Variation in Clinical Characteristics and Longitudinal Outcomes in Individuals with Opioid Use Disorder Diagnosis Codes.


Journal

Journal of general internal medicine
ISSN: 1525-1497
Titre abrégé: J Gen Intern Med
Pays: United States
ID NLM: 8605834

Informations de publication

Date de publication:
02 2023
Historique:
received: 03 03 2022
accepted: 28 06 2022
pmc-release: 01 02 2024
pubmed: 13 7 2022
medline: 3 3 2023
entrez: 12 7 2022
Statut: ppublish

Résumé

Patterns of opioid use vary, including prescribed use without aberrancy, limited aberrant use, and potential opioid use disorder (OUD). In clinical practice, similar opioid-related International Classification of Disease (ICD) codes are applied across this spectrum, limiting understanding of how groups vary by sociodemographic factors, comorbidities, and long-term risks. (1) Examine how Veterans assigned opioid abuse/dependence ICD codes vary at diagnosis and with respect to long-term risks. (2) Determine whether those with limited aberrant use share more similarities to likely OUD vs those using opioids as prescribed. Longitudinal observational cohort study. National sample of Veterans categorized as having (1) likely OUD, (2) limited aberrant opioid use, or (3) prescribed, non-aberrant use based upon enhanced medical chart review. Comparison of sociodemographic and clinical factors at diagnosis and rates of age-adjusted mortality, non-fatal opioid overdose, and hospitalization after diagnosis. An exploratory machine learning analysis investigated how closely those with limited aberrant use resembled those with likely OUD. Veterans (n = 483) were categorized as likely OUD (62.1%), limited aberrant use (17.8%), and prescribed, non-aberrant use (20.1%). Age, proportion experiencing homelessness, chronic pain, anxiety disorders, and non-opioid substance use disorders differed by group. All-cause mortality was high (44.2 per 1000 person-years (95% CI 33.9, 56.7)). Hospitalization rates per 1000 person-years were highest in the likely OUD group (831.5 (95% CI 771.0, 895.5)), compared to limited aberrant use (739.8 (95% CI 637.1, 854.4)) and prescribed, non-aberrant use (411.9 (95% CI 342.6, 490.4). The exploratory analysis reclassified 29.1% of those with limited aberrant use as having likely OUD with high confidence. Veterans assigned opioid abuse/dependence ICD codes are heterogeneous and face variable long-term risks. Limited aberrant use confers increased risk compared to no aberrant use, and some may already have OUD. Findings warrant future investigation of this understudied population.

Sections du résumé

BACKGROUND
Patterns of opioid use vary, including prescribed use without aberrancy, limited aberrant use, and potential opioid use disorder (OUD). In clinical practice, similar opioid-related International Classification of Disease (ICD) codes are applied across this spectrum, limiting understanding of how groups vary by sociodemographic factors, comorbidities, and long-term risks.
OBJECTIVE
(1) Examine how Veterans assigned opioid abuse/dependence ICD codes vary at diagnosis and with respect to long-term risks. (2) Determine whether those with limited aberrant use share more similarities to likely OUD vs those using opioids as prescribed.
DESIGN
Longitudinal observational cohort study.
PARTICIPANTS
National sample of Veterans categorized as having (1) likely OUD, (2) limited aberrant opioid use, or (3) prescribed, non-aberrant use based upon enhanced medical chart review.
MAIN MEASURES
Comparison of sociodemographic and clinical factors at diagnosis and rates of age-adjusted mortality, non-fatal opioid overdose, and hospitalization after diagnosis. An exploratory machine learning analysis investigated how closely those with limited aberrant use resembled those with likely OUD.
KEY RESULTS
Veterans (n = 483) were categorized as likely OUD (62.1%), limited aberrant use (17.8%), and prescribed, non-aberrant use (20.1%). Age, proportion experiencing homelessness, chronic pain, anxiety disorders, and non-opioid substance use disorders differed by group. All-cause mortality was high (44.2 per 1000 person-years (95% CI 33.9, 56.7)). Hospitalization rates per 1000 person-years were highest in the likely OUD group (831.5 (95% CI 771.0, 895.5)), compared to limited aberrant use (739.8 (95% CI 637.1, 854.4)) and prescribed, non-aberrant use (411.9 (95% CI 342.6, 490.4). The exploratory analysis reclassified 29.1% of those with limited aberrant use as having likely OUD with high confidence.
CONCLUSIONS
Veterans assigned opioid abuse/dependence ICD codes are heterogeneous and face variable long-term risks. Limited aberrant use confers increased risk compared to no aberrant use, and some may already have OUD. Findings warrant future investigation of this understudied population.

Identifiants

pubmed: 35819683
doi: 10.1007/s11606-022-07732-w
pii: 10.1007/s11606-022-07732-w
pmc: PMC9971398
doi:

Substances chimiques

Analgesics, Opioid 0

Types de publication

Observational Study Journal Article Research Support, Non-U.S. Gov't Research Support, N.I.H., Extramural Research Support, U.S. Gov't, Non-P.H.S.

Langues

eng

Sous-ensembles de citation

IM

Pagination

699-706

Subventions

Organisme : HSRD VA
ID : SDR 21-107
Pays : United States
Organisme : NIA NIH HHS
ID : AG062043
Pays : United States
Organisme : NIDA NIH HHS
ID : 5K23DA047475-02
Pays : United States
Organisme : HSRD VA
ID : CDA 18-008
Pays : United States
Organisme : HSRD VA
ID : SFT 21-101
Pays : United States
Organisme : HSRD VA
ID : IK2 HX002612
Pays : United States
Organisme : NIDA NIH HHS
ID : K23 DA047475
Pays : United States

Informations de copyright

© 2022. This is a U.S. Government work and not under copyright protection in the US; foreign copyright protection may apply.

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Auteurs

Victoria D Powell (VD)

Palliative Care Program, Division of Geriatric and Palliative Medicine, University of Michigan, Ann Arbor, MI, USA. powellvd@med.umich.edu.
Geriatrics Research, Education, and Clinical Center, LTC Charles S. Kettles VA Medical Center, Ann Arbor, MI, USA. powellvd@med.umich.edu.

Colin Macleod (C)

Division of General Medicine, Department of Internal Medicine, University of Michigan, Ann Arbor, MI, USA.

Jeremy Sussman (J)

Division of General Medicine, Department of Internal Medicine, University of Michigan, Ann Arbor, MI, USA.
VA Center for Clinical Management Research (CCMR), VA Ann Arbor Healthcare System, Ann Arbor, MI, USA.

Lewei A Lin (LA)

VA Center for Clinical Management Research (CCMR), VA Ann Arbor Healthcare System, Ann Arbor, MI, USA.
Addiction Center, Department of Psychiatry, University of Michigan, Ann Arbor, MI, USA.

Amy S B Bohnert (ASB)

VA Center for Clinical Management Research (CCMR), VA Ann Arbor Healthcare System, Ann Arbor, MI, USA.
Department of Anesthesiology, University of Michigan, Ann Arbor, MI, USA.

Pooja Lagisetty (P)

Division of General Medicine, Department of Internal Medicine, University of Michigan, Ann Arbor, MI, USA.
VA Center for Clinical Management Research (CCMR), VA Ann Arbor Healthcare System, Ann Arbor, MI, USA.

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