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      A statewide system for maternal-infant linked longitudinal surveillance: Indiana’s model for improving maternal and child health

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          Abstract

          Indiana, located in the Midwest region of the United States, faces significant challenges with respect to health, especially maternal and child health (MCH). These challenges include high rates of stillbirth, neonatal abstinence syndrome (NAS) and congenital syphilis (CS). Not only are these often-fatal conditions underreported, but it can also be difficult to track them longitudinally, as mothers and infants are not routinely linked through electronic health records (EHRs). This paper describes the process, structure and planned outcomes of a partnership between Indiana University, Regenstrief Institute and public health partners in support of the U.S. Centers for Disease Control and Prevention’s Pregnant People-Infant Linked Longitudinal Surveillance (PILLARS) program. Together, academic, clinical and public health organisations are collaboratively developing an infrastructure and deploying novel methods to surveil stillbirth, CS and NAS longitudinally. The infrastructure includes: (a) deploying deterministic and probabilistic algorithms to link mothers and their infants using multiple, linked data sources; (b) creating and maintaining a registry of maternal-infant dyads; (c) using the registry to perform longitudinal surveillance in collaboration with Indiana public health authorities on stillbirth, NAS and CS and (d) translating information from surveillance activities into action by collaborating with public health and community-based organisations to improve and implement prevention activities in vulnerable Indiana communities. Our long-term goal is to improve outcomes for these conditions and other priority MCH outcomes by expanding our work to additional MCH use cases.

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          The Indiana network for patient care: a working local health information infrastructure. An example of a working infrastructure collaboration that links data from five health systems and hundreds of millions of entries.

          The Indiana Network for Patient Care (INPC) is a local health information infrastructure (LHII) that includes information from the five major hospital systems (fifteen separate hospitals), the county and state public health departments, and Indiana Medicaid and RxHub and that carries 660 million separate results. It provides cross-institutional access to physicians in emergency rooms and hospitals based on patient-physician proximity or on hospital credentialing. The network includes and delivers laboratory, radiology, dictation, and other documents to a majority of Indianapolis office practices. The INPC began operation seven years ago and is one of the first and best examples of an LHII.
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            Making stillbirths count, making numbers talk - Issues in data collection for stillbirths

            Background Stillbirths need to count. They constitute the majority of the world's perinatal deaths and yet, they are largely invisible. Simply counting stillbirths is only the first step in analysis and prevention. From a public health perspective, there is a need for information on timing and circumstances of death, associated conditions and underlying causes, and availability and quality of care. This information will guide efforts to prevent stillbirths and improve quality of care. Discussion In this report, we assess how different definitions and limits in registration affect data capture, and we discuss the specific challenges of stillbirth registration, with emphasis on implementation. We identify what data need to be captured, we suggest a dataset to cover core needs in registration and analysis of the different categories of stillbirths with causes and quality indicators, and we illustrate the experience in stillbirth registration from different cultural settings. Finally, we point out gaps that need attention in the International Classification of Diseases and review the qualities of alternative systems that have been tested in low- and middle-income settings. Summary Obtaining high-quality data will require consistent definitions for stillbirths, systematic population-based registration, better tools for surveys and verbal autopsies, capacity building and training in procedures to identify causes of death, locally adapted quality indicators, improved classification systems, and effective registration and reporting systems.
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              The Linked CENTURY Study: linking three decades of clinical and public health data to examine disparities in childhood obesity

              Background Despite the need to identify the causes of disparities in childhood obesity, the existing epidemiologic studies of early life risk factors have several limitations. We report on the construction of the Linked CENTURY database, incorporating CENTURY (Collecting Electronic Nutrition Trajectory Data Using Records of Youth) Study data with birth certificates; and discuss the potential implications of combining clinical and public health data sources in examining the etiology of disparities in childhood obesity. Methods We linked the existing CENTURY Study, a database of 269,959 singleton children from birth to age 18 years with measured heights and weights, with each child’s Massachusetts birth certificate, which captures information on their mothers’ pregnancy history and detailed socio-demographic information of both mothers and fathers. Results Overall, 74.2 % were matched, resulting in 200,343 children in the Linked CENTURY Study with 1,580,597 well child visits. Among this cohort, 94.0 % (188,334) of children have some father information available on the birth certificate and 60.9 % (121,917) of children have at least one other sibling in the dataset. Using maternal race/ethnicity from the birth certificate as an indicator of children’s race/ethnicity, 75.7 % of children were white, 11.6 % black, 4.6 % Hispanic, and 5.7 % Asian. Based on socio-demographic information from the birth certificate, 20.0 % of mothers were non-US born, 5.9 % smoked during pregnancy, 76.3 % initiated breastfeeding, and 11.0 % of mothers had their delivery paid for by public health insurance. Using clinical data from the CENTURY Study, 22.7 % of children had a weight-for-length ≥ 95th percentile between 1 and 24 months and 12.0 % of children had a body mass index ≥ 95th percentile at ages 5 and 17 years. Conclusions By linking routinely-collected data sources, it is possible to address research questions that could not be answered with either source alone. Linkage between a clinical database and each child’s birth certificate has created a unique dataset with nearly complete racial/ethnic and socio-demographic information from both parents, which has the potential to examine the etiology of racial/ethnic and socioeconomic disparities in childhood obesity.

                Author and article information

                Journal
                Int J Popul Data Sci
                Int J Popul Data Sci
                IJPDS
                International Journal of Population Data Science
                Swansea University
                2399-4908
                11 November 2024
                2024
                : 9
                : 2
                : 2395
                Affiliations
                [1 ] Department of Health Policy and Management, Indiana University Richard M. Fairbanks School of Public Health, 1050 Wishard Blvd, Indianapolis, IN 46202, United States of America
                [2 ] Center for Biomedical Informatics, Regenstrief Institute, 1101 W 10th St, Indianapolis, IN 46202, United States of America
                [3 ] Department of Pediatrics, Sandra Eskenazi Outpatient Health Center, Eskenazi Health, 720 Eskenazi Ave, Indianapolis IN 46202, United States of America
                [4 ] Regenstrief Data Services, Regenstrief Institute, 1101 W 10th St, Indianapolis, IN 46202, United States of America
                [5 ] Indiana Health Information Exchange, 846 N Senate Ave # 300, Indianapolis, IN 46202, United States of America
                [6 ] Indiana Department of Health, 2 N Meridian St, Indianapolis, IN 46204, United States of America
                [7 ] Marion County Public Health Department, 3838 N. Rural Street, Indianapolis, IN 46205, United States of America
                [8 ] Bell Flower Clinic, Marion County Public Health Department, 640 Eskenazi Ave, Indianapolis, IN 46202, United States of America
                [9 ] Department of Medicine, Indiana University School of Medicine, 545 Barnhill Drive, Indianapolis, IN 46202, United States of America
                [10 ] Department of Family Medicine, Indiana University School of Medicine, 980 Indiana Avenue, Lockefield Village 1164, Indianapolis, IN 46202, United States of America
                Author notes
                [*] [* ]Corresponding author: Jill Inderstrodt ji3@ 123456iu.edu

                Statement of conflicts of interest: The authors declare that they have no conflicts of interest.

                Article
                9:2:10
                10.23889/ijpds.v9i2.2395
                12076274
                40370791
                5b8a955d-f58c-4fa8-960f-7e66c5f51669

                This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

                History
                Categories
                Population Data Science

                data linkage,maternal health,child health,health information exchange

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