Systematic review of validated case definitions to identify hypertensive disorders of pregnancy in administrative healthcare databases

Abstract

Background Administrative data are frequently used to study cardiovascular disease (CVD) risk in women with hypertensive disorders of pregnancy (HDP). Little is known about the validity of case-finding definitions (CFDs, eg, disease classification codes/algorithms) designed to identify HDP in administrative databases. Methods A systematic review of the literature. We searched MEDLINE, Embase, CINAHL, Web of Science and grey literature sources for eligible studies. Two independent reviewers screened articles for eligibility and extracted data. Quality of reporting was assessed using checklists; risk of bias was assessed using the Quality Assessment of Diagnostic Accuracy Studies-2 (QUADAS-2) tool, adapted for administrative studies. Findings were summarised descriptively. Results Twenty-six studies were included; most (62%) validated CFDs for a variety of maternal and/or neonatal outcomes. Six studies (24%) reported reference standard definitions for all HDP definitions validated; seven reported all 2×2 table values for ≥1 CFD or they were calculable. Most CFDs (n=83; 58%) identified HDP with high specificity (ie, ≥98%); however, sensitivity varied widely (3%-100%). CFDs validated for any maternal hypertensive disorder had the highest median sensitivity (91%, range: 15%-97%). Quality of reporting was generally poor, and all studies were at unclear or high risk of bias on ≥1 QUADAS-2 domain. Conclusions Even validated CFDs are subject to bias. Researchers should choose the CFD(s) that best align with their research objective, while considering the relative importance of high sensitivity, specificity, negative predictive value and/or positive predictive value, and important characteristics of the validation studies from which they were derived (eg, study prevalence of HDP, spectrum of disease studied, methodological rigour, quality of reporting and risk of bias). Higher quality validation studies on this topic are urgently needed. PROSPERO registration number CRD42021239113.