Background: There is increasing interest in using administrative data to examine pregnancy outcomes. The accuracy of using claims to identify particular pregnancy outcomes is not well known.
Objectives: To assess the performance of an algorithm for identification of pregnancy outcomes within a commercial insurer's administrative database as compared with medical records.
Methods: In a retrospective study of pregnant women with psoriasis or chronic inflammatory arthritis and a general population comparator group, an 8.5% random sample of pregnancies, stratified by pregnancy outcome, was identified in a large claims database using STORK (Systematic Tracking of Real Kids), a process that identifies pregnancies and links mothers and babies in administrative claims. Outcomes for live births (single and multiple), non-live outcomes (stillbirth, spontaneous and non-spontaneous abortions), and unknown outcomes were identified using a claims algorithm. Medical charts were sought and reviewed to confirm outcomes in claims. Positive predictive values (PPVs) and 95% confidence intervals (CIs) were calculated to estimate the proportion of claims that were true cases.
Results: Medical records were received for 300/457 pregnancies. Outcome data were recorded in the procured medical records for 180/232 live birth and 53/55 non-live birth claims. The PPV for claims-based live birth outcomes was 98.3 % (95%CI: 94.8-99.6). All 53 charts for non-live outcome claims were confirmed as non-live [PPV=100%, (95%CI: 91.6-100.0)]. Finer distinctions within these categories were also assessed. Among live births, the PPV for claims identifying single full term live births was 97.2% (95%CI: 92.6-99.1) but for multiple live births it was 18.8% (95%CI: 5.0-46.3). Among non-live births, the PPV for spontaneous abortions was 100% (95%CI: 86.0-100.0); but, for non-spontaneous abortions it was 23.1% (95%CI: 6.1-54.0) with 10/13 of those claims described in charts as spontaneous.
Conclusions: Our algorithm performed well in discriminating live and non-live pregnancy outcomes and in identifying spontaneous abortions, but did not perform well for differentiating multiple live births or non-spontaneous abortions.
