Diagnostic accuracy of a screening electronic alert tool for severe sepsis and septic shock in the emergency department

Alsolamy, Sami; Salamah, Majid Al; Thagafi, M.; Al‐Dorzi, Hasan M.; Marini, Abdellatif M.; Aljerian, Nawfal; Alenezi, Farhan; Alhunaidi, F.; Mahmoud, Ahmed; Alamry, Ahmed; Arabi, Yaseen M.

doi:10.1186/s12911-014-0105-7

Cited by 45 publications

(33 citation statements)

References 15 publications

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“…To assist clinicians in detecting patients at risk of physiological instability clinical decision support and automation of warnings have been advocated [7,8]. Such systems have to rely on the data in the Electronic Health Record Systems (EHRs) to provide accurate warnings.…”

Section: Background and Significancementioning

confidence: 99%

Exploring Vital Sign Data Quality in Electronic Health Records with Focus on Emergency Care Warning Scores

Skyttberg

Chen²,

Blomqvist³

et al. 2017

Appl Clin Inform

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Although vital signs that were recorded in completely electronic documentation practices showed plausible results regarding correctness, completeness and currency, the study concludes that vital signs documented in Swedish emergency care EHRs cannot generally be considered fit for use for calculation of triage and warning scores. Low completeness and currency were found if the documentation was not completely electronic.

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Section: Background and Significancementioning

confidence: 99%

Exploring Vital Sign Data Quality in Electronic Health Records with Focus on Emergency Care Warning Scores

Skyttberg

Chen²,

Blomqvist³

et al. 2017

Appl Clin Inform

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“…The sensitivity and specificity of alerts has been a challenge when implementing an electronic reminding system for early detection of sepsis [14][15][16]. A unique feature of this study was examining the accuracy of alerts on medical-surgical units with patients at risk for varying levels of sepsis severity vs. previous studies conducted in the emergency department or ICUs or just with patients experiencing severe sepsis/ septic shock [14][15][16]. We found that sensitivity was 95.1% and specificity was 82% with the highest sensitivity for severely ill patients (100%).…”

Section: Discussionmentioning

confidence: 99%

“…Some studies implemented screening tools [13,14] while others included alerts based on patient parameters, order sets, and recommended interventions [10][11][12]14]. The sensitivity and specificity of alerts varied considerably across studies [14][15][16]. The higher rate of accurately detecting sepsis is associated with settings such as the emergency department or ICUs.…”

Section: Summary Of Multi-focal Interventions To Detect Sepsis and Immentioning

confidence: 99%

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

et al. 2017

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SummarySummary: To conduct an independent secondary analysis of a multi-focal intervention for early detection of sepsis that included implementation of change management strategies, electronic surveillance 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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“…The test performance of these alerts may provide one reason for their limited success. Using physician orders in the emergency department may improve specificity of an EHR alert system, but physician orders have not been utilized to represent infection in published sepsis alerts [18][19].…”

Section: Introductionmentioning

confidence: 99%

Validation of test performance and clinical time zero for an electronic health record embedded severe sepsis alert

Rolnick¹,

Downing²,

Shepard³

et al. 2016

Appl Clin Inform

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SummaryBachground: Increasing use of EHRs has generated interest in the potential of computerized clinical decision support to improve treatment of sepsis. Electronic sepsis alerts have had mixed results due to poor test characteristics, the inability to detect sepsis in a timely fashion and the use of outside software limiting widespread adoption. We describe the development, evaluation and validation of an accurate and timely severe sepsis alert with the potential to impact sepsis management. Objective: To develop, evaluate, and validate an accurate and timely severe sepsis alert embedded in a commercial EHR. Methods: The sepsis alert was developed by identifying the most common severe sepsis criteria among a cohort of patients with ICD 9 codes indicating a diagnosis of sepsis. This alert requires criteria in three categories: indicators of a systemic inflammatory response, evidence of suspected infection from physician orders, and markers of organ dysfunction. Chart review was used to evaluate test performance and the ability to detect clinical time zero, the point in time when a patient develops severe sepsis. Results: Two physicians reviewed 100 positive cases and 75 negative cases. Based on this review, sensitivity was 74.5%, specificity was 86.0%, the positive predictive value was 50.3%, and the negative predictive value was 94.7%. The most common source of end-organ dysfunction was MAP less than 70 mm/Hg (59%). The alert was triggered at clinical time zero in 41% of cases and within three hours in 53.6% of cases. 96% of alerts triggered before a manual nurse screen. Conclusion:We are the first to report the time between a sepsis alert and physician chart-review clinical time zero. Incorporating physician orders in the alert criteria improves specificity while maintaining sensitivity, which is important to reduce alert fatigue. By leveraging standard EHR functionality, this alert could be implemented by other healthcare systems. BackgroundSepsis is the most common cause of death in hospitalized patients and costs the U.S. health care system $20 billion annually [1][2]. Similar to other acute medical conditions such as acute myocardial infarction or stroke, early diagnosis and treatment of sepsis is critical to positive treatment outcomes. For every hour delay in initiating antibiotics after the development of severe sepsis, expected patient mortality increases significantly [3][4][5]. Though timely administration of antibiotics and fluids is associated with improved patient outcomes, barriers to early recognition and treatment of sepsis continue to present significant challenges. Early signs of the progression from simple sepsis to sepsis with end-organ dysfunction (severe sepsis) may be subtle and non-specific. For that reason, treatment often fails to adhere to guidelines despite generally consistent evidence supporting standardized treatment [6].The recent widespread adoption of electronic health record systems (EHRs), combined with increasingly sophisticated clinical decision support, has generated i...

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Diagnostic accuracy of a screening electronic alert tool for severe sepsis and septic shock in the emergency department

Cited by 45 publications

References 15 publications

Exploring Vital Sign Data Quality in Electronic Health Records with Focus on Emergency Care Warning Scores

Exploring Vital Sign Data Quality in Electronic Health Records with Focus on Emergency Care Warning Scores

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

Validation of test performance and clinical time zero for an electronic health record embedded severe sepsis alert

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