Development of a Linked Perinatal Data Resource From State Administrative and Community-Based Program Data
- 315 Downloads
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.
KeywordsHome visiting Early childhood development Data linking
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.
- 2.Clements, K. M., Barfield, W. D., Kotelchuck, M., et al. (2006). Birth characteristics associated with early intervention referral, evaluation for eligibility, and program eligibility in the first year of life. Maternal and Child Health Journal, 10(5), 433–441. doi: 10.1007/s10995-006-0080-4.CrossRefGoogle Scholar
- 5.Health Resources and Services Administration. (2012). Maternal, infant, and early childhood home visiting program. Accessed November 1, 2012 http://mchb.hrsa.gov/programs/homevisiting/index.html.
- 8.Kempe, R. S., & Kempe, C. H. (1978). Child abuse. Cambridge, Mass: Harvard University Press.Google Scholar
- 9.Squires, J., Bricker, D. D., & Twombly, E. (2009). Ages and stages questionnaires: A parent-completed child monitoring system (3rd ed.). Baltimore: Paul H. Brooks Pub. Co.Google Scholar
- 10.Black, C., & Roos, L. L. (2005). Linking and combining data to develop statistics for understanding the population’s health. In D. J. Friedman, E. L. Hunter, & R. G. Parrish (Eds.), Health statistics: Shaping policy and practice to improve the population’s health (pp. 214–240). New York, NY: Oxford University Press.CrossRefGoogle Scholar
- 13.Manitoba Centre for Health Policy. (2012). Concept: LINKS: A record linkage package. Accessed October 2, 2012 http://mchp-appserv.cpe.umanitoba.ca/viewConcept.php?conceptID=1029.
- 16.U.S. Census Bureau. (2012). American community survey. Accessed November 12, 2012 http://www.census.gov/acs/www/.
- 17.Krieger, N., Chen, J. T., Waterman, P. D., et al. (2003). Choosing area based socioeconomic measures to monitor social inequalities in low birth weight and childhood lead poisoning: The public health disparities geocoding project (US). Journal of Epidemiology and Community Health, 57(3), 186–199.CrossRefGoogle Scholar
- 19.Kitzman, H., Olds, D. L., Henderson, C. R., Jr., et al. (1997). Effect of prenatal and infancy home visitation by nurses on pregnancy outcomes, childhood injuries, and repeated childbearing. A randomized controlled trial. JAMA, the Journal of the American Medical Association, 278(8), 644–652.CrossRefGoogle Scholar
- 23.Behrman RE, Butler AS, Institute of Medicine (U.S.). (2007). Committee on understanding premature birth and assuring healthy outcomes. Preterm birth: Causes, consequences, and prevention. Washington, D.C.: National Academies Press.Google Scholar
- 24.Herman A, McCarthy B, Bakewell J, et al. (1997). Data linkage methods used in maternally-linked birth and infant death surveillance data sets from the United States (Georgia, Missouri, Utah and Washington State), Israel, Norway, Scotland and Western Australia. Paediatric and Perinatal Epidemiology, 11(S1):5–22. doi: 10.1046/j.1365-3016.11.s1.11.x.
- 30.Cheung, N. T., Fung, V., Chow, Y. Y., et al. (2001). Structured data entry of clinical information for documentation and data collection. Studies in Health Technology and Information, 84(Pt 1), 609–613.Google Scholar
- 38.Vinikoor, L. C., Messer, L. C., Laraia, B. A., et al. (2010). Reliability of variables on the North Carolina birth certificate: A comparison with directly queried values from a cohort study. Paediatric and Perinatal Epidemiology, 24(1), 102–112. doi: 10.1111/j.1365-3016.2009.01087.x.CrossRefGoogle Scholar