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OBJECTIVE: The Centers for Disease Control and Prevention's 2022 Clinical Practice Guideline for Prescribing Opioids for Pain cautioned that inflexible opioid prescription duration limits may harm patients. Information about the relationship between initial opioid prescription duration and a subsequent refill could inform prescribing policies and practices to optimize patient outcomes. We assessed the association between initial opioid duration and an opioid refill prescription. METHODS: We conducted a retrospective cohort study of adults ≥19 years of age in 10 US health systems between 2013 and 2018 from outpatient care with a diagnosis for back pain without radiculopathy, back pain with radiculopathy, neck pain, joint pain, tendonitis/bursitis, mild musculoskeletal pain, severe musculoskeletal pain, urinary calculus, or headache. Generalized additive models were used to estimate the association between opioid days' supply and a refill prescription. RESULTS: Overall, 220,797 patients were prescribed opioid analgesics upon an outpatient visit for pain. Nearly a quarter (23.5%) of the cohort received an opioid refill prescription during follow-up. The likelihood of a refill generally increased with initial duration for most pain diagnoses. About 1 to 3 fewer patients would receive a refill within 3 months for every 100 patients initially prescribed 3 vs. 7 days of opioids for most pain diagnoses. The lowest likelihood of refill was for a 1-day supply for all pain diagnoses, except for severe musculoskeletal pain (9 days' supply) and headache (3-4 days' supply). CONCLUSIONS: Long-term prescription opioid use increased modestly with initial opioid prescription duration for most but not all pain diagnoses examined.
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Dor Musculoesquelética , Radiculopatia , Adulto , Humanos , Analgésicos Opioides/uso terapêutico , Estudos Retrospectivos , Pacientes Ambulatoriais , Dor Musculoesquelética/diagnóstico , Dor Musculoesquelética/tratamento farmacológico , Prescrições , Cefaleia , Padrões de Prática Médica , Dor nas CostasRESUMO
BACKGROUND: Given significant risks associated with long-term prescription opioid use, there is a need for non-pharmacological interventions for treating chronic pain. Activating patients to manage chronic pain has the potential to improve health outcomes. The ACTIVATE study was designed to evaluate the effectiveness of a 4-session patient activation intervention in primary care for patients on long-term opioid therapy. METHODS: The two-arm, pragmatic, randomized trial was conducted in two primary care clinics in an integrated health system from June 2015-August 2018. Consenting participants were randomized to the intervention (n = 189) or usual care (n = 187). Participants completed online and interviewer-administered surveys at baseline, 6- and 12- months follow-up. Prescription opioid use was extracted from the EHR. The primary outcome was patient activation assessed by the Patient Activation Measure (PAM). Secondary outcomes included mood, function, overall health, non-pharmacologic pain management strategies, and patient portal use. We conducted a repeated measure analysis and reported between-group differences at 12 months. RESULTS: At 12 months, the intervention and usual care arms had similar PAM scores. However, compared to usual care at 12 months, the intervention arm demonstrated: less moderate/severe depression (odds ratio [OR] = 0.40, 95%CI 0.18-0.87); higher overall health (OR = 3.14, 95%CI 1.64-6.01); greater use of the patient portal's health/wellness resources (OR = 2.50, 95%CI 1.42-4.40) and lab/immunization history (OR = 2.70, 95%CI 1.29-5.65); and greater use of meditation (OR = 2.72; 95%CI 1.61-4.58) and exercise/physical therapy (OR = 2.24, 95%CI 1.29-3.88). At 12 months, the intervention arm had a higher physical health measure (mean difference 1.63; 95%CI: 0.27-2.98). CONCLUSION: This trial evaluated the effectiveness of a primary care intervention in improving patient activation and patient-reported outcomes among adults with chronic pain on long-term opioid therapy. Despite a lack of improvement in patient activation, a brief intervention in primary care can improve outcomes such as depression, overall health, non-pharmacologic pain management, and engagement with the health system. TRIAL REGISTRATION: The study was registered on 10/27/14 on ClinicalTrials.gov (NCT02290223).
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Dor Crônica , Transtornos Relacionados ao Uso de Opioides , Adulto , Humanos , Dor Crônica/tratamento farmacológico , Analgésicos Opioides/uso terapêutico , Participação do Paciente , Manejo da Dor , Transtornos Relacionados ao Uso de Opioides/terapia , Atenção Primária à SaúdeRESUMO
BACKGROUND: In response to the opioid crisis in the United States, population-level prescribing of opioids has been decreasing; there are concerns, however, that dose reductions are related to potential adverse events. OBJECTIVE: Examine associations between opioid dose reductions and risk of 1-month potential adverse events (emergency department (ED) visits, opioid overdose, benzodiazepine prescription fill, all-cause mortality). DESIGN: This observational cohort study used electronic health record and claims data from eight United States health systems in a prescription opioid registry (Clinical Trials Network-0084). All opioid fills (excluding buprenorphine) between 1/1/2012 and 12/31/2018 were used to identify baseline periods with mean morphine milligram equivalents daily dose of ≥ 50 during six consecutive months. PATIENTS: We identified 60,040 non-cancer patients with ≥ one 2-month dose reduction period (600,234 unique dose reduction periods). MAIN MEASURES: Analyses examined associations between dose reduction levels (1- < 15%, 15- < 30%, 30- < 100%, 100% over 2 months) and potential adverse events in the month following a dose reduction using logistic regression analysis, adjusting for patient characteristics. KEY RESULTS: Overall, dose reduction periods involved mean reductions of 18.7%. Compared to reductions of 1- < 15%, dose reductions of 30- < 100% were associated with higher odds of ED visits (OR 1.14, 95% CI 1.10, 1.17), opioid overdose (OR 1.41, 95% CI 1.09-1.81), and all-cause mortality (OR 1.39, 95% CI 1.16-1.67), but lower odds of a benzodiazepine fill (OR 0.83, 95% CI 0.81-0.85). Dose reductions of 15- < 30%, compared to 1- < 15%, were associated with higher odds of ED visits (OR 1.08, 95% CI 1.05-1.11) and lower odds of a benzodiazepine fill (OR 0.93, 95% CI 0.92-0.95), but were not associated with opioid overdose and all-cause mortality. CONCLUSIONS: Larger reductions for patients on opioid therapy may raise risk of potential adverse events in the month after reduction and should be carefully monitored.
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INTRODUCTION: The relationship between tobacco smoking status and SARS-CoV-2 infection and coronavirus disease 2019 (COVID-19) severity is highly debated. We conducted a retrospective cohort study ofâ >2.4 million adults in a large healthcare system to evaluate whether smoking is associated with SARS-CoV-2 infection and disease severity. AIMS AND METHODS: This retrospective cohort study of 2,427,293 adults in KPNC from March 5, 2020 (baseline) to December 31, 2020 (pre-vaccine) included smoking status (current, former, never), socio-demographics, and comorbidities from the electronic health record. SARS-CoV-2 infection (identified by a positive PCR test) and COVID-19 severity (hospitalization, ICU admission or deathâ ≤â 30 days of COVID-19 diagnosis) were estimated in time-to-event analyses using Cox proportional hazard regression models adjusting for covariates. Secondary analyses examined COVID-19 severity among patients with COVID-19 using logistic regression. RESULTS: During the study, 44,270 patients had SARS-CoV-2 infection. Current smoking was associated with lower adjusted rates of SARS-CoV-2 infection (aHRâ =â 0.64 95% CI: 0.61-0.67), COVID-19-related hospitalization (aHRâ =â 0.48 95% CI: 0.40-0.58), ICU admission (aHRâ =â 0.62 95% CI: 0.42-0.87), and death (aHRâ =â 0.52 95% CI: 0.27-0.89) than never-smoking. Former smoking was associated with a lower adjusted rate of SARS-CoV-2 infection (aHRâ =â 0.96 95% CI: 0.94-0.99) and higher adjusted rates of hospitalization (aHRâ =â 1.10 95% CI: 1.03-1.08) and death (aHRâ =â 1.32 95% CI: 1.11-1.56) than never-smoking. Logistic regression analyses among patients with COVID-19 found lower odds of hospitalization for current versus never-smoking and higher odds of hospitalization and death for former versus never-smoking. CONCLUSIONS: In the largest US study to date on smoking and COVID-19, current and former smoking showed lower risk of SARS-CoV-2 infection than never-smoking, while a history of smoking was associated with higher risk of severe COVID-19. IMPLICATIONS: In this cohort study of 2.4 million adults, adjusting for socio-demographics and medical comorbidities, current tobacco smoking was associated with a lower risk of both SARS-CoV-2 infection and severe COVID-19 illness compared to never-smoking. A history of smoking was associated with a slightly lower risk of SARS-CoV-2 infection and a modestly higher risk of severe COVID-19 illness compared to never-smoking. The lower observed COVID-19 risk for current versus never-smoking deserves further investigation. Results support prioritizing individuals with smoking-related comorbidities for vaccine outreach and treatments as they become available.
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COVID-19 , Prestação Integrada de Cuidados de Saúde , Humanos , Adulto , Teste para COVID-19 , Estudos de Coortes , Estudos Retrospectivos , COVID-19/epidemiologia , SARS-CoV-2 , Fumar Tabaco , California/epidemiologia , Gravidade do Paciente , HospitalizaçãoRESUMO
BACKGROUND: Multiple digital data sources can capture moment-to-moment information to advance a robust understanding of opioid use disorder (OUD) behavior, ultimately creating a digital phenotype for each patient. This information can lead to individualized interventions to improve treatment for OUD. OBJECTIVE: The aim is to examine patient engagement with multiple digital phenotyping methods among patients receiving buprenorphine medication for OUD. METHODS: The study enrolled 65 patients receiving buprenorphine for OUD between June 2020 and January 2021 from 4 addiction medicine programs in an integrated health care delivery system in Northern California. Ecological momentary assessment (EMA), sensor data, and social media data were collected by smartphone, smartwatch, and social media platforms over a 12-week period. Primary engagement outcomes were meeting measures of minimum phone carry (≥8 hours per day) and watch wear (≥18 hours per day) criteria, EMA response rates, social media consent rate, and data sparsity. Descriptive analyses, bivariate, and trend tests were performed. RESULTS: The participants' average age was 37 years, 47% of them were female, and 71% of them were White. On average, participants met phone carrying criteria on 94% of study days, met watch wearing criteria on 74% of days, and wore the watch to sleep on 77% of days. The mean EMA response rate was 70%, declining from 83% to 56% from week 1 to week 12. Among participants with social media accounts, 88% of them consented to providing data; of them, 55% of Facebook, 54% of Instagram, and 57% of Twitter participants provided data. The amount of social media data available varied widely across participants. No differences by age, sex, race, or ethnicity were observed for any outcomes. CONCLUSIONS: To our knowledge, this is the first study to capture these 3 digital data sources in this clinical population. Our findings demonstrate that patients receiving buprenorphine treatment for OUD had generally high engagement with multiple digital phenotyping data sources, but this was more limited for the social media data. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR2-10.3389/fpsyt.2022.871916.
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Buprenorfina , Transtornos Relacionados ao Uso de Opioides , Feminino , Humanos , Masculino , Participação do Paciente , Buprenorfina/uso terapêutico , Avaliação Momentânea Ecológica , Etnicidade , Transtornos Relacionados ao Uso de Opioides/tratamento farmacológicoRESUMO
BACKGROUND: Despite high prevalence of polysubstance use, recent data on concurrent alcohol use in patients with specific substance use disorders (SUDs) are lacking. OBJECTIVE: To examine associations between specific SUDs and alcohol consumption levels. METHODS: Using electronic health record data, we conducted a cross-sectional study of 2,720,231 primary care adults screened for alcohol use between 2014 and 2017 at Kaiser Permanente Northern California. Alcohol consumption levels were categorized as no reported use, low-risk use, and unhealthy use (exceeding daily, weekly, or both recommended drinking limits). Using multinomial logistic regression, and adjusting for sociodemographic and health characteristics, we examined the odds of reporting each alcohol consumption level in patients with a prior-year SUD diagnosis (alcohol, cannabis, cocaine, inhalant, opioid, sedative/anxiolytic, stimulant, other drug, nicotine, any SUD except nicotine) compared to those without. RESULTS: The sample was 52.9% female, 48.1% White; the mean age was 46 years (SD = 18). Patients with SUDs were less likely to report low-risk alcohol use relative to no use compared with patients without SUDs. Patients with alcohol or nicotine use disorder had higher odds of reporting unhealthy alcohol use relative to no use; however, patients with all other SUDs (except cocaine) had lower odds. Among patients who reported any alcohol use (n = 861,427), patients with SUDs (except opioid) had higher odds of exceeding recommended limits than those without. CONCLUSION: The associations of unhealthy alcohol use and SUDs suggest that screening for both alcohol and drug use in primary care presents a crucial opportunity to prevent and treat SUDs early.
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Alcoolismo , Cocaína , Transtornos Relacionados ao Uso de Substâncias , Adulto , Alcoolismo/diagnóstico , Alcoolismo/epidemiologia , Analgésicos Opioides , Estudos Transversais , Feminino , Humanos , Masculino , Pessoa de Meia-Idade , Nicotina , Atenção Primária à Saúde , Transtornos Relacionados ao Uso de Substâncias/diagnóstico , Transtornos Relacionados ao Uso de Substâncias/epidemiologiaRESUMO
BACKGROUND: Pragmatic primary care trials aim to test interventions in "real world" health care settings, but clinics willing and able to participate in trials may not be representative of typical clinics. This analysis compared patients in participating and non-participating clinics from the same health systems at baseline in the PRimary care Opioid Use Disorders treatment (PROUD) trial. METHODS: This observational analysis relied on secondary electronic health record and administrative claims data in 5 of 6 health systems in the PROUD trial. The sample included patients 16-90 years at an eligible primary care visit in the 3 years before randomization. Each system contributed 2 randomized PROUD trial clinics and 4 similarly sized non-trial clinics. We summarized patient characteristics in trial and non-trial clinics in the 2 years before randomization ("baseline"). Using mixed-effect regression models, we compared trial and non-trial clinics on a baseline measure of the primary trial outcome (clinic-level patient-years of opioid use disorder (OUD) treatment, scaled per 10,000 primary care patients seen) and a baseline measure of the secondary trial outcome (patient-level days of acute care utilization among patients with OUD). RESULTS: Patients were generally similar between the 10 trial clinics (n = 248,436) and 20 non-trial clinics (n = 341,130), although trial clinics' patients were slightly younger, more likely to be Hispanic/Latinx, less likely to be white, more likely to have Medicaid/subsidized insurance, and lived in less wealthy neighborhoods. Baseline outcomes did not differ between trial and non-trial clinics: trial clinics had 1.0 more patient-year of OUD treatment per 10,000 patients (95% CI: - 2.9, 5.0) and a 4% higher rate of days of acute care utilization than non-trial clinics (rate ratio: 1.04; 95% CI: 0.76, 1.42). CONCLUSIONS: trial clinics and non-trial clinics were similar regarding most measured patient characteristics, and no differences were observed in baseline measures of trial primary and secondary outcomes. These findings suggest trial clinics were representative of comparably sized clinics within the same health systems. Although results do not reflect generalizability more broadly, this study illustrates an approach to assess representativeness of clinics in future pragmatic primary care trials.
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Seguro , Transtornos Relacionados ao Uso de Opioides , Estados Unidos , Humanos , Transtornos Relacionados ao Uso de Opioides/tratamento farmacológico , Transtornos Relacionados ao Uso de Opioides/complicações , Medicaid , Registros Eletrônicos de Saúde , Atenção Primária à Saúde/métodosRESUMO
Background: Most states have legalized medical cannabis, yet little is known about how medical cannabis use is documented in patients' electronic health records (EHRs). We used natural language processing (NLP) to calculate the prevalence of clinician-documented medical cannabis use among adults in an integrated health system in Washington State where medical and recreational use are legal. Methods: We analyzed EHRs of patients ≥18 years old screened for past-year cannabis use (November 1, 2017-October 31, 2018), to identify clinician-documented medical cannabis use. We defined medical use as any documentation of cannabis that was recommended by a clinician or described by the clinician or patient as intended to manage health conditions or symptoms. We developed and applied an NLP system that included NLP-assisted manual review to identify such documentation in encounter notes. Results: Medical cannabis use was documented for 16,684 (5.6%) of 299,597 outpatient encounters with routine screening for cannabis use among 203,489 patients seeing 1,274 clinicians. The validated NLP system identified 54% of documentation and NLP-assisted manual review the remainder. Language documenting reasons for cannabis use included 125 terms indicating medical use, 28 terms indicating non-medical use and 41 ambiguous terms. Implicit documentation of medical use (e.g., "edible THC nightly for lumbar pain") was more common than explicit (e.g., "continues medical cannabis use"). Conclusions: Clinicians use diverse and often ambiguous language to document patients' reasons for cannabis use. Automating extraction of documentation about patients' cannabis use could facilitate clinical decision support and epidemiological investigation but will require large amounts of gold standard training data.
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Maconha Medicinal , Processamento de Linguagem Natural , Adolescente , Adulto , Documentação , Humanos , Maconha Medicinal/uso terapêutico , Medidas de Resultados Relatados pelo Paciente , Atenção Primária à SaúdeRESUMO
BACKGROUND: Hepatitis C and HIV are associated with opioid use disorders (OUD) and injection drug use. Medications for OUD can prevent the spread of HCV and HIV. OBJECTIVE: To describe the prevalence of documented OUD, as well as receipt of office-based medication treatment, among primary care patients with HCV or HIV. DESIGN: Retrospective observational cohort study using electronic health record and insurance data. PARTICIPANTS: Adults ≥ 18 years with ≥ 2 visits to primary care during the study (2014-2016) at 6 healthcare systems across five states (CO, CA, OR, WA, and MN). MAIN MEASURES: The primary outcome was the diagnosis of OUD; the secondary outcome was OUD treatment with buprenorphine or oral/injectable naltrexone. Prevalence of OUD and OUD treatment was calculated across four groups: HCV only; HIV only; HCV and HIV; and neither HCV nor HIV. In addition, adjusted odds ratios (AOR) of OUD treatment associated with HCV and HIV (separately) were estimated, adjusting for age, gender, race/ethnicity, and site. KEY RESULTS: The sample included 1,368,604 persons, of whom 10,042 had HCV, 5821 HIV, and 422 both. The prevalence of diagnosed OUD varied across groups: 11.9% (95% CI: 11.3%, 12.5%) for those with HCV; 1.6% (1.3%, 2.0%) for those with HIV; 8.8% (6.2%, 11.9%) for those with both; and 0.92% (0.91%, 0.94%) among those with neither. Among those with diagnosed OUD, the prevalence of OUD medication treatment was 20.9%, 16.0%, 10.8%, and 22.3%, for those with HCV, HIV, both, and neither, respectively. HCV was not associated with OUD treatment (AOR = 1.03; 0.88, 1.21), whereas patients with HIV had a lower probability of OUD treatment (AOR = 0.43; 0.26, 0.72). CONCLUSIONS: Among patients receiving primary care, those diagnosed with HCV and HIV were more likely to have documented OUD than those without. Patients with HIV were less likely to have documented medication treatment for OUD.
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Buprenorfina , Infecções por HIV , Hepatite C , Transtornos Relacionados ao Uso de Opioides , Adulto , Buprenorfina/uso terapêutico , Infecções por HIV/tratamento farmacológico , Infecções por HIV/epidemiologia , Hepatite C/tratamento farmacológico , Hepatite C/epidemiologia , Humanos , Tratamento de Substituição de Opiáceos , Transtornos Relacionados ao Uso de Opioides/tratamento farmacológico , Transtornos Relacionados ao Uso de Opioides/epidemiologia , Prevalência , Atenção Primária à Saúde , Estudos RetrospectivosRESUMO
BACKGROUND: Unhealthy alcohol use is a serious and costly public health problem. Alcohol screening and brief interventions are effective in reducing unhealthy alcohol consumption. However, rates of receipt and delivery of brief interventions vary significantly across healthcare settings, and relatively little is known about the associated patient and provider factors. METHODS: This study examines patient and provider factors associated with the receipt of brief interventions for unhealthy alcohol use in an integrated healthcare system, based on documented brief interventions in the electronic health record. Using multilevel logistic regression models, we retrospectively analyzed 287,551 adult primary care patients (and their 2952 providers) who screened positive for unhealthy drinking between 2014 and 2017. RESULTS: We found lower odds of receiving a brief intervention among patients exceeding daily or weekly drinking limits (vs. exceeding both limits), females, older age groups, those with higher medical complexity, and those already diagnosed with alcohol use disorders. Patients with other unhealthy lifestyle activities (e.g., smoking, no/insufficient exercise) were more likely to receive a brief intervention. We also found that female providers and those with longer tenure in the health system were more likely to deliver brief interventions. CONCLUSIONS: These findings point to characteristics that can be targeted to improve universal receipt of brief intervention.
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Alcoolismo/terapia , Intervenção em Crise/estatística & dados numéricos , Pessoal de Saúde/estatística & dados numéricos , Pacientes/estatística & dados numéricos , Atenção Primária à Saúde/estatística & dados numéricos , Adolescente , Adulto , Idoso , Idoso de 80 Anos ou mais , Alcoolismo/psicologia , Feminino , Humanos , Masculino , Pessoa de Meia-Idade , Atenção Primária à Saúde/métodos , Estudos Retrospectivos , Adulto JovemRESUMO
PURPOSE: This review sought to (a) describe definitions of long-term opioid therapy (LTOT) outcome measures, and (b) identify the predictors associated with the transition from short-term opioid use to LTOT for opioid-naïve individuals. METHODS: We conducted a systematic review of the peer-reviewed literature (January 2007 to July 2018). We included studies examining opioid use for more than 30 days. We classified operationalization of LTOT based on criteria used in the definitions. We extracted LTOT predictors from multivariate models in studies of opioid-naïve individuals. RESULTS: The search retrieved 5,221 studies, and 34 studies were included. We extracted 41 unique variations of LTOT definitions. About 36% of definitions required a cumulative duration of opioid use of 3 months. Only 17% of definitions considered consecutive observation periods, 27% used days' supply, and no definitions considered dose. We extracted 76 unique predictors of LTOT from seven studies of opioid-naïve patients. Common predictors included pre-existing comorbidities (21.1%), non-opioid prescription medication use (13.2%), substance use disorders (10.5%), and mental health disorders (10.5%). CONCLUSIONS: Most LTOT definitions aligned with the chronic pain definition (pain more than 3 months), and used cumulative duration of opioid use as a criterion, although most did not account for consistent use. Definitions were varied and rarely accounted for prescription characteristics, such as days' supply. Predictors of LTOT were similar to known risk factors of opioid abuse, misuse, and overdose. As LTOT becomes a central component of quality improvement efforts, researchers should incorporate criteria to identify consistent opioid use to build the evidence for safe and appropriate use of prescription opioids.
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Analgésicos Opioides/uso terapêutico , Dor Crônica/tratamento farmacológico , HumanosRESUMO
BACKGROUND: Individuals with major depressive disorder (MDD) and bipolar disorder (BD) have particularly high rates of chronic non-cancer pain (CNCP) and are also more likely to receive prescription opioids for their pain. However, there have been no known studies published to date that have examined opioid treatment patterns among individuals with schizophrenia. METHODS: Using electronic medical record data across 13 Mental Health Research Network sites, individuals with diagnoses of MDD (N = 65,750), BD (N = 38,117) or schizophrenia or schizoaffective disorder (N = 12,916) were identified and matched on age, sex and Medicare status to controls with no documented mental illness. CNCP diagnoses and prescription opioid medication dispensings were extracted for the matched samples. Multivariate analyses were conducted to evaluate (1) the odds of receiving a pain-related diagnosis and (2) the odds of receiving opioids, by separate mental illness diagnosis category compared with matched controls, controlling for age, sex, Medicare status, race/ethnicity, income, medical comorbidities, healthcare utilization and chronic pain diagnoses. RESULTS: Multivariable models indicated that having a MDD (OR = 1.90; 95% CI = 1.85-1.95) or BD (OR = 1.71; 95% CI = 1.66-1.77) diagnosis was associated with increased odds of a CNCP diagnosis after controlling for age, sex, race, income, medical comorbidities and healthcare utilization. By contrast, having a schizophrenia diagnosis was associated with decreased odds of receiving a chronic pain diagnosis (OR = 0.86; 95% CI = 0.82-0.90). Having a MDD (OR = 2.59; 95% CI = 2.44-2.75) or BD (OR = 2.12; 95% CI = 1.97-2.28) diagnosis was associated with increased odds of receiving chronic opioid medications, even after controlling for age, sex, race, income, medical comorbidities, healthcare utilization and chronic pain diagnosis; having a schizophrenia diagnosis was not associated with receiving chronic opioid medications. CONCLUSIONS: Individuals with serious mental illness, who are most at risk for developing opioid-related problems, continue to be prescribed opioids more often than their peers without mental illness. Mental health clinicians may be particularly well-suited to lead pain assessment and management efforts for these patients. Future research is needed to evaluate the effectiveness of involving mental health clinicians in these efforts.
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Analgésicos Opioides , Dor Crônica , Transtorno Depressivo Maior , Padrões de Prática Médica , Medicamentos sob Prescrição , Adulto , Idoso , Analgésicos Opioides/uso terapêutico , Dor Crônica/tratamento farmacológico , Dor Crônica/epidemiologia , Transtorno Depressivo Maior/diagnóstico , Transtorno Depressivo Maior/tratamento farmacológico , Transtorno Depressivo Maior/epidemiologia , Feminino , Humanos , Masculino , Medicare , Transtornos Mentais/complicações , Pessoa de Meia-Idade , Transtornos Relacionados ao Uso de Opioides , Padrões de Prática Médica/estatística & dados numéricos , Estados Unidos/epidemiologiaRESUMO
BACKGROUND: The Affordable Care Act (ACA) has increased insurance coverage for people with HIV (PWH) in the United States. To inform health policy, it is useful to investigate how enrollment through ACA Exchanges, deductible levels, and demographic factors are associated with health care utilization and HIV clinical outcomes among individuals newly enrolled in insurance coverage following implementation of the ACA. METHODS: Among PWH newly enrolled in an integrated health care system (Kaiser Permanente Northern California) in 2014 (N = 880), we examined use of health care and modeled associations between enrollment mechanisms (enrolled in a Qualified Health Plan through the California Exchange vs. other sources), deductibles (none, $1-$999 and > = $1000), receipt of benefits from the California AIDS Drug Assistance Program (ADAP), demographic factors, and three-year patterns of health service utilization (primary care, psychiatry, substance treatment, emergency, inpatient) and HIV outcomes (CD4 counts; viral suppression at HIV RNA < 75 copies/mL). RESULTS: Health care use was greatest immediately after enrollment and decreased over 3 years. Those with high deductibles were less likely to use primary care (OR = 0.64, 95% CI = 0.49-0.84, p < 0.01) or psychiatry OR = 0.59, 95% CI = 0.37, 0.94, p = 0.03) than those with no deductible. Enrollment via the Exchange was associated with fewer psychiatry visits (rate ratio [RR] = 0.40, 95% CI = 0.18-0.86; p = 0.02), but ADAP was associated with more psychiatry visits (RR = 2.22, 95% CI = 1.24-4.71; p = 0.01). Those with high deductibles were less likely to have viral suppression (OR = 0.65, 95% CI = 0.42-1.00; p = 0.05), but ADAP enrollment was associated with viral suppression (OR = 2.20, 95% CI = 1.32-3.66, p < 0.01). Black (OR = 0.35, 95% CI = 0.21-0.58, p < 0.01) and Hispanic (OR = 0.50, 95% CI = 0.29-0.85, p = 0.01) PWH were less likely to be virally suppressed. CONCLUSIONS: In this sample of PWH newly enrolled in an integrated health care system in California, findings suggest that enrollment via the Exchange and higher deductibles were negatively associated with some aspects of service utilization, high deductibles were associated with worse HIV outcomes, but support from ADAP appeared to help patients achieve viral suppression. Race/ethnic disparities remain important to address even among those with access to insurance coverage.
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Prestação Integrada de Cuidados de Saúde , Infecções por HIV , California/epidemiologia , Infecções por HIV/tratamento farmacológico , Infecções por HIV/epidemiologia , Acessibilidade aos Serviços de Saúde , Humanos , Cobertura do Seguro , Estudos Longitudinais , Aceitação pelo Paciente de Cuidados de Saúde , Patient Protection and Affordable Care Act , Estados UnidosRESUMO
Emergency clinicians are on the front lines of responding to the opioid epidemic and are leading innovations to reduce opioid overdose deaths through safer prescribing, harm reduction, and improved linkage to outpatient treatment. Currently, there are no nationally recognized quality measures or best practices to guide emergency department quality improvement efforts, implementation science researchers, or policymakers seeking to reduce opioid-associated morbidity and mortality. To address this gap, in May 2017, the National Institute on Drug Abuse's Center for the Clinical Trials Network convened experts in quality measurement from the American College of Emergency Physicians' (ACEP's) Clinical Emergency Data Registry, researchers in emergency and addiction medicine, and representatives from federal agencies, including the National Institute on Drug Abuse and the Centers for Medicare & Medicaid Services. Drawing from discussions at this meeting and with experts in opioid use disorder treatment and quality measure development, we developed a multistakeholder quality improvement framework with specific structural, process, and outcome measures to guide an emergency medicine agenda for opioid use disorder policy, research, and clinical quality improvement.
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Overdose de Drogas/prevenção & controle , Serviço Hospitalar de Emergência/organização & administração , Transtornos Relacionados ao Uso de Opioides/prevenção & controle , Assistência ao Paciente/normas , Padrões de Prática Médica/normas , Analgésicos Opioides/intoxicação , Consenso , Humanos , Transtornos Relacionados ao Uso de Opioides/diagnóstico , Melhoria de Qualidade , Estados UnidosRESUMO
Background: Problematic use of alcohol and other drugs (AOD) is highly prevalent among people living with the human immunodeficiency virus (PLWH), and untreated AOD use disorders have particularly detrimental effects on human immunodeficiency virus (HIV) outcomes. The Healthcare Effectiveness Data and Information Set (HEDIS) measures of treatment initiation and engagement are important benchmarks for access to AOD use disorder treatment. To inform improved patient care, we compared HEDIS measures of AOD use disorder treatment initiation and engagement and health care utilization among PLWH and patients without an HIV diagnosis. Methods: Patients with a new AOD use disorder diagnosis documented between October 1, 2014, and August 15, 2015, were identified using electronic health records (EHR) and insurance claims data from 7 health care systems in the United States. Demographic characteristics, clinical diagnoses, and health care utilization data were also obtained. AOD use disorder treatment initiation and engagement rates were calculated using HEDIS measure criteria. Factors associated with treatment initiation and engagement were examined using multivariable logistic regression models. Results: There were 469 PLWH (93% male) and 86,096 patients without an HIV diagnosis (60% male) in the study cohort. AOD use disorder treatment initiation was similar in PLWH and patients without an HIV diagnosis (10% vs. 11%, respectively). Among those who initiated treatment, few engaged in treatment in both groups (9% PLWH vs. 12% patients without an HIV diagnosis). In multivariable analysis, HIV status was not significantly associated with either AOD use disorder treatment initiation or engagement. Conclusions: AOD use disorder treatment initiation and engagement rates were low in both PLWH and patients without an HIV diagnosis. Future studies need to focus on developing strategies to efficiently integrate AOD use disorder treatment with medical care for HIV.
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Infecções por HIV/epidemiologia , Serviços de Saúde Mental/estatística & dados numéricos , Participação do Paciente/estatística & dados numéricos , Transtornos Relacionados ao Uso de Substâncias/terapia , Adolescente , Adulto , Idoso , Assistência Ambulatorial , Estudos de Casos e Controles , Comorbidade , Feminino , Pesquisa sobre Serviços de Saúde , Hospitalização , Humanos , Masculino , Pessoa de Meia-Idade , Transtornos Relacionados ao Uso de Substâncias/epidemiologia , Estados Unidos/epidemiologia , Adulto JovemRESUMO
Background: Medical comorbidity may influence treatment initiation and engagement for alcohol and other drug (AOD) use disorders. We examined the association between medical comorbidity and Healthcare Effectiveness Data and Information Set (HEDIS) treatment initiation and engagement measures.Methods: We used electronic health record and insurance claims data from 7 US health care systems to identify patients with AOD use disorders between October 1, 2014, and August 15, 2015 (N = 86,565). Among patients identified with AOD use disorders in outpatient and emergency department (ED) settings, we examined how Charlson/Deyo comorbidity index scores and medical complications of AOD use were associated with treatment initiation. Among those who initiated treatment in inpatient and outpatient/ED settings, we also examined how comorbidity and AOD use-related medical complications were associated with treatment engagement. Analyses were conducted using generalized estimating equation logistic regression modeling.Results: Among patients identified as having an AOD diagnosis in outpatient and ED settings (n = 69,965), Charlson/Deyo comorbidity index scores of 2 or more were independently associated with reduced likelihood of initiation (risk ratio [RR] = 0.80, 95% confidence interval [CI] = 0.74, 0.86; reference score = 0), whereas prior-year diagnoses of cirrhosis (RR = 1.25, 95% CI = 1.12, 1.35) and pancreatic disease (RR = 1.34, 95% CI = 1.15, 1.56) were associated with greater likelihood of initiation. Among those who were identified in outpatient/ED settings and initiated, higher comorbidity scores were associated with lower likelihood of engagement (score 1: RR = 0.85, 95% CI = 0.76, 0.94; score 2+: RR = 0.61, 95% CI = 0.53, 0.71).Conclusion: Medical comorbidity was associated with lower likelihood of initiating or engaging in AOD treatment, but cirrhosis and pancreatic disease were associated with greater likelihood of initiation. Interventions to improve AOD treatment initiation and engagement for patients with comorbidities are needed, such as integrating medical and AOD treatment.
Assuntos
Serviços de Saúde Mental/estatística & dados numéricos , Participação do Paciente/estatística & dados numéricos , Transtornos Relacionados ao Uso de Substâncias/terapia , Adolescente , Adulto , Assistência Ambulatorial , Doenças Cardiovasculares/epidemiologia , Estudos de Coortes , Comorbidade , Doenças do Sistema Digestório/epidemiologia , Serviço Hospitalar de Emergência , Doenças do Sistema Endócrino/epidemiologia , Feminino , Pesquisa sobre Serviços de Saúde , Hospitalização , Humanos , Modelos Logísticos , Masculino , Transtornos Mentais/epidemiologia , Doenças Metabólicas/epidemiologia , Pessoa de Meia-Idade , Doenças Musculoesqueléticas/epidemiologia , Doenças do Sistema Nervoso/epidemiologia , Doenças Respiratórias/epidemiologia , Estudos Retrospectivos , Transtornos Relacionados ao Uso de Substâncias/epidemiologia , Estados Unidos/epidemiologia , Ferimentos e Lesões/epidemiologia , Adulto JovemRESUMO
Background: Only 10% of patients with alcohol and other drug (AOD) disorders receive treatment. The AOD Initiation and Engagement in Treatment (AOD-IET) measure was added to the national Healthcare Effectiveness Data and Information Set (HEDIS) to improve access to care. This study identifies factors related to improving AOD-IET rates. Methods: We include data from 7 health systems with differing geographic, patient demographic, and organizational characteristics; all used a common Virtual Data Warehouse containing electronic health records and insurance claims data. Multilevel logistic regression models examined AOD-IET among adults (18+). Results: A total of 86,565 patients had an AOD diagnosis qualifying for the HEDIS denominator. The overall initiation rate was 27.9% with wide variation; the overall engagement rate was 11.5% and varied from 4.5% to 17.9%. Women versus men (odds ratio [OR] = 0.81, 95% confidence interval [CI] = 0.76-0.86); Hispanics (OR = 0.85, 95% CI = 0.79-0.91), black/African Americans (OR = 0.82, 95% CI = 0.75-0.90), and Asian Americans (OR = 0.83, 95% CI = 0.72-0.95) versus whites; and patients aged 65+ versus 18-29 (OR = 0.82, 95% CI = 0.74-0.90) had lower odds of initiation. Patients aged 30-49 versus 18-29 (OR = 1.11, 95% CI = 1.04-1.19) and those with prior psychiatric (OR = 1.26, 95% CI = 1.18-1.35) and medical (OR = 1.18, 95% CI = 1.10-1.26) conditions had higher odds of initiation. Identification in primary care versus other departments was related to lower odds of initiation (emergency department [ED]: OR = 1.55, 95% CI = 1.45-1.66; psychiatry/AOD treatment: OR = 3.58, 95% CI = 3.33-3.84; other outpatient: OR = 1.19, 95% CI = 1.06-1.32). Patients aged 30-49 versus 18-29 had higher odds of engagement (OR = 1.26, 95% CI = 1.10-1.43). Patients aged 65+ versus 18-29 (OR = 0.51, 95% CI = 0.43-0.62) and black/African Americans versus whites (OR = 0.64, 95% CI = 0.53-0.77) had lower odds. Those initiating treatment in psychiatry/AOD treatment versus primary care (OR = 7.02, 95% CI = 5.93-8.31) had higher odds of engagement; those in inpatient (OR = 0.40, 95% CI = 0.32-0.50) or other outpatient (OR = 0.73, 95% CI = 0.59-0.91) settings had lower odds. Discussion: Rates of initiation and engagement varied but were low. Findings identified age, race/ethnicity, co-occurring conditions, and department of identification as key factors associated with AOD-IET. Focusing on these could help programs develop interventions that facilitate AOD-IET for those less likely to receive care.
Assuntos
Etnicidade/estatística & dados numéricos , Serviços de Saúde Mental/estatística & dados numéricos , Participação do Paciente/estatística & dados numéricos , Transtornos Relacionados ao Uso de Substâncias/terapia , Adolescente , Adulto , Negro ou Afro-Americano , Fatores Etários , Idoso , Assistência Ambulatorial , Asiático , Serviço Hospitalar de Emergência , Feminino , Acessibilidade aos Serviços de Saúde , Pesquisa sobre Serviços de Saúde , Hispânico ou Latino , Hospitalização , Humanos , Modelos Logísticos , Masculino , Pessoa de Meia-Idade , Análise Multinível , Atenção Primária à Saúde , Fatores Sexuais , Transtornos Relacionados ao Uso de Substâncias/diagnóstico , População Branca , Adulto JovemRESUMO
Background: The prevalence of opioid use disorder (OUD) has increased rapidly in the United States and improving treatment access is critical. Among patients with OUD, we examined factors associated with the Healthcare Effectiveness Data and Information Set (HEDIS) performance measures of alcohol and other drug (AOD) treatment initiation and engagement. Methods: Electronic health record and claims data between October 1, 2014, and August 15, 2015, from 7 health systems were used to identify patients (n = 11,490) with a new index OUD diagnosis (no AOD diagnosis prior <60 days) based on International Classification of Diseases (ICD)-9 codes. Multivariable generalized linear models with a logit link clustered on health system were used to examine the associations of patient demographic and clinical characteristics, and department of index diagnosis, with HEDIS measures of treatment initiation and engagement. Results: The prevalence of OUD among all AOD diagnoses varied across health systems, as did rates of AOD initiation (5.7%-21.6%) and engagement (7.6%-24.6%). Those diagnosed in the emergency department (adjusted odds ratio [aOR] = 1.58, 95% confidence interval [CI] = 1.27,1.97) or psychiatry/AOD treatment (aOR = 2.92, 95% CI = 2.47,3.46) were more likely to initiate treatment compared with primary care. Older patients were less likely to initiate (age 50-64 vs. age 18-29: aOR = 0.42, 95% CI = 0.35, 0.51; age 65+ vs. age 18-29: aOR = 0.34, 95% CI = 0.26, 0.43), as were women (aOR = 0.72, 95% CI = 0.62, 0.85). Patients diagnosed in psychiatry/AOD treatment (aOR = 2.67, 95% CI = 1.98, 3.60) compared with primary care were more likely to engage in treatment. Those identified in an inpatient setting (aOR = 0.19, 95% CI = 0.14, 0.27 vs. primary care), those with medical comorbidity (aOR = 0.70, 95% CI = 0.52, 0.95), and older patients (age 50-64 vs. 18-29: aOR = 0.64, 95% CI = 0.46, 0.88; age 65+ vs. 18-29: aOR = 0.36, 95% CI = 0.22, 0.57) were less likely to engage in treatment. Conclusions: Rates of initiation and engagement for OUD patients vary widely with noticeable room for improvement, particularly in this critical time of the opioid crisis. Targeting patient and system factors may improve health system performance, which is key to improving patient outcomes.
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Serviços de Saúde Mental/estatística & dados numéricos , Transtornos Relacionados ao Uso de Opioides/terapia , Participação do Paciente/estatística & dados numéricos , Adolescente , Adulto , Fatores Etários , Idoso , Delírio do Despertar , Feminino , Pesquisa sobre Serviços de Saúde , Humanos , Masculino , Pessoa de Meia-Idade , Transtornos Relacionados ao Uso de Opioides/diagnóstico , Atenção Primária à Saúde , Psiquiatria , Fatores Sexuais , Adulto JovemRESUMO
Background: Psychiatric comorbidity is common among patients with alcohol and other drug (AOD) use disorders. To better understand how psychiatric comorbidity influences AOD treatment access in health care systems, the present study examined treatment initiation and engagement among a large, diverse sample of patients with comorbid psychiatric and AOD use disorders. Methods: This study utilized data from a multisite observational study examining Healthcare Effectiveness Data and Information Set (HEDIS) measures of initiation and engagement in treatment (IET) among patients with AOD use disorders from 7 health care systems. Participants were aged 18 or older with at least 1 AOD index diagnosis between October 1, 2014, and August 15, 2015. Data elements extracted from electronic health records and insurance claims data included patient demographic characteristics, ICD-9 (International Classification of Diseases, Ninth Revision) diagnostic codes, and procedure codes. Descriptive analyses and multivariate logistic regression models were used to examine the relationship between patient-level factors and IET measures. Results: Across health care systems, out of a total of 86,565 patients who had at least 1 AOD index diagnosis during the study period, 66.2% (n = 57,335) patients also had a comorbid psychiatric disorder. Among patients with a comorbid psychiatric disorder, 34.9% (n = 19,998) initiated AOD treatment, and of those, 10.3% (n = 2,060) engaged in treatment. After adjusting for age, sex, and race/ethnicity, patients with comorbid psychiatric disorders were more likely to initiate (odds ratio [OR] = 3.20, 95% confidence interval [CI] = 3.08, 3.32) but no more likely to engage (OR = 0.56, 95% CI = 0.51, 0.61) in AOD treatment, compared with those without a comorbid psychiatric disorder. Conclusions: Findings suggest that identification of comorbid psychiatric disorders may increase initiation in AOD treatment. However, innovative efforts are needed to enhance treatment engagement both generally and especially for individuals without diagnosed psychiatric conditions.
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Transtornos de Ansiedade/epidemiologia , Transtorno Depressivo/epidemiologia , Serviços de Saúde Mental/estatística & dados numéricos , Participação do Paciente/estatística & dados numéricos , Transtornos Psicóticos/epidemiologia , Transtornos Relacionados ao Uso de Substâncias/terapia , Adolescente , Adulto , Idoso , Assistência Ambulatorial , Comorbidade , Serviço Hospitalar de Emergência , Feminino , Pesquisa sobre Serviços de Saúde , Hospitalização , Humanos , Masculino , Transtornos Mentais/epidemiologia , Pessoa de Meia-Idade , Transtornos Relacionados ao Uso de Substâncias/epidemiologia , Estados Unidos/epidemiologia , Adulto JovemRESUMO
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.