Publications

BACKGROUND: Many Veterans treated within the VA Healthcare System (VA) are also enrolled in fee-for-service (FFS) Medicare and receive treatment outside the VA. Prior research has not accounted for the multiple ways that Veterans receive services across healthcare systems.

OBJECTIVE: We aimed to establish a typology of VA and Medicare utilization among dually enrolled Veterans with type 2 diabetes.

DESIGN: This was a retrospective cohort.

PARTICIPANTS: 316,775 community-dwelling Veterans age ≥ 65 years with type 2 diabetes who were dually enrolled in the VA and FFS Medicare in 2008-2009.

METHODS: Using latent class analysis, we identified classes of Veterans based upon their probability of using VA and Medicare diabetes care services, including patient visits, laboratory tests, glucose test strips, and medications. We compared the amount of healthcare use between classes and identified factors associated with class membership using multinomial regression.

KEY RESULTS: We identified four distinct latent classes: class 1 (53.9%) had high probabilities of VA use and low probabilities of Medicare use; classes 2 (17.2%), 3 (21.8%), and 4 (7.0%) had high probabilities of VA and Medicare use, but differed in their Medicare services used. For example, Veterans in class 3 received test strips exclusively through Medicare, while Veterans in class 4 were reliant on Medicare for medications. Living ≥ 40 miles from a VA predicted membership in classes 3 (OR 1.1, CI 1.06-1.15) and 4 (OR 1.11, CI 1.04-1.18), while Medicaid eligibility predicted membership in class 4 (OR 4.30, CI 4.10-4.51).

CONCLUSIONS: Veterans with diabetes can be grouped into four distinct classes of dual health system use, representing a novel way to characterize how patients use multiple services across healthcare systems. This classification has applications for identifying patients facing differential risk from care fragmentation.

BACKGROUND: All Department of Veterans Affairs Medical Centers (VAMCs) operate under a single national drug formulary, yet substantial variation in prescribing and spending exists across facilities. Local management of the national formulary may differ across VAMCs and may be one cause of this variation.

OBJECTIVE: To characterize variation in the management of nonformulary medication requests and pharmacy and therapeutics (P&T) committee member perceptions of the formulary environment at VAMCs nationwide.

METHODS: We performed an online survey of the chief of pharmacy and an additional staff pharmacist and physician on the P&T committee at all VAMCs. Respondents were asked questions regarding criteria for use for nonformulary medications, specific procedures for ordering nonformulary medications in general and specific lipid-lowering and diabetes agents, the appeals process, and the formulary environment at their VAMCs. We compared responses across facilities and between chiefs of pharmacy, pharmacists, and physicians.

RESULTS: A total of 212 chief pharmacists (n = 80), staff pharmacists (n = 78), and physicians (n = 54) responded, for an overall response rate of 49%. In total, 107/143 (75%) different VAMCs were represented. The majority of VAMCs reported adhering to national criteria for use, with 38 (36%) being very adherent and 69 (65%) being mostly adherent. There was substantial variation between VAMCs regarding how nonformulary drugs were ordered, evaluated, and appealed. The nonformulary lipid-lowering drugs ezetimibe, rosuvastatin, and atorvastatin were viewable to providers in the order entry screen at 67 (63%), 67 (63%), and 64 (60%) VAMCs, respectively. The nonformulary diabetes medication pioglitazone was only viewable at 58 (55%) VAMCs. In the remaining VAMCs, providers could not order these nonformulary drugs through the normal order-entry process. For questions about the formulary environment, physician respondent perceptions differed from those of staff pharmacists and chief pharmacists. Compared with pharmacy chiefs and staff pharmacists, physicians were less likely to agree that providers at their VAMC prescribed too many nonformulary medications (47% and 44% vs. 12%, P < 0.001), more likely to agree that providers must jump through too many hoops to prescribe nonformulary medication (5% and 3% vs. 25%, P < 0.001), and more likely to agree that providers make an effort to convert new patients from nonformulary to formulary lipid-lowering (65% and 73% vs. 94%, P <0.02) and diabetic medications (49% and 50% vs. 88%, P < 0.001).

CONCLUSIONS: Although the Department of Veterans Affairs (VA) operates under a single national formulary, we found significant differences among VAMCs regarding their management of nonformulary medication requests. We also found differences among formulary leaders regarding their perception of the environment in which their VAMC's formulary is managed. These findings have important implications not just for VA, but for any organization that develops, implements, and manages drug formularies across multiple facilities.

BACKGROUND AND AIMS: Uncertainty about optimal treatment duration for buprenorphine opioid agonist therapy may lead to substantial variation in provider and payer decision-making regarding treatment course. We aimed to identify distinct trajectories of buprenorphine use and examine outcomes associated with these trajectories to guide health system interventions regarding treatment length.

DESIGN: Retrospective cohort study.

SETTING: US Pennsylvania Medicaid.

PATIENTS: A total of 10 945 enrollees aged 18-64 years initiating buprenorphine treatment between 2007 and 2012.

MEASUREMENTS: Group-based trajectory models were used to identify trajectories based on monthly proportion of days covered with buprenorphine in the 12 months post-treatment initiation. We used separate multivariable Cox proportional hazard models to examine associations between trajectories and time to first all-cause hospitalization and emergency department (ED) visit within 12 months after the first-year treatment.

FINDINGS: Six trajectories [Bayesian information criterion (BIC) = -86 246.70] were identified: 24.9% discontinued buprenorphine < 3 months, 18.7% discontinued between 3 and 5 months, 12.4% discontinued between 5 and 8 months, 13.3% discontinued > 8 months, 9.5% refilled intermittently and 21.2% refilled persistently for 12 months. Persistent refill trajectories were associated with an 18% lower risk of all-cause hospitalizations [hazard ratio (HR) = 0.82, 95% confidence interval (CI) = 0.70-0.95] and 14% lower risk of ED visits (HR = 0.86, 95% CI = 0.78-0.95) in the subsequent year, compared with those discontinuing between 3 and 5 months.

CONCLUSIONS: Six distinct buprenorphine treatment trajectories were identified in this population-based low-income Medicaid cohort in Pennsylvania, USA. There appears to be an association between persistent use of buprenorphine for 12 months and lower risk of all-cause hospitalizations/emergency department visits.

BACKGROUND: Physicians face the choice of multiple ingredients when prescribing drugs in many therapeutic categories. For conditions with considerable patient heterogeneity in treatment response, customizing treatment to individual patient needs and preferences may improve outcomes.

AIMS OF THE STUDY: To assess variation in the diversity of antipsychotic prescribing for mental health conditions, a necessary although not sufficient condition for personalizing treatment. To identify patient caseload, physician, and organizational factors associated with the diversity of antipsychotic prescribing.

METHODS: Using 2011 data from Pennsylvania's Medicaid program, IMS Health's HCOSTM database, and the AMA Masterfile, we identified 764 psychiatrists who prescribed antipsychotics to 10 patients. We constructed three physician-level measures of diversity/concentration of antipsychotic prescribing: number of ingredients prescribed, share of prescriptions for most preferred ingredient, and Herfindahl-Hirschman index (HHI). We used multiple membership linear mixed models to examine patient caseload, physician, and healthcare organizational predictors of physician concentration of antipsychotic prescribing.

RESULTS: There was substantial variability in antipsychotic prescribing concentration among psychiatrists, with number of ingredients ranging from 2-17, share for most preferred ingredient from 16%-85%, and HHI from 1,088-7,270. On average, psychiatrist prescribing behavior was relatively diversified; however, 11% of psychiatrists wrote an average of 55% of their prescriptions for their most preferred ingredient. Female prescribers and those with smaller shares of disabled or serious mental illness patients had more concentrated prescribing behavior on average.

DISCUSSION: Antipsychotic prescribing by individual psychiatrists in a large state Medicaid program varied substantially across psychiatrists. Our findings illustrate the importance of understanding physicians' prescribing behavior and indicate that even among specialties regularly prescribing a therapeutic category, some physicians rely heavily on a small number of agents.

IMPLICATIONS FOR HEALTH POLICIES, HEALTH CARE PROVISION AND USE: Health systems may need to offer educational interventions to clinicians in order to improve their ability to tailor treatment decisions to the needs of individual patients.

IMPLICATIONS FOR FUTURE RESEARCH: Future studies should examine the impact of the diversity of antipsychotic prescribing to determine whether more diversified prescribing improves patient adherence and outcomes.

BACKGROUND: Medications to treat and prevent chronic disease have substantially reduced morbidity and mortality; however, their diffusion has been uneven. Little is known about prescribing of chronic disease medications by nurse practitioners (NPs) and physician assistants (PAs), despite their increasingly important role as primary care providers. Thus, we sought to conduct an exploratory analysis to examine prescribing of new chronic disease medications by NPs and PAs compared to primary care physicians (PCPs).

METHODS: We obtained prescribing data from IMS Health's Xponent™ on all NPs, PAs, and PCPs in Pennsylvania regularly prescribing anticoagulants, antihypertensives, oral hypoglycemics, and/or HMG-Co-A reductase inhibitors pre- and post-introduction of five new drugs in these classes that varied in novelty (i.e., dabigatran, aliskiren, sitagliptin or saxagliptin, and pitavastatin). We constructed three measures of prescriber adoption during the 15-month post-FDA approval period: 1) any prescription of the medication, 2) proportion of prescriptions in the class for the medication, and 3) time to adoption (first prescription) of the medication.

RESULTS: From 2007 to 2011, the proportion of antihypertensive prescriptions prescribed by NPs and PAs approximately doubled from 2.0 to 4.2 % and 2.2 to 4.9 %, respectively. Similar trends were found for anticoagulants, oral hypoglycemics, and HMG-Co-A reductase inhibitors. By 2011, more PCPs had prescribed each of the newly approved medications than NPs and PAs (e.g., 44.3 % vs. 18.5 % vs. 20 % for dabigatran among PCPs, NPs, and PAs). Across all medication classes, the newly approved drugs accounted for a larger share of prescriptions in the class for PCPs followed by PAs, followed by NPs (e.g., dabigatran: 4.9 % vs. 3.2 % vs. 2.8 %, respectively). Mean time-to-adoption for the newly approved medications was shorter for PCPs compared to NPs and PAs (e.g., dabigatran, 7.3 vs. 8.2 vs. 8.5 months; P all medications <0.001).

CONCLUSIONS: PCPs were more likely to prescribe each of the newly approved medications per each measure of drug adoption, regardless of drug novelty. Differences in the rate and speed of drug adoption between PCPs, NPs, and PAs may have important implications for care and overall costs at the population level as NPs and PAs continue taking on a larger role in prescribing.

BACKGROUND: Variation in physician adoption of new medications is poorly understood. Traditional approaches (eg, measuring time to first prescription) may mask substantial heterogeneity in technology adoption.

OBJECTIVE: Apply group-based trajectory models to examine the physician adoption of dabigratran, a novel anticoagulant.

METHODS: A retrospective cohort study using prescribing data from IMS Xponent™ on all Pennsylvania physicians regularly prescribing anticoagulants (n=3911) and data on their characteristics from the American Medical Association Masterfile. We examined time to first dabigatran prescription and group-based trajectory models to identify adoption trajectories in the first 15 months. Factors associated with rapid adoption were examined using multivariate logistic regressions.

OUTCOMES: Trajectories of monthly share of oral anticoagulant prescriptions for dabigatran.

RESULTS: We identified 5 distinct adoption trajectories: 3.7% rapidly and extensively adopted dabigatran (adopting in ≤3 mo with 45% of prescriptions) and 13.4% were rapid and moderate adopters (≤3 mo with 20% share). Two groups accounting for 21.6% and 16.1% of physicians, respectively, were slower to adopt (6-10 mo post-introduction) and dabigatran accounted for <10% share. Nearly half (45.2%) of anticoagulant prescribers did not adopt dabigatran. Cardiologists were much more likely than primary care physicians to rapidly adopt [odds ratio (OR)=12.2; 95% confidence interval (CI), 9.27-16.1] as were younger prescribers (age 36-45 y: OR=1.49, 95% CI, 1.13-1.95; age 46-55: OR=1.34, 95% CI, 1.07-1.69 vs. >55 y).

CONCLUSIONS: Trajectories of physician adoption of dabigatran were highly variable with significant differences across specialties. Heterogeneity in physician adoption has potential implications for the cost and effectiveness of treatment.

BACKGROUND: Regional variation in US Medicare prescription drug spending is driven by higher prescribing of costly brand-name drugs in some regions. This variation likely arises from differences in the speed of diffusion of newly-approved medications. Second-generation antipsychotics were widely adopted for treatment of severe mental illness and for several off-label uses. Rapid diffusion of new psychiatric drugs likely increases drug spending but its relationship to non-drug spending is unclear. The impact of antipsychotic diffusion on drug and medical spending is of great interest to public payers like Medicare, which finance a majority of mental health spending in the US.

AIMS: We examine the association between physician adoption of new antipsychotics and antipsychotic spending and non-drug medical spending among disabled and elderly Medicare enrollees.

METHODS: We linked physician-level data on antipsychotic prescribing from an all-payer dataset (IMS Health's XponentTM) to patient-level data from Medicare. Our physician sample included 16,932 US. psychiatrists and primary care providers with > 10 antipsychotic prescriptions per year from 1997-2011. We constructed a measure of physician adoption of 3 antipsychotics introduced during this period (quetiapine, ziprasidone and aripiprazole) by estimating a shared frailty model of the time to first prescription for each drug. We then assigned physicians to one of 306 U.S. hospital referral regions (HRRs) and measured the average propensity to adopt per region. Using 2010 data for a random sample of 1.6 million Medicare beneficiaries, we identified 138,680 antipsychotic users. A generalized linear model with gamma distribution and log link was used to estimate the effect of region-level adoption propensity on beneficiary-level antipsychotic spending and non-drug medical spending adjusting for patient demographic and socioeconomic characteristics, health status, eligibility category, and whether the antipsychotic was for an on- vs. off-label use.

RESULTS: In our sample, mean patient age was 62 years, 42% were male, and 86% had low-income. Half of antipsychotic users in Medicare had an on-label indication. The weighted average propensity to adopt the three new antipsychotics varied four-fold across HRRs. For every one standard deviation increase in the propensity to adopt there was a 5% increase in antipsychotic spending after adjusting for covariates (adjusted ratio of spending 1.05, 95% CI 1.01-1.08, p = 0.005). Physician propensity to adopt new antipsychotics was not associated with non-drug medical spending (adjusted ratio 0.96, 95% CI 0.91-1.01, p < 0.117).

DISCUSSION: These findings suggest wide regional variation in physicians' propensity to adopt new antipsychotic medications. While physician adoption of new antipsychotics was positively associated with antipsychotic expenditures, it was not associated with non-drug spending. Our analysis is limited to Medicare and may not generalize to other payers. Also, claims data do not allow for the measurement of health outcomes, which would be important to evaluate when calculating the value of rapid vs. slow technology adoption.