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Common data elements for substance use disorders in electronic health records: the NIDA Clinical Trials Network experience
Author(s) -
Ghitza Udi E.,
GoreLangton Robert E.,
Lindblad Robert,
Shide David,
Subramaniam Geetha,
Tai Betty
Publication year - 2013
Publication title -
addiction
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.424
H-Index - 193
eISSN - 1360-0443
pISSN - 0965-2140
DOI - 10.1111/j.1360-0443.2012.03876.x
Subject(s) - reimbursement , medicine , health care , referral , medicaid , clinical decision support system , intervention (counseling) , brief intervention , health information technology , family medicine , nursing , medical emergency , decision support system , data mining , computer science , economics , economic growth
Aims  Electronic health records (EHRs) are essential in improving quality and enhancing efficiency of health‐care delivery. By 2015, medical care receiving service reimbursement from US Centers for Medicare and Medicaid Services (CMS) must show ‘meaningful use’ of EHRs. Substance use disorders (SUD) are grossly under‐detected and under‐treated in current US medical care settings. Hence, an urgent need exists for improved identification of and clinical intervention for SUD in medical settings. The National Institute on Drug Abuse Clinical Trials Network (NIDA CTN) has leveraged its infrastructure and expertise and brought relevant stakeholders together to develop consensus on brief screening and initial assessment tools for SUD in general medical settings, with the objective of incorporation into US EHRs. Methods  Stakeholders were identified and queried for input and consensus on validated screening and assessment for SUD in general medical settings to develop common data elements to serve as shared resources for EHRs on screening, brief intervention and referral to treatment (SBIRT), with the intent of supporting interoperability and data exchange in a developing Nationwide Health Information Network. Results  Through consensus of input from stakeholders, a validated screening and brief assessment instrument, supported by Clinical Decision Support tools, was chosen to be used at out‐patient general medical settings. Conclusions  The creation and adoption of a core set of validated common data elements and the inclusion of such consensus‐based data elements for general medical settings will enable the integration of SUD treatment within mainstream health care, and support the adoption and ‘meaningful use’ of the US Office of the National Coordinator for Health Information Technology (ONC)‐certified EHRs, as well as CMS reimbursement.

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