Affordability and adherence gains for Medicare Part D low-income subsidy recipients when low-income subsidy benefits expanded in 2024.

BACKGROUND: The lowest-income beneficiaries enrolled in the Medicare Part D prescription drug program receive "full subsidies" that waive the premium and deductible and impose minimal copayments. Those with slightly higher incomes and assets may be eligible for "partial subsidies." Prior to 2024, individuals receiving partial subsidies faced reduced Part D premiums and deductibles and paid 15% coinsurance. Under provisions of the Inflation Reduction Act, recipients of partial subsidies were upgraded to full subsidies beginning in 2024. The objective of this pilot study was to assess whether the new policy is likely to reduce cost-related nonadherence to prescribed medications- a common problem faced by older adults even among those receiving subsidies. OBJECTIVE: To compare cost-related nonadherence among partial- vs full-subsidy recipients with similar characteristics. METHODS: We used 2019 Medicare Current Beneficiary Survey data for the study. The Medicare Current Beneficiary Survey is uniquely suited for this work because it contains administrative data on low-income subsidy enrollment plus extensive survey-based information on financial resources necessary to establish program eligibility and rates of cost-related nonadherence. Explanatory variables included sociodemographic characteristics, economic resources, work status, and health variables. RESULTS: We found that the partial-subsidy group reported significantly more cost-related nonadherence (39% vs 22%; P = 0.01) arising both from a lower propensity to fill some prescriptions (23% vs 12%; P = 0.03) and to more delays in filling others (29% vs 8%; P = 0.03). The differences were more pronounced for women and racial and ethnic minority groups in contrast to men and majority populations, respectively. Because the study samples were small, we could not conduct a detailed regression analysis. CONCLUSIONS: The magnitude of cost-related nonadherence effects associated with partial-subsidy cost sharing suggests that the Inflation Reduction Act policy to expand low-income subsidies may boost medication adherence, most notably among women and racial and ethnic minority groups.

Deductible double jeopardy: patients may pay more out of pocket when pregnancy crosses 2 years.

OBJECTIVES: This study explores the concern that annual high-deductible commercial insurance plan design may yield higher out-of-pocket costs when an episode of maternity care spans 2 years, exposing patients to their cost-sharing limits twice during their episode of care. STUDY DESIGN: Cross-sectional study of Health Care Cost Institute commercial claims. METHODS: The study sample comprises 1,379,300 deliveries among high-deductible health plan enrollees in years 2012 through 2021. Patients' mean cost sharing is calculated across all service types for 3 time periods: (1) delivery hospitalization, (2) maternity episode from 40 weeks prior to delivery hospitalization through 12 weeks after discharge, and (3) extended period spanning 3 years from January of the year before delivery through December of the year after delivery. RESULTS: For each of the 3 episode measurements, mean out-of-pocket spending is highest among those who deliver in January and declines in each subsequent month until August and September (the delivery months with most pregnancy and postpartum periods within the same year), then flattens for the remainder of the year. Mean cost sharing for the maternity episode was $6308 in January and $4998 in December, a difference of $1310. Patients delivering in January also had mean out-of-pocket costs $1491 greater for delivery hospitalization and $1005 greater over the 3-year period than patients delivering in December. CONCLUSIONS: Higher out-of-pocket spending is observed when patients face their cost-sharing limits twice within an episode of maternity care, and this difference persists even when evaluating 3 calendar years of patients' out-of-pocket spending.

Evaluating a novel online behavioural intervention to encourage cost-conscious strategies among US adults with chronic conditions who are enrolled in a high-deductible health plan: a proof-of-concept pilot study.

OBJECTIVES: Patients with chronic conditions enrolled in high-deductible health plans (HDHPs) face cost-related access barriers and high out-of-pocket spending. Our objectives were to develop a novel behavioural intervention to help HDHP enrollees with chronic conditions use cost-conscious strategies and evaluate the intervention's preliminary effectiveness, acceptability and feasibility. DESIGN: Prospective. SETTING: Online (USA). PARTICIPANTS: 36 US adults enrolled in an HDHP through their employer or an exchange with diabetes, hypertension, asthma, coronary artery disease and/or chronic obstructive pulmonary disease. 31/36 participants completed the study. INTERVENTION: We developed a 5-week intervention consisting of a website with educational modules on discussing costs with clinicians, saving for future healthcare costs, comparing healthcare prices and quality, preparing for appointments, following up after appointments and planning for future healthcare needs; and emails encouraging participants to access each module. OUTCOMES: We conducted a single-arm proof-of-concept pilot study of the intervention. Baseline and postintervention surveys measured primary outcomes of health insurance literacy and confidence in using cost-conscious strategies. 10 participants completed postintervention interviews. RESULTS: 31 (86%) participants completed a baseline and postintervention survey. Mean health insurance literacy scores (20-80 scale) improved from 56.5 to 67.1 (p<0.001). Mean confidence scores (0-10 scale) improved for talking to a healthcare provider about cost (6.1-7.6, p=0.0094), saving for healthcare (5.8-6.6, p=0.068), comparing prices (5.4-6.9, p=0.005) and comparing quality (6.1 to 7.6, p=0.0034). Participants found the website easy to use and helpful for learning about cost-conscious strategies on postintervention interviews. CONCLUSIONS: Our novel behavioural intervention was acceptable to HDHP enrollees with chronic conditions, feasible to deliver and associated with increased health insurance literacy and confidence in using cost-conscious strategies. This intervention should be tested in a definitive randomised controlled trial that is fully powered to evaluate its effects on cost-related access barriers, out-of-pocket spending and health outcomes in this growing patient population.

Association of copayments with healthcare utilization and expenditures among Medicaid enrollees with a substance use disorder.

BACKGROUND: The purpose of this study was to examine the association between copayments and healthcare utilization and expenditures among Medicaid enrollees with substance use disorders. METHODS: This study used claims data (2020-2021) from a private insurer participating in Arkansas's Medicaid expansion. We compared service utilization and expenditures for enrollees in different Medicaid program structures with varying copayments. Enrollees with incomes above 100 % FPL (N = 10,240) had copayments for substance use treatment services while enrollees below 100 % FPL (N = 2478) did not. Demographic, diagnostic, utilization, and cost information came from claims and enrollment information. The study identified substance use and clinical comorbidities using claims from July through December 2020 and evaluated utilization and costs in 2021. Generalized linear models (GLM) estimated outcomes using single equation and two-part modeling. A gamma distribution and log link were used to model expenditures, and negative binomial models were used to model utilization. A falsification test comparing behavioral health telemedicine utilization, which had no cost sharing in either group, assessed whether differences in the groups may be responsible for observed findings. RESULTS: Substance use enrollees with copayments were less likely to have a substance use or behavioral health outpatient (-0.04 PP adjusted; p = 0.001) or inpatient visit (-0.04 PP; p = 0.001) relative to their counterparts without copayments, equal to a 17 % reduction in substance use or behavioral health outpatient services and a nearly 50 % reduction in inpatient visits. The reduced utilization among enrollees with a copayment was associated with a significant reduction in total expenses ($954; p = 0.001) and expenses related to substance use or behavioral health services ($532; p = 0.001). For enrollees with at least one behavioral health visit, there were no differences in outpatient or inpatient utilization or expenditures between enrollees with and without copayments. Copayments had no association with non-behavioral health or telemedicine services where neither group had cost sharing. CONCLUSION: Copayments serve as an initial barrier to substance use treatment, but are not associated with the amount of healthcare utilization conditional on using services. Policy makers and insurers should consider the role of copayments for treatment services among enrollees with substance use disorders in Medicaid programs.

Do high-deductible health plans affect price paid for childbirth?

OBJECTIVE: To test whether out-of-pocket costs and negotiated hospital prices for childbirth change after enrollment in high-deductible health plans (HDHPs) and whether price effects differ in markets with more hospitals. DATA SOURCES: Administrative medical claims data from 2010 to 2014 from three large commercial insurers with plans in all U.S. states provided by the Health Care Cost Institute (HCCI). STUDY DESIGN: I identify employer groups that switched from non-HDHPs in 1 year to HDHPs in a subsequent year. I estimate enrollees' change in out-of-pocket costs and negotiated hospital prices for childbirth after HDHP switch, relative to a comparison group of employers that do not switch plans. I use a triple-difference design to estimate price changes for enrollees in markets with more hospital choices. Finally, I re-estimate models with hospital-fixed effects. DATA COLLECTION: From the HCCI sample, childbearing women enrolled in an employer-sponsored plan with at least 10 people. PRINCIPAL FINDINGS: Switching to an HDHP increases out-of-pocket cost $227 (p < 0.001; comparison group base $790) and has no meaningful effect on hospital-negotiated prices (-$26, p = 0.756; comparison group base $5821). HDHP switch is associated with a marginally statistically significant price increase in markets with three or fewer hospitals ($343, p = 0.096; comparison group base $5806) and, relative to those markets, with a price decrease in markets with more than three hospitals (-$512; p = 0.028). Predicted prices decrease from $5702 to $5551 after HDHP switch in markets with more than three hospitals due primarily to lower prices conditional on using the same hospital. CONCLUSIONS: Prices for childbirth in markets with more hospitals decrease after HDHP switch due to lower hospital prices for HDHPs relative to prices at those same hospitals for non-HDHPs. These results reinforce previous findings that HDHPs do not promote price shopping but suggest negotiated prices may be lower for HDHP enrollees.

Trend and effects of high-deductible health insurance plans in the health care system: financial access problems in management of cognitive impairment.

BACKGROUND: High-deductible health plans (HDHPs) are characterized by higher deductibles and lower monthly premiums compared with a typical health plan. HDHPs may reduce, or delay, needed care, which will ultimately lead to poorer access to care for chronically affected participants. OBJECTIVES: To (1) investigate the HDHP enrollment trend and (2) determine the effects of HDHPs on financial access problems for individuals with self-reported cognitive impairment. METHODS: Data between 2010 and 2018 were obtained from the National Health Interview Survey (NHIS). Individuals with cognitive impairment were identified if they were limited by memory difficulties. Problems regarding financial access to health care were assessed based on 6 survey questions from the Centers for Disease Control and Prevention. Multivariable logistic regressions were implemented to evaluate the effects of HDHPs. RESULTS: This study identified 1,148 individuals with cognitive impairment, representing 3.9 million individuals in the United States from 2010 to 2018. A nearly 2-fold increase in HDHP enrollment with cognitive impairment was observed from 2010 (20.9%) to 2018 (41.9%). This increase is similar to that reported for noncognitively impaired individuals. After controlling for possible confounding variables, cognitively impaired individuals with HDPHs were more likely to have overall financial access difficulties compared with those without HDHPs (OR = 1.17, 95% CI = 0.88-1.56, P = 0.271), but this likelihood was not statistically significant. CONCLUSIONS: HDHPs are intended to support effective care options and reduce health care costs. However, our research found that among individuals with cognitive impairment, those with HDHPs experienced some financial access problems, such as affording medical care, follow-up care, and specialists, than those without HDHPs, indicating that HDHPs might have unintended consequences for health care usage. DISCLOSURES: No outside funding supported this study. The authors have no conflicts of interest or financial interests to disclose.

Accuracy of Physician Estimates of Out-of-Pocket Costs for Medication Filling.

Importance: One-third of US residents have trouble paying their medical bills. They often turn to their physicians for help navigating health costs and insurance coverage. Objective: To determine whether physicians can accurately estimate out-of-pocket expenses when they are given all of the necessary information about a drug's price and a patient's insurance plan. Design, Setting, and Participants: This national mail-in survey used a random sample of US physicians. The survey was sent to 900 outpatient physicians (300 each of primary care, gastroenterology, and rheumatology). Physicians were excluded if they were in training, worked primarily for the Veterans Administration or Indian Health Service, were retired, or reported 0% outpatient clinical effort. Analyses were performed from July to December 2020. Main Outcomes and Measures: In a hypothetical vignette, a patient was prescribed a new drug costing $1000/month without insurance. A summary of her private insurance information was provided, including the plan's deductible, coinsurance rates, copays, and out-of-pocket maximum. Physicians were asked to estimate the drug's out-of-pocket cost at 4 time points between January and December, using the plan's 4 types of cost-sharing: (1) deductibles, (2) coinsurance, (3) copays, and (4) out-of-pocket maximums. Multivariate linear regression was used to assess differences in performance by specialty, adjusting for attitudes toward cost conversations, demographics, and clinical characteristics. Results: The response rate was 45% (405 of 900) and 371 respondents met inclusion criteria. Among the respondents included in this study, 59% (n = 220) identified as male, 23% (n = 84) as Asian, 3% (n = 12) as Black, 6% (n = 24) as Hispanic, and 58% (n = 216) as White; 30% (n = 112) were primary care physicians, 35% (n = 128) were gastroenterologists, and 35% (n = 131) were rheumatologists; and the mean (SD) age was 49 (10) years. Overall, 52% of physicians (n = 192) accurately estimated costs before the deductible was met, 62% (n = 228) accurately used coinsurance information, 61% (n = 224) accurately used copay information, and 57% (n = 210) accurately estimated costs once the out-of-pocket maximum was met. Only 21% (n = 78) of physicians answered all 4 questions correctly. Ability to estimate out-of-pocket costs was not associated with specialty, attitudes toward cost conversations, or clinic characteristics. Conclusions and Relevance: This survey study found that many US physicians have difficulty estimating out-of-pocket costs, even when they have access to their patients' insurance plans. The mechanics involved in calculating real-time out-of-pocket costs are complex. These findings suggest that increased price transparency and simpler insurance cost-sharing mechanisms are needed to enable informed cost conversations at the point of prescribing.

Financial Burden of Discarded Weight-based Antineoplastic Drugs to Payers and Patients in the Private Insurance Market.

Background: Our study estimated insurance payments and patient out-of-pocket (OOP) expenses associated with discarded weight-based intravenous antineoplastic drugs for privately insured US adult patients with cancer. Methods: We identified patients who received weight-based antineoplastic drugs from a 2017 MarketScan health risk assessment (IBM Corp, Armonk, NY) linked to claims data. Using weight information in the health risk assessment, we derived the recommended dose and calculated the percentage of drugs discarded. We applied ß-regression to determine factors associated with the discarded percentages. To compare patients with and without high-deductible plans, we employed a generalized linear model and a 2-part model to examine insurance payment and OOP expense, respectively. All statistical tests were 2-sided. Results: Of 27 350 claims for 58 weight-based antineoplastic drugs from 1970 patients, the median discarded percentage was 9.8% (mean [SD] = 12.8% [10.5%]). Aside from drug and tumor type, statistically significantly higher discarded percentages were found for patients in the lowest weight group (5.5% [95% confidence interval = 4.7% to 6.4%]; P < .001; weight <150 lb [68.0 kg] vs ≥200 lb [90.7 kg]). Private payers spent $5090 per patient in 2017 on discarded weight-based antineoplastic drugs, and patients' mean OOP expense on discarded drugs was $63. In total, 39.7% of patients had high-deductible plans. The adjusted mean OOP expense for discarded drugs was statistically significantly higher for those in high-deductible plans ($95 vs $47; P < .001). Conclusions: Private insurers incurred substantial financial burden from discarded weight-based antineoplastic drugs. Although the OOP expenses of discarded drugs were modest for most privately insured patients with cancer, approximately 5% spent more than $400 on the discarded drugs. Policies designed to reduce drug waste from single-dose, weight-based antineoplastic drugs should evaluate their financial consequences for payers and patients.

Federal Out-of-Network Balance Billing Legislation: Context and Implications for Radiology Practices.

Out-of-network (OON) balance billing, commonly known as surprise billing but better described as a surprise gap in health insurance coverage, occurs when an individual with private health insurance (vs a public insurer such as Medicare) is administered unanticipated care from a physician who is not in their health plan's network. Such unexpected OON care may result in substantial out-of-pocket costs for patients. Although ending surprise billing is patient centric, patient protective, and noncontroversial, passing federal legislation was challenging given its ability to disrupt insurer-physician good-faith negotiations and thus impact in-network rates. Like past proposals, the recently passed No Surprises Act takes patients out of the middle of insurer-physician OON reimbursement disputes, limiting patients' expense to standard in-network cost-sharing amounts. The new law, based on arbitration, attempts to protect good-faith negotiations between physicians and insurance companies and encourages network contracting. Radiology practices, even those that are fully in network or that never practiced surprise billing, could nonetheless be affected. Ongoing rulemaking processes will have meaningful roles in determining how the law is made operational. Physician and stakeholder advocacy has been and will continue to be crucial to the ongoing evolution of this process. © RSNA, 2021.

Association of Branded Prescription Drug Rebate Size and Patient Out-of-Pocket Costs in a Nationally Representative Sample, 2007-2018.

Importance: Over the past decade, branded prescription drug manufacturers have substantially increased list prices while offering larger rebate payments to health care insurers. Whereas larger rebates can partially offset increases in list prices for insurers, patient out-of-pocket costs may be directly associated with list prices for individuals without insurance and indirectly associated with list prices for individuals with insurance through deductibles or coinsurance. Objective: To investigate the association between rebates and patient out-of-pocket costs and whether this association differs by coverage type (ie, Medicare, commercial, or uninsured) and before and after 2014. Design, Setting, and Participants: This cross-sectional study was conducted using data from the Medical Expenditure Panel Survey (MEPS) combined with pricing data for single-source branded drugs from SSR Health from 2007 through 2018. The study was conducted among a nationally representative sample of the noninstitutionalized civilian US population. Included individuals were respondents to MEPS with at least 1 prescription for a single-source branded drug who were covered by Medicare or commercial insurance or were uninsured during an entire year. Data analyses were conducted from August 2019 through March 2021. Exposures: Estimated rebate size. Main Outcomes and Measures: Out-of-pocket costs per prescription were calculated, adjusting for year and drug. Results: Among 38 131 individuals with at least 1 prescription, the mean age was 54 years (95% CI, 54 to 55 years), with 22 044 women (57.8%) and 29 086 White individuals (76.3%). The sample included 444 unique drugs with a survey-weighted total of 4.7 billion prescriptions. Estimated mean (SE) rebates increased from $34 ($1) per prescription in 2007 to $374 ($9) per prescription in 2018. The rebate sizes were associated with statistically significant mean out-of-pocket increases per branded prescription of $4 (95% CI, $4 to $4) from 2007 to 2013 and $11 (95% CI, $10 to $12) from 2014 to 2018. From 2014 to 2018, rebate sizes were associated with statistically significant mean increases in out-of-pocket costs per prescription of $13 (95% CI, $12 to $13) for individuals with Medicare, $6 (95% CI, $6 to $7) for individuals with commercial insurance, and $39 (95% CI, $34 to $44) for individuals without insurance. After adjusting for list prices, there was no association between rebates and out-of-pocket costs, with a change from 2014 to 2018 of -$0.01 (95% CI, -$0.04 to $0.02). Conclusions and Relevance: These findings suggest that drug manufacturers may have provided larger rebates to insurers primarily by increasing list prices and that individuals without insurance had greater cost increases. The results emphasize the need for policy solutions that decouple list prices and out-of-pocket costs.

Non-warfarin oral anticoagulant copayments and adherence in atrial fibrillation: A population-based cohort study.

BACKGROUND: In patients with atrial fibrillation, incomplete adherence to anticoagulants increases risk of stroke. Non-warfarin oral anticoagulants (NOACs) are expensive; we evaluated whether higher copayments are associated with lower NOAC adherence. METHODS: Using a national claims database of commercially-insured patients, we performed a cohort study of patients with atrial fibrillation who newly initiated a NOAC from 2012 to 2018. Patients were stratified into low (<$35), medium ($35-$59), or high (≥$60) copayments and propensity-score weighted based on demographics, insurance characteristics, comorbidities, prior health care utilization, calendar year, and the NOAC received. Follow-up was 1 year, with censoring for switching to a different anticoagulant, undergoing an ablation procedure, disenrolling from the insurance plan, or death. The primary outcome was adherence, measured by proportion of days covered (PDC). Secondary outcomes included NOAC discontinuation (no refill for 30 days after the end of NOAC supply) and switching anticoagulants. We compared PDC using a Kruskal-Wallis test and rates of discontinuation and switching using Cox proportional hazards models. RESULTS: After weighting patients across the 3 copayment groups, the effective sample size was 17,558 patients, with balance across 50 clinical and demographic covariates (standardized differences <0.1). Mean age was 62 years, 29% of patients were female, and apixaban (43%), and rivaroxaban (38%) were the most common NOACs. Higher copayments were associated with lower adherence (P < .001), with a PDC of 0.82 (Interquartile range [IQR] 0.36-0.98) among those with high copayments, 0.85 (IQR 0.41-0.98) among those with medium copayments, and 0.88 (IQR 0.41-0.99) among those with low copayments. Compared to patients with low copayments, patients with high copayments had higher rates of discontinuation (hazard ratio [HR] 1.13, 95% confidence interval [CI] 1.08-1.19; P < .001). CONCLUSIONS: Among atrial fibrillation patients newly initiating NOACs, higher copayments in commercial insurance were associated with lower adherence and higher rates of discontinuation in the first year. Policies to lower or limit cost-sharing of important medications may lead to improved adherence and better outcomes among patients receiving NOACs.

Patient preferences for provider choice: a discrete choice experiment.

OBJECTIVES: There is an ongoing policy discussion regarding an adequate breadth of provider networks. Health plans with "restricted networks" of providers have proved surprisingly popular on the Affordable Care Act health insurance exchanges because of a substantial gap in premiums between plans with open networks and closed networks. The objective of this paper is to assess which other attributes of the provider network matter to patients when choosing health insurance. STUDY DESIGN: We used a discrete choice experiment to analyze the effect of previously unobserved characteristics regarding provider networks on plan choice, including wait time, breadth, travel time, whether the plan covers care for their personal doctor, and monthly premium. Hypothetical plan options were offered to respondents of an online survey using Qualtrics software. METHODS: We used mixed multinomial logit models to estimate preference-based utilities for attributes of primary care provider networks and willingness to pay. RESULTS: Coverage of a personal doctor was the most important attribute, followed by premium, wait time to see a primary care provider, the breadth of the network, and travel time to the closest doctor covered by the plan. Respondents were willing to pay $95 per month to have a plan that covers care for their personal doctor, and they were willing to wait 6 days for an appointment to have a plan covering care for their personal doctor. CONCLUSIONS: The results of this study provide new insights to federal and state legislators developing new models or standards on network adequacy and patient decision support tools.

Effect of high-deductible insurance on health care use in bipolar disorder.

OBJECTIVES: To determine the impact of high-deductible health plans (HDHPs) on health care use among individuals with bipolar disorder. STUDY DESIGN: Interrupted time series with propensity score-matched control group design, using a national health insurer's claims data set with medical, pharmacy, and enrollment data. METHODS: The intervention group was composed of 2862 members with bipolar disorder who were enrolled for 1 year in a low-deductible (≤$500) plan and then 1 year in an HDHP (≥$1000) after an employer-mandated switch. HDHP members were propensity score matched 1:3 to contemporaneous controls in low-deductible plans. The main outcomes included out-of-pocket spending per health care service, mental health-related outpatient visits (subclassified as visits to nonpsychiatrist mental health providers and to psychiatrists), emergency department (ED) visits, and hospitalizations. RESULTS: Mean pre- to post-index date out-of-pocket spending per visit on all mental health office visits, nonpsychiatrist mental health provider visits, and psychiatrist visits increased by 21.9% (95% CI, 15.1%-28.6%), 33.8% (95% CI, 2.0%-65.5%), and 17.8% (95% CI, 12.2%-23.4%), respectively, among HDHP vs control members. The HDHP group experienced a -4.6% (95% CI, -11.7% to 2.5%) pre- to post change in mental health outpatient visits relative to controls, a -10.9% (95% CI, -20.6% to -1.3%) reduction in nonpsychiatrist mental health provider visits, and unchanged psychiatrist visits. ED visits and hospitalizations were also unchanged. CONCLUSIONS: After a mandated switch to HDHPs, members with bipolar disorder experienced an 11% decline in visits to nonpsychiatrist mental health providers but unchanged psychiatrist visits, ED visits, and hospitalizations. HDHPs do not appear to have a "blunt instrument" effect on health care use in bipolar disorder; rather, patients might make trade-offs to preserve important care.

Value-based insurance design in Louisiana: Blue Cross Blue Shield's Zero Dollar Co-pay program.

OBJECTIVES: To determine whether a program that eliminated pharmacy co-pays, the Blue Cross Blue Shield of Louisiana (BCBSLA) Zero Dollar Co-pay (ZDC) program, decreased health care spending. Previous studies have found that value-based insurance designs like the ZDC program have little or no impact on total health care spending. ZDC included an expansive set of medications related to 4 chronic diseases rather than a limited set of medications for 1 or 2 chronic diseases. Additionally, ZDC focused on the most at-risk patients. STUDY DESIGN: ZDC began in 2014 and enrolled patients over time based on (1) when a patient answered a call from a nurse care manager and (2) when a patient or their employer changed the benefit structure to meet the program criteria. During 2015 and 2016, 265 patients with at least 1 chronic condition (asthma, diabetes, hypertension, mental illness) enrolled in ZDC. METHODS: Observational study using within-patient variation and variation in patient enrollment month to identify the impact of the ZDC program on health spending measures. We used 100% BCBSLA claims data from January 2015 to June 2018. Monthly level event studies were used to test for differential spending patterns prior to ZDC enrollment. RESULTS: We found that total spending decreased by $205.9 (P = .049) per member per month, or approximately 18%. We saw a decrease in medical spending ($195.0; P = .023) but did not detect a change in pharmacy spending ($7.59; P = .752). We found no evidence of changes in spending patterns prior to ZDC enrollment. CONCLUSIONS: The ZDC program provides evidence that value-based insurance designs that incorporate a comprehensive set of medications and focus on populations with chronic disease can reduce spending.

Exploring factors that influence positive WOM in the health insurance industry.

Health insurance companies have an interest in understanding what factors may lead to positive word-of-mouth (WOM) from consumers. This research identifies factors that influence positive WOM about health insurance firms. Using data collected from 425 insurance policy holders, we find influential factors vary depending on the purchase source. Significant factors identified in the study that influence positive word-of-mouth include service quality, plan satisfaction, and plan type (individual vs. family). Further, claim count, preferred information source, and deductible levels also affect the spread of positive WOM differently among purchase sources. The study concludes with a discussion of implications and future research.

Impact of a Copayment Reduction Intervention on Medication Persistence and Cardiovascular Events in Hospitals With and Without Prior Medication Financial Assistance Programs.

Background Hospitals commonly provide a short-term supply of free P2Y12 inhibitors at discharge after myocardial infarction, but it is unclear if these programs improve medication persistence and outcomes. The ARTEMIS (Affordability and Real-World Antiplatelet Treatment Effectiveness After Myocardial Infarction Study) trial randomized hospitals to usual care versus waived P2Y12 inhibitor copayment costs for 1-year post-myocardial infarction. Whether the impact of this intervention differed between hospitals with and without pre-existing medication assistance programs is unknown. Methods and Results In this post hoc analysis of the ARTEMIS trial, we examined the associations of pre-study free medication programs and the randomized copayment voucher intervention with P2Y12 inhibitor persistence (measured by pharmacy fills and patient report) and major adverse cardiovascular events using logistic regression models including a propensity score. Among 262 hospitals, 129 (49%) offered pre-study free medication assistance. One-year P2Y12 inhibitor persistence and major adverse cardiovascular events risks were similar between patients treated at hospitals with and without free medication programs (adjusted odds ratio 0.93, 95% CI, 0.82-1.05 and hazard ratio 0.92, 95% CI, 0.80-1.07, respectively). The randomized copayment voucher intervention improved persistence, assessed by pharmacy fills, in both hospitals with (53.6% versus 44.0%, adjusted odds ratio 1.45, 95% CI, 1.20-1.75) and without (59.0% versus 48.3%, adjusted odds ratio 1.46, 95% CI, 1.25-1.70) free medication programs (Pinteraction=0.71). Differences in patient-reported persistence were not significant after adjustment. Conclusions While hospitals commonly report the ability to provide free short-term P2Y12 inhibitors, we did not find association of this with medication persistence or major adverse cardiovascular events among patients with insurance coverage for prescription medication enrolled in the ARTEMIS trial. An intervention that provided copayment assistance vouchers for 1 year was successful in improving medication persistence in hospitals with and without pre-existing short-term medication programs. Registration URL: https://www.clini​caltr​ials.gov/. Unique identifier: NCT02406677.

Expand predeductible coverage without increasing premiums or deductibles.

Innovative, cost-neutral plan designs that cover more essential services on a predeductible basis, while decreasing exposure to and spending on harmful care, would better meet the clinical and financial needs of millions of Americans.