4.2 Article

The importance of identification when measuring performance in addiction treatment

Journal

SUBSTANCE ABUSE
Volume 40, Issue 3, Pages 263-267

Publisher

ROUTLEDGE JOURNALS, TAYLOR & FRANCIS LTD
DOI: 10.1080/08897077.2019.1580240

Keywords

Engagement; identification; Medicaid; performance; quality

Funding

  1. Substance Abuse and Mental Health Services Administration (SAMHSA), Center for Financing Reform and Innovation [HHSS283200700029I/HHSS28342002T]
  2. SAMHSA IDIQ Prime Contract [HHSS283200700029I]
  3. National Institute on Drug Abuse (NIDA), Center to Improve System Performance of Substance Use Disorder Treatment [P30 DA035772]

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Background: Identifying and effectively treating individuals with substance use disorders (SUDs) is an important priority for state Medicaid programs, given the enormous toll that SUDs take on individuals, their families, and their communities. In this paper, we describe how the Healthcare Effectiveness Data and Information Set (HEDIS) measure Identification of Alcohol and Other Drug Services can be used, along with eligible population prevalence rates, to expand states' ability to track how well their Medicaid programs identify enrollees with SUDs and link them with treatment (measured by initiation and engagement performance measures). Methods: We use the 2009 Medicaid MAX data on utilization and enrollment along with information from the National Survey of Drug Use and Health (NSDUH) to obtain state-level estimates of alcohol and drug abuse and dependence among Medicaid beneficiaries for 7 illustrative states. We calculate identification, initiation, and engagement measures using specifications from the National Committee on Quality Assurance (NCQA). Results: NSDUH data showed that the eligible population prevalence rate (the average rate of alcohol or drug abuse or dependence) among the 7 states was 10.0%, whereas the average identification rate was 2.9%. The gap between the prevalence and identification rates ranged from 5.1% to 11.0% among the 7 states. The initiation rates ranged from 36.9% to 57.1%. The states' engagement rates ranged from 11.8% to 31.1%, although rates differ by age, gender, and race/ethnicity in some states. Conclusion: Including identification along with initiation and engagement measures allows states to determine how well they are performing in a more complete spectrum from need, to recognition and documentation of enrollees with SUDs, to initiation of treatment, to continuation of early treatment.

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