Publications

OBJECTIVES: The US opioid medication epidemic has resulted in serious health consequences for patients. Formulary management tools adopted by payers, specifically prior authorization (PA) policies, may lower the rates of opioid medication abuse and overdose. We compared rates of opioid abuse and overdose among enrollees in plans that varied in their use of PA from "High PA" (ie, required PA for 17 to 74 opioids), with "Low PA" (ie, required PA for 1 opioid), and "No PA" policies for opioid medications.

STUDY DESIGN: Retrospective cohort study of patients initiating opioid treatment in Pennsylvania Medicaid from 2010 to 2012.

METHODS: Generalized linear models with generalized estimating equations were employed to assess the relationships between the presence of PA policies and opioid medication abuse and overdose, as measured in Medicaid claims data, adjusting for demographics, comorbid health conditions, benzodiazepine/muscle relaxant use, and emergency department use.

RESULTS: The study cohort included 297,634 enrollees with a total of 382,828 opioid treatment episodes. Compared with plans with No PA, enrollees in High PA (adjusted rate ratio [ARR], 0.89; 95% confidence interval [CI], 0.85-0.93; P <.001) and Low PA plans (ARR, 0.93; 95% CI, 0.87-1.00; P = .04) had lower rates of abuse. Enrollees in the Low PA plan had a lower rate of overdose than those within plans with No PA (ARR, 0.75; 95% CI, 0.59-0.95; P = .02). High PA plan enrollees were also less likely than No PA enrollees to experience an overdose, but this association was not statistically significant (ARR, 0.88; 95% CI, 0.76-1.02; P = .08).

CONCLUSIONS: Enrollees within Medicaid plans that utilize PA policies appear to have lower rates of abuse and overdose following initiation of opioid medication treatment.

WHAT IS KNOWN AND OBJECTIVE: There are few studies examining both drug-drug and drug-disease interactions in older adults. Therefore, the objective of this study was to describe the prevalence of potential drug-drug and drug-disease interactions and associated factors in community-dwelling older adults.

METHODS: This cross-sectional study included 3055 adults aged 70-79 without mobility limitations at their baseline visit in the Health Aging and Body Composition Study conducted in the communities of Pittsburgh PA and Memphis TN, USA. The outcome factors were potential drug-drug and drug-disease interactions as per the application of explicit criteria drawn from a number of sources to self-reported prescription and non-prescription medication use.

RESULTS: Over one-third of participants had at least one type of interaction. Approximately one quarter (25·1%) had evidence of had one or more drug-drug interactions. Nearly 10·7% of the participants had a drug-drug interaction that involved a non-prescription medication. % The most common drug-drug interaction was non-steroidal anti-inflammatory drugs (NSAIDs) affecting antihypertensives. Additionally, 16·0% had a potential drug-disease interaction with 3·7% participants having one involving non-prescription medications. The most common drug-disease interaction was aspirin/NSAID use in those with history of peptic ulcer disease without gastroprotection. Over one-third (34·0%) had at least one type of drug interaction. Each prescription medication increased the odds of having at least one type of drug interaction by 35-40% [drug-drug interaction adjusted odds ratio (AOR) = 1·35, 95% confidence interval (CI) = 1·27-1·42; drug-disease interaction AOR = 1·30; CI = 1·21-1·40; and both AOR = 1·45; CI = 1·34-1·57]. A prior hospitalization increased the odds of having at least one type of drug interaction by 49-84% compared with those not hospitalized (drug-drug interaction AOR = 1·49, 95% CI = 1·11-2·01; drug-disease interaction AOR = 1·69, CI = 1·15-2·49; and both AOR = 1·84, CI = 1·20-2·84).

WHAT IS NEW AND CONCLUSION: Drug interactions are common among community-dwelling older adults and are associated with the number of medications and hospitalization in the previous year. Longitudinal studies are needed to evaluate the impact of drug interactions on health-related outcomes.

BACKGROUND: Health systems may play an important role in identification of patients at-risk of opioid medication overdose. However, standard measures for identifying overdose risk in administrative data do not exist.

OBJECTIVE: Examine the association between opioid medication overdose and 2 validated measures of nonmedical use of prescription opioids within claims data.

RESEARCH DESIGN: A longitudinal retrospective cohort study that estimated associations between overdose and nonmedical use.

SUBJECTS: Adult Pennsylvania Medicaid program 2007-2012 patients initiating opioid treatment who were: nondual eligible, without cancer diagnosis, and not in long-term care facilities or receiving hospice.

MEASURES: Overdose (International Classification of Disease, ninth edition, prescription opioid poisonings codes), opioid abuse (opioid use disorder diagnosis while possessing an opioid prescription), opioid misuse (a composite indicator of number of opioid prescribers, number of pharmacies, and days supplied), and dose exposure during opioid treatment episodes.

RESULTS: A total of 372,347 Medicaid enrollees with 583,013 new opioid treatment episodes were included in the cohort. Opioid overdose was higher among those with abuse (1.5%) compared with those without (0.2%, P<0.001). Overdose was higher among those with probable (1.8%) and possible (0.9%) misuse compared with those without (0.2%, P<0.001). Abuse [adjusted rate ratio (ARR), 1.52; 95% confidence interval (CI), 1.10-2.10), probable misuse (ARR, 1.98; 95% CI, 1.46-2.67), and possible misuse (ARR, 1.76; 95% CI, 1.48-2.09) were associated with significantly more events of opioid medication overdose compared with those without.

CONCLUSIONS: Claims-based measures can be used by health systems to identify individuals at-risk of overdose who can be targeted for restrictions on opioid prescribing, dispensing, or referral to treatment.

This study uses Medicaid data to compare prescription opioid use, duration of opioid use, and rates of medication-assisted treatment (buprenorphine, methadone, or naltrexone) among enrollees before and after an overdose event.

BACKGROUND: Optimism and cynical hostility independently predict morbidity and mortality in Women's Health Initiative (WHI) participants and are associated with current smoking. However, their association with smoking cessation in older women is unknown.

PURPOSE: The purpose of this study is to test whether optimism (positive future expectations) or cynical hostility (mistrust of others) predicts smoking cessation in older women.

METHODS: Self-reported smoking status was assessed at years 1, 3, and 6 after study entry for WHI baseline smokers who were not missing optimism or cynical hostility scores (n = 10,242). Questionnaires at study entry assessed optimism (Life Orientation Test-Revised) and cynical hostility (Cook-Medley, cynical hostility subscale). Generalized linear mixed models adjusted for sociodemographics, lifestyle factors, and medical and psychosocial characteristics including depressive symptoms.

RESULTS: After full covariate adjustment, optimism was not related to smoking cessation. Each 1-point increase in baseline cynical hostility score was associated with 5% lower odds of cessation over 6 years (OR = 0.95, CI = 0.92-0.98, p = 0.0017).

CONCLUSIONS: In aging postmenopausal women, greater cynical hostility predicts lower smoking cessation over time. Future studies should examine whether individuals with this trait may benefit from more intensive cessation resources or whether attempting to mitigate cynical hostility itself may aid smoking cessation.

OBJECTIVE: Underuse of clozapine and overuse of antipsychotic polypharmacy are both indicators of poor quality of care. This study examined variation in prescribing clozapine and antipsychotic polypharmacy across providers, as well as factors associated with these practices.

METHODS: Using 2010-2012 Pennsylvania Medicaid data, prescribers were identified if they wrote antipsychotic prescriptions for ten or more nonelderly adult patients with schizophrenia annually. Generalized linear mixed models with a binomial distribution and a logit link were used to examine prescriber-level annual percentages of patients with clozapine use and with long-term (≥90 days) antipsychotic polypharmacy and associated characteristics of prescribers' patient caseloads, prescriber characteristics, and Medicaid payer (fee-for-service versus managed care plans).

RESULTS: The study cohort included 645 prescribers in 2010, 632 in 2011, and 650 in 2012. In 2012, the mean prescriber-level annual percentage of patients with any clozapine use was 7% (range 0%-89%), and the mean percentage of patients with any long-term antipsychotic polypharmacy was 7% (range 0%-45%) (similar rates were found during 2010-2012). Prescribers with high prescription volume, a smaller percentage of patients from racial or ethnic minority groups, and a larger percentage of patients eligible for Supplemental Security Income were more likely to use both clozapine and antipsychotic polypharmacy for treating schizophrenia. Prescriber specialty and Medicaid payer were also associated with prescribers' practices.

CONCLUSIONS: Considerable variation was found in clozapine and antipsychotic polypharmacy practices across prescribers in their treatment of schizophrenia. Targeting efforts to selected prescribers holds promise as an approach to promote evidence-based antipsychotic prescribing.

INTRODUCTION: Expanding Medicaid coverage to low-income adults may have increased smoking cessation through improved access to evidence-based treatments. Our study sought to determine if states' decisions to expand Medicaid increased recent smoking cessation.

METHODS: Using pooled cross-sectional data from the Behavioral Risk Factor Surveillance Survey for the years 2011-2015, we examined the association between state Medicaid coverage and the probability of recent smoking cessation among low-income adults without dependent children who were current or former smokers (n=36,083). We used difference-in-differences estimation to examine the effects of Medicaid coverage on smoking cessation, comparing low-income adult smokers in states with Medicaid coverage to comparable adults in states without Medicaid coverage, with ages 18-64 years to those ages 65 years and above. Analyses were conducted for the full sample and stratified by sex.

RESULTS: Residence in a state with Medicaid coverage among low-income adult smokers ages 18-64 years was associated with an increase in recent smoking cessation of 2.1 percentage points (95% confidence interval, 0.25-3.9). In the comparison group of individuals ages 65 years and above, residence in a state with Medicaid coverage expansion was not associated with a change in recent smoking cessation (-0.1 percentage point, 95% confidence interval, -2.1 to 1.8). Similar increases in smoking cessation among those ages 18-64 years were estimated for females and males (1.9 and 2.2 percentage point, respectively).

CONCLUSION: Findings are consistent with the hypothesis that Medicaid coverage expansions may have increased smoking cessation among low-income adults without dependent children via greater access to preventive health care services, including evidence-based smoking cessation services.

OBJECTIVE: Second-generation antipsychotics increase the risk of diabetes and other metabolic conditions among individuals with schizophrenia. Although metabolic testing is recommended to reduce this risk, low testing rates have prompted concerns about negative health consequences and downstream medical costs. This study simulated the effect of increasing metabolic testing rates on ten-year prevalence rates of prediabetes and diabetes (diabetes conditions) and their associated health care costs.

METHODS: A microsimulation model (N=21,491 beneficiaries) with a ten-year time horizon was used to quantify the impacts of policies that increased annual testing rates in a Medicaid population with schizophrenia. Data sources included California Medicaid data, National Health and Nutrition Examination Survey data, and the literature. In the model, metabolic testing increased diagnosis of diabetes conditions and diagnosis prompted prescribers to switch patients to lower-risk antipsychotics. Key inputs included observed diagnoses, prescribing rates, annual testing rates, imputed rates of undiagnosed diabetes conditions, and literature-based estimates of policy effectiveness.

RESULTS: Compared with 2009 annual testing rates, ten-year outcomes for policies that achieved universal testing reduced exposure to higher-risk antipsychotics by 14%, time to diabetes diagnosis by 57%, and diabetes prevalence by .6%. These policies were associated with higher spending because of testing and earlier treatment.

CONCLUSIONS: The model showed that policies promoting metabolic testing provided an effective approach to improve the safety of second-generation antipsychotic prescribing in a Medicaid population with schizophrenia; however, the policies led to additional costs at ten years. Simulation studies are a useful source of information on the potential impacts of these policies.