Drug treatment programs know who they serve, but can only estimate who they do not serve;the inability to accurately measure unmet treatment need, especially among women of reproductive age, is a key barrier to developing interventions to reduce drug-related health consequences for women, their children, and society. This proposal describes an innovative collaboration to link two existing independent state data systems to create a new, unique longitudinal, epidemiologic database that combines drug treatment data with hospital utilization and health outcomes data, to broadly identify drug-related problems and the prevalence of unmet treatment need, and to track drug-related health outcomes among Massachusetts women of reproductive age and their children. For the first time, women in need of drug treatment services who did not receive them will be individually identifiable, allowing for better estimation and description of unmet need. The new linked data will permit assessment of disparities among women with met and unmet treatment need through multiple sources of data, including using a tested algorithm to identify drug diagnoses in hospital data. Moreover, the linked data will allow the examination of subsequent health outcomes among women ages 15-49, and birth outcomes among their children. The two data sources to be linked are: (1) the population-based MA Pregnancy to Early Life Longitudinal (PELL) data system that includes vital records (births, fetal deaths and deaths);hospital discharge, observational stay, and emergency department visit records;and the MA Birth Defects Registry;and (2) the MA Bureau of Substance Abuse Services (BSAS) treatment data system that contains treatment records for over 25,000 annual admissions of women of reproductive age to BSAS-funded substance abuse treatment facilities. The three broad study aims are: 1. Link PELL data to the MDPH-BSAS Treatment Database and verify linkages. 2. Develop and pilot methods a) among all MA women of reproductive age, identify women with drug abuse or dependence (2002-2007), assess unmet need for treatment services, and characterize disparities in treatment use;b) among MA women who had deliveries (2003-2006), describe the pattern of identification and treatment of drug problems in the periods before, during, and after pregnancy, assess unmet need for drug treatment by timing, and characterize pregnancy outcomes;and c) among MA women with an identified drug problem develop preliminary multivariate models with predisposing and enabling factors predicting receipt of treatment, and, among women who delivered, risk for prematurity. 3. Develop an R01 proposal to describe the impact of substance abuse and treatment on women's and children's health, based on bivariate and multivariate analyses proposed for this study and a tandem NIH/NIAAA study.
This innovative public-private collaboration links two existing independent state data systems (BSAS and PELL) to create a new, unique longitudinal and epidemiologic database that combines drug treatment data with hospital utilization and health outcomes data, to broadly identify drug-related problems and the prevalence of unmet treatment need, and to track drug-related health and birth outcomes among Massachusetts women of reproductive age. For the first time, women in need of drug treatment services who did not receive them will be individually identifiable, allowing for accurate estimation and description of unmet need, a critical step to improve state drug treatment programs for women of reproductive age.
|Kotelchuck, Milton; Cheng, Erika R; Belanoff, Candice et al. (2017) The Prevalence and Impact of Substance Use Disorder and Treatment on Maternal Obstetric Experiences and Birth Outcomes Among Singleton Deliveries in Massachusetts. Matern Child Health J 21:893-902|
|Derrington, Taletha Mae; Bernstein, Judith; Belanoff, Candice et al. (2015) Refining Measurement of Substance Use Disorders Among Women of Child-Bearing Age Using Hospital Records: The Development of the Explicit-Mention Substance Abuse Need for Treatment in Women (EMSANT-W) Algorithm. Matern Child Health J 19:2168-78|
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