Evaluating the impact of a computerized surveillance algorithm and decision support system on sepsis mortality

Journal of the American Medical Informatics Association

Volumn 24, Issue 1, 2017, Pages 88-95

  Manaktala, Sharad ^a   Claypool, Stephen R ^a  

^a Wolters Kluwer Health   (United States)

Author keywords

Change management; Clinical decision support; Electronic surveillance; Sepsis; Sepsis mortality; Septic shock

Indexed keywords

ADULT; ALGORITHM; ARTICLE; CHANGE MANAGEMENT; CLINICAL EVALUATION; CONTROLLED STUDY; DECISION SUPPORT SYSTEM; DISEASE SURVEILLANCE; FEMALE; HOSPITAL READMISSION; HOSPITALIZATION; HUMAN; ICD-9; MAJOR CLINICAL STUDY; MALE; MEDICAL RECORD REVIEW; MIDDLE AGED; MOBILE APPLICATION; MORTALITY; PRACTICE GUIDELINE; PREVALENCE; SENSITIVITY AND SPECIFICITY; SEPSIS; SHOCK; ALABAMA; CLINICAL DECISION SUPPORT SYSTEM; CONTROLLED CLINICAL TRIAL; HOSPITAL MORTALITY; PHYSIOLOGIC MONITORING; PROCEDURES; TEACHING HOSPITAL; TOTAL QUALITY MANAGEMENT;

ALABAMA; ALGORITHMS; DECISION SUPPORT SYSTEMS, CLINICAL; FEMALE; HOSPITAL MORTALITY; HOSPITALS, TEACHING; HUMANS; MALE; MIDDLE AGED; MOBILE APPLICATIONS; MONITORING, PHYSIOLOGIC; QUALITY IMPROVEMENT; SENSITIVITY AND SPECIFICITY; SEPSIS;

EID: 85014637868     PISSN: 10675027     EISSN: 1527974X     Source Type: Journal    
DOI: 10.1093/jamia/ocw056     Document Type: Article

References (35)

1. Gaieski DF, Edwards JM, Kallan MJ, Carr BG. Benchmarking the incidence and mortality of severe sepsis in the United States. Crit Care Med. 2013;41(5):1167-1174.
2. Torio CM, Andrews RM. National inpatient hospital costs: the most expensive conditions by payer, 2011. 2013.
3. Kumar A, Zarychanski R, Light B, et al. Early combination antibiotic therapy yields improved survival compared with monotherapy in septic shock: a propensity-matched analysis. Crit Care Med. 2010;38(9):1773-1785.
4. Dellinger RP, Levy MM, Rhodes A, et al. Surviving sepsis campaign: international guidelines for management of severe sepsis and septic shock:2012.Crit Care Med. 2013;41(2):580-637.
5. Rivers E, Nguyen B, Havstad S, et al. Early goal-directed therapy in the treatment of severe sepsis and septic shock. N Engl J Med. 2001;345(19): 1368-1377.
6. Levy MM, Rhodes A, Phillips GS, et al. Surviving Sepsis Campaign: association between performance metrics and outcomes in a 7.5-year study. Intensive Care Med. 2014;40(11):1623-1633.
7. Gao F, Melody T, Daniels DF, Giles S, Fox S. The impact of compliance with 6-hour and 24-hour sepsis bundles on hospital mortality in patients with severe sepsis: a prospective observational study. Crit Care. 2005;9(6): R764-R770.
8. Young MP, Gooder VJ, Bride K, James B, Fisher ES. Inpatient transfers to the intensive care unit. J General Internal Med. 2003;18(2):77-83.
9. Lundberg JS, Perl TM, Wiblin T, et al. Septic shock: an analysis of outcomes for patients with onset on hospital wards versus intensive care units. Crit Care Med. 1998;26(6):1020-1024.
10. Thiel SW, Asghar MF, Micek ST, Reichley RM, Doherty JA, Kollef MH. Hospital-wide impact of a standardized order set for the management of bacteremic severe sepsis. Crit Care Med. 2009;37(3):819-824.
11. Kliger J, Singer SJ, Hoffman FH. Using the Integrated Nurse Leadership Program to Reduce Sepsis Mortality. Jt Commission J Qual Patient Safety. 2015;41(6):264-272.
12. Paul M, Andreassen S, Nielsen AD, et al. Prediction of Bacteremia Using TREAT, a Computerized Decision-Support System. Clin Infect Dis. 2006; 42(9):1274-1282.
13. Harrison AM, Herasevich V, Gajic O. Automated Sepsis Detection, Alert, and Clinical Decision Support: Act on It or Silence the Alarm? Crit Care Med. 2015;43(8):1776-1777.
14. Henry KE, Hager DN, Pronovost PJ, Saria S. A targeted real-time early warning score (TREWScore) for septic shock. Sci TranslMed. 2015;7(299): 299ra122.
15. Nguyen SQ, Mwakalindile E, Booth JS, et al. Automated electronic medical record sepsis detection in the emergency department. Peer J. 2014;2:e343.
16. Bailey TC, Chen Y, Mao Y, et al. A trial of a real-time alert for clinical deterioration in patients hospitalized on general medical wards. J Hosp Med. 2013;8(5):236-242.
17. Semler MW, Weavind L, Hooper MH, et al. An electronic tool for the evaluation and treatment of sepsis in the ICU: a randomized controlled trial. Crit Care Med. 2015;43(8):1595-1602.
18. Nelson JL, Smith BL, Jared JD, Younger JG. Prospective trial of real-time electronic surveillance to expedite early care of severe sepsis. Ann Emerg Med. 2011;57(5):500-504.
19. Buck KM. Developing an early sepsis alert program. J Nurs Care Qual. 2014;29(2):124-132.
20. Umscheid CA, Betesh J, VanZandbergen C, et al. Development, implementation, and impact of an automated early warning and response system for sepsis. J Hosp Med. 2015;10(1):26-31.
21. HIMSS Clinical Decision Support Workgroup and Task Force. Improving Outcomes With Clinical Decision Support: an Implementer's Guide. 2nd edn. Osheroff JA, ed. HIMSS; 2011.
22. Neviere R, Parsons P, Wilson K. Sepsis and the systemic inflammatory response syndrome: definitions, epidemiology, and prognosis. UpToDate, Parsons PE, Ed. UpToDate [Internet]. April 24, 2015 [cited 3/27/2015 3:09:39 PM; 3/27/2015 3:09:39 PM; 3/27/2015 12:31:02 PM]:May 27, 2015.
23. Bone RC, Balk RA, Cerra FB, et al. Definitions for sepsis and organ failure and guidelines for the use of innovative therapies in sepsis. The ACCP/ SCCM Consensus Conference Committee. American College of Chest Physicians/Society of Critical Care Medicine. Chest J. 1992;101(6): 1644-1655.
24. Dellinger RP, Levy MM, Rhodes A, et al. Surviving Sepsis Campaign: international guidelines for management of severe sepsis and septic shock,2012.Intensive Care Med. 2013;39(2):165-228.
25. Angus DC, Linde-Zwirble WT, Lidicker J, Clermont G, Carcillo J, Pinsky MR. Epidemiology of severe sepsis in the United States: analysis of incidence, outcome, and associated costs of care. Crit Care Med. 2001;29(7): 1303-1310.
26. Iwashyna TJ,Odden A, Rohde J, et al. Identifying patients with severe sepsis using administrative claims: patient-level validation of the Angus implementation of the international consensus conference definition of severe sepsis. Med Care. 2014;52(6):e39-e43.
27. Levy MM, Fink MP, Marshall JC, et al. 2001 SCCM/ESICM/ACCP/ATS/ SIS International Sepsis Definitions Conference. Intensive Care Med. 2003;29(4):530-538.
28. Elixhauser A, Steiner C, Harris DR, Coffey RM. Comorbidity measures for use with administrative data. Med Care. 1998;36(1):8-27.
29. van Walraven C, Austin PC, Jennings A, Quan H, Forster AJ. A modification of the Elixhauser comorbidity measures into a point system for hospital death using administrative data. Med Care. 2009:626-633.
30. Viera AJ, Garrett JM. Understanding interobserver agreement: the kappa statistic. Fam Med. 2005;37(5):360-363.
31. Brandt BN, Gartner AB, Moncure M, et al. Identifying severe sepsis via electronic surveillance. Am J Med Qual. 2015;30(6):559-565.
32. Ehrlichman P, Trach L, Patel B, Maheshwari V, SeckelM. 983: sensitivity and positive predictive value of CERNER EMR based sepsis recognition tool. Crit Care Med. 2014;42(12):A1597.
33. Jones S, Mullally M, Ingleby S, Buist M, Bailey M, Eddleston JM. Bedside electronic capture of clinical observations and automated clinical alerts to improve compliance with an Early Warning Score protocol. 2011.
34. Jones TK, Fuchs BD, Small DS, et al. Post-acute care use and hospital readmission after sepsis. Ann Am Thorac Soc. 2015;12(6):904-913.
35. Singer M, Deutschman CS, Seymour C, et al. The third international consensus definitions for sepsis and septic shock (sepsis-3). JAMA. 2016;315(8):801-810.