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Development of a Linked Perinatal Data Resource From State Administrative and Community-Based Program Data

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Abstract

To demonstrate a generalizable approach for developing maternal-child health data resources using state administrative records and community-based program data. We used a probabilistic and deterministic linking strategy to join vital records, hospital discharge records, and home visiting data for a population-based cohort of at-risk, first time mothers enrolled in a regional home visiting program in Southwestern Ohio and Northern Kentucky from 2007 to 2010. Because data sources shared no universal identifier, common identifying elements were selected and evaluated for discriminating power. Vital records then served as a hub to which other records were linked. Variables were recoded into clinically significant categories and a cross-set of composite analytic variables was constructed. Finally, individual-level data were linked to corresponding area-level measures by census tract using the American Communities Survey. The final data set represented 2,330 maternal-infant pairs with both home visiting and vital records data. Of these, 56 pairs (2.4 %) did not link to either maternal or infant hospital discharge records. In a 10 % validation subset (n = 233), 100 % of the reviewed matches between home visiting data and vital records were true matches. Combining multiple data sources provided more comprehensive details of perinatal health service utilization and demographic, clinical, psychosocial, and behavioral characteristics than available from a single data source. Our approach offers a template for leveraging disparate sources of data to support a platform of research that evaluates the timeliness and reach of home visiting as well as its association with key maternal-child health outcomes.

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Acknowledgments

Dr. Goyal was supported by the BIRCWH K12 program, co-funded by the Office of Research on Women’s Health and the Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD), Award Number 5K12HD051953-07. Dr. Ammerman was supported by Grant R01MH087499 from the National Institute of Mental Health. The content is solely the responsibility of the authors and does not represent the official views of the NICHD, the NIMH, or the NIH. The authors acknowledge support of the United Way of Greater Cincinnati, Kentucky H.A.N.D.S., and Ohio Help Me Grow, and technical assistance from Ted Folger.

Author information

Authors and Affiliations

  1. Perinatal Institute and Biomedical Informatics, Cincinnati Children’s Hospital, Cincinnati, OH, USA

    Eric S. Hall

  2. Perinatal Institute, Cincinnati Children’s Hospital, Cincinnati, OH, USA

    Neera K. Goyal & Megan M. Miller

  3. Every Child Succeeds, Cincinnati Children’s Hospital, Cincinnati, OH, USA

    Robert T. Ammerman, Jodie A. Short & Judith B. Van Ginkel

  4. Biostatistics and Epidemiology, Cincinnati Children’s Hospital, Cincinnati, OH, USA

    David E. Jones

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  1. Eric S. Hall
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  2. Neera K. Goyal
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  3. Robert T. Ammerman
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  4. Megan M. Miller
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Corresponding author

Correspondence to Eric S. Hall.

Additional information

Dr. Hall and Dr. Goyal are co-first authors who contributed equally to this work.

Appendix

Appendix

See Table 5.

Table 5 International classification of diseases, 9th revision, clinical modification (ICD-9-CM) codes used to categorize hospital discharge diagnoses
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Hall, E.S., Goyal, N.K., Ammerman, R.T. et al. Development of a Linked Perinatal Data Resource From State Administrative and Community-Based Program Data. Matern Child Health J 18, 316–325 (2014). https://doi.org/10.1007/s10995-013-1236-7

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