Development and Validation of an Algorithm to Identify Prenatal Care in Administrative Data: Predictive Validity for...

To develop and validate a hierarchical algorithm for assigning prenatal care (PNC) encounters using claims data while ensuring continuity of care.

We conducted a retrospective cohort study among South Carolina Medicaid beneficiaries. Using a six-step hierarchical algorithm-incorporating specialty designations, diagnostic/procedure codes, and adjustments for inpatient stays and supplemental visits-we assigned PNC encounters and identified predominant PNC providers. To assess predictive validity, we examined associations between predominant provider status and adverse birth outcomes (obtained from linked birth certificates and claims data) using logit-binomial generalized estimating equations with robust standard errors, and we compared models' performance using both model fit statistics and 10-fold cross-validation.

We used South Carolina Medicaid data on live-birth pregnancies from 2016 to 2021. We followed participants from conception until delivery.

Initial screening identified 302 package/bundle payment claims, leading to the exclusion of 299 pregnancies (0.3%) from further analysis. The final analytic dataset contained 1,072,615 confirmed PNC encounters for 90,581 (97%) pregnancies. This study identified predominant providers for 87,573 pregnancies (98% of cases with at least two PNC encounters). The analysis of predictive validity revealed significant protective associations for two outcomes when comparing pregnancies with versus without predominant providers: preterm birth (adjusted RR: 0.68, 95% CI: 0.59-0.77) and low-birth-weight (adjusted RR: 0.68, 95% CI: 0.57-0.80).

This study developed and validated a claims-based algorithm to identify PNC utilization in South Carolina Medicaid data. Predictive validity tests revealed that predominant provider status was associated with reduced adverse birth outcomes, suggesting care continuity may improve perinatal health. Future research could apply this algorithm to examine causal relationships between predominant provider status and specific outcomes (e.g., preterm birth, low birth weight), while accounting for institutional and socioeconomic confounders. These findings offer a foundation for optimizing PNC delivery through continuity-focused interventions.