Bruce E. Landon

Introduction: Medical claim denials impose substantial costs on providers but may also reduce low-value care, resulting in lower expenditures and better quality. Little is known about how denial rates vary across payer and provider segments, including for safety-net providers. Methods: Using a large, multipayer claims dataset from 2019, we examined initial denials, appeal patterns, and final denials by payer segment, service type, and provider safety-net status. Results: Medicaid managed care had the highest initial denial rate for professional claims (15.1%), while Medicare Advantage had the highest rates for inpatient (20.0%) and outpatient (16.5%) claims. Safety-net providers faced uniformly higher initial denial rates than nonsafety-net providers across professional (13.6% vs 9.2%), inpatient (18.3% vs 14.7%), and outpatient (13.3% vs 12.9%) services. Conclusion: Safety-net providers absorbed a disproportionate share of denial costs. These providers’ lack of negotiating leverage to secure favorable terms with payers could be 1 driver of these disparities, as could higher rates of low-value care delivery. A standardized framework for the terms and conditions governing payer–provider contracts could help ensure all claims are decided based on the same set of rules.

Background: Enrollment in Medicare Advantage (MA) has expanded rapidly and MA plans may rely on selective provider networks to manage utilization. While selective contracting has been described for primary care physicians, less is known about how MA networks are constructed for surgical specialists such as urologists, who manage common and costly conditions including prostate cancer. Methods: We conducted a national observational study using a 20% sample of Medicare fee-for-service claims (2016 to 2021) linked to 2021 MA network data. We identified 9,124 urologists practicing in hospital referral regions (HRR) with at least one MA network. Urologists were classified as in-network or out-of-network within each network-HRR and further categorized by network breadth, defined as narrow (<30% of local urologists) or broad. Outcomes were weighted by network enrollment and included urologist characteristics, prostate cancer-related and benign procedure volume, and two claims-based quality measures: use of MRI prior to prostate biopsy and consultation with radiation oncology after new prostate cancer diagnosis. Results: Among 9,124 urologists, 98% participated in at least one MA network. Across 7,516 network-HRR combinations, networks included a mean of 42 urologists (SD 47), with inclusion ranging from 9% to 100% of local urologists. Compared with the average urologist excluded from a network in the HRR, the average in-network urologist had a higher annual patient volume (107 vs 95, p<0.01), performed more prostate biopsies (3.18 vs. 2.89 per year, p<0.01), and performed more prostatectomies (0.48 vs. 0.35 per year, p<0.01), without differences in quality measures. The average urologist in narrow networks had a lower overall procedure volume but were more likely to perform prostatectomy among newly diagnosed patients (21% vs. 14%, p<0.01). Quality patterns were mixed, with higher MRI use prior to biopsy (15% vs. 12%, p<0.01) but lower radiation oncology consultation (50% vs. 54%, p<0.01). Among 12,735 network-county combinations, 1.8% failed to meet Medicare’s urologist adequacy standards. Conclusions: MA urology networks vary widely in breadth and composition. Narrow networks are associated with distinct prostate cancer management patterns that may have implications for access and quality, underscoring the need to assess specialty network adequacy standards.

Given a marked expansion in the work of primary care in recent decades, it is critical to have an accurate understanding of the time involved in managing a primary care panel and the determinants of this time. To estimate the yearly work effort involved for primary care physicians (PCPs) in caring for a patient panel, explore how work effort varies by clinical full-time equivalent (cFTE) status, and identify patient panel factors associated with differential time expenditure. Cross-sectional, observational study using electronic health record and administrative data scaled by a literature-based estimate of activities inadequately captured by these data sources. 33 clinics in the Mass General Brigham health system. 406 attending PCPs who delivered care for at least 9 months in 2021. Total yearly time expenditure per patient and full-time PCP. The median work effort for a full-time PCP was 2844.3 yearly hours (IQR, 2324.9 to 3478.9 yearly hours), or 61.8 weekly hours (IQR, 50.5 to 75.6 weekly hours), for a 1.0-cFTE physician assuming a 46-week work year. This translates to a median of 1.7 hours (IQR, 1.4 to 2.2 hours) per patient per year. Part-time PCPs spent more time per patient on average than full-time PCPs. Patient medical advice request volume and certain panel characteristics, including greater average age, medical complexity, and percentage of patients with Medicaid, were associated with greater yearly PCP time expenditure per patient. Derivation of data from a single integrated health system and lack of information about practice structures and staff supports for PCPs. Primary care physicians spend a median of 62 weekly hours caring for a patient panel. Panel characteristics and patient message volume are associated with time expenditure. These findings provide valuable insights for designing sustainable primary care roles and adjusting panel size expectations. The Physicians Foundation.

The growing complexity of cancer care may be driving an increase in subspecialized medical oncologists who focus on treating specific cancer types. However, little is known about trends in subspecialization among oncologists and differences in utilization of subspecialists. To quantify trends in oncologist subspecialization and assess differences in utilization of subspecialized cancer care in the United States. Retrospective cohort study using Medicare claims data from 2007 to 2021. National, fee-for-service Medicare. Medicare beneficiaries initiating chemotherapy between 2008 and 2020. Chemotherapy episodes were defined using methods from the Oncology Care Model. Subspecialization was identified based on whether oncologists managed more than 80% of chemotherapy episodes within a single cancer category. Outcomes included the annual share of oncologists classified as subspecialists, and the share of chemotherapy episodes managed by these oncologists, stratified by cancer type, geography, and socioeconomic characteristics. Among 18 633 oncologists and 9.25 million chemotherapy episodes, the proportion of episodes managed by subspecialists increased from 9% in 2008 to 18% in 2020. Utilization varied widely across cancer types and regions, with the highest levels observed in large metropolitan areas. Differences by income widened over time: in 2020, 27.6% of episodes in the highest-income counties were managed by subspecialists, compared with only 8.8% in the lowest-income counties, despite higher cancer mortality in the latter. Analyses were limited to fee-for-service Medicare beneficiaries and excluded patients treated with surgery or radiation alone. Subspecialization was defined using practice patterns rather than formal training, and the study does not assess patient outcomes or causal effects. Subspecialization in oncology is increasing but is unevenly distributed, with growing differences in utilization across income groups and regions. National Institute on Aging.

BACKGROUND: The authorization process and coverage/reimbursement mechanisms for medical devices play critical roles in device adoption and usage. However, international variation in these processes remains poorly characterized, especially with regard to data transparency and the effects of reimbursement on usage. METHODS: This study examined publicly available databases, governmental agency recommendations and policies, and press releases from the United States, Canada, the United Kingdom, and the Netherlands to compare the regulatory approval processes and coverage/reimbursement mechanisms for 2 novel cardiovascular devices introduced in the early and late 2000’s: the Watchman left atrial appendage occlusion device and the Impella percutaneous ventricular assist device. In addition to qualitative comparisons for each country, this study compared the date of the first regulatory review, time from submission to review completion, device approval date, agency approval requirements, number of review cycles, and necessity of postapproval studies as determined by the regulator, date of funding decision, final funding decision, and requirements for device reimbursement by relevant government payors. RESULTS: Authorization data were easily accessible for the United States and Canada but extremely limited for the United Kingdom and the Netherlands. Chronologically, authorization occurred ≈10 years earlier in Europe (United Kingdom and the Netherlands) than in North America (United States and Canada) for both devices. The United States was the only country where the principal public payor (Medicare) explicitly reimbursed both procedures. The United States was similarly notable for more rapid adoption and higher utilization of both devices than the other countries, with the Watchman implanted at 3.4 devices per 100 000 adults annually and Impella used in 7 to 8 procedures per 100 000 people annually. In contrast, uptake was far lower in Canada and Europe. CONCLUSIONS: This research provides insights into how differences among countries in authorization and reimbursement mechanisms may impact the adoption and usage of medical devices, and may inform future policies on these processes.

Background and ObjectivesEarly presentation and acute treatment for patients presenting with ischemic stroke are associated with improved outcomes. The onset of the COVID-19 pandemic was associated...

The federal government spends billions of dollars per year on payments to Medicare Advantage (MA) plans based, in part, on beneficiaries' risk scores. Despite this, little is known about the true burden of chronic medical conditions among MA beneficiaries compared with those in fee-for-service (FFS) Medicare. To determine whether the prevalence of chronic medical conditions is higher among MA compared with FFS beneficiaries. Cross-sectional. Population based. Adults aged 65 years or older enrolled in MA or FFS Medicare. Using direct physical examination and laboratory data from the National Health and Nutrition Examination Survey (2015 to 2018), we compared the age- and sex-standardized prevalence of obesity, hypertension, hyperlipidemia, diabetes, and chronic kidney disease between MA and FFS beneficiaries. The unweighted study population included 2446 respondents corresponding to a weighted total of 45 426 711 adults (34.4% MA, 65.6% FFS Medicare). The prevalence of obesity (41.1% vs. 40.6%; standardized difference [SDiff], 0.48 percentage points [pp] [95% CI, -5.2 to 6.2 pp]), hypertension (70.9% vs. 71.0%; SDiff, -0.05 pp [CI, -5.8 to 5.7 pp]), hyperlipidemia (79.4% vs. 82.3%; SDiff, -2.86 pp [CI, -7.0 to 1.3 pp]), and chronic kidney disease (19.2% vs. 22.8%; SDiff, -3.48 pp [CI, -9.2 to 2.3 pp]) was not higher among MA beneficiaries compared with FFS beneficiaries. However, the prevalence of diabetes was higher in MA (33.3% vs. 26.3%; SDiff, 7.00 pp [CI, 3.3 to 10.7 pp]). Differences in the severity of specific medical conditions between groups could not be assessed. In this nationally representative study from 2015 to 2018, the prevalence of obesity, hypertension, hyperlipidemia, and chronic kidney disease was not higher among MA compared with FFS beneficiaries; however, the prevalence of diabetes was higher among MA beneficiaries. National Heart, Lung, and Blood Institute (NHLBI) and American Heart Association (AHA).

More than 83 million people in the United States live in primary care shortage areas. As the US healthcare system faces a contracting primary care physician workforce, advanced practice providers are playing an increasingly important role in the delivery of primary care services. In parallel, public discourse regarding the differences in care delivery by advanced practice providers versus physicians has also expanded. In this commentary, we describe 3 main evidence gaps hindering optimal physician and advanced practice provider work organization in contemporary primary care delivery: (1) gaps in understanding the unique and overlapping competencies of each role group, (2) gaps in evaluating and defining optimal role delineation, and (3) gaps in payment models supporting effective collaboration. We subsequently present key needs in these 3 areas, including technology-based approaches to track physician and advanced practice provider competencies, increased empirical data on different clinical teaming structures, and exploration of novel models for primary care payment. We also note the need for an enhanced understanding of patient perspectives regarding primary care role types and teaming structures.