Dr. Songyuan Deng, an Associate Scientist at the South Carolina Center for Rural and Primary Healthcare at the USC School of Medicine-Columbia, has conducted a study proposing an algorithm to identify the predominant prenatal care provider and estimate the percentage of identified predominant providers.

Previous studies applied plurality (providing the most visits) and majority (providing majority of visits) to identify the predominant provider in primary care setting, with only visit frequency information. This study proposed an algorithm that included both visit frequency and sequence information in prenatal care (PNC) to identify the predominant provider and estimated the percentage of identified predominant providers.

By applying PNC frequency information, a predominant provider can be identified for 81% of pregnancies. After adding sequential information, a predominant provider can be identified for 92% of pregnancies. In addition, applying this algorithm revealed a longer distance for pregnant individuals travelling to their predominant provider (an average of 5 miles) than to the nearest provider.

Integrating visit frequency and sequence information, rather than relying solely on frequency, and incorporating dispersion information as a supplement allows for a better understanding of how patients seek PNC, particularly for the continuity of prenatal care. This insight is crucial for understanding which provider renders a big impact on prenatal care and birth outcomes for a pregnant woman.

Deng S, Renaud S, Bennett KJ. Who is your prenatal care provider? An algorithm to identify the predominant prenatal care provider with claims data. BMC Health Serv Res. 2024 May 27;24(1):665. doi: 10.1186/s12913-024-11080-2. PMID: 38802871; PMCID: PMC11131320.