Filtering authentic sepsis arising in the ICU using administrative codes coupled to a SIRS screening protocol
- PMID: 28190560
- DOI: 10.1016/j.jcrc.2017.01.012
Filtering authentic sepsis arising in the ICU using administrative codes coupled to a SIRS screening protocol
Abstract
Purpose: Using administrative codes and minimal physiologic and laboratory data, we sought a high-specificity identification strategy for patients whose sepsis initially appeared during their ICU stay.
Materials and methods: We studied all patients discharged from an academic hospital between September 1, 2013 and October 31, 2014. Administrative codes and minimal physiologic and laboratory criteria were used to identify patients at high risk of developing the onset of sepsis in the ICU. Two clinicians then independently reviewed the patient record to verify that the screened-in patients appeared to become septic during their ICU admission.
Results: Clinical chart review verified sepsis in 437/466 ICU stays (93.8%). Of these 437 encounters, only 151 (34.6%) were admitted to the ICU with neither SIRS nor evidence of infection and therefore appeared to become septic during their ICU stay.
Conclusions: Selected administrative codes coupled to SIRS criteria and applied to patients admitted to ICU can yield up to 94% authentic sepsis patients. However, only 1/3 of patients thus identified appeared to become septic during their ICU stay. Studies that depend on high-intensity monitoring for description of the time course of sepsis require clinician review and verification that sepsis initially appeared during the monitoring period.
Keywords: Administrative codes; Detection; Epidemiology; Intensive care unit; Sepsis; Systemic inflammatory response syndrome.
Copyright © 2017 Elsevier Inc. All rights reserved.
Similar articles
-
Low sensitivity of qSOFA, SIRS criteria and sepsis definition to identify infected patients at risk of complication in the prehospital setting and at the emergency department triage.Scand J Trauma Resusc Emerg Med. 2017 Nov 3;25(1):108. doi: 10.1186/s13049-017-0449-y. Scand J Trauma Resusc Emerg Med. 2017. PMID: 29100549 Free PMC article.
-
A comparison of pre ICU admission SIRS, EWS and q SOFA scores for predicting mortality and length of stay in ICU.J Crit Care. 2017 Oct;41:191-193. doi: 10.1016/j.jcrc.2017.05.017. Epub 2017 May 25. J Crit Care. 2017. PMID: 28575814
-
Comparison of qSOFA and SIRS for predicting adverse outcomes of patients with suspicion of sepsis outside the intensive care unit.Crit Care. 2017 Mar 26;21(1):73. doi: 10.1186/s13054-017-1658-5. Crit Care. 2017. PMID: 28342442 Free PMC article.
-
Performance of the quick Sequential (sepsis-related) Organ Failure Assessment score as a prognostic tool in infected patients outside the intensive care unit: a systematic review and meta-analysis.Crit Care. 2018 Feb 6;22(1):28. doi: 10.1186/s13054-018-1952-x. Crit Care. 2018. PMID: 29409518 Free PMC article. Review.
-
The value of sepsis definitions in daily ICU-practice.Acta Clin Belg. 2006 Sep-Oct;61(5):220-6. doi: 10.1179/acb.2006.037. Acta Clin Belg. 2006. PMID: 17240735 Review.
Cited by
-
Improving transitions and outcomes of sepsis survivors (I-TRANSFER): a type 1 hybrid protocol.BMC Palliat Care. 2022 Jun 2;21(1):98. doi: 10.1186/s12904-022-00973-w. BMC Palliat Care. 2022. PMID: 35655168 Free PMC article.
-
Validation of a machine learning algorithm for early severe sepsis prediction: a retrospective study predicting severe sepsis up to 48 h in advance using a diverse dataset from 461 US hospitals.BMC Med Inform Decis Mak. 2020 Oct 27;20(1):276. doi: 10.1186/s12911-020-01284-x. BMC Med Inform Decis Mak. 2020. PMID: 33109167 Free PMC article.
MeSH terms
Grants and funding
LinkOut - more resources
Full Text Sources
Other Literature Sources
Medical
