Diagnostic accuracy and effectiveness of automated electronic sepsis alert systems: A systematic review

Journal of Hospital Medicine

Volumn 10, Issue 6, 2015, Pages 396-402

  Makam, Anil N ^a   Nguyen, Oanh K ^a   Auerbach, Andrew D ^b  

^a UNIVERSITY OF TEXAS SOUTHWESTERN MEDICAL CENTER   (United States)

^b UNIVERSITY OF CALIFORNIA   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

AUTOMATED ELECTRONIC SEPSIS ALERT SYSTEM; CLINICAL EFFECTIVENESS; DATA ANALYSIS; DATA PROCESSING; DATA SYNTHESIS; DIAGNOSTIC ACCURACY; HUMAN; LENGTH OF STAY; MORTALITY; OUTCOME ASSESSMENT; PATIENT ASSESSMENT; PREDICTIVE VALUE; PRIORITY JOURNAL; REVIEW; RISK ASSESSMENT; RISK FACTOR; SENSITIVITY AND SPECIFICITY; SEPSIS; SYSTEMATIC REVIEW; TOTAL QUALITY MANAGEMENT; ALARM MONITOR; BIBLIOGRAPHIC DATABASE; CLINICAL DECISION SUPPORT SYSTEM; DIFFERENTIAL DIAGNOSIS; EARLY DIAGNOSIS; PHYSICIAN ORDER ENTRY SYSTEM; REPRODUCIBILITY; STANDARDS; STATISTICS AND NUMERICAL DATA;

CLINICAL ALARMS; DATABASES, BIBLIOGRAPHIC; DECISION SUPPORT SYSTEMS, CLINICAL; DIAGNOSIS, DIFFERENTIAL; EARLY DIAGNOSIS; HUMANS; MEDICAL ORDER ENTRY SYSTEMS; OUTCOME ASSESSMENT (HEALTH CARE); PREDICTIVE VALUE OF TESTS; REPRODUCIBILITY OF RESULTS; SEPSIS;

EID: 84930383716     PISSN: 15535592     EISSN: 15535606     Source Type: Journal    
DOI: 10.1002/jhm.2347     Document Type: Review

References (25)

1. Torio CM, Andrews RM. National inpatient hospital costs: the most expensive conditions by payer, 2011: statistical brief #160. Healthcare Cost and Utilization Project (HCUP) Statistical Briefs. Rockville, MD: Agency for Healthcare Research and Quality; 2013.
2. Hall MJ, Williams SN, DeFrances CJ, Golosinskiy A. Inpatient care for septicemia or sepsis: a challenge for patients and hospitals. NCHS Data Brief. 2011;(62):1-8.
3. Martin GS, Mannino DM, Eaton S, Moss M. The epidemiology of sepsis in the United States from 1979 through 2000. N Engl J Med. 2003;348(16):1546-1554.
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. Pro CI, Yealy DM, Kellum JA, et al. A randomized trial of protocol-based care for early septic shock. N Engl J Med. 2014;370(18):1683-1693.
7. Turi SK, Von Ah D. Implementation of early goal-directed therapy for septic patients in the emergency department: a review of the literature. J Emerg Nurs. 2013;39(1):13-19.
8. Fong JJ, Cecere K, Unterborn J, Garpestad E, Klee M, Devlin JW. Factors influencing variability in compliance rates and clinical outcomes among three different severe sepsis bundles. Ann Pharmacother. 2007;41(6):929-936.
9. Ferrer R, Artigas A, Levy MM, et al. Improvement in process of care and outcome after a multicenter severe sepsis educational program in Spain. JAMA. 2008;299(19):2294-2303.
10. Hooper MH, Weavind L, Wheeler AP, et al. Randomized trial of automated, electronic monitoring to facilitate early detection of sepsis in the intensive care unit*. Crit Care Med. 2012;40(7):2096-2101.
11. Whiting PF, Rutjes AW, Westwood ME, et al. QUADAS-2: a revised tool for the quality assessment of diagnostic accuracy studies. Ann Intern Med. 2011;155(8):529-536.
12. Owens DK, Lohr KN, Atkins D, et al. AHRQ series paper 5: grading the strength of a body of evidence when comparing medical interventions-agency for healthcare research and quality and the effective health-care program. J Clin Epidemiol. 2010;63(5):513-523.
13. Meurer WJ, Smith BL, Losman ED, et al. Real-time identification of serious infection in geriatric patients using clinical information system surveillance. J Am Geriatr Soc. 2009;57(1):40-45.
14. 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.
15. Nguyen SQ, Mwakalindile E, Booth JS, et al. Automated electronic medical record sepsis detection in the emergency department. PeerJ. 2014;2:e343.
16. Thiel SW, Rosini JM, Shannon W, Doherty JA, Micek ST, Kollef MH. Early prediction of septic shock in hospitalized patients. J Hosp Med. 2010;5(1):19-25.
17. Berger T, Birnbaum A, Bijur P, Kuperman G, Gennis P. A Computerized alert screening for severe sepsis in emergency department patients increases lactate testing but does not improve inpatient mortality. Appl Clin Inform. 2010;1(4):394-407.
18. McRee L, Thanavaro JL, Moore K, Goldsmith M, Pasvogel A. The impact of an electronic medical record surveillance program on outcomes for patients with sepsis. Heart Lung. 2014;43(6):546-549.
19. Sawyer AM, Deal EN, Labelle AJ, et al. Implementation of a real-time computerized sepsis alert in nonintensive care unit patients. Crit Care Med. 2011;39(3):469-473.
20. Brun-Buisson C. The epidemiology of the systemic inflammatory response. Intensive Care Med. 2000;26(suppl 1):S64-S74.
21. Nanji KC, Slight SP, Seger DL, et al. Overrides of medication-related clinical decision support alerts in outpatients. J Am Med Inform Assoc. 2014;21(3):487-491.
22. Siebig S, Kuhls S, Imhoff M, Gather U, Scholmerich J, Wrede CE. Intensive care unit alarms-how many do we need? Crit Care Med. 2010;38(2):451-456.
23. Singal G, Currier P. How can we best use electronic data to find and treat the critically ill?*. Crit Care Med. 2012;40(7):2242-2243.
24. Ash JS, Sittig DF, Dykstra R, et al. Identifying best practices for clinical decision support and knowledge management in the field. Stud Health Technol Inform. 2010;160(pt 2):806-810.
25. Wright A, Phansalkar S, Bloomrosen M, et al. Best practices in clinical decision support: the case of preventive care reminders. Appl Clin Inform. 2010;1(3):331-345.