Impact of a standardized rapid response system on outcomes in a large healthcare jurisdiction

Resuscitation

Volumn 107, Issue , 2016, Pages 47-56

  Chen, Jack ^a   Ou, Lixin ^a   Flabouris, Arthas ^b,c   Hillman, Ken ^a   Bellomo, Rinaldo ^d   Parr, Michael ^e  

^a UNIVERSITY OF NEW SOUTH WALES   (Australia)

^b ROYAL ADELAIDE HOSPITAL   (Australia)

^c UNIVERSITY OF ADELAIDE   (Australia)

^d Austin Medical Centre   (Australia)

^e LIVERPOOL HOSPITAL   (Australia)

Author keywords

Cardiopulmonary arrests; Medical emergency team; Rapid response system; Rapid response team

Indexed keywords

ADULT; AGED; ARTICLE; CARDIOVASCULAR MORTALITY; FAILURE TO RESCUE (HEALTH CARE); FEMALE; HEALTH CARE SYSTEM; HEART ARREST; HOSPITAL ADMISSION; HOSPITAL MORTALITY; HUMAN; INCIDENCE; MAJOR CLINICAL STUDY; MALE; MORTALITY RATE; NEW SOUTH WALES; POPULATION RESEARCH; PRIORITY JOURNAL; PUBLIC HOSPITAL; RAPID RESPONSE TEAM; RESCUE PERSONNEL; STANDARDIZATION; TIME SERIES ANALYSIS; BENCHMARKING; EPIDEMIOLOGY; HOSPITALIZATION; INTENSIVE CARE; MIDDLE AGED; MORTALITY; ORGANIZATION AND MANAGEMENT; PROCEDURES; PROGRAM EVALUATION; STANDARDS; STATISTICS AND NUMERICAL DATA; SURVIVAL ANALYSIS; TREATMENT OUTCOME; TRENDS;

ADULT; AGED; BENCHMARKING; CRITICAL CARE; FEMALE; HEART ARREST; HOSPITAL MORTALITY; HOSPITAL RAPID RESPONSE TEAM; HOSPITALIZATION; HOSPITALS, PUBLIC; HUMANS; INTERRUPTED TIME SERIES ANALYSIS; MALE; MIDDLE AGED; NEW SOUTH WALES; OUTCOME AND PROCESS ASSESSMENT (HEALTH CARE); PROGRAM EVALUATION; SURVIVAL ANALYSIS;

EID: 84983483124     PISSN: 03009572     EISSN: 18731570     Source Type: Journal    
DOI: 10.1016/j.resuscitation.2016.07.240     Document Type: Article

References (24)

1. 1 Institute of Medicine, To error is human: building a safer health system. 1999, National Academy Press, Washington D.C.
2. 2 Morrison, L.J., Neumar, R.W., Zimmerman, J.L., et al. Strategies for improving survival after in-hospital cardiac arrest in the United States: 2013 consensus recommendations: a consensus statement from the American Heart Association. Circulation 127 (2013), 1538–1563.
3. 3 James, J.T., A new, evidence-based estimate of patient harms associated with hospital care. J Patient Saf 9 (2013), 122–128.
4. 4 Jones, D.A., DeVita, M.A., Bellomo, R., Rapid-response teams. N Engl J Med 365 (2011), 139–146.
5. 5 Bellomo, R., Goldsmith, D., Uchino, S., et al. A prospective before-and-after trial of a medical emergency team. Med J Aust 179 (2003), 283–287.
6. 6 Buist, M.D., Moore, G.E., Bernard, S.A., et al. Effects of a medical emergency team on reduction of incidence of and mortality from unexpected cardiac arrests in hospital: preliminary study. Br Med J 324 (2002), 387–390.
7. 7 Chen, J., Bellomo, R., Flabouris, A., et al. The relationship between early emergency team calls and serious adverse events. Crit Care Med 37 (2009), 148–153.
8. 8 Jones, D.A., Bagshaw, S.M., Barrett, J., et al. The role of the medical emergency team in end-of-life care: a multicenter, prospective, observational study. Crit Care Med 40 (2012), 98–103.
9. 9 Winters, B.D., Weaver, S.J., Pfoh, E.R., et al. Rapid-response systems as a patient safety strategy: a systematic review. Ann Intern Med 158 (2013), 417–425.
10. 10 Chan, P.S., Jain, R., Nallmothu, B.K., et al. Rapid response teams: a systematic review and meta-analysis. Arch Intern Med 170 (2010), 18–26.
11. 11 Maharaj, R., Raffaele, I., Wendon, J., Rapid response systems: a systematic review and meta-analysis. Crit Care, 19, 2015, 254.
12. 12 Hughes, C., Pain, C., Braithwaite, J., et al. ‘Between the flags’: implementing a rapid response system at scale. BMJ Qual Saf 23 (2014), 714–717.
13. 13 Agency for Healthcare Research and Quality, Patient Safety Indicators (PSI) Version 3.1 Comparative Data. 2007, Agency for Healthcare Research and Quality.
14. 14 Barker, A.L., Brand, C.A., Evans, S.M., et al. Death in low-mortality diagnosis-related groups: frequency, and the impact of patient and hospital characteristics. Med J Aust 195 (2011), 89–94.
15. 15 Wagner, A.K., Soumerai, S.B., Zhang, F., et al. Segmented regression analysis of interrupted time series studies in medication use research. J Clin Pharm Ther 27 (2002), 299–309.
16. 16 Zou, G., A modified Poisson regression approach to prospective studies with binary data. Am J Epidemiol, 159, 2004, 5.
17. 17 White, H., A heteroskedasticity-consistent covariance matrix estimator and a direct test for heteroskedasticity. Econometrica, 48, 1980, 22.
18. 18 Pink B. Socio-Economic Indexes for Areas (SEIFA) 2011, 2011.
19. 19 Quan, H., Sundararajan, V., Halfon, P., et al. Coding algorithms for defining comorbidities in ICD-9-CM and ICD-10 administrative data. Med Care 43 (2005), 1130–1139.
20. 20 Wennberg, J.E., Staiger, D.O., Sharp, S.M., et al. Observational intensity bias associated with illness adjustment: cross sectional analysis of insurance claims. BMJ, 346, 2013, f549.
21. 21 Chen, J., Ou, L., Hillman, K.M., et al. Cardiopulmonary arrest and mortality trends, and their association with rapid response system expansion. Med J Aust, 201, 2014, 4.
22. 22 Moriarty, J.P., Schiebel, N.E., Johnson, M.G., et al. Evaluating implementation of a rapid response team: considering alternative outcome measures. Int J Qual Health Care 26 (2014), 49–57.
23. 23 Hillman, K.M., Chen, J., Jones, D., Rapid response systems. Med J Aust 201 (2014), 519–521.
24. 24 Chen, J., Flabouris, A., Bellomo, R., et al. The medical emergency team system and not-for-resuscitation orders: results from the MERIT study. Resuscitation 79 (2008), 391–397.