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      Preparing linked population data for research: cohort study of prisoner perinatal health outcomes

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          Abstract

          Background

          A study of pregnancy outcomes related to pregnancy in prison in New South Wales, Australia, designed a two stage linkage to add maternal history of incarceration and serious mental health morbidity, neonatal hospital admission and infant congenital anomaly diagnosis to birth data. Linkage was performed by a dedicated state-wide data linkage authority. This paper describes use of the linked data to determine pregnancy prison exposure pregnancy for a representative population of mothers.

          Methods

          Researchers assessed the quality of linked records; resolved multiple-matched identities; transformed event-based incarceration records into person-based prisoner records and birth records into maternity records. Inconsistent or incomplete records were censored. Interrogation of the temporal relationships of all incarceration periods from the prisoner record with pregnancies from birth records identified prisoner maternities. Interrogation of maternities for each mother distinguished prisoner mothers who were incarcerated during pregnancy, from prisoner control mothers with pregnancies wholly in the community and a subset of prisoner mothers with maternities both types of maternity. Standard descriptive statistics are used to provide population prevalence of exposures and compare data quality across study populations stratified by mental health morbidity.

          Results

          Women incarcerated between 1998 and 2006 accounted for less than 1 % of the 404,000 women who gave birth in NSW between 2000 and 2006, while women with serious mental health morbidity accounted for 7 % overall and 68 % of prisoners. Rates of false positive linkage were within the predicted limits set by the linkage authority for non-prisoners, but were tenfold higher among prisoners (RR 9.9; 95%CI 8.2, 11.9) and twice as high for women with serious mental health morbidity (RR 2.2; 95%CI 1.9, 2.6). This case series of 597 maternities for 558 prisoners pregnant while in prison (of whom 128 gave birth in prison); and 2,031 contemporaneous prisoner control mothers is one of the largest available.

          Conclusions

          Record linkage, properly applied, offers the opportunity to extend knowledge about vulnerable populations not amenable to standard ascertainment. Dedicated linkage authorities now provide linked data for research. The data are not research ready. Perinatal exposures are time-critical and require expert processing to prepare the data for research.

          Electronic supplementary material

          The online version of this article (doi:10.1186/s12874-016-0174-7) contains supplementary material, which is available to authorized users.

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          Most cited references19

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          Administrative record linkage as a tool for public health research.

          Linked administrative databases offer a powerful resource for studying important public health issues. Methods developed and implemented in several jurisdictions across the globe have achieved high-quality linkages for conducting health and social research without compromising confidentiality. Key data available for linkage include health services utilization, population registries, place of residence, family ties, educational outcomes, and use of social services. Linking events for large populations of individuals across disparate sources and over time permits a range of research possibilities, including the capacity to study low-prevalence exposure-disease associations, multiple outcome domains within the same cohort of individuals, service utilization and chronic disease patterns, and life course and transgenerational transmission of health. Limited information on variables such as individual-level socioeconomic status (SES) and social supports is outweighed by strengths that include comprehensive follow-up, continuous data collection, objective measures, and relatively low expense. Ever advancing methodologies and data holdings guarantee that research using linked administrative databases will make increasingly important contributions to public health research.
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            Research use of linked health data--a best practice protocol.

            This article outlines a protocol for facilitating access to administrative data for the purpose of health services research, when these data are sourced from multiple organisations. This approach is designed to promote confidence in the community and among data custodians that there are benefits of linked health information being used and that individual privacy is being rigorously protected. Linked health administration data can provide an unparalleled resource for the monitoring and evaluation of health care services. However, for a number of reasons, these data have not been readily available to researchers. In Australia, an additional barrier to research is the result of health data sets being collected by different levels of government - thus all are not available to any one authority. To improve this situation, a practical blue-print for the conduct of data linkage is proposed. This should provide an approach suitable for most projects that draw large volumes of information from multiple sources, especially when this includes organisations in different jurisdictions. Health data, although widely and diligently collected, continue to be under-utilised for research and evaluation in most countries. This protocol aims to make these data more easily available to researchers by providing a controlled and secure mechanism that guarantees privacy protection.
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              Quality of data in perinatal population health databases: a systematic review.

              Administrative or population health datasets (PHDS) are increasingly being used for research related to maternal and infant health. However, the accuracy and completeness of the information in the PHDS is important to ensure validity of the results of this research. To compile and review studies that validate the reporting of conditions and procedures related to pregnancy, childbirth, and newborns and provide a tool of reference for researchers. A systematic search was conducted of Medline and EMBASE databases to find studies that validated routinely collected datasets containing diagnoses and procedures related to pregnancy, childbirth, and newborns. To be included datasets had to be validated against a gold standard, such as review of medical records, maternal interview or survey, specialized register, or laboratory data. Sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and/or κ statistic for each diagnosis or procedure code were calculated. Forty-three validation studies were included. Under-enumeration was common, with the level of ascertainment increasing as time from diagnosis/procedure to birth decreased. Most conditions and procedures had high specificities indicating few false positives, and procedures were more accurately reported than diagnoses. Hospital discharge data were generally more accurate than birth data, however identifying cases from more than 1 dataset further increased ascertainment. This comprehensive collection of validation studies summarizing the quality of perinatal population data will be an invaluable resource to all researchers working with PHDS.
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                Author and article information

                Contributors
                l.hilder@unsw.edu.au
                Journal
                BMC Med Res Methodol
                BMC Med Res Methodol
                BMC Medical Research Methodology
                BioMed Central (London )
                1471-2288
                16 June 2016
                16 June 2016
                2016
                : 16
                : 72
                Affiliations
                [ ]National Perinatal Epidemiology and Statistics Unit, University of New South Wales, Sydney, Australia
                [ ]Faculty of Arts and Social Sciences, University of New South Wales, Sydney, Australia
                [ ]College of Medicine, Biology and Environment, Australian National University, Canberra, Australia
                [ ]Faculty of Health University of Technology Sydney, Conjoint School of Women’s and Children’s Health, University of NSW, Sydney, Australia
                Article
                174
                10.1186/s12874-016-0174-7
                4910208
                27312027
                57382613-bbd7-4753-8f2c-09ffc1d31cc0
                © The Author(s). 2016

                Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

                History
                : 19 February 2016
                : 20 May 2016
                Categories
                Research Article
                Custom metadata
                © The Author(s) 2016

                Medicine
                cohort,linked data preparation,exposure status,perinatal,pregnancy,prisoner
                Medicine
                cohort, linked data preparation, exposure status, perinatal, pregnancy, prisoner

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