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CEM/IFEM Symousium: Quality and Safety in Emergency Care November 15th, 2011   Michael Schull, MD

Mitigating threats to high quality, safe patient care created by ED overcrowding: The Canadian Perspective. CEM/IFEM Symousium: Quality and Safety in Emergency Care November 15th, 2011   Michael Schull, MD. Disclosures. Advisor to Ontario Ministry of Health and Long-Term Care

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CEM/IFEM Symousium: Quality and Safety in Emergency Care November 15th, 2011   Michael Schull, MD

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  1. Mitigating threats to high quality, safe patient care created by ED overcrowding: The Canadian Perspective CEM/IFEM Symousium: Quality and Safety in Emergency Care November 15th, 2011   Michael Schull, MD

  2. Disclosures • Advisor to Ontario Ministry of Health and Long-Term Care • No industry funding • Funded by several Canadian Federal research agencies

  3. Objectives: • To provide a perspective on efforts to reduce risks associated with ED overcrowding in Canada • (as opposed to providing the perspectives of a Canadian…)

  4. Summary, take home, money slide • Where system-wide efforts have taken place to mitigate ED overcrowding in Canada, the target has been reduction in overall ED length-of-stay (waiting time) • ED LOS = waiting time = total time in ED

  5. Common interventions to reduce ED LOS • Waiting time targets • Public reporting • Pay-for-performance incentives • LEAN-type interventions to improve ED and in-patient flow, and speed hospital discharges • Sanctions for poor performance

  6. Variation in ED waiting time targets

  7. Have we got this right? • Is targeting reductions in overall ED LOS the right approach? • Mixed views on use of ED waiting time as a quality/safety indicator • Should we rather target high acuity conditions with time sensitive treatments (STEMI, stroke, sepsis)?

  8. Question: are ED patients who were not admitted to hospital at greater risk of death or hospitalization within 7 days of ED departure when they visited an ED during a shift with long ED waiting times? Design: 5 years of data, all higher volume EDs, controlled for important confounders, databases included death certificates so could include deaths in community as well.

  9. Adjusted odds ratios (95% CI) by DEGREE OF CROWDING for death and hospitalization within 7 days of an ED visit, all discharged high acuity patients

  10. If overall waiting times are bad, does that make waiting time targets good? • Longer ED waiting times associated with serious adverse events, but that doesn’t mean that better performance on current ED waiting time targets will improve outcomes….

  11. Adjusted odds ratios (95% CI) by TARGET ATTAINMENT for death and hospitalization within 7 days of an ED visit, all discharged high acuity patients Not yet peer-reviewed!

  12. “Informal” vs formal LEAN-type efforts to improve patient flow • Many hospitals working to improve waiting times, and some have brought in consultants for LEAN or Six Sigma programs to improve patient flow • Might this convey some safety advantage, or put excess emphasis on efficiency at the expense of patient safety?

  13. “Informal” vs formal LEAN-type efforts to improve patient flow • Ontario launched ED Process Improvement Program at 90 hospitals from 2009-2011 in 4 waves • 8-month, consultant led model, ED, in-patient and discharge teams to improve flow • Evaluated in comparison with control sites, looking at effect on waiting times and patien safety

  14. Independent effect of LEAN-type intervention compared with control hospitals (wave 3) Better Worse

  15. To develop a consensus on a prioritized and parsimonious set of evidence-based quality of care indicators for EDs. The process was led by a nationally representative committees (reps from administration, EM, health information, government, and provincial quality councils). A comprehensive review of the scientific literature was conducted to identify candidate indicators CJEM 2011; 13(5)

  16. Top priority indicators by ranking

  17. Gaps in existing indicators • Patient satisfaction/experience • Healthy workplace • Elder care • Hospital-community integration

  18. So we have indicators…could somebody please use them? • Limited adoption at a system level, though many hospitals measure some of the indicators. • Extent of sharing of data across sites is unknown, but likely limited • Limited “shelf-life”, sundown clauses?

  19. Would managing more indicators help mitigate crowding? • Doubtful: focusing solely on potential adverse consequences of crowding by measuring multiple focused indicators might lead to a piecemeal approach to ED patient care based on chief complaint or diagnosis. • Need balanced approach: focus on overall waiting times AND condition-specific ones

  20. But are we forgetting more remote effects of crowding after leaving our EDs? • Solutions for ED crowding lie largely outside the ED…similarly, should we be looking beyond our EDs when thinking about quality/safety? • E.g. Failure to ensure adequate follow-up for our discharged patients?

  21. Follow-up outpatient care within 30 days of ED discharge for an acute exacerbation of CHF, COPD or Diabetes, all EDs, Ontario, 2005-2008 Source: Schull et al. ICES unpublished

  22. Care model post-ED discharge for CHF and 1 year mortality, all Ontario EDs, 2004-2006 Source: Lee et al. Circulation November 2, 2010 vol. 122 no. 18 1806-1814

  23. But are we forgetting more remote effects of crowding after leaving our EDs? • What about remote adverse consequences of decisions made in the ED…such as causing cancer. • (mis)use of ionizing radiation among ED patients

  24. Rate of CT utilization among all ED patients, USA vs Ontario (2003-2008) Berdahl C et al. SAEM 2011

  25. Thank you! We’d like to open the floor to shorter speeches disguised as questions.

  26. Change in Median ED Waiting Time Post-LEAN-type intervention (wave 3)

  27. Change in Median ED Waiting Time Post-LEAN-type intervention (wave 3)

  28. Change in Median ED Waiting Time Post-LEAN-type intervention (wave 3)

  29. Change in Median ED Waiting Time Post-LEAN-type intervention (wave 3) Heterogeneity is not noise! While these hospitals did worse? Why did these hospitals do better?

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