Objective: To examine performance of a sepsis surveillance system in a simulated environment where modifications to parameters and settings for identification of at-risk patients can be explored in-depth.
Materials and methods: This was a multiple center observational cohort study. The study population comprised 14 917 adults hospitalized in 2016. An expert-driven rules algorithm was applied against 15.1 million data points to simulate a system with binary notification of sepsis events. Three system scenarios were examined: a scenario as derived from the second version of the Consensus Definitions for Sepsis and Septic Shock (SEP-2), the same scenario but without systolic blood pressure (SBP) decrease criteria (near SEP-2), and a conservative scenario with limited parameters. Patients identified by scenarios as being at-risk for sepsis were assessed for suspected infection. Multivariate binary logistic regression models estimated mortality risk among patients with suspected infection.
Results: First, the SEP-2-based scenario had a hyperactive, unreliable parameter SBP decrease >40 mm Hg from baseline. Second, the near SEP-2 scenario demonstrated adequate reliability and sensitivity. Third, the conservative scenario had modestly higher reliability, but sensitivity degraded quickly. Parameters differed in predicting mortality risk and represented a substitution effect between scenarios.
Discussion: Configuration of parameters and alert criteria have implications for patient identification and predicted outcomes.
Conclusion: Performance of scenarios was associated with scenario design. A single hyperactive, unreliable parameter may negatively influence adoption of the system. A trade-off between modest improvements in alert reliability corresponded to a steep decline in condition sensitivity in scenarios explored.
Keywords: classification; decision support; ergonomics; expert systems; sepsis.
© The Author(s) 2019. Published by Oxford University Press on behalf of the American Medical Informatics Association.
Assessment of Clinical Criteria for Sepsis: For the Third International Consensus Definitions for Sepsis and Septic Shock (Sepsis-3).JAMA. 2016 Feb 23;315(8):762-74. doi: 10.1001/jama.2016.0288. JAMA. 2016. PMID: 26903335 Free PMC article.
Developing a New Definition and Assessing New Clinical Criteria for Septic Shock: For the Third International Consensus Definitions for Sepsis and Septic Shock (Sepsis-3).JAMA. 2016 Feb 23;315(8):775-87. doi: 10.1001/jama.2016.0289. JAMA. 2016. PMID: 26903336 Free PMC article. Review.
The Third International Consensus Definitions for Sepsis and Septic Shock (Sepsis-3).JAMA. 2016 Feb 23;315(8):801-10. doi: 10.1001/jama.2016.0287. JAMA. 2016. PMID: 26903338 Free PMC article.
Systemic Inflammatory Response Syndrome.2019 Nov 21. In: StatPearls [Internet]. Treasure Island (FL): StatPearls Publishing; 2020 Jan–. StatPearls. 2020 Jan–. PMID: 31613449 Free Books & Documents. Review.
Evidence Underpinning the Centers for Medicare & Medicaid Services' Severe Sepsis and Septic Shock Management Bundle (SEP-1): A Systematic Review.Ann Intern Med. 2018 Apr 17;168(8):558-568. doi: 10.7326/M17-2947. Epub 2018 Feb 20. Ann Intern Med. 2018. PMID: 29459977
- Moskowitz A, Andersen LW, Cocchi M., et al. The misapplication of severity of illness scores toward clinical decision making. Am J Respir Crit Care Med 2016; 1943: 256–8. - PubMed
- Alberto L, Marshall AP, Walker R., et al. Screening for sepsis in general hospitalized patients: a systematic review. J Hosp Infect 2017; 964: 305–15. - PubMed
- Despins LA. Automated detection of sepsis using electronic medical record data: a systematic review. J Healthc Qual 2017; 396: 322–33. - PubMed
- Fernando SM, Tran A, Taljaard M., et al. Prognostic accuracy of the Quick Sequential Organ Failure Assessment for mortality in patients with suspected infection: a systematic review and meta-analysis. Ann Intern Med 2018; 1684: 266–75. - PubMed
- Capan M, Hoover S, Ivy JS., et al. Not all organ dysfunctions are created equal: prevalence and mortality in sepsis. J Crit Care 2018; 48: 257–62. - PubMed