Browsing by Subject "International Classification of Diseases"

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    Measurement-based care using DSM-5 for opioid use disorder: can we make opioid medication treatment more effective?
    (Addiction (Abingdon, England), 2019-08) Marsden, John; Tai, Betty; Ali, Robert; Hu, Lian; Rush, A John; Volkow, Nora

    Context and purpose

    Measurement-based care (MBC) is an evidence-based health-care practice in which indicators of disease are tracked to inform clinical actions, provide feedback to patients and improve outcomes. The current opioid crisis in multiple countries provides a pressing rationale for adopting a basic MBC approach for opioid use disorder (OUD) using DSM-5 to increase treatment retention and effectiveness.

    Proposal

    To stimulate debate, we propose a basic MBC approach using the 11 symptoms of OUD (DSM-5) to inform the delivery of medications for opioid use disorder (MOUD; including methadone, buprenorphine and naltrexone) and their evaluation in office-based primary care and specialist clinics. Key features of a basic MBC approach for OUD using DSM-5 are described, with an illustration of how clinical actions are guided and outcomes communicated. For core treatment tasks, we propose that craving and drug use response to MOUD should be assessed after 2 weeks, and OUD remission status should be evaluated at 3, 6 and 12 months (and exit from MOUD treatment) and beyond. Each of the 11 DSM-5 symptoms of OUD should be discussed with the patient to develop a case formulation and guide selection of adjunctive psychological interventions, supplemented with information on substance use, and optionally extended with information from other clinical instruments. A patient-reported outcome measure should be recorded and discussed at each remission assessment.

    Conclusions

    MBC can be used to tailor and adapt MOUD treatment to increase engagement, retention and effectiveness. MBC practice principles can help promote patient-centred care in OUD, personalized addiction therapeutics and facilitate communication of outcomes.
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    Substance use and mental diagnoses among adults with and without type 2 diabetes: Results from electronic health records data.
    (Drug and alcohol dependence, 2015-11) Wu, Li-Tzy; Ghitza, Udi E; Batch, Bryan C; Pencina, Michael J; Rojas, Leoncio Flavio; Goldstein, Benjamin A; Schibler, Tony; Dunham, Ashley A; Rusincovitch, Shelley; Brady, Kathleen T
    BACKGROUND:Comorbid diabetes and substance use diagnoses (SUD) represent a hazardous combination, both in terms of healthcare cost and morbidity. To date, there is limited information about the association of SUD and related mental disorders with type 2 diabetes mellitus (T2DM). METHODS:We examined the associations between T2DM and multiple psychiatric diagnosis categories, with a focus on SUD and related psychiatric comorbidities among adults with T2DM. We analyzed electronic health record (EHR) data on 170,853 unique adults aged ≥18 years from the EHR warehouse of a large academic healthcare system. Logistic regression analyses were conducted to estimate the strength of an association for comorbidities. RESULTS:Overall, 9% of adults (n=16,243) had T2DM. Blacks, Hispanics, Asians, and Native Americans had greater odds of having T2DM than whites. All 10 psychiatric diagnosis categories were more prevalent among adults with T2DM than among those without T2DM. Prevalent diagnoses among adults with T2MD were mood (21.22%), SUD (17.02%: tobacco 13.25%, alcohol 4.00%, drugs 4.22%), and anxiety diagnoses (13.98%). Among adults with T2DM, SUD was positively associated with mood, anxiety, personality, somatic, and schizophrenia diagnoses. CONCLUSIONS:We examined a large diverse sample of individuals and found clinical evidence of SUD and psychiatric comorbidities among adults with T2DM. These results highlight the need to identify feasible collaborative care models for adults with T2DM and SUD related psychiatric comorbidities, particularly in primary care settings, that will improve behavioral health and reduce health risk.
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    Validation of ICDPIC software injury severity scores using a large regional trauma registry.
    (Inj Prev, 2015-10) Greene, Nathaniel H; Kernic, Mary A; Vavilala, Monica S; Rivara, Frederick P
    BACKGROUND: Administrative or quality improvement registries may or may not contain the elements needed for investigations by trauma researchers. International Classification of Diseases Program for Injury Categorisation (ICDPIC), a statistical program available through Stata, is a powerful tool that can extract injury severity scores from ICD-9-CM codes. We conducted a validation study for use of the ICDPIC in trauma research. METHODS: We conducted a retrospective cohort validation study of 40,418 patients with injury using a large regional trauma registry. ICDPIC-generated AIS scores for each body region were compared with trauma registry AIS scores (gold standard) in adult and paediatric populations. A separate analysis was conducted among patients with traumatic brain injury (TBI) comparing the ICDPIC tool with ICD-9-CM embedded severity codes. Performance in characterising overall injury severity, by the ISS, was also assessed. RESULTS: The ICDPIC tool generated substantial correlations in thoracic and abdominal trauma (weighted κ 0.87-0.92), and in head and neck trauma (weighted κ 0.76-0.83). The ICDPIC tool captured TBI severity better than ICD-9-CM code embedded severity and offered the advantage of generating a severity value for every patient (rather than having missing data). Its ability to produce an accurate severity score was consistent within each body region as well as overall. CONCLUSIONS: The ICDPIC tool performs well in classifying injury severity and is superior to ICD-9-CM embedded severity for TBI. Use of ICDPIC demonstrates substantial efficiency and may be a preferred tool in determining injury severity for large trauma datasets, provided researchers understand its limitations and take caution when examining smaller trauma datasets.