Correlation Between Patient-Reported Outcome Measures and Health Insurance Provider Types in Patients with Hip Osteoarthritis.

BACKGROUND: Patient-reported outcome measures (PROMs) are frequently utilized to assess patient perceptions of health and function. Numerous factors influence self-reported physical and mental health outcome scores. The purpose of this study was to examine if an association exists between insurance payer type and baseline PROM scores in patients diagnosed with hip osteoarthritis. METHODS: We retrospectively reviewed the baseline PROM scores of 5,974 patients diagnosed with hip osteoarthritis according to the International Classification of Diseases, Tenth Revision (ICD-10) code within our institutional database from 2015 to 2020. We examined Hip disability and Osteoarthritis Outcome Score-Physical Function Short-form (HOOS-PS), Patient-Reported Outcomes Measurement Information System (PROMIS) Physical Function Short Form 10a (PF10a), PROMIS Global-Mental, and PROMIS Global-Physical scores. Descriptive analyses, analysis of variance (ANOVA), analysis of covariance (ANCOVA), and post hoc analyses were utilized to assess variations in PROM scores across insurance type. RESULTS: The mean age (and standard deviation) of the study population was 63.5 ± 12.2 years, and 55.7% of patients were female. The Medicaid cohort had a comparatively higher percentage of Black, Hispanic, and non-English-speaking patients and a lower median household income. The Charlson Comorbidity Index was highest in the Medicare and Medicaid insurance cohorts. Patients utilizing commercial insurance consistently demonstrated the highest baseline PROMs, and patients utilizing Medicaid consistently demonstrated the lowest baseline PROMs. Subsequent analyses found significantly poorer mean scores for the Medicaid cohort for all 4 PROMs when compared with the commercial insurance and Medicare cohorts. These score differences exceeded the minimal clinically important differences (MCIDs). For the PROMIS Global-Mental subscore, a significantly lower mean score was observed for the Workers' Compensation and motor vehicle insurance cohort when compared with the commercial insurance and Medicare cohort. This difference also exceeded the MCID. CONCLUSIONS: PROM scores in patients with hip osteoarthritis varied among those with different insurance types. Variations in certain demographic and health indices are potential drivers of these observed baseline PROM differences. For patients with hip osteoarthritis, the use of PROMs for research, clinical, or quality-linked payment metrics should acknowledge baseline variation between patients with different insurance types. LEVEL OF EVIDENCE: Prognostic Level IV. See Instructions for Authors for a complete description of levels of evidence.

COVID-19 International Collaborative Research by the Health Insurance Review and Assessment Service Using Its Nationwide Real-world Data: Database, Outcomes, and Implications.

This article aims to introduce the inception and operation of the COVID-19 International Collaborative Research Project, the world's first coronavirus disease 2019 (COVID-19) open data project for research, along with its dataset and research method, and to discuss relevant considerations for collaborative research using nationwide real-world data (RWD). COVID-19 has spread across the world since early 2020, becoming a serious global health threat to life, safety, and social and economic activities. However, insufficient RWD from patients was available to help clinicians efficiently diagnose and treat patients with COVID-19, or to provide necessary information to the government for policy-making. Countries that saw a rapid surge of infections had to focus on leveraging medical professionals to treat patients, and the circumstances made it even more difficult to promptly use COVID-19 RWD. Against this backdrop, the Health Insurance Review and Assessment Service (HIRA) of Korea decided to open its COVID-19 RWD collected through Korea's universal health insurance program, under the title of the COVID-19 International Collaborative Research Project. The dataset, consisting of 476 508 claim statements from 234 427 patients (7590 confirmed cases) and 18 691 318 claim statements of the same patients for the previous 3 years, was established and hosted on HIRA's in-house server. Researchers who applied to participate in the project uploaded analysis code on the platform prepared by HIRA, and HIRA conducted the analysis and provided outcome values. As of November 2020, analyses have been completed for 129 research projects, which have been published or are in the process of being published in prestigious journals.

Differences in High- and Low-Value Cardiovascular Testing by Health Insurance Provider.

Background Quality of care incentives and reimbursements for cardiovascular testing differ between insurance providers. We hypothesized that there are differences in the use of guideline-concordant testing between Medicaid versus commercial insurance patients <65 years, and between Medicare Advantage versus Medicare fee-for-service patients ≥65 years. Methods and Results Using data from the Colorado All-Payer Claims Database from 2015 to 2018, we identified patients eligible to receive a high-value test recommended by guidelines: assessment of left ventricular function among patients hospitalized with acute myocardial infarction or incident heart failure, or a low-value test that provides minimal patient benefit: stress testing prior to low-risk surgery or routine stress testing within 2 years of percutaneous coronary intervention or coronary artery bypass graft surgery. Among 145 616 eligible patients, 37% had fee-for-service Medicare, 18% Medicare Advantage, 22% Medicaid, and 23% commercial insurance. Using multilevel logistic regression models adjusted for patient characteristics, Medicaid patients were less likely to receive high-value testing for acute myocardial infarction (odds ratio [OR], 0.84 [0.73-0.98]; P=0.03) and heart failure (OR, 0.59 [0.51-0.70]; P<0.01) compared with commercially insured patients. Medicare Advantage patients were more likely to receive high-value testing for acute myocardial infarction (OR, 1.35 [1.15-1.59]; P<0.01) and less likely to receive low-value testing after percutaneous coronary intervention/ coronary artery bypass graft (OR, 0.63 [0.55-0.72]; P<0.01) compared with Medicare fee-for-service patients. Conclusions Guideline-concordant testing was less likely to occur among patients with Medicaid compared with commercial insurance, and more likely to occur among patients with Medicare Advantage compared with fee-for-service Medicare. Insurance plan features may provide valuable targets to improve guideline-concordant testing.

Cost drivers of locally advanced rectal cancer treatment-An analysis of a leading healthcare insurer.

BACKGROUND: To evaluate the economic burden of locally advanced rectal cancer (LARC) treatment from a society perspective through analysis of health insurance-derived data of commercially insured and Medicare Advantage (MA) patients. METHODS: Retrospective cost analysis of patients undergoing rectal resection within a multimodal (neoadjuvant chemoradiation + adjuvant chemotherapy) treatment strategy between January 1, 2010 and October 31, 2018, using the claims OptumLabs Data Warehouse database. RESULTS: In total, 1738 (935 commercial and 803 MA) patients were included. Overall treatment costs totaled $230,881,746 (on average $183 653 ± 82 384 per commercially insured and $73 681 ± 32 917 per MA patient). Cost distribution according to category (commercially insured patients) was: 29.92% related to outpatient care (follow-up visits/diagnostics), radiotherapy: 21.83%, index resection: 20.62%, chemotherapy: 17.44%, surgical inpatient: 6.32%, medical inpatient: 3.28%, emergency room: 0.58%. Relative cost distribution of the index resection itself differed marginally between the three approaches and was 21.49% for open, 19.30% for laparoscopic, and 20.93% for robotic surgery. Relative cost distributions of neoadjuvant, adjuvant, and outpatient treatments remained unchanged, independently of the surgical approach. This representation was similar in MA patients. CONCLUSION: Index-surgery related costs were outweighed by costs related to oncological and outpatient workup/follow-up treatments independently of both surgical approach and insurance type.

Opioid use in older adults and Medicare Part D.

OBJECTIVE: To determine whether the introduction of prescription drug coverage under Medicare Part D increased opioid prescriptions, patient care-seeking for pain, and pain diagnoses among elderly Medicare-eligible adults. STUDY SETTING: Office visits by adults aged 18 years or older from the 2000-2016 National Ambulatory Medical Care Survey (12 375 207 253 office visits), and respondents from the 2000-2017 Medical Expenditure Panel Survey (4 023 418 681 individuals). STUDY DESIGN: We compared care-seeking for pain, provider-assigned pain diagnoses, and opioid prescriptions before and after the Medicare eligibility age of 65, and before and after Part D's implementation using a regression discontinuity, difference-in-differences design. Analyses were adjusted for age, sex, race, and year. PRINCIPAL FINDINGS: Patient care-seeking for pain increased by 11.4 office visits per 100 people (95% confidence interval 2.0-20.8), or 29%, in response to the implementation of Part D. Opioid prescriptions and diagnoses of pain-related conditions did not change significantly, but the financing of opioid prescriptions shifted from private to public payers at age 65. CONCLUSIONS: The introduction of Medicare Part D was not associated with increased opioid use among older adults. Rather, opioid use among the elderly has been driven by high levels of opioid use among commercially insured adults who subsequently age into Medicare. Our findings raise the question of whether more judicious prescribing to younger adults coupled with concerted efforts to deprescribe opioids when appropriate may prevent problematic opioid use among the elderly.

Pricing in commercial dental insurance and provider markets.

OBJECTIVE: To examine the impact of commercial dental insurer and provider concentration on dentist reimbursement. DATA SOURCES: We utilized provider data from the American Dental Association, reimbursement data from IBM Watson MarketScan® Commercial Research Databases, submitted billed charges from FAIR Health® , dental insurance market concentration data from FAIR Health® , and county-level demographic and economic data from the Area Health Resources File and the Council for Community and Economic Research. STUDY DESIGN: We used the Herfindahl-Hirschman Index to separately measure commercial dental insurance concentration and dentist concentration. We studied the effect of provider and insurance concentration on dentist reimbursement. Using two-stage least squares, we accounted for potential endogeneity in dental insurer and provider concentration. PRINCIPAL FINDINGS: Across the dental procedures we examined, a 10 percent increase in dental insurance concentration is associated with a 1.95 percent (P-value = .033) reduction in gross payments to dentists. Conversely, a 10 percent increase in dentist concentration is associated with a more modest 0.71 percent (P-value = .024) increase in gross payments. A 10 percent increase in dental insurance concentration is associated with a 1.16 percentage point (P-value = .016) decline in the allowed-to-list price ratio, while a 10 percent increase in dentist concentration is associated with a 0.56 percentage point (P-value = .001) increase in the allowed-to-list price ratio. Similar patterns were found across dental procedure subcategories. CONCLUSIONS: Dental provider markets are substantially less concentrated than insurance markets, which may limit the ability of dentists to garner higher reimbursement.

Health system integration with physician specialties varies across markets and system types.

OBJECTIVE: To examine system integration with physician specialties across markets and the association between local system characteristics and their patterns of physician integration. DATA SOURCES: Data come from the AHRQ Compendium of US Health Systems and IQVIA OneKey database. STUDY DESIGN: We examined the change from 2016 to 2018 in the percentage of physicians in systems, focusing on primary care and the 10 most numerous nonhospital-based specialties across the 382 metropolitan statistical areas (MSAs) in the US. We also categorized systems by ownership, mission, and payment program participation and examined how those characteristics were related to their patterns of physician integration in 2018. DATA COLLECTION/EXTRACTION METHODS: We examined local healthcare markets (MSAs) and the hospitals and physicians that are part of integrated systems that operate in these markets. We characterized markets by hospital and insurer concentration and systems by type of ownership and by whether they have an academic medical center (AMC), a 340B hospital, or accountable care organization. PRINCIPAL FINDINGS: Between 2016 and 2018, system participation increased for primary care and the 10 other physician specialties we examined. In 2018, physicians in specialties associated with lucrative hospital services were the most commonly integrated with systems including hematology-oncology (57%), cardiology (55%), and general surgery (44%); however, rates varied substantially across markets. For most specialties, high market concentration by insurers and hospital-systems was associated with lower rates of physician integration. In addition, systems with AMCs and publicly owned systems more commonly affiliated with specialties unrelated to the physicians' potential contribution to hospital revenue, and investor-owned systems demonstrated more limited physician integration. CONCLUSIONS: Variation in physician integration across markets and system characteristics reflects physician and systems' motivations. These integration strategies are associated with the financial interests of systems and other strategic goals (eg, medical education, and serving low-income populations).

Changes in Drug List Prices and Amounts Paid by Patients and Insurers.

Importance: High out-of-pocket drug costs can cause patients to skip treatment and worsen outcomes, and high insurer drug payments could increase premiums. Drug wholesale list prices have doubled in recent years. However, because of manufacturer discounts and rebates, the extent to which increases in wholesale list prices are associated with amounts paid by patients and insurers is poorly characterized. Objective: To determine whether increases in wholesale list prices are associated with increases in amounts paid by patients and insurers for branded medications. Design, Setting, and Participants: Cross-sectional retrospective study analyzing pharmacy claims for patients younger than 65 years in the IBM MarketScan Commercial Database and pricing data from SSR Health, LLC, between January 1, 2010, and December 31, 2016. Pharmacy claims analyzed represent claims of employees and dependents participating in employer health benefit programs belonging to large employers. Rebate data were estimated from sales data from publicly traded companies. Analysis focused on the top 5 patent-protected specialty and 9 traditional brand-name medications with the highest total drug expenditures by commercial insurers nationwide in 2014. Data were analyzed from July 2017 to July 2020. Exposures: Calendar year. Main Outcomes and Measures: Changes in inflation-adjusted amounts paid by patients and insurers for branded medications. Results: In this analysis of 14.4 million pharmacy claims made by 1.8 million patients from 2010-2016, median drug wholesale list price increased by 129% (interquartile range [IQR], 78%-133%), while median insurance payments increased by 64% (IQR, 28%-120%) and out-of-pocket costs increased by 53% (IQR, 42%-82%). The mean percentage of wholesale list price accounted for by discounts increased from 17% in 2010 to 21% in 2016, and the mean percentage of wholesale list price accounted for by rebates increased from 22% in 2010 to 24% in 2016. For specialty medications, median patient out-of-pocket costs increased by 85% (IQR, 73%-88%) from 2010 to 2016 after adjustment for inflation and 42% (IQR, 25%-53%) for nonspecialty medications. During that same period, insurer payments increased by 116% for specialty medications (IQR, 100%-127%) and 28% for nonspecialty medications (IQR, 5%-34%). Conclusions and Relevance: This study's findings suggest that drug list prices more than doubled over a 7-year study period. Despite rising manufacturer discounts and rebates, these price increases were associated with large increases in patient out-of-pocket costs and insurer payments.

The Impact of COVID-19 on the Insurance Industry.

This study investigated the impact of COVID-19 on the insurance industry by studying the case of Ghana from March to June 2020. With a parallel comparison to previous pandemics such as SARS-CoV, H1N1 and MERS, we developed outlines for simulating the impact of the pandemic on the insurance industry. The study used qualitative and quantitative interviews to estimate the impact of the pandemic. Presently, the trend is an economic recession with decreasing profits but increasing claims. Due to the cancellation of travels, events and other economic losses, the Ghanaian insurance industry witnessed a loss currently estimated at GH Ȼ112 million. Our comparison and forecast predicts a normalization of economic indicators from January 2021. In the meantime, while the pandemic persists, insurers should adapt to working from remote locations, train and equip staff to work under social distancing regulations, enhance cybersecurity protocols and simplify claims/premium processing using e-payment channels. It will require the collaboration of the Ghana Ministry of Health, Banking Sector, Police Department, Customs Excise and Preventive Service, other relevant Ministries and the international community to bring the pandemic to a stop.

Does the chronically ill population in the Netherlands switch their health insurer as often as the general population? Empirical evidence from a nationwide survey study.

BACKGROUND: Consumer mobility is an important aspect of a health insurance system based on managed competition. Both the general population and insured with a chronic illness should enjoy an equal opportunity to switch their insurer every year. We studied possible differences in the rates of switching between these two groups in the Netherlands. METHODS: A structured questionnaire was sent to 1500 members of Nivel's Dutch Health Care Consumer Panel (response rate: 47%) and to 1911 chronically ill members of the National Panel of the Chronically ill and Disabled (response rate: 84%) in February 2016. Associations between switching and background characteristics were estimated using logistic regression analyses with interaction effects. RESULTS: In general, we did not find significant differences in switching rates between the general population and chronically ill population. However, a combination of the population and background characteristics demonstrated that young insured with a chronic illness switched significantly less often than young insured from the general population (1% versus 17%). CONCLUSIONS: Our results demonstrated that the group of young people with a chronic illness is less inclined to switch insurer. This observation suggests that this group might either face difficulties or barriers which prevents them from switching, or that they experience a high level of satisfaction with their current insurer. Further research should therefore focus on unravelling the mechanisms which explain the differences in switching rates.

Male breast cancer: a closer look at patient and tumor characteristics and factors that affect survival using the National Cancer Database.

OBJECTIVE: To comprehensively describe the tumor and clinical characteristics of breast cancer in a cohort of male patients and to assess the factors that affect survival. BACKGROUND: Much of the standard care of male breast cancer is based on the diagnosis and treatment strategies of female breast cancer. However, important clinical differences between the two have been elucidated, which suggests the need for unique attention to male breast cancer. METHODS: We evaluated the records of male patients who were diagnosed with breast cancer between 2004 and 2015 using the National Cancer Database (NCDB). Data obtained were demographic characteristics, clinical and tumor data, type of therapy, as well as survival data. We used descriptive statistics to characterize our study population. We then performed a survival and Cox proportional hazards analysis. RESULTS: We identified 16,498 patients (median age: 63 years). Several treatment modalities were used, of which surgery was the most common (14,882 [90.4%]). The total follow-up time was 13 years (156 months). Five-year survival was 77.7% (95% CI 76.9-78.4) and 10-year survival was 60.7%. In a Cox proportional hazards model, mastectomy was associated with the greatest survival (hazard ratio [HR] 0.49; p < 0.001). CONCLUSION: We report what is to our knowledge the largest national population-based cohort of male breast cancer patients. Importantly, our data suggests that similar to female patients, several treatment modalities are significantly associated with improved survival in male patients, particularly surgery. Increasing age, black race, government insurance, more comorbidities, and higher tumor stages are associated with decreased survival.

A budget impact analysis for making treatment decisions based on anti-cyclic citrullinated peptide (anti-CCP) testing in rheumatoid arthritis.

Aim: Given that rheumatoid arthritis (RA) patients with high anti-citrullinated protein antibodies (ACPA) titer values respond well to abatacept, the aim of this study was to estimate the annual budget impact of anti-cyclic citrullinated peptide (anti-CCP) testing and treatment selection based on anti-CCP test results.Materials and methods: Budget impact analysis was conducted for patients with moderate-to-severe RA on biologic or Janus kinase inhibitor (JAKi) treatment from a hypothetical US commercial payer perspective. The following market scenarios were compared: (1) 90% of target patients receive anti-CCP testing and the results of anti-CCP testing do not impact the treatment selection; (2) 100% of target patients receive anti-CCP testing and the results of anti-CCP testing have an impact on treatment selection such that an increased proportion of patients with high titer of ACPA receive abatacept. A hypothetical assumption was made that the use of abatacept would be increased by 2% in Scenario 2 versus 1. Scenario analyses were conducted by varying the target population and rebate rates.Results: In a hypothetical health plan with one million insured adults, 2,181 patients would be on a biologic or JAKi treatment for moderate-to-severe RA. In Scenario 1, the anti-CCP test cost was $186,155 and annual treatment cost was $101,854,295, totaling to $102,040,450. In Scenario 2, the anti-CCP test cost increased by $20,684 and treatment cost increased by $160,467, totaling an overall budget increase of $181,151. This was equivalent to a per member per month (PMPM) increase of $0.015. The budget impact results were consistently negligible across the scenario analyses.Limitations: The analysis only considered testing and medication costs. Some parameters used in the analysis, such as the rebate rates, are not generalizable and health plan-specific.Conclusions: Testing RA patients to learn their ACPA status and increasing use of abatacept among high-titer ACPA patients result in a small increase in the total budget (<2 cents PMPM).

Review of Insurance Coverage for Abdominal Contouring Procedures in the Postbariatric Population.

BACKGROUND: Following bariatric surgery, patients develop problems related to lax abdominal skin that may be addressed by contouring procedures. Third-party insurers have subjective requirements for coverage of these procedures that can limit patient access. The authors sought to determine how well third-party payers cover abdominal contouring procedures in this population. METHODS: The authors conducted a cross-sectional analysis of insurance policies for coverage of panniculectomy, lower back excision, and circumferential lipectomy. Abdominoplasty was evaluated as an alternative to panniculectomy. Insurance companies were selected based on their market share and state enrolment. A list of medical necessity criteria was abstracted from the policies that offered coverage. RESULTS: Of the 55 companies evaluated, 98 percent had a policy that covered panniculectomy versus 36 percent who would cover lower back excision (p < 0.0001), and one-third provided coverage for circumferential lipectomy. Of the insurers who covered panniculectomy, only 30 percent would also cover abdominoplasty. Documentation of secondary skin conditions was the most prevalent criterion in panniculectomy policies (100 percent), whereas impaired function and secondary skin conditions were most common for coverage of lower back excision (73 percent and 73 percent, respectively). Frequency of criteria for panniculectomy versus lower back excision differed most notably for (1) secondary skin conditions (100 percent versus 73 percent; p = 0.0030), (2) weight loss (45 percent versus 7 percent; p = 0.0106), and (3) duration of weight stability (82 percent versus 53 percent; p = 0.0415). CONCLUSIONS: For the postbariatric population, panniculectomy was covered more often and had more standardized criteria than lower back excision or circumferential lipectomy. However, all have vast intracompany and interpolicy variations in coverage criteria that may reduce access to procedures, even among patients with established indications.

Using Health Insurance Network Provider Data and Public Data Sets to Identify SARS-CoV-2 Vaccinators in the USA.

Objective: Mass vaccination planning is occurring at all levels of government in advance of regulatory approval and manufacture of a SARS-CoV-2 vaccine for distribution sometime in 2021. We outline a methodology in which both health insurance provider network data and publicly available data sources can be used to identify and plan for SARS-CoV-2 vaccinator capacity at the county level. Methods: Sendero Health Plans, Inc. provider network data, Texas State Board of Pharmacy data, US Census Bureau data, and H1N1 monovalent vaccine data were utilized to identify providers with demonstrated capacity to vaccinate the population in Travis County, Texas to achieve an estimated SARS-CoV-2 herd immunity target of 67%. Results: Within the Sendero network, 2,356 non-pharmacy providers were identified with 788 (33.4%) practicing in primary care and 1,569 (66.6%) practicing as specialists. Of the total, 686 (29.1%) provided at least one immunization between January 1, 2019 and September 30, 2020. There are 300 pharmacies with active licenses in Travis County with 161 (53.7%) classified as community pharmacies. We estimate that 1,707,098 doses of a 2-dose SARS-CoV-2 vaccine series will need to be administered within Travis County, Texas to achieve the estimated 67% herd immunity threshold to disrupt person-to-person transmission of the SARS-CoV-2 virus based on 2020 census data. Conclusion: A community-based health insurance plan can use data from its provider network and public data sources to support the CDC call to action to identify SARS-CoV-2 vaccinators in the community, including physicians, nurse practitioners, physician assistants, and pharmacies in order to provide macro level estimates of SARS-CoV-2 administration and throughput.

Evaluating the performance of a predictive modeling approach to identifying members at high-risk of hospitalization.

Aims: To evaluate the risk-of-hospitalization (ROH) models developed at Blue Cross Blue Shield of Louisiana (BCBSLA) and compare this approach to the DxCG risk-score algorithms utilized by many health plans.Materials and Methods: Time zero for this study was December 31, 2016. BCBSLA members were eligible for study inclusion if they were fully insured; aged 80 years or younger; and had continuous enrollment starting on or before June 1, 2016, through time zero. Up to 2 years of historical claims data from time zero per patient was included for model development. Members were excluded if they had cancer, renal failure, or were admitted for hospice. The Blue Cross ROH models were developed using (1) regularized logistic regression and (2) random decision forests (a tree ensemble learning classification method). All models were generated using Scikit-learn: Machine Learning in Python. Prognostic capabilities of DxCG risk-score algorithms were compared to those of the Blue Cross models.Results: When stratifying by the top 0.1% of members with the highest ROH, the Blue Cross logistic regression model had the highest area under the receiving operator characteristics curve (0.862) based on the result of 10-fold cross-validation. The Blue Cross random decision forests model had the highest positive predictive value (49.0%) and positive likelihood ratio (61.4), but sensitivity, specificity, negative predictive values, and negative likelihood ratios were similar across all four models.Limitations: The Blue Cross ROH models were developed and evaluated using BCBSLA data, and predictive power may fluctuate if applied to other databases.Conclusions: The predictability of the Blue Cross models show how member-specific, regional data can be used to accurately identify patients with a high ROH, which may allow healthcare workers to intervene earlier and subsequently reduce the healthcare burden for patients and providers.

Intensity of community-based programs by long-term care insurers and the likelihood of frailty: Multilevel analysis of older Japanese adults.

The World Health Organization (WHO) argues that governments can postpone declining capacity of older adults by providing sufficient support. Yet, to our knowledge, no study has focused on the role of local governments for realizing healthy ageing. This study examined the association between the intensity of community-based programs for frailty postponement by long-term care insurers (as municipalities) and the likelihood of frailty. We analyzed repeated cross-sectional data of three waves (2010-11, 2013, and 2016) from the Japan Gerontological Evaluation Study (JAGES). Participants included 375,400 older adults aged 65 years or older (M = 74.1) living in a total of 81 regions covered by insurers in Japan. Frailty was assessed by a governmental standardized index, the Kihon Check List (KCL; a basic function check list in Japanese). Estimations were obtained using a multilevel logistic model with random slopes. We found that every social activity per hundred older people organized by a long-term care insurer was significantly associated with an 11% reduction of the likelihood of frailty (Odds ratio = 0.89; 95% credible interval = 0.81, 0.99). Although the main effect of educational events was not significant, the point estimate was slightly larger for people with lower levels of education than for those with higher education. The results also suggested that insurer-organized social activities could be more beneficial in communities with few opportunities for civic participation. The variation in intensity of community-based programs by long-term care insurers may explain part of a disparity in the likelihood of frailty between municipalities.

Rural-Urban Differences In Individual-Market Health Plan Affordability After Subsidy Payment Cuts.

This article investigates changes in the affordability of individual health plans (Marketplace plans) that were compliant with the Affordable Care Act following the termination of cost-sharing reduction subsidy payments in 2017. We examined how states' and insurers' responses to these cuts affected enrollees differently depending on whether they lived in rural or urban geographic areas and were or were not eligible for Advance Premium Tax Credits. Using data for 2014-19 from the Health Insurance Exchange Compare database and other sources, we found that subsidy-eligible enrollees in rural markets gained access to Marketplace plans that were more affordable than those available to their urban counterparts, after the cuts affected premiums in 2018. Average minimum net monthly premiums for subsidized enrollees in majority-rural geographic rating areas decreased from $288 in 2017 to $162 in 2019, while those of their urban counterparts decreased from $275 to $180. In contrast, rural enrollees without subsidies faced the least affordable premiums for Marketplace plans.

Participation rate determines completion rate for specific health guidance as implemented by public health insurers.

Completion rate for specific health guidance (SHG) based on specific health checkup (SHC) status in Japan is very low. This study aimed to clarify factors affecting the rate using questionnaire survey, which was conducted by mail between December 2016 and January 2017 for insurers in the Tokai Region of Japan. The subjects were 69 insurers and the collection rate was 25.1%. The SHG participation rate was 26.3%, and the SHG completion rate was even lower (23.6%) than the participation rate. The rate was significantly lower in dependents than in insured persons. Multiple regression analysis with SHG completion rate as the dependent variable indicated that only "participation rate in SHG" was positively related to completion rate. With SHG participation rate as the dependent variable, however, having an insurer who "implemented SHG," "provided a thorough explanation to the subscribers of the objectives and significance of SHC and SHG when the programs were begun," and "provided health guidance to non-obese individuals" and SHC implementation rate were positively correlated with participation rate. Multiple regression analysis using completion rates for the two types of SHG, i.e., motivational and active support, as the dependent variables indicated that SHG participation rate was a positive factor for each type. Participation rate in each type was positively correlated to "ex-post assessment of the SHG," and/or insured persons. The primary factor affecting SHG completion rates was the SHG participation rate. It is also important, however, that insurers encourage participation of subscribers, especially dependents, in SHG.

Concentration of Physician Services Across Insurers and Effects on Quality: Early Evidence From Medicare Advantage.

BACKGROUND: A growing proportion of Medicare beneficiaries is covered by private insurers through Medicare Advantage, yet little is known about how these plans are structured in terms of relationships with physicians and implications for quality of care. OBJECTIVE: The objective of this study was to assess whether greater physician concentration of services across insurers was associated with higher quality in Medicare Advantage (MA), overall and particularly among MA insurers serving a high proportion of vulnerable enrollees. RESEARCH DESIGN: A retrospective cohort design with regression analysis. DATA SOURCES: The primary dataset was 2014 MA encounter records submitted by insurers to the Centers for Medicare and Medicaid Services, covering 600,329 physicians across 119 insurers. These data were merged with Centers for Medicare and Medicaid Services data on MA contract quality rating as well as physician characteristics in the Medicare Data on Provider Practice and Specialty file. MEASURES: Two measures were generated to capture the concentration of physician services across insurers: the percentage of a physician's Medicare services which was through MA (MA penetration); and the percentage of a physician's MA services with a specific insurer (insurer share of MA services). RESULTS: Greater MA penetration and insurer share of MA services were each associated with higher MA plan quality. The relationship between insurer share and quality was stronger in contracts with a relatively high percentage of disabled enrollees. CONCLUSION: Greater physician concentration of services across MA insurers was associated with a higher quality of care overall and especially among vulnerable enrollees.