Commercial Insurer Market Power and Medicaid Managed Care Networks.

Over 70% of Medicaid beneficiaries are enrolled in Medicaid managed care (MMC). MMC provider networks therefore represent a critical determinant of access to the Medicaid program. Many MMC insurers also participate in commercial insurance markets where prices are high, and some insurers exercise considerable market power. In this paper, we examined the relationship between commercial insurer market power and MMC physician network breadth using linked national enrollment data and provider directory data. Insurers with more commercial market power had broader Medicaid physician networks. Insurers with over 30% market share had 37.3% broader Medicaid networks than insurers in the same county that had no commercial market share. These differences were driven by greater breadth among primary care providers, as well as other specialists including OB/GYNs, surgeons, neurologists, and cardiologists. Commercial insurance market power may have spillovers on access to care for MMC beneficiaries.

Changes in Healthcare Spending Attributable to High Deductible Health Plan Offer Among Enrollees with Comorbid Substance Use Disorder and Cardiovascular Disease.

BACKGROUND: The rise in prevalence of high deductible health plans (HDHPs) in the United States may raise concerns for high-need, high-utilization populations such as those with comorbid chronic conditions. In this study, we examine changes in total and out-of-pocket (OOP) spending attributable to HDHPs for enrollees with comorbid substance use disorder (SUD) and cardiovascular disease (CVD). METHODS: We used de-identified administrative claims data from 2007 to 2017. SUD and CVD were defined using algorithms of ICD 9 and 10 codes and HEDIS guidelines. The main outcome measures of interest were spending measure for all non-SUD/CVD-related services, SUD-specific services, and CVD-specific services, for all services and medications specifically. We assessed both total and OOP spending. We used an intent-to-treat two-part model approach to model spending and computed the marginal effect of HDHP offer as both the dollar change and percent change in spending attributable to HDHP offer. RESULTS: Our sample included 33,684 enrollee-years and was predominantly white and male with a mean age of 53 years. The sample had high demonstrated substantial healthcare utilization with 94% using any non-SUD/CVD services, and 84% and 78% using SUD and CVD services, respectively. HDHP offer was associated with a 17.0% (95% CI = [0.07, 0.27] increase in OOP spending for all non-SUD/CVD services, a 21.1% (95% CI = [0.11, 0.31]) increase in OOP spending for all SUD-specific services, and a 13.1% (95% CI = [0.04, 0.23]) increase in OOP spending for all CVD-specific services. HDHP offer was also associated with a significant increase in OOP spending on non-SUD/CVD-specific medications and SUD-specific medications, but not CVD-specific medications. CONCLUSIONS: This study suggests that while HDHPs do not change overall levels of annual spending among enrollees with comorbid CVD and SUD, they may increase the financial burden of healthcare services by raising OOP costs, which could negatively impact this high-need and high-utilization population.

Deductible imputation in administrative medical claims datasets.

OBJECTIVE: To validate imputation methods used to infer plan-level deductibles and determine which enrollees are in high-deductible health plans (HDHPs) in administrative claims datasets. DATA SOURCES AND STUDY SETTING: 2017 medical and pharmaceutical claims from OptumLabs Data Warehouse for US individuals <65 continuously enrolled in an employer-sponsored plan. Data include enrollee and plan characteristics, deductible spending, plan spending, and actual plan-level deductibles. STUDY DESIGN: We impute plan deductibles using four methods: (1) parametric prediction using individual-level spending; (2) parametric prediction with imputation and plan characteristics; (3) highest plan-specific mode of individual annual deductible spending; and (4) deductible spending at the 80th percentile among individuals meeting their deductible. We compare deductibles' levels and categories for imputed versus actual deductibles. DATA COLLECTION/EXTRACTION METHODS: Not applicable. PRINCIPAL FINDINGS: All methods had a positive predictive value (PPV) for determining high- versus low-deductible plans of ≥87%; negative predictive values (NPV) were lower. The method imputing plan-specific deductible spending modes was most accurate and least computationally intensive (PPV: 95%; NPV: 91%). This method also best correlated with actual deductible levels; 69% of imputed deductibles were within $250 of the true deductible. CONCLUSIONS: In the absence of plan structure data, imputing plan-specific modes of individual annual deductible spending best correlates with true deductibles and best predicts enrollees in HDHPs.

Enrollment Trends In Self-Funded Employer-Sponsored Insurance, 2015 And 2021.

The share of employer-sponsored health insurance enrollment in self-funded plans grew from 55 percent in 2015 to 60 percent in 2021. Growth was concentrated in states with an initially low share but was widespread across most states (88.0 percent saw growth) and counties (78.2 percent saw growth). There were substantial differences in plan types in the self-funded and fully insured markets.

Do Insurers With Greater Market Power Negotiate Consistently Lower Prices for Hospital Care? Evidence From Hospital Price Transparency Data.

This study examined if greater insurer market power was associated with consistently lower negotiated prices within each hospital for 44 shoppable and emergency procedures, using price transparency data disclosed by 1,506 hospitals in metropolitan areas. We used multi-level fixed effects models to estimate the within-hospital variation in plan-level insurer-negotiated prices (from the largest insurer, the second largest insurer, other major insurers, and nonmajor insurers) and cash-pay prices as a function of insurer market power. For shoppable services, relative to nonmajor insurers, the largest, second largest, and other major insurers negotiated 23%, 16%, and 3% lower prices, respectively, while cash prices were 17% higher. For emergency room visits, while the largest insurers paid 5% less than nonmajor insurers, the second largest and other major insurers did not pay lower prices. Stratified analyses by type of shoppable services found varying magnitudes and patterns of price discounts associated with insurer market power.

Hospital Prices in Medicaid Managed Care.

This cross-sectional study uses hospitals' self-disclosed pricing information to characterize Medicaid managed care hospital prices.

Do minimum wage laws affect employer-sponsored insurance provision?

Employers may respond to minimum wage increases by adjusting their health benefits. We examine the impact of state minimum wage increases on employer health benefit offerings using the 2002-2020 Medical Expenditure Panel Survey - Insurance/Employer Component data. Our primary regression specifications are difference-in-differences models that estimate the relationship between within-state changes in employer-sponsored insurance and minimum wage laws over time. We find that a $1 increase in minimum wages is associated with a 0.92 percentage point (p.p.) decrease in the percentage of employers offering health insurance, largely driven by small employers and employers with a greater share of low-wage employees. A $1 increase is also associated with a 1.83 p.p. increase in the prevalence of plans with a deductible requirement, but we do not find consistent evidence that other benefit characteristics are affected. We find no consequent change in uninsurance, likely explained by an increase in Medicaid enrollment.

Trends in Medicare Advantage participation among commercial insurers.

OBJECTIVES: Commercial health insurers can participate in the rapidly growing Medicare Advantage (MA) market, which may affect network formation and prices in traditional commercial insurance markets. We aim to quantify the prevalence and growth of commercial insurers participating in MA within the same state. STUDY DESIGN: Repeated cross-sectional analysis of Clarivate's Interstudy enrollment data comprising the universe of insurers in the United States from 2015 to 2021. METHODS: We calculated the share of employer-sponsored insurance (ESI) enrollees covered by an insurer offering MA in their state in 2015, 2017, 2019, and 2021. We documented this share across states, years, and the state's 2015 tercile. RESULTS: Between 2015 and 2021, the share of ESI enrollees covered by an insurer offering MA in the same state increased from 83.5% to 95.3%. This growth was concentrated in states with initially low rates in 2015 (lowest 2015 state tercile, ≤ 70.5%), in which the share grew from 47.6% to 87.9%. In 2015, 23.5% of states had a share greater than 90.0% compared with 74.5% in 2021. CONCLUSIONS: By 2021, almost all ESI enrollees were covered by insurers who participated in MA in the same state. Future research should investigate how insurer participation in MA affects network formation and prices in commercial markets.

Choice of high-deductible health plans among enrollees with a substance use disorder.

INTRODUCTION: High-deductible health plans (HDHPs) expose enrollees to increased out-of-pocket costs for their medical care, which can exacerbate the undertreatment of substance use disorders (SUDs). However, the factors that influence whether an enrollee with SUD chooses an HDHP are not well understood. In this study, we examine the factors associated with an individual with an SUD's decision to enroll in an HDHP. METHODS: Using de-identified administrative commercial claims and enrollment data from OptumLabs (2007-2017), we identified individuals at employers offering at least one HDHP and one non-HDHP plan. We modeled whether an enrollee chose an HDHP using linear regression on plan and enrollee demographic characteristics. Key plan characteristics included whether a plan had a health savings account (HSA) or a health reimbursement arrangement (HRA). Key demographic variables included age, race/ethnicity, census block income range, census block highest educational attainment, and sex. We separately investigate new enrollment decisions (i.e., not previously enrolled in an HDHP) and re-enrollment decisions, as well as decisions among single enrollees and families of differing sizes. The study also adjusted models for additional plan characteristics, employer and year fixed effects, and census division. Robust standard errors were clustered at the employer level. RESULTS: The sample comprised 30,832 plans and 318,334 enrollees. Among enrollees with new enrollment decisions, 24.6 % chose an HDHP; 93.8 % of HDHP enrollees chose to re-enroll in an HDHP. The study found the presence of a plan HRA to be associated with a higher probability of new and re-enrollment in an HDHP. We found that older enrollees with SUD were less likely to newly enroll in an HDHP, while enrollees who were non-White, living in lower-income census blocks, and living in lower educational attainment census blocks were more likely to newly enroll in an HDHP. Higher levels of health care utilization in the prior year were associated with a lower probability of newly enrolling in an HDHP but associated with a higher probability of re-enrolling. CONCLUSION: Given the emerging evidence that HDHPs may discourage SUD treatment, greater HDHP enrollment could exacerbate health disparities.

Hospital Prices For Commercial Plans Are Twice Those For Medicare Advantage Plans When Negotiated By The Same Insurer.

Most major insurers operate in both the commercial health insurance and Medicare Advantage (MA) markets. We investigated the ratio of commercial-to-MA prices negotiated by the same insurer, in the same hospital and for the same services, using 2022 price information disclosed by hospitals in compliance with the hospital price transparency rule. Insurers negotiated median hospital prices for commercial plans that were two to three times higher than their MA prices in the same hospital for the same service. The median commercial-to-MA price ratio in the same hospital varied, from 1.8 for surgery and medicine services to 2.2 for laboratory tests and emergency department visits and 2.4 for imaging services. In multivariable Poisson regression analysis, higher ratios were associated with system-affiliated, nonprofit, and teaching hospitals, as well as with large national insurers. These findings reflect the differences in financial incentives and regulatory policies in the commercial and MA markets. Because insurers respond to differing incentives by obtaining different negotiated prices across markets, policy and practice efforts that alter incentives for insurers may have the potential to lower commercial prices.

Psychiatrist Networks In Medicare Advantage Plans Are Substantially Narrower Than In Medicaid And ACA Markets.

Medicare Advantage now covers twenty-eight million older adults, many of whom have mental health needs. Enrollees are often restricted to providers who participate in a health plan's network, which may present a barrier to care. We used a novel data set linking network service areas, plans, and providers to compare psychiatrist network breadth-the percentage of providers in a given area that are considered "in network" for a plan-across Medicare Advantage, Medicaid managed care, and Affordable Care Act plan markets. We found that nearly two-thirds of psychiatrist networks in Medicare Advantage were narrow (that is, they contained fewer than 25 percent of providers in a network's service area) compared with approximately 40 percent in Medicaid managed care and Affordable Care Act plan markets. We did not observe similar differences in network breadth for primary care physicians or other physician specialists across markets. Amid efforts to strengthen network adequacy, our findings suggest that psychiatrist networks in Medicare Advantage are particularly narrow, which may disadvantage enrollees as they attempt to obtain mental health services.

High-deductible Health Plans and Nonfatal Opioid Overdose.

OBJECTIVES: Opioid-related overdose is a public health emergency in the United States. Meanwhile, high-deductible health plans (HDHPs) have become more prevalent in the United States over the last 2 decades, raising concern about their potential for discouraging high-need populations, like those with opioid use disorder (OUD), from engaging in care that may mitigate the probability of overdose. This study assesses the impact of an employer offering an HDHP on nonfatal opioid overdose among commercially insured individuals with OUD in the United States. RESEARCH DESIGN: We used deidentified insurance claims data from 2007 to 2017 with 97,788 person-years. We used an intent-to-treat, difference-in-differences regression framework to estimate the change in the probability of a nonfatal opioid overdose among enrollees with OUD whose employers began offering an HDHP insurance option during the study period compared with the change among those whose employer never offered an HDHP. We also used an event-study model to account for dynamic time-varying treatment effects. RESULTS: Across both comparison and treatment groups, 2% of the sample experienced a nonfatal opioid overdose during the study period. Our primary model and robustness checks revealed no impact of HDHP offer on the probability of a nonfatal overdose. CONCLUSIONS: Our study suggests that HDHP offer was not associated with an observed increase in the probability of nonfatal opioid overdose among commercially insured person-years with OUD. However, given the strong evidence that medications for OUD (MOUD) can reduce the risk of overdose, research should explore which facets of insurance design may impact MOUD use.

Do High-Deductible Health Plans Incentivize Changing the Timing of Substance Use Disorder Treatment?

A high-deductible health plan (HDHP) may incentivize enrollees to limit health care use at the beginning of a plan year, when they are responsible for 100% of costs, or to increase the use of care at the end of the year, when enrollees may have less cost exposure. We investigated both the impact of the deductible reset that occurs at the beginning of a plan year and the option to enroll in an HDHP on the use of substance use disorder (SUD) treatment services over the course of a health plan year. We found decreases in SUD treatment use following the increase in cost exposure related to a deductible reset. There was no variation in this behavior between HDHP offer enrollees and comparison enrollees who were not offered an HDHP. These findings reinforce that cost-sharing poses a barrier to SUD care and continuity of care, which can increase the risk of adverse clinical outcomes.

Impact of High Deductible Health Plans on U.S. Adults With Chronic Pain.

INTRODUCTION: Chronic pain affects an estimated 20% of U.S. adults. Because high-deductible health plans have captured a growing share of the commercial insurance market, it is unknown how high-deductible health plans impact care for chronic pain. METHODS: Using 2007-2017 claims data from a large national commercial insurer, statistical analyses conducted in 2022-2023 estimated changes in enrollee outcomes before and after their firm began offering a high-deductible health plan compared with changes in outcomes in a comparison group of enrollees at firms never offering a high-deductible health plan. The sample included 757,530 commercially insured adults aged 18-64 years with headache, low back pain, arthritis, neuropathic pain, or fibromyalgia. Outcomes, measured at the enrollee year level, included the probability of receiving any chronic pain treatment, nonpharmacologic pain treatment, and opioid and nonopioid prescriptions; the number of nonpharmacologic pain treatment days; number and days' supply of opioid and nonopioid prescriptions; and total annual spending and out-of-pocket spending. RESULTS: High-deductible health plan offer was associated with a 1.2 percentage point reduction (95% CI= -1.8, -0.5) in the probability of any chronic pain treatment and an $11 increase (95% CI=$6, $15) in annual out-of-pocket spending on chronic pain treatments among those with any use, representing a 16% increase in average annual out-of-pocket spending over the pre-high deductible health plan offer annual average. Results were driven by changes in nonpharmacologic treatment use. CONCLUSIONS: By reducing the use of nonpharmacologic chronic pain treatments and marginally increasing out-of-pocket costs among those using these services, high-deductible health plans may discourage more holistic, integrated approaches to caring for patients with chronic pain conditions.

State Policy and the Breadth of Buprenorphine-Prescriber Networks in Medicaid Managed Care.

Provider networks in Medicaid Managed Care (MMC) play a crucial role in ensuring access to buprenorphine, a highly effective treatment for opioid use disorder. Using a difference-in-differences approach that compares network breadth across provider specialties and market segments within the same state, we investigated the association between three Medicaid policies and the breadth of MMC networks for buprenorphine prescribers: Medicaid expansion, substance use disorder (SUD) network adequacy criteria, and SUD carveouts. We found that both Medicaid expansion and SUD network adequacy criteria were associated with substantially increased breadth in buprenorphine-prescriber networks in MMC. In both cases, we found that the associations were largely driven by increases in the network breadth of primary care physician prescribers. Our findings suggest that Medicaid expansion and SUD network adequacy criteria may be effective strategies at states' disposal to improve access to buprenorphine.

The Relationships Among Cash Prices, Negotiated Rates, And Chargemaster Prices For Shoppable Hospital Services.

Hospitals must disclose their cash prices, commercial negotiated rates, and chargemaster prices for seventy common, shoppable services under the hospital price transparency rule. Examining prices reported by 2,379 hospitals as of September 9, 2022, we found that a given hospital's cash prices and commercial negotiated rates both tended to reflect a predetermined and consistent percentage discount from its chargemaster prices. On average, cash prices and commercial negotiated rates were 64 percent and 58 percent of the corresponding chargemaster prices for the same procedures at the same hospital and in the same service setting, respectively. Cash prices were lower than the median commercial negotiated rates in 47 percent of instances, and most likely so at hospitals with government or nonprofit ownership, located outside of metropolitan areas, or located in counties with relatively high uninsurance rates or low median household incomes. Hospitals with stronger market power were most likely to offer cash prices below their median negotiated rates, whereas hospitals in areas where insurers had stronger market power were less likely to do so.

Measurement Approaches to Estimating Methadone Continuity in Opioid Use Disorder Care.

BACKGROUND: Long-term treatment with medications for opioid use disorder (OUD), including methadone, is lifesaving. There has been little examination of how to measure methadone continuity in claims data. OBJECTIVES: To develop an approach for measuring methadone continuity in claims data, and compare estimates of methadone versus buprenorphine continuity. RESEARCH DESIGN: Observational cohort study using de-identified commercial claims from OptumLabs Data Warehouse (January 1, 2017-June 30, 2021). SUBJECTS: Individuals diagnosed with OUD, ≥1 methadone or buprenorphine claim and ≥180 days continuous enrollment (N=29,633). MEASURES: OUD medication continuity: months with any use, days of continuous use, and proportion of days covered. RESULTS: 5.4% (N=1607) of the study cohort had any methadone use. Ninety-seven percent of methadone claims (N=160,537) were from procedure codes specifically used in opioid treatment programs. Place of service and primary diagnosis codes indicated that several methadone procedure codes were not used in outpatient OUD care. Methadone billing patterns indicated that estimating days-supply based solely on dates of service and/or procedure codes would yield inaccurate continuity results and that an approach incorporating the time between service dates was more appropriate. Among those using methadone, mean [s.d.] months with any use, days of continuous use, and proportion of days covered were 4.8 [1.8] months, 79.7 [73.4] days, and 0.64 [0.36]. For buprenorphine, the corresponding continuity estimates were 4.6 [1.9], 80.7 [70.0], and 0.73 [0.35]. CONCLUSIONS: Estimating methadone continuity in claims data requires a different approach than that for medications largely delivered by prescription fills, highlighting the importance of consistency and transparency in measuring methadone continuity across studies.

Psychiatrist and Nonpsychiatrist Physician Network Breadth in Dual Eligible Special Needs Plans.

OBJECTIVE: Dual Eligible Special Needs Plans (D-SNPs) are a type of Medicare Advantage (MA) plan for individuals who have both Medicare and Medicaid coverage. The authors compared the breadths of psychiatrist and nonpsychiatrist provider networks in D-SNPs and other MA plans. METHODS: MA plan provider network data were merged with plan service areas and a nationwide provider database to form a data set with 843 observations on networks subclassified by state and network type (D-SNP or other MA) covering 42 U.S. states and Washington, D.C. Network breadth measured the in-network fraction of clinically active Medicare-accepting psychiatrists and other physician providers in the plans' service areas in each state. Regression analyses were used to compare psychiatrist and nonpsychiatrist network breadth and psychiatrist-nonpsychiatrist breadth differences between D-SNPs and other MA plans, after adjustment for state-level differences. RESULTS: Mean psychiatrist network breadth was 0.319 in D-SNPs and 0.299 in other MA plans, and nonpsychiatrist network breadth was 0.346 in D-SNPs and 0.358 in other MA plans. Psychiatrist networks were narrower than nonpsychiatrist networks (0.303 vs. 0.355, p<0.001), but mean psychiatrist network breadth did not differ between D-SNPs and other MA plans. In regression analyses, the psychiatrist-nonpsychiatrist breadth difference was smaller in D-SNPs (-0.031) than in other MA plans (-0.060) (p=0.002). CONCLUSIONS: Psychiatrist provider networks in a nationwide sample of D-SNPs had similar breadth as psychiatrist networks used in other MA plans. Special provider network adequacy requirements for psychiatrists in D-SNP networks may be worthy of further consideration given D-SNPs' disproportionate enrollment of adults with serious mental illness who have dual Medicare-Medicaid insurance coverage.