Dataset Information

Validation of Test Performance and Clinical Time Zero for an Electronic Health Record Embedded Severe Sepsis Alert.

ABSTRACT: 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.To develop, evaluate, and validate an accurate and timely severe sepsis alert embedded in a commercial EHR.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.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.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.

SUBMITTER: Rolnick J

PROVIDER: S-EPMC4941860 | biostudies-literature | 2016

REPOSITORIES: biostudies-literature

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Validation of Test Performance and Clinical Time Zero for an Electronic Health Record Embedded Severe Sepsis Alert.

Rolnick Joshua J Downing N Lance NL Shepard John J Chu Weihan W Tam Julia J Wessels Alexander A Li Ron R Dietrich Brian B Rudy Michael M Castaneda Leon L Shieh Lisa L

Applied clinical informatics 20160622 2

<h4>Bachground</h4>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.< ...[more]

PMID: 27437061

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Project description:Study objectiveRecognition of pediatric sepsis is a key clinical challenge. We evaluate the performance of a sepsis recognition process including an electronic sepsis alert and bedside assessment in a pediatric emergency department (ED).MethodsThis was a cohort study with quality improvement intervention in a pediatric ED. Exposure was a positive electronic sepsis alert, defined as elevated pulse rate or hypotension, concern for infection, and at least one of the following: abnormal capillary refill, abnormal mental status, or high-risk condition. A positive electronic sepsis alert prompted team assessment or huddle to determine need for sepsis protocol. Clinicians could initiate team assessment or huddle according to clinical concern without positive electronic sepsis alert. Severe sepsis outcome defined as activation of the sepsis protocol in the ED or development of severe sepsis requiring ICU admission within 24 hours.ResultsThere were 182,509 ED visits during the study period, with 86,037 before electronic sepsis alert implementation and 96,472 afterward, and 1,112 (1.2%) positive electronic sepsis alerts. Overall, 326 patients (0.3%) were treated for severe sepsis within 24 hours. Test characteristics of the electronic sepsis alert alone to detect severe sepsis were sensitivity 86.2% (95% confidence interval [CI] 82.0% to 89.5%), specificity 99.1% (95% CI 99.0% to 99.2%), positive predictive value 25.4% (95% CI 22.8% to 28.0%), and negative predictive value 100% (95% CI 99.9% to 100%). Inclusion of the clinician screen identified 43 additional electronic sepsis alert-negative children, with severe sepsis sensitivity 99.4% (95% CI 97.8% to 99.8%) and specificity 99.1% (95% CI 99.1% to 99.2%). Electronic sepsis alert implementation increased ED sepsis detection from 83% to 96%.ConclusionElectronic sepsis alert for severe sepsis demonstrated good sensitivity and high specificity. Addition of clinician identification of electronic sepsis alert-negative patients further improved sensitivity. Implementation of the electronic sepsis alert was associated with improved recognition of severe sepsis.

Project description:Background. While often first treated in the emergency department (ED), identification of sepsis is difficult. Electronic medical record (EMR) clinical decision tools offer a novel strategy for identifying patients with sepsis. The objective of this study was to test the accuracy of an EMR-based, automated sepsis identification system. Methods. We tested an EMR-based sepsis identification tool at a major academic, urban ED with 64,000 annual visits. The EMR system collected vital sign and laboratory test information on all ED patients, triggering a "sepsis alert" for those with ?2 SIRS (systemic inflammatory response syndrome) criteria (fever, tachycardia, tachypnea, leukocytosis) plus ?1 major organ dysfunction (SBP ? 90 mm Hg, lactic acid ?2.0 mg/dL). We confirmed the presence of sepsis through manual review of physician, nursing, and laboratory records. We also reviewed a random selection of ED cases that did not trigger a sepsis alert. We evaluated the diagnostic accuracy of the sepsis identification tool. Results. From January 1 through March 31, 2012, there were 795 automated sepsis alerts. We randomly selected 300 cases without a sepsis alert from the same period. The true prevalence of sepsis was 355/795 (44.7%) among alerts and 0/300 (0%) among non-alerts. The positive predictive value of the sepsis alert was 44.7% (95% CI [41.2-48.2%]). Pneumonia and respiratory infections (38%) and urinary tract infection (32.7%) were the most common infections among the 355 patients with true sepsis (true positives). Among false-positive sepsis alerts, the most common medical conditions were gastrointestinal (26.1%), traumatic (25.7%), and cardiovascular (20.0%) conditions. Rates of hospital admission were: true-positive sepsis alert 91.0%, false-positive alert 83.0%, no sepsis alert 5.7%. Conclusions. This ED EMR-based automated sepsis identification system was able to detect cases with sepsis. Automated EMR-based detection may provide a viable strategy for identifying sepsis in the ED.

Project description:This study aimed to assess the potential impact of implementing an electronic alert system (EAS) for systemic inflammatory syndrome (SIRS) and sepsis in pediatric patients mortality. This retrospective study had a pre and post design. We enrolled patients aged ≤ 14 years who were diagnosed with sepsis/severe sepsis upon admission to the pediatric intensive care unit (PICU) of our tertiary hospital from January 2014 to December 2018. We implemented an EAS for the patients with SIRS/sepsis. The patients who met the inclusion criteria pre-EAS implementation comprised the control group, and the group post-EAS implementation was the experimental group. Mortality was the primary outcome, while length of stay (LOS) and mechanical ventilation in the first hour were the secondary outcomes. Of the 308 enrolled patients, 147 were in the pre-EAS group and 161 in the post-EAS group. In terms of mortality, 44 patients in the pre-EAS group and 28 in the post-EAS group died (p 0.011). The average LOS in the PICU was 7.9 days for the pre-EAS group and 6.8 days for the post-EAS group (p 0.442). Considering the EAS initiation time as the "zero time", early recognition of SIRS and sepsis via the EAS led to faster treatment interventions in post-EAS group, which included fluid boluses with median (25th, 75th percentile) time of 107 (37, 218) min vs. 30 (11,112) min, p < 0.001) and time to initiate antimicrobial therapy median (25th, 75th percentile) of 170.5 (66,320) min vs. 131 (53,279) min, p 0.042). The difference in mechanical ventilation in the first hour of admission was not significant between the groups (25.17% vs. 24.22%, p 0.895). The implementation of the EAS resulted in a statistically significant reduction in the mortality rate among the patients admitted to the PICU in our study. An EAS can play an important role in saving lives and subsequent reduction in healthcare costs. Further enhancement of systematic screening is therefore highly recommended to improve the prognosis of pediatric SIRS and sepsis. The implementation of the EAS, warrants further validation in multicenter or national studies.

Dataset Information

Validation of Test Performance and Clinical Time Zero for an Electronic Health Record Embedded Severe Sepsis Alert.

Publications

Validation of Test Performance and Clinical Time Zero for an Electronic Health Record Embedded Severe Sepsis Alert.

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