Appl Clin Inform 2017; 08(01): 47-66
DOI: 10.4338/ACI-2016-07-RA-0112
Research Article
Schattauer GmbH

Secondary Analysis of an Electronic Surveillance System Combined with Multi-focal Interventions for Early Detection of Sepsis

Bonnie L. Westra
1   University of Minnesota, School of Nursing, Minneapolis, MN, USA 55455
,
Sean Landman
2   University of Minnesota, Department of Computer Science & Engineering, Minneapolis, MN, USA
,
Pranjul Yadav
2   University of Minnesota, Department of Computer Science & Engineering, Minneapolis, MN, USA
,
Michael Steinbach
2   University of Minnesota, Department of Computer Science & Engineering, Minneapolis, MN, USA
› Author Affiliations
FundingThis study was funded by Wolters Kluwer
Further Information

Correspondence to:

Bonnie L. Westra, PhD, RN, FAAN, FACMI
University of Minnesota, School of Nursing
308 Harvard St SE, WDH 5–140
Minneapolis, MN, USA 55455

Publication History

Received: 14 July 2016

Accepted: 11 January 2016

Publication Date:
20 December 2017 (online)

 

Summary

Summary: To conduct an independent secondary analysis of a multi-focal intervention for early detection of sepsis that included implementation of change management strategies, electronic surveil-lance for sepsis, and evidence based point of care alerting using the POC AdvisorTM application. Methods: Propensity score matching was used to select subsets of the cohorts with balanced covariates. Bootstrapping was performed to build distributions of the measured difference in rates/ means. The effect of the sepsis intervention was evaluated for all patients, and High and Low Risk subgroups for illness severity. A separate analysis was performed patients on the intervention and non-intervention units (without the electronic surveillance). Sensitivity, specificity, and the positive predictive values were calculated to evaluate the accuracy of the alerting system for detecting sepsis or severe sepsis/ septic shock.

Results: There was positive effect on the intervention units with sepsis electronic surveillance with an adjusted mortality rate of –6.6%. Mortality rates for non-intervention units also improved, but at a lower rate of –2.9%. Additional outcomes improved for patients on both intervention and non-intervention units for home discharge (7.5% vs 1.1%), total length of hospital stay (-0.9% vs –0.3%), and 30 day readmissions (-6.6% vs –1.6%). Patients on the intervention units showed better outcomes compared with non-intervention unit patients, and even more so for High Risk patients. The sensitivity was 95.2%, specificity of 82.0% and PPV of 50.6% for the electronic surveillance alerts. Conclusion: There was improvement over time across the hospital for patients on the intervention and non-intervention units with more improvement for sicker patients. Patients on intervention units with electronic surveillance have better outcomes; however, due to differences in exclusion criteria and types of units, further study is needed to draw a direct relationship between the electronic surveillance system and outcomes.


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Conflicts of interest

None of the listed authors have any financial or personal relationships with other people or organizations that may inappropriately influence or bias the objectivity of submitted content and /or its acceptance of publication in this journal.

  • References

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  • 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 Fleischmann C, Thomas-Rueddel DO, Hartmann M, Hartog CS, Welte T, Heublein S, Heublein S, Dennler U, Reinhart K. Hospital incidence and mortality rates of sepsis. Dtsch Arztebl Int 2016; 113 (Suppl. 10) 159-166.
  • 4 Yende S, Austin S, Rhodes A, Finfer S, Opal S, Thompson T, Bozza FA, LaRosa SP, Ranieri VM, Angus DC. Long-term quality of life among survivors of severe sepsis: Analyses of two international trials. Crit Care Med 2016; 44 (Suppl. 08) 1461-1467.
  • 5 Shiramizo SC, Marra AR, Durao MS, Paes AT, Edmond MB, Pavao dos Santos OF. Decreasing mortality in severe sepsis and septic shock patients by implementing a sepsis bundle in a hospital setting. PLoS One 2011; 6 (Suppl. 11) e26790.
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  • 11 Giuliano KK, Lecardo M, Staul L. Impact of protocol watch on compliance with the surviving sepsis campaign. Am J Crit Care 2011; 20 (Suppl. 04) 313-321.
  • 12 McKinley BA, Moore LJ, Sucher JF, Todd SR, Turner KL, Valdivia A, Sailors RM, Moore FA. Computer protocol facilitates evidence-based care of sepsis in the surgical intensive care unit. J Trauma 2011; 70 (Suppl. 05) 1153-1166. discussion 1166-1167.
  • 13 Powell KK, Fowler RJ. Driving sepsis mortality down: Emergency department and critical care partnerships. Crit Care Nurs Clin North Am 2014; 26 (Suppl. 04) 487-498.
  • 14 Herasevich V, Pieper MS, Pulido J, Gajic O. Enrollment into a time sensitive clinical study in the critical care setting: Results from computerized septic shock sniffer implementation. J Am Med Inform Assoc 2011; 18 (Suppl. 05) 639-644.
  • 15 Umscheid CA, Betesh J, VanZandbergen C, Hanish A, Tait G, Mikkelsen ME, French B, Fuchs BD. Development, implementation, and impact of an automated early warning and response system for sepsis. J Hosp Med 2015; 10 (Suppl. 01) 26-31.
  • 16 Alsolamy S, Al Salamah M, Al Thagafi M, Al-Dorzi HM, Marini AM, Aljerian N, Al-Enezi F, Al-Hunaidi F, Mahmoud AM, Alamry A, Arabi YM. Diagnostic accuracy of a screening electronic alert tool for severe sepsis and septic shock in the emergency department.. BMC Med Inform Decis Mak 2014 14. 105 doi:10.1186/s12911–014–0105–7
  • 17 Manaktala S, Claypool SR. Evaluating the impact of a computerized surveillance algorithm and decision support system on sepsis mortality.. JAMIA 2016; ocw056.
  • 18 Neviere R, Parsons PE, Finlay T. Sepsis and the systemic inflammatory response syndrome: definitions, epidemiology, and prognosis.. Parsons PE ,Ed. UpToDate. September, 19, 2016. www.uptodate.com Last accessed 9/27/2016
  • 19 Manaktala S, Claypool SR. Evaluating the impact of a computerized surveillance algorithm and decision support system on sepsis mortality. Journal of the American Medical Informatics Association. 2016; May 25-ocw056
  • 20 Iwashyna TJ, Odden A, Rohde J, Bonham C, Kuhn L, Malani P, Chen L, Flanders S. 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 (Suppl. 06) e39-e43.
  • 21 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 (Suppl. 07) 1303-1310.
  • 22 Charlson ME, Pompei P, Ales KL, MacKenzie CR. A new method of classifying prognostic comorbidity in longitudinal studies: Development and validation. 1987 40. 5 373-383.
  • 23 Quan H, Sundararajan V, Halfon P, Fong A, Burnand B, Luthi JC, Saunders LD, Beck CA, Feasby TE, Ghali WA. Coding algorithms for defining comorbidities in ICD-9-CM and ICD-10 administrative data. Med Care 2005; 43 (Suppl. 11) 1130-1139.
  • 24 Austin PC. An introduction to propensity score methods for reducing the effects of confounding in observational studies. Multivariate Behav Res 2011; 46 (Suppl. 03) 399-424.
  • 25 R Development Core Team (2011). R: A Language and Environment for Statistical Computing.. Vienna, Austria : the R Foundation for Statistical Computing. ISBN: 3–900051–07–0. Available online at http://www.R-project.org. Last accessed 9/27/16
  • 26 Ho DE, Imai K, King G, Stuart EA. MatchIt: Nonparametric preprocessing for parametric causal inference. Journal of Statistical Software 2011; 42 (Suppl. 08) 1-21.
  • 27 Normand ST, Landrum MB, Guadagnoli E, Ayanian JZ, Ryan TJ, Cleary PD, McNeil BJ. Validating recommendations for coronary angiography following acute myocardial infarction in the elderly: A matched analysis using propensity scores. J Clin Epidemiol 2001; 54 (Suppl. 04) 387-398.
  • 28 Angus DC, Barnato AE, Bell D, Bellomo R, Chong CR, Coats TJ, Davies A, Delaney A, Harrison DA, Holdgate A, Howe B, Huang DT, Iwashyna T, Kellum JA, Peake SL, Pike F, Reade MC, Rowan KM, Singer M, Webb SA, Weissfeld LA, Yealy DM, Young JD. A systematic review and meta-analysis of early goal-directed therapy for septic shock: The ARISE ProCESS and ProMISe investigators. Intensive Care Med 2015; 41 (Suppl. 09) 1549-1560.
  • 29 ARISE Investigators, ANZICS Clinical Trials Group. Peake SL, Delaney A, Bailey M, Bellomo R, Cameron PA, Cooper DJ, Higgins AM, Holdgate A, Howe BD, Webb SA, Williams P. Goal-directed resuscitation for patients with early septic shock. N Engl J Med 2014; 371 (Suppl. 16) 1496-1506.

Correspondence to:

Bonnie L. Westra, PhD, RN, FAAN, FACMI
University of Minnesota, School of Nursing
308 Harvard St SE, WDH 5–140
Minneapolis, MN, USA 55455

  • References

  • 1 Singer M, Deutschman CS, Seymour CW, Shankar-Hari M, Annane D, Bauer M, Bellomo R, Bernard GR, Chiche JD, Coopersmith CM, Hotchkiss RS, Levy MM, Marshall JC, Martin GS, Opal SM, Rubenfeld GD, van der Poll T, Vincent JL, Angus DC. The third international consensus definitions for sepsis and septic shock (sepsis-3). JAMA 2016; 315 (Suppl. 08) 801-810.
  • 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 Fleischmann C, Thomas-Rueddel DO, Hartmann M, Hartog CS, Welte T, Heublein S, Heublein S, Dennler U, Reinhart K. Hospital incidence and mortality rates of sepsis. Dtsch Arztebl Int 2016; 113 (Suppl. 10) 159-166.
  • 4 Yende S, Austin S, Rhodes A, Finfer S, Opal S, Thompson T, Bozza FA, LaRosa SP, Ranieri VM, Angus DC. Long-term quality of life among survivors of severe sepsis: Analyses of two international trials. Crit Care Med 2016; 44 (Suppl. 08) 1461-1467.
  • 5 Shiramizo SC, Marra AR, Durao MS, Paes AT, Edmond MB, Pavao dos Santos OF. Decreasing mortality in severe sepsis and septic shock patients by implementing a sepsis bundle in a hospital setting. PLoS One 2011; 6 (Suppl. 11) e26790.
  • 6 Damiani E, Donati A, Serafini G, Rinaldi L, Adrario E, Pelaia P, Busani S, Girardis M. Effect of performance improvement programs on compliance with sepsis bundles and mortality: A systematic review and meta-analysis of observational studies. PLoS One 2015; 10 (Suppl. 05) e0125827.
  • 7 Dellinger RP, Levy MM, Rhodes A, Annane D, Gerlach H, Opal SM, Sevransky JE, Sprung CL, Douglas IS, Jaeschke R, Osborn TM, Nunnally ME, Townsend SR, Reinhart K, Kleinpell RM, Angus DC, Deutschman CS, Machado FR, Rubenfeld GD, Webb S, Beale RJ, Vincent JL, Moreno R. Surviving Sepsis Campaign Guidelines Committee including The Pediatric Subgroup.. Surviving sepsis campaign: International guidelines for management of severe sepsis and septic shock, 2012. Intensive Care Med 2013; 39 (Suppl. 02) 165-228.
  • 8 Levy MM, Rhodes A, Phillips GS, Townsend SR, Schorr CA, Beale R, Osborn T, Lemeshow S, Chiche JD, Artigas A, Dellinger RP. Surviving sepsis campaign: Association between performance metrics and outcomes in a 7.5-year study. Crit Care Med 2015; 43 (Suppl. 01) 3-12.
  • 9 Levy MM, Dellinger RP, Townsend SR, Linde-Zwirble WT, Marshall JC, Bion J, Schorr C, Artigas A, Ramsay G, Beale R, Parker MM, Gerlach H, Reinhart K, Silva E, Harvey M, Regan S, Angus DC. The surviving sepsis campaign: Results of an international guideline-based performance improvement program targeting severe sepsis. Intensive Care Med 2010; 36 (Suppl. 02) 222-231.
  • 10 Palleschi MT, Sirianni S, O’Connor N, Dunn D, Hasenau SM. An interprofessional process to improve early identification and treatment for sepsis. J Healthc Qual 2014; 36 (Suppl. 04) 23-31.
  • 11 Giuliano KK, Lecardo M, Staul L. Impact of protocol watch on compliance with the surviving sepsis campaign. Am J Crit Care 2011; 20 (Suppl. 04) 313-321.
  • 12 McKinley BA, Moore LJ, Sucher JF, Todd SR, Turner KL, Valdivia A, Sailors RM, Moore FA. Computer protocol facilitates evidence-based care of sepsis in the surgical intensive care unit. J Trauma 2011; 70 (Suppl. 05) 1153-1166. discussion 1166-1167.
  • 13 Powell KK, Fowler RJ. Driving sepsis mortality down: Emergency department and critical care partnerships. Crit Care Nurs Clin North Am 2014; 26 (Suppl. 04) 487-498.
  • 14 Herasevich V, Pieper MS, Pulido J, Gajic O. Enrollment into a time sensitive clinical study in the critical care setting: Results from computerized septic shock sniffer implementation. J Am Med Inform Assoc 2011; 18 (Suppl. 05) 639-644.
  • 15 Umscheid CA, Betesh J, VanZandbergen C, Hanish A, Tait G, Mikkelsen ME, French B, Fuchs BD. Development, implementation, and impact of an automated early warning and response system for sepsis. J Hosp Med 2015; 10 (Suppl. 01) 26-31.
  • 16 Alsolamy S, Al Salamah M, Al Thagafi M, Al-Dorzi HM, Marini AM, Aljerian N, Al-Enezi F, Al-Hunaidi F, Mahmoud AM, Alamry A, Arabi YM. Diagnostic accuracy of a screening electronic alert tool for severe sepsis and septic shock in the emergency department.. BMC Med Inform Decis Mak 2014 14. 105 doi:10.1186/s12911–014–0105–7
  • 17 Manaktala S, Claypool SR. Evaluating the impact of a computerized surveillance algorithm and decision support system on sepsis mortality.. JAMIA 2016; ocw056.
  • 18 Neviere R, Parsons PE, Finlay T. Sepsis and the systemic inflammatory response syndrome: definitions, epidemiology, and prognosis.. Parsons PE ,Ed. UpToDate. September, 19, 2016. www.uptodate.com Last accessed 9/27/2016
  • 19 Manaktala S, Claypool SR. Evaluating the impact of a computerized surveillance algorithm and decision support system on sepsis mortality. Journal of the American Medical Informatics Association. 2016; May 25-ocw056
  • 20 Iwashyna TJ, Odden A, Rohde J, Bonham C, Kuhn L, Malani P, Chen L, Flanders S. 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 (Suppl. 06) e39-e43.
  • 21 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 (Suppl. 07) 1303-1310.
  • 22 Charlson ME, Pompei P, Ales KL, MacKenzie CR. A new method of classifying prognostic comorbidity in longitudinal studies: Development and validation. 1987 40. 5 373-383.
  • 23 Quan H, Sundararajan V, Halfon P, Fong A, Burnand B, Luthi JC, Saunders LD, Beck CA, Feasby TE, Ghali WA. Coding algorithms for defining comorbidities in ICD-9-CM and ICD-10 administrative data. Med Care 2005; 43 (Suppl. 11) 1130-1139.
  • 24 Austin PC. An introduction to propensity score methods for reducing the effects of confounding in observational studies. Multivariate Behav Res 2011; 46 (Suppl. 03) 399-424.
  • 25 R Development Core Team (2011). R: A Language and Environment for Statistical Computing.. Vienna, Austria : the R Foundation for Statistical Computing. ISBN: 3–900051–07–0. Available online at http://www.R-project.org. Last accessed 9/27/16
  • 26 Ho DE, Imai K, King G, Stuart EA. MatchIt: Nonparametric preprocessing for parametric causal inference. Journal of Statistical Software 2011; 42 (Suppl. 08) 1-21.
  • 27 Normand ST, Landrum MB, Guadagnoli E, Ayanian JZ, Ryan TJ, Cleary PD, McNeil BJ. Validating recommendations for coronary angiography following acute myocardial infarction in the elderly: A matched analysis using propensity scores. J Clin Epidemiol 2001; 54 (Suppl. 04) 387-398.
  • 28 Angus DC, Barnato AE, Bell D, Bellomo R, Chong CR, Coats TJ, Davies A, Delaney A, Harrison DA, Holdgate A, Howe B, Huang DT, Iwashyna T, Kellum JA, Peake SL, Pike F, Reade MC, Rowan KM, Singer M, Webb SA, Weissfeld LA, Yealy DM, Young JD. A systematic review and meta-analysis of early goal-directed therapy for septic shock: The ARISE ProCESS and ProMISe investigators. Intensive Care Med 2015; 41 (Suppl. 09) 1549-1560.
  • 29 ARISE Investigators, ANZICS Clinical Trials Group. Peake SL, Delaney A, Bailey M, Bellomo R, Cameron PA, Cooper DJ, Higgins AM, Holdgate A, Howe BD, Webb SA, Williams P. Goal-directed resuscitation for patients with early septic shock. N Engl J Med 2014; 371 (Suppl. 16) 1496-1506.