Dataset Information

Impact of a Value-based Formulary on Medication Utilization, Health Services Utilization, and Expenditures.

ABSTRACT: BACKGROUND:Value-based benefit design has been suggested as an effective approach to managing the high cost of pharmaceuticals in health insurance markets. Premera Blue Cross, a large regional health plan, implemented a value-based formulary (VBF) for pharmaceuticals in 2010 that explicitly used cost-effectiveness analysis (CEA) to inform medication copayments. OBJECTIVE OF THE STUDY:The objective of the study was to determine the impact of the VBF. DESIGN:Interrupted time series of employer-sponsored plans from 2006 to 2013. SUBJECTS:Intervention group: 5235 beneficiaries exposed to the VBF. CONTROL GROUP:11,171 beneficiaries in plans without any changes in pharmacy benefits. INTERVENTION:The VBF-assigned medications with lower value (estimated by CEA) to higher copayment tiers and assigned medications with higher value to lower copayment tiers. MEASURES:Primary outcome was medication expenditures from member, health plan, and member plus health plan perspectives. Secondary outcomes were medication utilization, emergency department visits, hospitalizations, office visits, and nonmedication expenditures. RESULTS:In the intervention group after VBF implementation, member medication expenditures increased by $2 per member per month (PMPM) [95% confidence interval (CI), $1-$3] or 9%, whereas health plan medication expenditures decreased by $10 PMPM (CI, $18-$2) or 16%, resulting in a net decrease of $8 PMPM (CI, $15-$2) or 10%, which translates to a net savings of $1.1 million. Utilization of medications moved into lower copayment tiers increased by 1.95 days' supply (CI, 1.29-2.62) or 17%. Total medication utilization, health services utilization, and nonmedication expenditures did not change. CONCLUSIONS:Cost-sharing informed by CEA reduced overall medication expenditures without negatively impacting medication utilization, health services utilization, or nonmedication expenditures.

SUBMITTER: Yeung K

PROVIDER: S-EPMC5233590 | biostudies-literature | 2017 Feb

REPOSITORIES: biostudies-literature

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Impact of a Value-based Formulary on Medication Utilization, Health Services Utilization, and Expenditures.

Yeung Kai K Basu Anirban A Hansen Ryan N RN Watkins John B JB Sullivan Sean D SD

Medical care 20170201 2

<h4>Background</h4>Value-based benefit design has been suggested as an effective approach to managing the high cost of pharmaceuticals in health insurance markets. Premera Blue Cross, a large regional health plan, implemented a value-based formulary (VBF) for pharmaceuticals in 2010 that explicitly used cost-effectiveness analysis (CEA) to inform medication copayments.<h4>Objective of the study</h4>The objective of the study was to determine the impact of the VBF.<h4>Design</h4>Interrupted time ...[more]

PMID: 27579915

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Project description:ObjectiveTo disentangle the relationships among food insecurity, health care utilization, and health care expenditures.Data sources/study settingWe use national data on 13 465 adults (age ≥ 18) from the 2016 Medical Expenditure Panel Survey (MEPS), the first year of the food insecurity measures.Study designWe employ two-stage empirical models (probit for any health care use/expenditure, ordinary least squares, and generalized linear models for amount of utilization/expenditure), controlling for demographics, health insurance, poverty status, chronic conditions, and other predictors.Principal findingsOur results show that the likelihood of any health care expenditure (total, inpatient, emergency department, outpatient, and pharmaceutical) is higher for marginal, low, and very low food secure individuals. Relative to food secure households, very low food secure households are 5.1 percentage points (P < .001) more likely to have any health care expenditure, and have total health care expenditures that are 24.8 percent higher (P = .011). However, once we include chronic conditions in the models (ie, high blood pressure, heart disease, stroke, emphysema, high cholesterol, cancer, diabetes, arthritis, and asthma), these underlying health conditions mitigate the differences in expenditures by food insecurity status (only the likelihood of any having any health care expenditure for very low food secure households remains statistically significant).ConclusionsPolicy makers and government agencies are focused on addressing deficiencies in social determinants of health and the resulting impacts on health status and health care utilization. Our results indicate that chronic conditions are strongly associated with food insecurity and higher health care spending. Efforts to alleviate food insecurity should consider the dual burden of chronic conditions. Finally, future research can address specific mechanisms underlying the relationships between food security, health, and health care.

Project description:BACKGROUND:Traditional budget impact models predict the financial consequences of a new drug entering the market. This study provides an example of applying the budget impact framework to a new research question of interest to managed care organizations-what is the budget impact of our formulary and utilization management (UM) policy changes? OBJECTIVE:To predict the 3-year annual budgetary impact of TRICARE's antidiabetic formulary and UM policy changes using TRICARE claims data. METHODS:A budget impact model was built in Microsoft Excel using health plan claims data for a 3-year time horizon. Model outcomes included spending on antidiabetic medications and medications used for side effect treatment. In sensitivity analyses, medical costs from inpatient, outpatient, and emergency room visits were also estimated. Model inputs included health plan antidiabetic medication utilization, as well as publicly available drug cost, rebate, dispensing fee, and patient cost-sharing estimates. Type of enrollee and pharmacy were also incorporated into the model. Sensitivity analyses varied estimates for utilization switch rates between preferred and nonpreferred agents, drug costs, rebates, and dispensing fees, as well as predicted impact from implementation delays. RESULTS:For the 623,827 affected by the formulary and UM policy changes, the model predicted annual savings that increased from $24 million in the first year to $43 million in the third year after the changes. The majority of savings came from drug acquisition costs, as opposed to rebates, copays, and dispensing fees. Sensitivity analyses found savings across all varied parameters and scenarios except an unlikely scenario when 0% of utilization switched from nonpreferred to preferred agents. The model also predicted that the formulary and UM policy changes would lead to $529,439 in savings from medical visit costs in Year 3. CONCLUSIONS:This budget impact model predicted cost savings from the payer's formulary and UM policy changes. DISCLOSURES:This project was supported by grant number F32HS024857 from the Agency for Healthcare Research and Quality (AHRQ), which contracted with the University of Maryland School of Pharmacy to conduct this study. The content is solely the responsibility of the authors and does not necessarily represent the official views of the AHRQ, which had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; or design to submit the manuscript for publication. The findings discussed in this manuscript represent the views of the authors and do not necessarily reflect the views of the Department of Defense, the Defense Health Agency, nor the Departments of the Army, Navy, and Air Force. Hung reports a grant from the AHRQ, during the conduct of the study, and personal fees from CVS Health and BlueCross BlueShield Association, outside the submitted work. Mullins reports grants and personal fees from Bayer and Pfizer and personal fees from Boehringer-Ingelheim, Janssen/J&J, Regeneron, and Sanofi, outside the submitted work. Mullins, Slejko, and Shaya are employed by the University of Maryland School of Pharmacy. Haines and Lugo have nothing to disclose. Part of this content was previously presented as a poster at the 2017 AMCP Managed Care & Specialty Pharmacy Annual Meeting; March 27-30, 2017; Denver, CO, and as poster and oral presentations at the 2017 AMCP Nexus Meeting; October 16-19, 2017; Dallas, TX. Part of this content was published as Hung's PhD dissertation.

Project description:BackgroundAs low- and middle-income countries progress toward Universal Health Coverage, there is an increasing focus on measuring out-of-pocket (OOP) expenditure and health services utilization within countries. While there have been several reforms to improve health services coverage and financial protection in Pakistan, there is limited empirical research comparing OOP expenditure and health services utilization between public and private facilities and exploring their determinants, a knowledge gap addressed in this study.MethodsWe used data from 2013 to 14 OOP Health Expenditure Survey, a population-based household survey carried out for Pakistan's National Health Accounts. The analysis included 7969 encounters from 4293 households. We conducted bivariate analyses to describe patterns of care utilization, estimated annualized expenditures by type and sector of care, and assessed expenditure composition. We used multivariable logistic regression modeling to identify factors associated with sector of care and generalized linear model (GLM) with log link and gamma distribution to identify determinants of OOP expenditures stratified by type of care (inpatient and outpatient).ResultsMost encounters (82.5%) were in the private sector and were for outpatient visits (85%). Several public-private differences were observed in annualized expenditures and expenditure components. Logistic regression results indicate males, wealthier individuals, Punjab and Sindh residents, and those in smaller households were more likely to access private outpatient care. In the inpatient model, rural residents were more likely to use a private provider, while Khyber Pakhtunkhwa residents were less likely to use private care. GLM results indicate private sector inpatient expenditures were approximately PKR 6660 (USD 61.8) higher than public sector expenditures, but no public-private differences were observed for outpatient expenditures. Several demographic factors were significantly associated with outpatient and inpatient expenditures. Of note, expenditures increased with increasing wealth, decreased with increasing household size, and differed by province and region.ConclusionsThis is the first study comprehensively investigating how healthcare utilization and OOP expenditures vary by sector, type of care, and socio-economic characteristics in Pakistan. The findings are expected to be particularly useful for the next phase of social health protection programs and supply side reforms, as they highlight sub-populations with higher OOP and private sector utilization.

Dataset Information

Impact of a Value-based Formulary on Medication Utilization, Health Services Utilization, and Expenditures.

Publications

Impact of a Value-based Formulary on Medication Utilization, Health Services Utilization, and Expenditures.

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