Researchers developed and validated a retrospective method for accurately identifying cases of hemolytic disease of the fetus and newborn (HDFN) to better understand its epidemiology, treatments and outcomes, according to a recent study published in JMIR Research Protocols.
Despite routine screening, the epidemiology and treatment patterns of HDFN remain poorly defined. Causes include maternal-fetal red blood cell antigen incompatibility, and current clinical practice focuses on screening and preventing alloimmunization.
“The findings from this study are expected to provide valuable insights into the prevalence, treatment patterns, and resource utilization associated with HDFN,” the authors wrote.
The authors aimed to establish a detailed and consistent approach for identifying HDFN cases in a large healthcare system, utilizing both structured electronic health records (EHR) data and natural language processing (NLP) assisted chart review, to quantify its incidence better and describe associated prenatal and postnatal outcomes, treatments, and resource utilization.
This retrospective cohort study, conducted on approximately 460,000 pregnancies within the Kaiser Permanente Southern California health system, compared maternal and infant characteristics by HDFN status and evaluated the association between HDFN and adverse perinatal outcomes. A total of 138 HDFN cases were identified, representing 0.03% of the pregnancies. Of these, 137 were live births (0.99%), and 1 was a stillbirth (0.01%).
The study also plans to investigate the annual prevalence, healthcare resource utilization, and treatment patterns among mothers and infants with HDFN. However these results were not presented in the preliminary summary.
While this method improves case detection beyond diagnostic codes alone, future work could benefit from prospective validation and the inclusion of expanded covariates to refine case criteria further and enhance generalizability.“Our novel methodology, combining both structured and unstructured data and a natural language processing–assisted chart review process, ensures the successful identification of true cases to carry out pharmaco-epidemiological studies,” the authors concluded.
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