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

Journal of Hospital Medicine - Tập 10 Số 6 - Trang 396-402 - 2015
Anil N. Makam1, Oanh Kieu Nguyen1, Andrew D. Auerbach2
1Division of General Internal Medicine University Texas Southwestern Medical Center Dallas Texas
2Divsion of Hospital Medicine University of California San Francisco San Francisco California

Tóm tắt

BACKGROUNDAlthough timely treatment of sepsis improves outcomes, delays in administering evidence‐based therapies are common.PURPOSETo determine whether automated real‐time electronic sepsis alerts can: (1) accurately identify sepsis and (2) improve process measures and outcomes.DATA SOURCESWe systematically searched MEDLINE, Embase, The Cochrane Library, and Cumulative Index to Nursing and Allied Health Literature from database inception through June 27, 2014.STUDY SELECTIONIncluded studies that empirically evaluated 1 or both of the prespecified objectives.DATA EXTRACTIONTwo independent reviewers extracted data and assessed the risk of bias. Diagnostic accuracy of sepsis identification was measured by sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and likelihood ratio (LR). Effectiveness was assessed by changes in sepsis care process measures and outcomes.DATA SYNTHESISOf 1293 citations, 8 studies met inclusion criteria, 5 for the identification of sepsis (n = 35,423) and 5 for the effectiveness of sepsis alerts (n = 6894). Though definition of sepsis alert thresholds varied, most included systemic inflammatory response syndrome criteria ± evidence of shock. Diagnostic accuracy varied greatly, with PPV ranging from 20.5% to 53.8%, NPV 76.5% to 99.7%, LR+ 1.2 to 145.8, and LR− 0.06 to 0.86. There was modest evidence for improvement in process measures (ie, antibiotic escalation), but only among patients in non–critical care settings; there were no corresponding improvements in mortality or length of stay. Minimal data were reported on potential harms due to false positive alerts.CONCLUSIONSAutomated sepsis alerts derived from electronic health data may improve care processes but tend to have poor PPV and do not improve mortality or length of stay. Journal of Hospital Medicine 2015;10:396–402. © 2015 Society of Hospital Medicine

Từ khóa


Tài liệu tham khảo

TorioCM AndrewsRM. 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.

Hall MJ, 2011, Inpatient care for septicemia or sepsis: a challenge for patients and hospitals, NCHS Data Brief, 1

10.1056/NEJMoa022139

10.1097/CCM.0b013e31827e83af

10.1056/NEJMoa010307

10.1056/NEJMoa1401602

10.1016/j.jen.2011.06.006

10.1345/aph.1K041

10.1001/jama.299.19.2294

10.1097/CCM.0b013e318250a887

10.7326/0003-4819-155-8-201110180-00009

10.1016/j.jclinepi.2009.03.009

10.1111/j.1532-5415.2008.02094.x

10.1016/j.annemergmed.2010.12.008

10.7717/peerj.343

10.1002/jhm.530

Berger T, 2010, A Computerized alert screening for severe sepsis in emergency department patients increases lactate testing but does not improve inpatient mortality, Appl Clin Inform, 1, 394, 10.4338/ACI-2010-09-RA-0054

10.1016/j.hrtlng.2014.05.009

10.1097/CCM.0b013e318205df85

10.1007/s001340051121

10.1136/amiajnl-2013-001813

10.1097/CCM.0b013e3181cb0888

10.1097/CCM.0b013e318256b99b

Ash JS, 2010, Identifying best practices for clinical decision support and knowledge management in the field, Stud Health Technol Inform, 160, 806

10.4338/ACI-2010-05-RA-0031

Thông tin
Thông tin xuất bản

Journal of Hospital Medicine

Tập 10 Số 6

396-402

Thông tin tác giả