Identifying Hemolytic Disease of the Fetus and Newborn within a Large Integrated Health Care System.

Autor:	Xie F; Department of Research and Evaluation, Kaiser Permanente Southern California, Pasadena, California., Fassett MJ; Department of Obstetrics and Gynecology, Kaiser Permanente West Los Angeles Medical Center, Los Angeles, California.; Department of Clinical Science, Kaiser Permanente Bernard J. Tyson School of Medicine, Pasadena, California., Shi JM; Department of Research and Evaluation, Kaiser Permanente Southern California, Pasadena, California., Chiu VY; Department of Research and Evaluation, Kaiser Permanente Southern California, Pasadena, California., Im TM; Department of Research and Evaluation, Kaiser Permanente Southern California, Pasadena, California., Kim S; Department of Research and Evaluation, Kaiser Permanente Southern California, Pasadena, California., Mensah NA; Department of Research and Evaluation, Kaiser Permanente Southern California, Pasadena, California., Khadka N; Department of Research and Evaluation, Kaiser Permanente Southern California, Pasadena, California., Park D; Department of Research and Evaluation, Kaiser Permanente Southern California, Pasadena, California., Mao C; Janssen Global Services LLC, a Johnson & Johnson company, Horsham, Pennsylvania., Molaei M; Janssen Global Services LLC, a Johnson & Johnson company, Horsham, Pennsylvania., Lin I; Janssen Scientific Affairs LLC, a Johnson & Johnson company, Horsham, Pennsylvania., Getahun D; Department of Research and Evaluation, Kaiser Permanente Southern California, Pasadena, California.; Department of Health Systems Science, Kaiser Permanente Bernard J. Tyson School of Medicine, Pasadena, California.
Jazyk:	angličtina
Zdroj:	American journal of perinatology [Am J Perinatol] 2024 Nov 12. Date of Electronic Publication: 2024 Nov 12.
DOI:	10.1055/a-2444-2314
Abstrakt:	Objective:  This study aims to identify hemolytic disease of the fetus and newborn (HDFN) pregnancies using electronic health records (EHRs) from a large integrated health care system. Study Design:  A retrospective cohort study was performed among pregnant patients receiving obstetrical care at Kaiser Permanente Southern California health care system between January 1, 2008, and June 30, 2022. Using structured (diagnostic/procedural codes, medication, and laboratory records) and unstructured (clinical notes analyzed via natural language processing) data abstracted from EHRs, we extracted HDFN-specific "indicators" (maternal positive antibody test and abnormal antibody titer, maternal/infant HDFN diagnosis and blood transfusion, hydrops fetalis, infant intravenous immunoglobulin [IVIG] treatment, jaundice/phototherapy, and first administrated Rho[D] Immune Globulin) to identify potential HDFN pregnancies. Chart reviews and adjudication were then performed on select combinations of indicators for case ascertainment. HDFN due to ABO alloimmunization alone was excluded. The HDFN frequency and proportion of each combination were fully analyzed. Results:  Among the 464,711 eligible pregnancies, a total of 136 pregnancies were confirmed as HDFN pregnancies. The percentage of the HDFN-specific indicators ranged from 0.02% (infant IVIG treatment) to 34.53% (infant jaundice/phototherapy) among the eligible pregnancies, and 32.35% (infant IVIG treatment) to 100% (maternal positive antibody test) among the 136 confirmed HDFN pregnancies. Four combination groups of four indicators, four combination groups of five indicators, and the unique combination of six indicators showed 100% of HDFN pregnancies, while 80.88% of confirmed HDFN pregnancies had the indicator combination of maternal positive antibody test, maternal/infant HDFN diagnosis, and infant jaundice/phototherapy. Conclusion:  We successfully identified HDFN pregnancies by leveraging a combination of medical indicators extracted from structured and unstructured data that may be used in future pharmacoepidemiologic studies. Traditional indicators (positive antibody test results, high titers, and clinical diagnosis codes) alone did not accurately identify HDFN pregnancies, highlighting an unmet need for improved practices in HDFN coding. Key Points: · A case ascertainment method was developed to identify HDFN from structured and unstructured data.. · The method used in this study may be used in future pharmacoepidemiologic studies.. · The study highlighted an unmet need for improved practices in HDFN coding.. Competing Interests: None declared. (The Author(s). This is an open access article published by Thieme under the terms of the Creative Commons Attribution-NonDerivative-NonCommercial License, permitting copying and reproduction so long as the original work is given appropriate credit. Contents may not be used for commercial purposes, or adapted, remixed, transformed or built upon. (https://creativecommons.org/licenses/by-nc-nd/4.0/).)
Databáze:	MEDLINE
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