The rising price of branded drugs has garnered considerable attention from the public and policy makers. This article investigates the complexities of pharmaceutical pricing, with an emphasis on the overlooked aspects of manufacturer rebates and out-of-pocket prices. Rebates granted by pharmaceutical manufacturers to insurers reduce the actual prices paid by insurers, causing the true prices of prescriptions to diverge from official statistics. We combined claims data on branded retail prescription drugs with estimates on rebates to provide new price index measures based on pharmacy prices, negotiated prices (after rebates), and out-of-pocket prices for the commercially insured population during the period 2007-20. We found that although retail pharmacy prices increased 9.1 percent annually, negotiated prices grew by a mere 4.3 percent, highlighting the importance of rebates in price measurement. Surprisingly, consumer out-of-pocket prices diverged from negotiated prices after 2016, growing 5.8 percent annually while negotiated prices remained flat. The concern over drug price inflation is more reflective of the rapid increase in consumer out-of-pocket expenses than the stagnated inflation of negotiated prices paid by insurers after 2016.

Given recent congressional interest in codifying price transparency regulations, it is important to understand the extent to which newly available price transparency data capture true underlying procedure-level prices. To that end, we compared the prices for maternity services negotiated between a large payer and 26 hospitals in Mississippi across 2 separate price transparency data sources: payer and hospital. The degree of file overlap is low, with only 16.3% of hospital-billing code observations appearing in both data sources. However, for the observations that overlap, pricing concordance is high: Corresponding prices have a correlation coefficient of 0.975, 77.4% match to the penny, and 84.4% are within 10%. Exact price matching rates are greater than 90% for 3 of the 4 service lines included in this study. Taken together, these results suggest that although administrative misalignment exists between payers and hospitals, there is a measure of signal amid the price transparency noise.

BACKGROUND: As U.S. legislators are urged to combat ghost networks in behavioral health and address the provider data quality issue, it becomes important to better characterize the variation in data quality of provider directories to understand root causes and devise solutions. Therefore, this manuscript examines consistency of address, phone number, and specialty information for physician entries from 5 national health plan provider directories by insurer, physician specialty, and state.
METHODS: We included all physicians in the Medicare Provider Enrollment, Chain, and Ownership System (PECOS) found in ≥ 2 health insurer physician directories across 5 large national U.S. health insurers. We examined variation in consistency of address, phone number, and specialty information among physicians by insurer, physician specialty, and state.
RESULTS: Of 634,914 unique physicians in the PECOS database, 449,282 were found in ≥ 2 directories and included in our sample. Across insurers, consistency of address information varied from 16.5 to 27.9%, consistency of phone number information varied from 16.0 to 27.4%, and consistency of specialty information varied from 64.2 to 68.0%. General practice, family medicine, plastic surgery, and dermatology physicians had the highest consistency of addresses (37-42%) and phone numbers (37-43%), whereas anesthesiology, nuclear medicine, radiology, and emergency medicine had the lowest consistency of addresses (11-21%) and phone numbers (9-14%) across health insurer directories. There was marked variation in consistency of address, phone number, and specialty information by state.
CONCLUSIONS: In evaluating a large national sample of U.S. physicians, we found minimal variation in provider directory consistency by insurer, suggesting that this is a systemic problem that insurers have not solved, and considerable variation by physician specialty with higher quality data among more patient-facing specialties, suggesting that physicians may respond to incentives to improve data quality. These data highlight the importance of novel policy solutions that leverage technology targeting data quality to centralize provider directories so as not to not reinforce existing data quality issues or policy solutions to create national and state-level standards that target both insurers and physician groups to maximize quality of provider information.

BACKGROUND: Recent studies document the rising prevalence of common ownership by institutional investors in specific industries. Those investors offer products, such as mutual and index funds, to trade securities on behalf of others and often own shares of multiple firms in the same industry to diversify portfolios. However, at present, few studies focus on common ownership trends in health care.
OBJECTIVE: This paper examines institutional investors\' common ownership in the major insurers offering plans in the Medicare Part D stand-alone prescription drug plan (PDP) market between 2013 and 2020.
METHODS: Using data from the Securities and Exchange Commission (SEC) database and the Center for Research in Securities Prices, we compute the percentages of outstanding shares of each insurer owned by institutional investors. Data visualization and network analysis are employed to assess the trends in common ownership among major insurers.
RESULTS: We document a high prevalence of and substantial increase in shared institutional investors in the PDP market. From 2013 to 2020, the degree of common ownership increased by 7% on average, and the common ownership network became more connected. Common ownership also varies across the 34 PDP regions depending on their reliance on listed insurers, that are traded in the stock exchange, offering stand-alone PDPs.
CONCLUSIONS: High and rising common ownership in the Medicare Part D PDP market raises policy questions about potential effects on plan offerings, premiums, and quality for consumers.

As people lose Medicaid because of the end of the COVID-19 public health emergency, many states will route former Medicaid managed care enrollees into Affordable Care Act Marketplace coverage with the same carrier. In 2021, 52.1 percent of Medicaid managed care enrollees were enrolled by a carrier that also had a plan on the Marketplace in the same county.

Healthcare organizations increasingly engage in activities to identify and address social determinants of health (SDOH) among their patients to improve health outcomes and reduce costs. While several studies to date have focused on the evolving role of hospitals and physicians in these types of population health activities, much less is known about the role health insurers may play. We used data from the National Longitudinal Survey of Public Health Systems for the period 2006 to 2018 to examine trends in health insurer participation in population health activities and in the multi-sector collaborative networks that support these activities. We also used a difference-in-differences approach to examine the impact of Medicaid expansion on insurer participation in population health networks. Insurer participation increased in our study period both in the delivery of population health activities and in the integration into collaborative networks that support these activities. Insurers were most likely to participate in activities focusing on community health assessment and policy development. Results from our adjusted difference-in-differences models showed variation in association between insurer participation in population health networks and Medicaid expansion (Table 2). Population health networks in expansion states experienced significant increases insurer participation in assessment (4.48 percentage points, P < .05) and policy and planning (7.66 percentage points, P < .05) activities. Encouraging insurance coverage gains through policy mechanisms like Medicaid expansion may not only improve access to healthcare services but can also act as a driver of insurer integration into population health networks.

This Viewpoint describes strategies for payers to improve health outcomes among sexual and gender minority people.

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.

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The rising cost of private health insurance and constraints within public health systems are global concerns. Genetic testing presents a transformative opportunity for health care to enhance health outcomes and optimise resource allocation through personalised medicine, early diagnosis, targeted treatments, managed care, and improved drug development. However, ethical and policy issues arise, including privacy, discrimination and equitable access to testing. Balancing these against potential health benefits poses a complex challenge. While some advocate for restricting health insurers from using genetic data, others argue that well-regulated private insurance can ensure affordability, improved health outcomes, and innovative care adoption. This article explores examples of improved health outcomes through genetic testing, identifies areas of risk related to insurers\' use of genetic data, evaluates the adequacy of New Zealand\'s legal framework, and emphasises the need for ethical and equitable policy solutions. The broader issues of data governance, biases in algorithms, and implications of artificial intelligence and machine learning warrant separate exploration.