William C Becker1,2, Robert Heimer3, Catherine M Dormitzer4, Molly Doernberg3, Gail D'Onofrio5, Lauretta E Grau3, Kathryn Hawk5, Hsiu-Ju Lin6, Alex M Secora4, David A Fiellin5,3. 1. Yale School of Medicine, 333 Cedar Street, New Haven, CT, 06510, USA. william.becker@yale.edu. 2. VA Connecticut Healthcare System, 950 Campbell Avenue, Mail Stop 151B, West Haven, CT, 06516, USA. william.becker@yale.edu. 3. Yale School of Public Health, 60 College Street, New Haven, CT, 06510, USA. 4. U.S. Food and Drug Administration, 10903 New Hampshire Avenue, Silver Spring, MD, 20993, USA. 5. Yale School of Medicine, 333 Cedar Street, New Haven, CT, 06510, USA. 6. University of Connecticut School of Social Work, 38 Prospect Street, Hartford, CT, 06103, USA.
Abstract
OBJECTIVE: Describe methods to compile a unified database from disparate state agency datasets linking person-level data on controlled substance prescribing, overdose, and treatment for opioid use disorder in Connecticut. METHODS: A multidisciplinary team of university, state and federal agency experts planned steps to build the data analytic system: stakeholder engagement, articulation of metrics, funding to establish the system, determination of needed data, accessing data and merging, and matching patient-level data. RESULTS: Stakeholder meetings occurred over a 6-month period driving selection of metrics and funding was obtained through a grant from the Food and Drug Administration. Through multi-stakeholder collaborations and memoranda of understanding, we identified relevant data sources, merged them and matched individuals across the merged dataset. The dataset contains information on sociodemographics, treatments and outcomes. Step-by-step processes are presented for dissemination. CONCLUSIONS: Creation of a unified database linking multiple sources in a timely and ongoing fashion may assist other states to monitor the public health impact of controlled substances, identify and implement interventions, and assess their effectiveness.
OBJECTIVE: Describe methods to compile a unified database from disparate state agency datasets linking person-level data on controlled substance prescribing, overdose, and treatment for opioid use disorder in Connecticut. METHODS: A multidisciplinary team of university, state and federal agency experts planned steps to build the data analytic system: stakeholder engagement, articulation of metrics, funding to establish the system, determination of needed data, accessing data and merging, and matching patient-level data. RESULTS: Stakeholder meetings occurred over a 6-month period driving selection of metrics and funding was obtained through a grant from the Food and Drug Administration. Through multi-stakeholder collaborations and memoranda of understanding, we identified relevant data sources, merged them and matched individuals across the merged dataset. The dataset contains information on sociodemographics, treatments and outcomes. Step-by-step processes are presented for dissemination. CONCLUSIONS: Creation of a unified database linking multiple sources in a timely and ongoing fashion may assist other states to monitor the public health impact of controlled substances, identify and implement interventions, and assess their effectiveness.
Entities:
Keywords:
Informatics; Opioid overdose; Opioid use disorder; Surveillance
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