1. Prevention of Serious Adverse Events in Belgian Acute Care Hospitals Filip Haegdorens PhD student Faculty of Medicine and Health Sciences Division Nursing and Midwifery Sciences University of Antwerp

2. Content 1.Context 2.What is known 3.Rapid Response System / Early Warning Score 4.Improving nurse observation and escalation 5.Current research

3. Healthcare is hazardous 44.000 - 98.000 patients die each year as a result of preventable errors in care44.000 - 98.000 patients die each year as a result of preventable errors in care IOM. To Err Is Human: Building a Safer Health System. National Academies Press, 2000.

4. Healthcare is hazardous 44.000 - 98.000 patients die each year as a result of preventable errors in care44.000 - 98.000 patients die each year as a result of preventable errors in care IOM. To Err Is Human: Building a Safer Health System. National Academies Press, 2000. † 43.458 † 42.297† 16.516

5. Healthcare is hazardous Medical errors do not result from individual recklessness or the actions of a particular group – not a “bad apple” problem.Medical errors do not result from individual recklessness or the actions of a particular group – not a “bad apple” problem. -Caused by faulty systems, processes, and conditions -Leading to mistakes or failure to prevent them IOM. To Err Is Human: Building a Safer Health System. National Academies Press, 2000.

6. It is a problem … Adverse events result in: 1. Invalidity at discharge 2. Death 3. Length of stay ➚ IOM. To Err Is Human: Building a Safer Health System. National Academies Press, 2000.

7. Conclusion: 1.Make it hard to do something wrong 2.Make it easy to do something right  Redesign the system IOM. To Err Is Human: Building a Safer Health System. National Academies Press, 2000.

8. Content 1.Context 2.What is known 3.Rapid Response System / Early Warning Score 4.Improving nurse observation and escalation 5.Current research

9. What is the problem? A significant proportion of hospital deaths occur after serious unforeseen adverse eventsA significant proportion of hospital deaths occur after serious unforeseen adverse events Zegers et al (2009). Adverse events and potentially preventable deaths in Dutch hospitals: results of a retrospective patient record review study. Qual Saf Health Care, 18(4), 297-302.

10. What is the problem? 84% of cardioresp. arrests are preceded by slow deterioration of vital signs84% of cardioresp. arrests are preceded by slow deterioration of vital signs 54% of patients received suboptimal care before admission to the ICU54% of patients received suboptimal care before admission to the ICU - Hillman KM et al. Antecedents to hospital deaths. Intern Med J 2001; 31, 343-348. - Schein RM et al. Clinical antecedents to in-hospital cardiopulmonary arrest. Chest 1990; 98, 1388-1392. - McQuillan P et al. Confidential inquiry into quality of care before admission to intensive care. BMJ 1998; 316, 1853-1858.

11. What are the consequences? 1.Unplanned ICU admissions 2.Cardiac arrest 3.Unexpected death

12. Nurses’ role Monitoring patients = fundamental element of nursingMonitoring patients = fundamental element of nursing Only 7,2% of nurses’ time is spent on patient assessment / vital signs monitoringOnly 7,2% of nurses’ time is spent on patient assessment / vital signs monitoring Nursing work conditions and staffing  patient safetyNursing work conditions and staffing  patient safety - Hendrich A et al. A 36-hospital time and motion study: how do medical-surgical nurses spend their time? The Permanente Journal 2008; 12, 25. - Page A. Keeping patients safe: Transforming the work environment of nurses. National Academies Press, 2004.

13. Nursing Hours Per Patient-day ➚Nursing Hours Per Patient-day ➚ -LOS ➘ -UTI ➘ -GI bleeding ➘ -Pneumonia ➘ -Shock or cardiac arrest ➘ -“failure to rescue” ➘ (death due to complication) Needleman J, Buerhaus P, Mattke S, Stewart M, Zelevinsky K. Nurse-staffing levels and the quality of care in hospitals. N Engl J Med 2002; 346, 1715-1722. Nurses’ role

14. To timely detect patients at risk in acute hospitals nurses have to observe frequently and qualitativelyTo timely detect patients at risk in acute hospitals nurses have to observe frequently and qualitatively  81% of patients had an incomplete or absent record of HR, BP and RR before cardiac arrest Hillman K et al. Introduction of the medical emergency team (MET) system: a cluster-randomized controlled trial. Lancet 2005; 365, 2091-2097. Nurses’ role

15. Root cause analysis SAEs 1.No observations 2.Clinical deterioration not recognized 3.Delay in getting medical support Recognising and responding appropriately to early signs of deterioration in hospitalised patients. NPSA, 2007

16. There is a high incidence of serious vital sign abnormalities in the period before serious adverse events. These antecedents may identify patients who would benefit from earlier intervention.

17. Content 1.Context 2.What is known 3.Rapid Response System / Early Warning Score 4.Improving nurse observation and escalation 5.Current research

18. What is a Rapid Response System? Hospitals need systems for detecting and treating patients in crisisHospitals need systems for detecting and treating patients in crisis Vulnerable patients routinely experience predictable downturns in their conditionVulnerable patients routinely experience predictable downturns in their condition Devita MA et al. Findings of the first consensus conference on medical emergency teams. Crit Care Med 2006; 34, 2463- 2478.

19. What is a Rapid Response System? Devita MA et al. Findings of the first consensus conference on medical emergency teams. Crit Care Med 2006; 34, 2463- 2478.

20. What is an Early Warning Score? Situated in the afferent limb of an RRSSituated in the afferent limb of an RRS Tracks ‘at risk’ patients (early detection)Tracks ‘at risk’ patients (early detection) Cut-off point  triggers responseCut-off point  triggers response  standardization of observing and interpretation of abnormal vital signs Devita MA et al. Findings of the first consensus conference on medical emergency teams. Crit Care Med 2006; 34, 2463- 2478.

21. What is an Early Warning Score? Score calculated from multiple vital signsScore calculated from multiple vital signs Predicts early deteriorationPredicts early deterioration Supports nursesSupports nurses NICE clinical guideline 50 Acutely ill patients in hospital: recognition of and response to acute illness in adults in hospital. London: National Institute for Health and Clinical Excellence 2007.

22. Effect on patient outcome? Single center, before-after studies implementing RRS  lower morbidity, mortality and cardiac arrest ratesSingle center, before-after studies implementing RRS  lower morbidity, mortality and cardiac arrest rates One RCT (Hilmann et al, 2005)  no effect on patient outcomeOne RCT (Hilmann et al, 2005)  no effect on patient outcome - RRS with single parameter triggering - Concentrates on efferent limb - Dacey MJ et al. The effect of a rapid response team on major clinical outcome measures in a community hospital*. Critical care medicine 2007; 35, 2076-2082. - DeVita M et al. Use of medical emergency team responses to reduce hospital cardiopulmonary arrests. Qual Saf Health Care 2004; 13, 251-254.

23. Content 1.Context 2.What is known 3.Rapid Response System / Early Warning Score 4.Improving nurse observation and escalation 5.Current research

24. An improvement initiative Pre- & post-intervention study in AntwerpPre- & post-intervention study in Antwerp Single center, surgical patientsSingle center, surgical patients 6 days postop6 days postop  Intervention: standardized observation and escalation protocol using an Early Warning Score  Concentrates on the afferent limb of the RRS De Meester K, Haegdorens F, Monsieurs KG, Verpooten GA, Holvoet A, Van Bogaert P. Six- day postoperative impact of a standardized nurse observation and escalation protocol: A preintervention and postintervention study. J Crit Care 2013;

25. An improvement initiative Results: 6 days PO unexpected deaths (no DNAR) dropped significantly – RRR 74%6 days PO unexpected deaths (no DNAR) dropped significantly – RRR 74% 6 days PO re-surgery dropped significantly – RRR 31%6 days PO re-surgery dropped significantly – RRR 31% More frequent observations / nursing shiftMore frequent observations / nursing shift  Still room for improvement … De Meester K, Haegdorens F, Monsieurs KG, Verpooten GA, Holvoet A, Van Bogaert P. Six- day postoperative impact of a standardized nurse observation and escalation protocol: A preintervention and postintervention study. J Crit Care 2013;

26. Content 1.Context 2.What is known 3.Rapid Response System / Early Warning Score 4.Improving nurse observation and patient outcomes 5.Current research

27. Current research The Afferent Limb Ascertainment and Response Method (ALARM) intervention study. Multi-center RCT in Belgium (10 hospitals)Multi-center RCT in Belgium (10 hospitals) Q4 2013 - Q4 2015Q4 2013 - Q4 2015 20 Surgical and 20 medical wards20 Surgical and 20 medical wards

28. Current research Main research question What is the effect of implementing an RRS in Belgian acute hospitals on unexpected death, cardiac arrest with CPR and unplanned admissions to the ICU?

29. Current research Intervention  standardized observation and communication protocol (with NEWS and SBAR) Extensive training (innovation decision model Rogers)Extensive training (innovation decision model Rogers) Implementation strategy targeted at existing barriersImplementation strategy targeted at existing barriers Rogers EM. Diffusion of innovations third edition. Free press, 2010.

30. Current research Data Vital signs samples (24h)Vital signs samples (24h) All vital signs preceding an SAE (24h)All vital signs preceding an SAE (24h) Outcome: unexpected death (no DNAR), cardiac arrest with CPR, unplanned ICU admissionsOutcome: unexpected death (no DNAR), cardiac arrest with CPR, unplanned ICU admissions Confounders: comorbidity, NHPPDConfounders: comorbidity, NHPPD

31. Current research  Study ends this year (Q4)  Data collection until mid 2016  Power analysis a priori: 92% to detect 50% reduction of unexpected death  Prospected population = ±75.000 patients

32. Acknowledgments Faculty of Medicine and Health Sciences Division Nursing and Midwifery Sciences University of Antwerp Prof. dr. P. Van Bogaert, RN, MA, PhD Prof. dr. K. Monsieurs, MD, PhD dr. K. De Meester, RN, MScN, PhD dr. K. Wouters, MSc, PhD M. Misselyn, RN Belgian Federal Public Service of Health, Food Chain Safety and Environment