Unscheduled care Urgent and Emergency Care Professor Derek Bell Acute Medicine Director NIHR CLAHRC for NW London Imperial College London Chelsea and Westminster Hospital
Value as the overarching, unifying goal Outcomes Defined by patient from patient s perspective Measured for patient s condition over entire episode of care VALUE FOR PATIENTS Cost Resources used, NOT price Measured for patient s condition over entire episode of care Value for Patients = Health Outcomes Cost of delivering outcomes Source: Tom Lee, Partners Health Care System, Boston Improving value for patients may be the only thing that all key stakeholders can agree upon Tom Lee, CEO Partners Network, Boston
What we know International crisis! = overcrowding Recognised in UK 2000 Quality of care could be better Patient outcomes Patient experience Staff experience Design (better) cost effective services Scientific approach complex system Collaboration
Unscheduled care is defined by patient or carer need Majority over 65 years old Young people die as well
Managing urgent and emergency care requires a whole systems approach. However, we all have a responsibility to manage our part of the patient care pathway optimally and not blame the patients or other specialties.
Health and Social Care Whole System: Overview of Patient Flows (Figures in parentheses are patient flows, in millions of cases per year) Self Care 1.4 billion 230m GP Primary Care (Consultations) 1 4 Emergency admissions Outpatient Attendances 2 2 Elective admissions 4 Elective Day Cases Health Incident 2 billion (99-00)) 9 10 3 Self to A&E 999 1 3 A&E Attendances 2 6 A&E Flow to Repeat Outpatients GP = 31m 340m Fast Access Primary Care (NHS Direct and Walk in Centres) Residential & Nursing Home Care HOSPITAL CARE SECTOR In Hospital Health Incidents Intermediate Care Home Care Pharmacy
Patterns of Illness behaviour in Medical Patients the physiology of the system Unstable Point of Care Concerns Stable Assessment 0-48Hours Days
Patient perception of quality related to waiting time in acute care Percentage rating care positively by time waiting to be examined by a nurse or doctor (n=39143) 98% 95% 89% 82% 71% 52% In UK now > 5% again No wait (17% of patients) 1-30 minutes (43% of patients) 31-60 minutes (26% of patients) Between 1 and 2 hours (17% of patients) Between 2 and 4 hours (11% of patients) Over 4 hours (3% of patients)
All cause mortality (%) Mortality 2002- Acute Medicine all cause (n=19533) P < 0.0001 14.0 12.0 10.0 12.7 11.8 10.9 9.4 8.0 7.0 6.0 4.0 2.0 0.0 2002 2003 2004 2005 20 *Odds Ratio 20 vs 2002 = 0.52 : NNT 17.6
Why patient flow groups? Warwick report Based on patient journey and experiences Aim to Simplify - understand/analyse variability Optimise access Maintain a whole system picture Reflects Volume Time Complexity of patient journey Staff Diagnostics Interventions Facilities Encourages thinking beyond professional or departmental boundaries
Acute patient flow groups Flow 1 < 4 hours ED minors Flow 2 0-72 hours AMU/ASU Flow 3 > 72 hours Medical Admissions H o m e Flow 4 > 72 hours Surgical admissions
National Performance - Flow 4 50% 55% 60% 65% 70% 75% 80% 85% 90% 95% 100% Se p- 05 O ct- 05 No v- 05 De c- 05 J an- Fe b- Ma r- Ap r- Ma y- J un- Jul- Au g- Se p- O ct- No v- De c- J an- Fe b- Ma r- Ap r- Ma y- J un- Jul- Au g- Se p- O ct- No v- De c- Lower quartile Median Upper quartile National Performance - Flow 3 50% 55% 60% 65% 70% 75% 80% 85% 90% 95% 100% Se p- 05 O ct- 05 No v- 05 De c- 05 J an- Fe b- Ma r- Ap r- Ma y- J un- Jul- Au g- Se p- O ct- No v- De c- J an- Fe b- Ma r- Ap r- Ma y- J un- Jul- Au g- Se p- O ct- No v- De c- Lower quartile Median Upper quartile National Performance - Flow 2 70% 75% 80% 85% 90% 95% 100% Se p- 05 O ct- 05 No v- 05 De c- 05 J an- Fe b- Ma r- Ap r- Ma y- J un- Jul- Au g- Se p- O ct- No v- De c- J an- Fe b- Ma r- Ap r- Ma y- J un- Jul- Au g- Se p- O ct- No v- De c- Lower quartile Median Upper quartile National Performance - Flow 1 90% 91% 92% 93% 94% 95% 96% 97% 98% 99% 100% Se p- 05 O ct- 05 No v- 05 De c- 05 J an- Fe b- Ma r- Ap r- Ma y- J un- Jul- Au g- Se p- O ct- No v- De c- J an- Fe b- Ma r- Ap r- Ma y- J un- Jul- Au g- Se p- O ct- No v- De c- Lower quartile Median Upper quartile
4 hour access in England 98% standard -----95%
10/01/2010 24/01/2010 /02/2010 21/02/2010 /03/2010 21/03/2010 04/04/2010 18/04/2010 02/05/2010 16/05/2010 30/05/2010 13//2010 27//2010 11//2010 25//2010 08/08/2010 22/08/2010 05/09/2010 19/09/2010 03/10/2010 17/10/2010 31/10/2010 14/11/2010 28/11/2010 12/12/2010 26/12/2010 09/01/2011 23/01/2011 /02/2011 20/02/2011 /03/2011 20/03/2011 03/04/2011 17/04/2011 01/05/2011 15/05/2011 29/05/2011 12//2011 26//2011 10//2011 24//2011 /08/2011 21/08/2011 04/09/2011 18/09/2011 02/10/2011 16/10/2011 30/10/2011 13/11/2011 27/11/2011 11/12/2011 25/12/2011 08/01/2012 22/01/2012 05/02/2012 19/02/2012 04/03/2012 18/03/2012 01/04/2012 15/04/2012 29/04/2012 13/05/2012 27/05/2012 10//2012 4 hr emergency care standard compliance, % Avg daily ED* attendance, n 100% 99% 98% 97% 96% 95% 94% 93% 92% 91% 90% 89% 88% 87% 86% 85% 84% 83% 82% 81% 80% Hairmyres ED* attendance, 4 hr emergency care standard compliance, 12 hr ED* LoS breaches Weekly compliance with 4 hr emergency access standard, %; average daily core ED* attendance, n; ED LoS > 12 hr, n Sources: local unvalidated TrakCare extracts and management information reports covering unscheduled activity for core ED sites Jan 2010 to 10 Jun 2012 Notes: (i) ED* refers to EDs, MIUs and trolleyed assessment areas; (ii) results are intended for management information only and are subject to change 300 97.4% 96.7% 250 94.7% 200 169 166 153 150 100 42 35 50 28 15 17 19 15 12 11 11 1 4 52 13 31 1 1 7 2 7 78 1 7 1 1 3 2 10 15 1 9 8 10108 1 1 7 1 0 Avg daily ED* attendance (w/e 10 Jun 2012): 166 12 hr ED* LoS breaches (w/e 10 Jun 2012): 1 4 hr ED* LoS compliance (w/e 10 Jun 2012): 94.7% Avg 4 hr ED* LoS compliance: 95.1% Lower/Natural process limit** HS6 national standard: 98.0%
No. of Attendances No. of Attendances 35 30 The data said... Buffered sustainable A&E Winter Profile (Dec 08) No buffer not sustainable 50 45 40 A&E Profile (Dec08) 25 20 15 10 5 Capacity 35 30 25 20 15 10 5 0 0.00 1.00 2.00 3.00 4.00 Waiting Time (Hours) 0 0.00 1.00 2.00 3.00 4.00 Waiting Time (Hours)
What we know Predictable Emergency activity Patient flow Plan systems Capacity and demand Staff and resources Monitor Process often time based Outcomes both clinical and patient reported experience
The data said... Scotland level admissions and discharges with A&E breaches 3500 Number of Inpatient Admissions Number of Inpatient Discharges Number of 4 hour breaches 3000 2500 2000 1500 1000 500 0
Scientific approach Measure Processes = the system Outcomes = clinical competence + system Patient experience listen and learn Mortality Greater for patients admitted at weekends Greater during handover periods Patients don t like waiting and poor communication
London data shows hospital mortality is higher at the weekend than midweek Total emergency admissions In hospital mortality following emergency admission Weekday 521,868 16,377 3.14 Weekend 159,676 5,531 3.46 In hospital mortality following emergency admission (%) +0.32 The 0.32% difference between weekday and weekend mortality equates to 520 potentially avoidable deaths The odds ratio is 1.1 P = <0.001
Hospital Outcome Measures relating to Emergency patient spells 100 hospitals Overall adjusted Case Fatality Rate (acfr) 4.3% 2.5% - 6.4% acfr of weekend admissions 4.8% 2.5% - 7.7% OR =1.15 acfr of weekday admissions 4.2% 2.1% - 6.6% 7 day readmission rate 8.9% 5.6% - 13.3% Mean LOS (days) 8.5 5.20-12.10
Seven day services essential for urgent care to avoid Increased mortality Increased hospital length of stay High value services Extended day? 24 hours?
Inclusive Consultant pattern of working Emerging themes Consultant of several days ( 1 day) No other clinical duties Twice daily acute take ward rounds 7/7.that review all patients Reduce adjusted case fatality rates (p<0.01) Beneficial effect on excess weekend mortality (p<0.05) Lower 28 day readmission rates (p<0.01)
What factors may contribute to this? Many factors but not the patients fault!
On bad days the system and people behave badly
Any bed any time is unsafe
Unscheduled care We know the problems implementing the solution..? Crossroads Danger of losing ground - turning the clock back Or reinventing buckled wheels Recognise economic and policy pressures Avoid silo working Listen to patients and carers Use data and continuously re-assess your systems We have done a lot but we need to do more!
Clinicia n Crisis management Patient Bed Pull to appropriate care Anticipatory versus crisis management: Consequences and mitigation of patient boarding Value-stream mapping patient value, staffing, waits, key interactions + Operational information Activity, bed-state, EDD and predictors (TRAK) Complementary predictive capacity and demand information (System Watch, SAS) Key: R 1 + _ R 9 + + R 1 R 3 Scheduling pharmacy; diagnostics; care package; transport; discharge letter criteria-led discharge discharge lounge Co-ordinated anticipatory management R 5 Buffering + Resource alignment Demand Appropriate bed available + + R - Operational Patient discharge 5 8am 9am 11am + support Ward round meeting R + 7 See Winter Pressures Report recommendations Reinforces/increases Inhibits Late-in-day discharge + staffing/capacity matches variation in streamed activity state-based escalation R Demand 4 smoothing elective/emergency balancing GP referral timing/7-day MIIU weekend community care/rehabilitation - + Patient Boarding R 8 Reduced bed availability + Length of stay Length of stay (hours) (days) + + Extended ward rounds + + R 6 R 2 Wait for bed + Lack of appropriate bed + + + System performance and process effectiveness monitoring information bed use (LoS) bed value (clinical cover) clinical risk (staff cover; displacement; handoffs) throughput clinical work clinical input R 9 KPM1 impact: HEAT E4: same-day surgery HEAT T1: older people readmission HEAT T6: LTC admission rates HEAT T10: ED attendances HEAT Standard 6: 4-hour emergency access Exacerbated by: use of short-stay assessment and/or low volume specialty beds use of inappropriate areas, including thinly staffed day-surgery, observation and winter surge wards fragmentation of patient group across multiple areas Reduced effectiveness and Improved quality and performance
Challenges Modelling Early warning System design Hospital design The IT infrastructure is fractured Engaging technological solutions with human dimension Recognise the landscape is changing
Proportion admitted The data said... 0.45 Number of A&E attendances per day vs proportion admitted 0.45 Number of A&E attendances per day vs proportion admitted 0.40 0.40 0.35 0.35 0.30 0.30 0.25 0.25 0.20 0.20 0.15 0.15 0.10 0.10 0.05 0.05 0.00 200 250 300 350 400 Attendances 0.00 100 150 200 250 300