Literature DB >> 30657438

The prevalence of Healthcare Effectiveness Data and Information Set (HEDIS) initiation and engagement in treatment among patients with cannabis use disorders in 7 US health systems.

Gwen T Lapham1,2, Cynthia I Campbell3, Bobbi Jo H Yarborough4, Rulin C Hechter5, Brian K Ahmedani6, Irina V Haller7, Andrea H Kline-Simon3, Derek D Satre3,8, Amy M Loree6, Constance Weisner3,8, Ingrid A Binswanger9,10,11.   

Abstract

Background: Cannabis use disorders (CUDs) have increased with more individuals using cannabis, yet few receive treatment. Health systems have adopted the Healthcare Effectiveness Data and Information Set (HEDIS) quality measures of initiation and engagement in alcohol and other drug (AOD) dependence treatment, but little is known about the performance of these among patients with CUDs.
Methods: This cohort study utilized electronic health records and claims data from 7 health care systems to identify patients with documentation of a new index CUD diagnosis (no AOD diagnosis ≤60 days prior) from International Classification of Diseases, Ninth revision, codes (October 1, 2014, to August 31, 2015). The adjusted prevalence of each outcome (initiation, engagement, and a composite of both) was estimated from generalized linear regression models, across index identification settings (inpatient, emergency department, primary care, addiction treatment, and mental health/psychiatry), AOD comorbidity (patients with CUD only and CUD plus other AOD diagnoses), and patient characteristics.
Results: Among 15,202 patients with an index CUD diagnosis, 30.0% (95% confidence interval [CI]: 29.2-30.7%) initiated, 6.9% (95% CI: 6.2-7.7%) engaged among initiated, and 2.1% (95% CI: 1.9-2.3%) overall both initiated and engaged in treatment. The adjusted prevalence of outcomes varied across index identification settings and was highest among patients diagnosed in addiction treatment, with 25.0% (95% CI: 22.5-27.6%) initiated, 40.9% (95% CI: 34.8-47.0%) engaged, and 12.5% (95% CI: 10.0-15.1%) initiated and engaged. The adjusted prevalence of each outcome was generally highest among patients with CUD plus other AOD diagnosis at index diagnosis compared with those with CUD only, overall and across index identification settings, and was lowest among uninsured and older patients.
Conclusion: Among patients with a new CUD diagnosis, the proportion meeting HEDIS criteria for initiation and/or engagement in AOD treatment was low and demonstrated variation across index diagnosis settings, AOD comorbidity, and patient characteristics, pointing to opportunities for improvement.

Entities:  

Keywords:  Cannabis; comorbidity; health services research; quality indicators; substance use disorder; treatment

Year:  2019        PMID: 30657438      PMCID: PMC6639163          DOI: 10.1080/08897077.2018.1544964

Source DB:  PubMed          Journal:  Subst Abus        ISSN: 0889-7077            Impact factor:   3.716


  38 in total

1.  What's the Risk? A simple approach for estimating adjusted risk measures from nonlinear models including logistic regression.

Authors:  Lawrence C Kleinman; Edward C Norton
Journal:  Health Serv Res       Date:  2008-09-11       Impact factor: 3.402

2.  Lessons from five states: public sector use of the Washington Circle performance measures.

Authors:  Deborah W Garnick; Margaret T Lee; Constance Horgan; Andrea Acevedo; Michael Botticelli; Spencer Clark; Steven Davis; Robert Gallati; Karin Haberlin; Andrew Hanchett; Dawn Lambert-Wacey; Tracy Leeper; James Siemianowski; Minakshi Tikoo
Journal:  J Subst Abuse Treat       Date:  2011-01-22

3.  Practical considerations on the use of the Charlson comorbidity index with administrative data bases.

Authors:  W D'Hoore; A Bouckaert; C Tilquin
Journal:  J Clin Epidemiol       Date:  1996-12       Impact factor: 6.437

4.  DSM-5 cannabis use disorder, substance use and DSM-5 specific substance-use disorders: Evaluating comorbidity in a population-based sample.

Authors:  Amie C Hayley; Con Stough; Luke A Downey
Journal:  Eur Neuropsychopharmacol       Date:  2017-06-27       Impact factor: 4.600

5.  DSM-5 cannabis use disorder in the National Epidemiologic Survey on Alcohol and Related Conditions-III: Gender-specific profiles.

Authors:  Bradley T Kerridge; Roger Pickering; Patricia Chou; Tulshi D Saha; Deborah S Hasin
Journal:  Addict Behav       Date:  2017-07-14       Impact factor: 3.913

Review 6.  DSM-5 criteria for substance use disorders: recommendations and rationale.

Authors:  Deborah S Hasin; Charles P O'Brien; Marc Auriacombe; Guilherme Borges; Kathleen Bucholz; Alan Budney; Wilson M Compton; Thomas Crowley; Walter Ling; Nancy M Petry; Marc Schuckit; Bridget F Grant
Journal:  Am J Psychiatry       Date:  2013-08       Impact factor: 18.112

Review 7.  Pharmacotherapies for cannabis dependence.

Authors:  Kushani Marshall; Linda Gowing; Robert Ali; Bernard Le Foll
Journal:  Cochrane Database Syst Rev       Date:  2014-12-17

8.  Criminal justice outcomes after engagement in outpatient substance abuse treatment.

Authors:  Deborah W Garnick; Constance M Horgan; Andrea Acevedo; Margaret T Lee; Lee Panas; Grant A Ritter; Robert Dunigan; Alfred Bidorini; Kevin Campbell; Karin Haberlin; Alice Huber; Dawn Lambert-Wacey; Tracy Leeper; Mark Reynolds; David Wright
Journal:  J Subst Abuse Treat       Date:  2013-10-14

9.  Facilitators and barriers in treatment seeking for cannabis dependence.

Authors:  Peggy van der Pol; Nienke Liebregts; Ron de Graaf; Dirk J Korf; Wim van den Brink; Margriet van Laar
Journal:  Drug Alcohol Depend       Date:  2013-08-26       Impact factor: 4.492

10.  Adapting Washington Circle performance measures for public sector substance abuse treatment systems.

Authors:  Deborah W Garnick; Margaret T Lee; Constance M Horgan; Andrea Acevedo
Journal:  J Subst Abuse Treat       Date:  2008-08-21
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  2 in total

1.  Psychoactive Drugs Like Cannabis -Induce Hypodopaminergic Anhedonia and Neuropsychological Dysfunction in Humans: Putative Induction of Dopamine Homeostasis via Coupling of Genetic Addiction Risk Severity (GARS) testing and Precision Pro-dopamine Regulation (KB220).

Authors:  Kenneth Blum; Joseph Morgan; Jean Lud Cadet; David Baron; Paul R Carney; Jag Khalsa; Rajendra D Badgaiyan; Mark S Gold
Journal:  Neurology (ECronicon)       Date:  2021-03-31

2.  Substance Use-related Emergency Department Visits and Resource Utilization.

Authors:  Weiwei Beckerleg; Joel Hudgins
Journal:  West J Emerg Med       Date:  2022-02-28
  2 in total

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