissions. This issue was resolved in June 215 when return clinics and coding were set up on TRAK for coding the AEC returns. Additionally there was a change to the coding process for medical patients going into the GP assessment area as of 22nd December 214. Prior to this GP assessment patients were coded as non- admissions in the ED campus and on the clock. These patients are now coded as admitted patients and no longer on the ED Campus. Rate of Emergency Medical Readmissions within 28 days (per 1 discharges) Number of emergency readmissions to any medical specialty within 28 days of discharge for patients initially admitted to a medical specialty Number of hospital discharges, for patients admitted to a medical specialty The data is now displaying normal variation. The SPC chart displays non-random variation for the Oct 14 to May 15 period, and Dec 14 / Jan 15 are outwith the upper control limits.see narrative for Emergency Medical Readmissions within 7 days. READMM7_NHSL Rate 9 85 8 75 7 65 6 55 5 45 4 35 3 25 2 15 1 Aug-13 Medical Readmissions within 7 Days READMM28_NHSL Rate 16 155 15 145 14 135 13 125 12 115 11 15 1 95 9 85 8 Aug-13 Medical Readmissions within 28 Days Rate Median National Average Rate Median National Average Description: Readmissions within 7 days give a more accurate picture of readmissions which are clinically related to the index episode and it has been shown that readmissions within 7 days are likely to contain a higher proportion of 'avoidable' readmissions than the broader category of readmissions within 28 days (Levy et al, 2).**Clinical Outcome Indicators, Clinical Resource and Audit Group (CRAG), 22 Description: Around 15% to up to 2% of 28-day readmissions could be regarded as avoidable*. The most promising interventions to prevent readmission appear to be those that concentrate on coordination and communication around the time of discharge. *Preventing emergency readmissions to hospital, a scoping review, E. Nolte, M. Roland, S. Guthrie, Laura Brereton, 212 (prepared for the UK Department of Health) Page 15 of 22 Print :15/1/215
Safe: Compliance with Emergency Surgical Readmissions Rate of Emergency Surgical Readmissions within 7 days (per 1 discharges) Number of emergency readmissions to any surgical specialty within 7 days of discharge for patients initially admitted to a surgical specialty Number of hospital discharges, for patients admitted to a surgical specialty The 7 day Surgical Readmissions Rate reporting has been moved into an SPC chart. The data is currently displaying normal variation. Rate of Emergency Surgical Readmissions within 28 days (per 1 discharges) Number of emergency readmissions to any surgical specialty within 28 days of discharge for patients initially admitted to a surgical specialty Number of hospital discharges, for patients admitted to a surgical specialty The 28 day Surgical Readmissions Rate reporting has been moved into an SPC chart. The data is currently displaying normal variation. READMS7_NHSL Surgical Readmissions within 7 Days READMS28_NHSL Surgical Readmissions within 28 Days Rate 5 45 4 35 3 25 2 15 1 5 Aug-13 Rate 8 75 7 65 6 55 5 45 4 35 3 25 2 15 1 5 Aug-13 Rate Median National Average Rate Median National Average Description: Readmissions within 7 days give a more accurate picture of readmissions which are clinically related to the index episode and it has been shown that readmissions within 7 days are likely to contain a higher proportion of 'avoidable' readmissions than the broader category of readmissions within 28 days (Levy et al, 2).**Clinical Outcome Indicators, Clinical Resource and Audit Group (CRAG), 22 Description: Around 15% to up to 2% of 28-day readmissions could be regarded as avoidable*. The most promising interventions to prevent readmission appear to be those that concentrate on coordination and communication around the time of discharge. *Preventing emergency readmissions to hospital, a scoping review, E. Nolte, M. Roland, S. Guthrie, Laura Brereton, 212 (prepared for the UK Department of Health) Page 16 of 22 Print :15/1/215
Quality Ambition: Effective "The most appropriate treatments, interventions, support and services will be provided at the right time to everyone who will benefit, and wasteful or harmful variation will be eradicated." Progress on this ambition is measured through clinical quality indicators, for stroke care and A&E waiting times Effective: Stroke Care Bundle Indicators & Thrombolysis % of patients who receive all key elements of the Stroke Care Bundle Total no. of patients admitted to hospital with a diagnosis of stroke who receive all the relevant key elements of the Stroke Care Bundle Total no. of patients admitted to hospital with a diagnosis of stroke This indicator replaces the previously reported stroke indicators for Stroke Admission and Stroke treatment. The Stroke Care Bundle includes the most important drivers for improving stroke outcomes, i.e. admitted to Stroke Unit within 1 day of admission / swallow screened on day of admission / scanned within 24hrs of admission / aspirin received within 1 day of admission. This change in reporting ensures that we utilise the opportunity to drive improvement with the key aspects of stroke care in Lanarkshire and to be consistent with national drivers for improvement. The reason for changing from Stroke Unit Admission in isolation to the bundle analysis is that admission to stroke unit is much less of a quality indicator than the stroke bundle. Compliance with the bundle has shown better outcomes and reduced mortality. The Standard for Stroke Care Bundle performance in Lanarkshire during August 215 was reached. Process Measure Process Measure % of stroke patients receiving thrombolysis within 1 hour of arrival Total no. of stroke patients receiving thrombolysis within 1 hour Total no. of stroke patients receiving thrombolysis (where dates and times of thrombolysis recorded) The thrombolysis door to needle time is a new indicator in the report. The Stroke MCN feels that recent changes to the pathway and process across the 3 sites has shown consistent improvement around patients accessing this timely intervention. By sharing this data on a monthly basis we can sustain the focus on achieving 6 min door to needle pathway involving ED, radiology and stroke service. The standard for Thrombolysis performance during August 215 was reached. Goal: Scottish Stroke Care Standards - The Stroke Care Bundle includes the most important drivers for improving stroke outcomes, i.e. admitted to Stroke Unit within 1 day of admission / swallow screened on day of admission / scanned within 24 hours of admission / aspirin received within 1 day of admission. Description: The Scottish Stroke Care Standards focus on those parameters which have the best evidence for having an effect on patient outcomes. Data reliability = High (see appendix c) Goal: Scottish Stroke Care Standards: 8% of patients receive the bolus of recombinant plasminogen activator within one hour of arrival Description: The Scottish Stroke Care Standards focus on those parameters which have the best evidence for having an effect on patient outcomes. Data reliability = High (see appendix c) Page 17 of 22 Print :15/1/215
Effective: Carotid Interventions for Stroke Patients % of stroke patients having a Carotid Intervention within 14 days of event No. of patients having a Carotid Intervention within 14 days of event that led to the patient first seeking medical attention No. of patients having a Carotid Intervention Following discussion with the Chief Executive, it was felt that by sharing the Carotid intervention data we would have a clearer focus on improving the inconsistent performance we currently have in achieving intervention within 14 days of symptom onset. We would hope over the coming months to develop a more robust pathway with radiology services, stroke services and vascular services in order to ensure a more seamless and timely pathway is embedded. Again, the performance against the Standard for Carotid Intervention in August was not met. There is a National Carotid event scheduled for 22nd October with representation from the Stroke MCN in Lanarkshire, along with Stroke and Vascular clinicians attending this. Clinical Quality colleagues will also be in attendance. Process Measure Goal: Scottish Stroke Care Standards - 8% of stroke patients have a Carotid Intervention within 14 days of event that led to the patient first seeking medical assistance Description: Carotid endarterectomy is a surgical procedure which aims to reduce the risk of stroke. The effectiveness of the procedure diminishes as time passes following the TIA/stroke event. Most benefit is derived from surgery performed within 14 days. Data reliability = High (see appendix c) Page 18 of 22 Print :15/1/215
Effective: Compliance with A&E Treatment Target % of A&E attendances waiting more than 4 hours The number of patients waiting for more than 4 hours at an A&E clinic. The number of patients attending an A&E department. Four hour waiting time breaches in August have increased in comparison to the previous month from 5.44% to 7.86%. A key factor in this increase was felt to be the junior doctor changeover and key learning will be enacted during the next changeover. The July % was the lowest reported % in the reporting period. % of A&E attendances waiting more than 12 hours The number of patients waiting for more than 12 hours at an A&E clinic. The number of patients attending an A&E department. 12 hour waiting time breaches for August have decreased in comparison to the previous month and at.4% is the lowest reported % since August 213. There has been a key focus on right place first time on all sites for those patients who are admitted. AE4HRS_NHSL A&E Waiting Times Breaches - 4Hrs AE12HRS_NHSL A&E Waiting Times Breaches - 12Hrs 2 1.4 % of A&E Waiting times breaches 18 15 13 1 8 5 3 % of A&E Waiting times breaches 1.2 1..8.6.4.2 Aug-15. Aug-15 % breaches Goal % breaches Goal Goal: 5% or less of A&E attendances waiting more than 4 hours Description: The Scottish Government standard for Accident and Emergency departments is that 95 % of all attendances are seen within 4 hours. The board should look for % of A&E waiting times breaches to be at or below the compliance line. Goal: Eliminate 12 hour waits Description: Actions against AIM 9 in the 214-17 NHSL Quality Assurance & Improvement Strategy includes measuring and reducing patient harms relating to patient flow. The Board should look for % of A&E waiting times breaching 12 hours to be reducing to zero. Page 19 of 22 Print :15/1/215
Appendix B - Notes on the data Average Hospital Length of Stay. The data reported only shows Inpatient Hospital Discharges. Total Hospital Length of Stay (HLOS) is linked to the discharge specialty and discharge date even if part of the hospital stay took place under different specialties and/or across different specified dates. This ultimately means some outlier long stays could have a big impact on Average HLOS for a specific specialty. The data reported only shows admissions where hospital Spell start date = admission date, therefore some hospital transfers will be excluded. Measures have not been standardised by age, sex and deprivation Average HLOS has not been adjusted for case mix so may reflect variations in complexity of patients treated Denominators are based on discharge dates to allow shorter reporting lag times. This means that the data on the local report will not be directly comparable with the national Early Warning Scorecard which uses admission dates for reporting. Data are subject to change following SMR validation processes. Readmissions d ata Me asures have not b ee n standardised by age, sex and deprivation R ates are only calculated using linked data held in the La narkshire TrakCare PMS and therefo re doe s not include re admissions to other Health Boards D enominators are based on discharge dates to allow shorter reportin g lag tim es. This m eans that the data on the local re port w ill not be directly compa rab le w ith the national Early W arning Scorecard which uses admission da tes for repo rting. D ata are subject to change following S MR validation processes. Deaths and Live Discharges The denominator for Unadjusted Patient Mortality includes Deaths and Live Discharges in all areas except for Obstetrics. Both the numerator and the denominator for Cardiac Arrest Rate exclude Cardiac Arrests and Deaths and Live Discharges in these areas respectively: - -Hairmyres CCU -Hairmyres Day Surgery Unit -Hairmyres Dental Day Unit -Hairmyres ITU -Hairmyres Maternity Day Assessment -Monklands Endoscopy Unit -Monklands Hospital Day Surgery Unit -Monklands Ward 16 Haem atology Day Unit -Monklands Ward 26 ITU -Wishaw General CCU -Wishaw General ICU -Wishaw General Medical Day Unit -Wishaw General Neonatal ICU -Wishaw General Surgical Day Unit -Wishaw General Ward 19 -Wishaw General Ward 2 -Wishaw General Ward 21 -Wishaw General Ward 22 -Wishaw General Ward 23 -Wishaw General Ward 24 Page 2 of 22 Print :15/1/215
Appendix B - Notes on the data (continued) Interpreting run charts using run chart rules RULE 1: A SHIFT 6 or more consecutive points either all above or all below the median line RULE 2: A TREND 5 or more consecutive points all going in the one direction (up or down) RULE 3: TOO MANY OR TOO FEW RUNS A non random pattern would be indicated by the data crossing the median too many or too few times (Reference table for this one) RULE 4: AN ASTRONOMICAL VALUE A value that is obviously, blatantly different and really stands out as being highly unusual Data Reliability Each metric has been graded for data reliability against the Clinical Quality Data Reliability Matrix (see Appendix C). The Data Reliability score is calculated based on the data source and sample size vs. the highest level of validation the data has been subject to. Notes: Whilst there is a drive to provide Clinical Quality data that is as complete, accurate and valid as possible, it is also important that data for local improvement is available as real time as possible and full validation is therefore not always possible or necessary. Clinical Quality data is reported from a variety of sources. The method of data collection and source of data will have an impact on the level of data validation, and subsequently the reliability of data reported: For example, data collected via direct observations of clinical practice (e.g. patient safety process measures) are based on an individual s judgement that something has happened at a particular point in time. This data can never be checked against source data (e.g. clinical records) and there is a reliance on the individual to provide an accurate account of events. Observational data would therefore be considered of low reliability in terms of accuracy. However, since observational measurement is in the main data for improvement, this level of reliability would be acceptable. Conversely, data extracted from clinical systems (e.g. laboratory results) should be of high reliability in terms of accuracy, as this is clinical data used for managing patient care. For reporting purposes however, this type of data would still need to be checked for format, completeness, duplicates and outliers and the level of reliability would increase depending on the level of validation applied. Page 21 of 22 Print :15/1/215
Appendix C - Clinical Quality Data Reliability Matrix HIGH Reliability of data LOW Reliability of data HIGH DATA SOURCE 5 4 3 2 Higher score = greater level of confidence in reliability of data Data extract from clinical systems (PMS / Labs etc.) Data transcribed from clinical records onto paper forms / databases (1% sample) Data which relies on individuals reporting incidences (e.g. extract from DATIX / cardiac arrest) Data from surveys / questionnaires / small sample casenote reviews HIGHEST LEVEL OF VALIDATION 5 4 3 2 1 Validation checks on format, External QA Locally validated completeness, Sense checks against source against source duplicates, prior to reporting data (e.g. ISD) data outliers & No validation standards 25 2 15 1 5 2 16 12 8 4 15 12 9 6 3 1 8 6 4 2 LOW 1 Data from direct observations of clinical practice 5 4 3 2 1 Page 22 of 22 Print :15/1/215