Validation of new ICD-10-based patient safety indicators for identification of in-hospital complications in surgical patients: a study of diagnostic accuracy. Issue 3 (22nd August 2019)

• Record Type: Journal Article
• Authors: McIsaac, Daniel I; Hamilton, Gavin M; Abdulla, Karim; Lavallée, Luke T; Moloo, Husien; Pysyk, Chris; Tufts, Jocelyn; Ghali, William A; Forster, Alan J
• Is Part Of: BMJ quality & safety. Volume 29:Issue 3(2020)
• Page Start: 209
• Page End: 216
• Publication Date: 2019-08-22
• Subjects: Adverse events, epidemiology and detection -- Chart review methodologies -- Healthcare quality improvement -- Incident reporting -- Surgery; Medical care -- Quality control -- Periodicals; Health facilities -- Risk management -- Periodicals; Medical errors -- Prevention -- Periodicals; 362.106805
• DOI: 10.1136/bmjqs-2018-008852
• Languages: English
• ISSNs: 2044-5415

Abstract

Abstract : Objective: Administrative data systems are used to identify hospital-based patient safety events; few studies evaluate their accuracy. We assessed the accuracy of a new set of patient safety indicators (PSIs; designed to identify in hospital complications). Study design: Prospectively defined analysis of registry data (1 April 2010–29 February 2016) in a Canadian hospital network. Assignment of complications was by two methods independently. The National Surgical Quality Improvement Programme (NSQIP) database was the clinical reference standard (primary outcome=any in-hospital NSQIP complication); PSI clusters were assigned using International Classification of Disease (ICD-10) codes in the discharge abstract. Our primary analysis assessed the accuracy of any PSI condition compared with any complication in the NSQIP; secondary analysis evaluated accuracy of complication-specific PSIs. Patients: All inpatient surgical cases captured in NSQIP data. Analysis: We assessed the accuracy of PSIs (with NSQIP as reference standard) using positive and negative predictive values (PPV/NPV), as well as positive and negative likelihood ratios (±LR). Results: We identified 12 898 linked episodes of care. Complications were identified by PSIs and NSQIP in 2415 (18.7%) and 2885 (22.4%) episodes, respectively. The presence of any PSI code had a PPV of 0.55 (95% CI 0.53 to 0.57) and NPV of 0.93 (95% CI 0.92 to 0.93); +LR 6.41 (95% CI 6.01 to 6.84) and −LR 0.40 (95% CI 0.37 to 0.42). Subgroup analyses (by surgery type and urgency) showed similar performance. Complication-specific PSIs had high NPVs (95% CI 0.92 to 0.99), but low to moderate PPVs (0.13–0.61). Conclusion: Validation of the ICD-10 PSI system suggests applicability as a first screening step, integrated with data from other sources, to produce an adverse event detection pathway that informs learning healthcare systems. However, accuracy was insufficient to directly identify or rule out individual-level complications.