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Objective: To investigate primary care practice ownership and specialist‐use patterns for commercially insured children with disabilities. Data Sources and Study Setting: A national commercial claims database and the Health Systems and Provider Database from 2012 to 2016 are the data sources for this study. Study Design: This cross‐sectional, descriptive study examines: (1) the most visited type of pediatric primary care physician and practice (independent or system‐owned); (2) pediatric and non‐pediatric specialist‐use patterns; and (3) how practice ownership relates to specialist‐use patterns. Data Collection/Extraction Methods: This study identifies 133,749 person‐years of commercially insured children with disabilities aged 0–18 years with at least 24 months of continuous insurance coverage by linking a national commercial claims data set with the Health Systems and Provider Database and applying the validated Children with Disabilities Algorithm. Principal Findings: Three‐quarters (75.9%) of children with disabilities received their pediatric primary care in independent practices. Nearly two thirds (59.6%) used at least one specialist with 45.1% using nonpediatric specialists, 28.8% using pediatric ones, and 17.0% using both. Specialist‐use patterns varied by both child age and specialist type. Children with disabilities in independent practices were as likely to see a specialist as those in system‐owned ones: 57.1% (95% confidence interval [95% CI] 56.7%–57.4%) versus 57.3% (95% CI 56.6%–58.0%), respectively (p = 0.635). The percent using two or more types of specialists was 46.1% (95% CI 45.4%–46.7%) in independent practices, comparable to that in systems 47.1% (95% CI 46.2%–48.0%) (p = 0.054). However, the mean number of specialist visits was significantly lower in independent practices than in systems—4.0 (95% CI 3.9%–4.0%) versus 4.4 (95% CI 4.3%–4.6%) respectively—reaching statistical significance with p < 0.0001. Conclusions: Recognizing how privately insured children with disabilities use pediatric primary care from pediatric and nonpediatric primary care specialists through both independent and system‐owned practices is important for improving care quality and value. [ABSTRACT FROM AUTHOR]

Objective Data Sources and Study Setting Study Design Data Collection/Extraction Methods Principal Findings Conclusions To systematically review Medicaid policies state‐by‐state for gender‐affirming surgery coverage.Primary data were collected for each US state utilizing the LexisNexis legal database, state legislature publications, and Medicaid manuals.A cross‐sectional study evaluating Medicaid coverage for numerous gender‐affirming surgeries.We previously reported on state health policies that protect gender‐affirming care under Medicaid coverage. Building upon our prior work, we systematically assessed the 27 states with protective policies to determine coverage for each type of gender‐affirming surgery. We analyzed Medicaid coverage for gender‐affirming surgeries in four domains: chest, genital, craniofacial and neck reconstruction, and miscellaneous procedures. Medicaid coverage for each type of surgery was categorized as explicitly covered, explicitly noncovered, or not described.Among the 27 states with protective Medicaid policies, 17 states (63.0%) provided explicit coverage for at least one gender‐affirming chest procedure and at least one gender‐affirming genital procedure, while only eight states (29.6%) provided explicit coverage for at least one craniofacial and neck procedure (p = 0.04). Coverage for specific surgical procedures within these three anatomical domains varied. The most common explicitly covered procedures were breast reduction/mastectomy and hysterectomy (n = 17, 63.0%). The most common explicitly noncovered surgery was reversal surgery (n = 12, 44.4%). Several states did not describe the specific surgical procedures covered; thus, final coverage rates are indeterminate.In 2022, 52.9% of states had health policies that protected gender‐affirming care under Medicaid; however, coverage for various gender‐affirming surgical procedures remains both variable and occasionally unspecified. When specified, craniofacial and neck reconstruction is the least covered anatomical area compared with chest and genital reconstruction. [ABSTRACT FROM AUTHOR]

Objectives: To analyze relationships between Medicaid automatic enrollment for child Supplemental Security Income (SSI) recipients and health insurance coverage during transitions. Data Sources and Study Setting: Medical Expenditure Panel Study, 2000–2020 and National Survey for Children with Special Health Care Needs, 2001–2010. Study Design: Leveraging variation in SSI‐Medicaid automatic enrollment status across regions and over time, we estimate a regression model to quantify associations between automatic enrollment and insurance coverage. We validate our findings in the NS‐CSHCN. Data Collection: Our sample includes children receiving SSI for a disability. We also analyze a subsample of children newly enrolled in SSI. Principal Findings: Automatic enrollment is associated with a statistically significant increase in insurance coverage. Expanding automatic enrollment to all states is associated with increases in Medicaid enrollment of 3% (CI 0.9%–6.7%) among all SSI children and 7% (CI 1.1%–13.9%) among children newly enrolled in SSI. We find similar decreases in uninsurance. Analysis in the NS‐CSHCN replicates these findings. Conclusions: Medicaid automatic enrollment policies are associated with increased insurance coverage for SSI children, particularly those transitioning into the program. Medicaid policy defaults could play an important role in reducing administrative burdens to improve children's coverage and access to care. [ABSTRACT FROM AUTHOR]

Objective: To measure differences in access to contraceptive services based on history of incarceration and its intersections with race/ethnicity and insurance status. Data Sources and Study Setting: Primary data were collected from telephone calls to physician offices in Alabama, Louisiana, and Mississippi in 2021. Study Design: We deployed a field experiment. The outcome variables were appointment offers, wait days, and questions asked of the caller. The independent variables were callers' incarceration history, race/ethnicity, and insurance. Data Collection Methods: Using standardized scripts, Black, Hispanic, and White female research assistants called actively licensed primary care physicians and Obstetrician/Gynecologists asking for the next available appointment for a contraception prescription. Physicians were randomly selected and randomly assigned to callers. In half of calls, callers mentioned recent incarceration. We also varied insurance status. Principal Findings: Appointment offer rates were five percentage points lower (95% CI: −0.10 to 0.01) for patients with a history of incarceration and 11 percentage points lower (95% CI: −0.15 to −0.06) for those with Medicaid. We did not find significant differences in appointment offer rates or wait days when incarceration status was interacted with race or insurance. Schedulers asked questions about insurance significantly more often to recently incarcerated Black patients and recently incarcerated patients who had Medicaid. Conclusions: Women with a history of incarceration have less access to medical appointments; this access did not vary by race or insurance status among women with a history of incarceration. [ABSTRACT FROM AUTHOR]

Objective: To describe insurance patterns and discontinuity during pregnancy, which may affect the experiences of the pregnant person: their timely access to care, continuity of care, and health outcomes. Data Sources and Study Setting: Data are from the PROMISE study, which utilizes data from community‐based health care organizations (CHCOs) (e.g., federally qualified health centers that serve patients regardless of insurance status or ability to pay) in the United States from 2005 to 2021. Study Design: This descriptive study was a cohort utilizing longitudinal electronic health record data. Data Collection/Extraction Methods: Insurance type at each encounter was recorded in the clinical database and coded as Private, Public, and Uninsured. Pregnant people were categorized into one of several insurance patterns. We analyzed the frequency and timing of insurance changes and care utilization within each group. Principal Findings: Continuous public insurance was the most common insurance pattern (69.2%), followed by uninsured/public discontinuity (11.8%), with 6.4% experiencing uninsurance throughout the entirety of pregnancy. Insurance discontinuity was experienced by 16.6% of pregnant people; a majority of these reflect people transitioning to public insurance. Those with continuous public insurance had the highest frequency of inadequate prenatal care (19.5%), while those with all three types of insurance during pregnancy had the highest percentage of intensive prenatal care (16.5%). The majority (71.7%–81.2%) of those with a discontinuous pattern experienced a single insurance change. Conclusions: Insurance discontinuity and uninsurance are common within our population of pregnant people seeking care at CHCOs. Our findings suggest that insurance status should be regarded as a dynamic rather than a static characteristic during pregnancy and should be measured accordingly. Future research is needed to assess the drivers of perinatal insurance discontinuity and if and how these discontinuities may affect health care access, utilization, and birth outcomes. [ABSTRACT FROM AUTHOR]

Objective: To investigate whether expanded access to Veterans Affairs (VA)‐purchased care increased overall utilization or induced a shift from other payers to VA for emergency care among VA enrollees. Data Sources and Study Setting: This study included all emergency department (ED) encounters in 2019 from hospitals in the state of New York. Study Design: We conducted a difference‐in‐differences analysis comparing VA enrollees to the general population before and after the implementation of the Maintaining Internal Systems and Strengthening Integrated Outside Networks (MISSION) Act in June 2019. Data Collection/Extraction Methods: We included all ED visits with individuals aged 30 or older at the time of the encounter. Individuals were considered eligible for the policy change if they were enrolled with VA at the beginning of 2019. Principal Findings: Of the 5,577,199 ED visits in the sample, 4.9% (n = 253,799) were made by VA enrollees. Of these, 44.9% of visits were paid by Medicare, 32.8% occurred in VA facilities, and 7% were paid by private health insurance. There was a 6.4% (2.91 percentage points; std. error = 0.18; p < 0.01) decrease in the proportion of ED visits paid by Medicare among VA enrollees relative to the general population after the implementation of the MISSION Act in June 2019. This decrease was larger for ED visits with a subsequent inpatient admission (−8.4%; 4.87 percentage points; std. error = 0.33; p < 0.01). There was no statistically significant change in the total volume of ED visits (0.06%; std. error = 0.08; p = 0.45). Conclusions: Leveraging a novel dataset, we demonstrate that MISSION Act implementation coincided with a shift in the financing of non‐VA ED visits from Medicare to VA without any increase in overall ED utilization. These findings have important implications for VA health care financing and delivery. [ABSTRACT FROM AUTHOR]

Objective: To quantify shared patient relationships between primary care physicians (PCPs) and cardiologists and oncologists and the degree to which those relationships were captured within insurance networks. Data Sources: Secondary analysis of Vericred data on physician networks, CareSet data on physicians' shared Medicare patients, and insurance plan attributes from Health Insurance Compare. Data validation exercises used data from Physician Compare and IQVIA. Study Design: Cross‐sectional study of the PCP‐to‐specialist in‐network shared patient percentage (primary outcome). We also categorized networks by insurance market segment (Medicare Advantage [MA], Medicaid managed care, small‐group or individually purchased), insurance plan type, and network breadth. Data Extraction: We analyzed data on 219,982 PCPs, 29,400 cardiologists, and 22,745 oncologists who, in 2021, accepted MA (n = 941 networks), Medicaid managed care (n = 293), and individually‐purchased (n = 332) and small‐group (n = 501) plans. Principal Findings: Networks captured, on average, 64.6% of PCP‐cardiology shared patient ties, and 61.8% of PCP‐oncologist ties. Less than half of in‐network ties (44.5% and 38.9%, respectively) were among physicians with a common organizational affiliation. After adjustment for network breadth, we found no evidence of differences in the shared patient percentage across insurance market segments or networks of different types (p‐value >0.05 for all comparisons). An exception was among national versus local and regional networks, where we found that national plans captured fewer shared patient ties, particularly among the narrowest networks (58.4% for national networksvs. 64.7% for local and regional networks for PCP‐cardiology). Conclusions: Given recent trends toward narrower networks, our findings underscore the importance of incorporating additional and nuanced measures of network composition to aid plan selection (for patients) and to guide regulatory oversight. [ABSTRACT FROM AUTHOR]

ObjectiveTo document differences among racial/ethnic/gender groups in specialty behavioral health care (BH) utilization/expenditures; examine whether these differences are driven by probability vs intensity of treatment; and identify whether differences are explained by socioeconomic status (SES).Data sourceThe cohort consists of adults continuously enrolled in Optum plans with BH benefits during 2013.Study designWe modeled each outcome using linear regressions among the entire sample stratified by race/ethnicity, language and gender. Then, we estimated logistic regressions of the probability that an enrollee had any spending/use in a given service category (service penetration) and linear regressions of spending/use among the user subpopulation (treatment intensity). Lastly, all analyses were rerun with SES controls.Data collectionThis study links administrative data from a managed BH organization to a commercial marketing database.Principal findingsWe found that in many cases, racial/ethnic minorities had lower specialty BH expenditures/utilization, relative to whites, primarily driven by differences in service penetration. Among women, relative to whites, Asian non-English speakers, Asian English speakers, Hispanic non-English speakers, Hispanic English speakers, and blacks had $106, $95, $90, $48, and $61 less in total expenditures. SES explained racial/ethnic differences in treatment intensity but not service penetration.ConclusionsIn this population, SES was not a major driver of racial/ethnic differences in specialty BH utilization. Future studies should explore the role of other factors not studied here, such as stigma, cultural competence, and geography.

OBJECTIVE:The Affordable Care Act (ACA) introduced reforms to mitigate adverse selection into and within the individual insurance market. We examined the traits and predicted medical spending of enrollees in California post-ACA. DATA SOURCES:Survey of 2,103 enrollees in individual market plans, on- and off-exchange, in 2014. STUDY DESIGN:We compared actual versus potential participants using data from the 2014 California Health Interview Survey on respondents who were individually insured or uninsured. We predicted annual medical spending for each group using age, sex, self-rated health, body mass index, smoking status, and income. PRINCIPAL FINDINGS:Average predicted spending was similar for actual ($3,377, 95 percent CI [$3,280-$3,474]) and potential participants ($3,257 [$3,060-$3,454]); however, some vulnerable subgroups were underrepresented. On- versus off-exchange enrollees differed in sociodemographic and health traits with modest differences in spending ($3,448 [$3,330-$3,565] vs. $3,175 [$3,012-$3,338]). CONCLUSIONS:We did not find evidence of selection into the overall insurance pool in 2014; however, differences by exchange status reflect the importance of including off-exchange enrollees in analyses and the pool for risk adjustment. California's post-ACA individual market has been a relative success, highlighting the importance of state policies and outreach efforts to encourage participation in the market.

Objective: To assess the association between the adoption of presumptive eligibility for pregnancy Medicaid in Kansas in 2016 and timely prenatal care access.Data Source: 2012-2019 National Center for Health Statistics natality files.Study Design: We used difference-in-differences to compare outcomes before (2012-2015) and after (2017-2019) presumptive eligibility in Kansas relative to seven control group states overall and stratified by maternal education. Outcomes included first-trimester prenatal care, the month of first prenatal visit, and adequate prenatal care.Data Collection/extraction Methods: All live births among adults aged 20 or older in Kansas, Idaho, Missouri, Nebraska, Tennessee, Utah, Wisconsin, and Wyoming.Principal Findings: Among all births, we found no evidence that presumptive eligibility in Kansas resulted in changes in prenatal care use. Among individuals with high school education or less, presumptive eligibility was associated with a 1.92 percentage-point increase (95% CI: 0.64, 4.35) in first-trimester prenatal care, driven by earlier month of first prenatal care visit.Conclusions: Presumptive eligibility in Medicaid non-expansion states may lead to small improvements in early prenatal care among individuals with lower education, but other interventions may be needed. [ABSTRACT FROM AUTHOR]

ObjectiveTo determine the effect of state-level dependent coverage expansion (DCE) with and without other state health reforms on exit from dependent coverage for adolescents and young adults (AYA).Data sourcesAdministrative longitudinal data for 131,542 privately insured AYA in Massachusetts (DCE with other reforms) versus Maine and New Hampshire (DCE without other reforms) across three periods: prereform (1/00-12/06), poststate reform (1/07-9/10), and postfederal reform (10/10-12/12).Study designA difference-in-differences estimator was used to determine the rate of exit from dependent coverage, age at exit from dependent coverage, and re-uptake of dependent coverage among AYA in states with comprehensive reforms versus DCE only.Principal findingsImplementation of DCE with other reforms was significantly associated with a 23 percent reduction in exit from dependent coverage among AYA compared to the reduction observed for DCE alone. Additionally, comprehensive reforms were associated with over two additional years of dependent coverage for the average AYA and a 33 percent increase in the odds of regaining dependent coverage after a prior loss.ConclusionsFindings suggest that an individual mandate and other reforms may enhance the effect of DCE in preventing loss of coverage among AYA.

ObjectiveDid mental health cost-sharing decrease following implementation of the Mental Health Parity and Addiction Equity Act (MHPAEA)?Data sourceSpecialty mental health copayments, coinsurance, and deductibles, 2008-2013, were obtained from benefits databases for "carve-in" plans from a national commercial managed behavioral health organization.Study designBivariate and regression-adjusted analyses compare the probability of use and (conditional) level of cost-sharing pre- and postparity. An interaction term is added to compare differential levels of pre- and postparity cost-sharing changes for plans that were and were not already at parity pre-MHPAEA.FindingsControlling for employer/plan characteristics, MHPAEA is associated with higher intermediate care copayments ($15.9) but lower outpatient ($2.6) copayments among in-network-only plans. Among plans with in- and out-of-network benefits, MHPAEA is associated with lower inpatient ($23.2) and outpatient ($2.5) copayments, but increases in inpatient and intermediate in-network and out-of-network coinsurance (about 1 percentage point). Among the few plans not at parity pre-MHPAEA, changes in use and level of cost-sharing associated with MHPAEA were more dramatic.ConclusionMixed evidence that MHPAEA led to more generous mental health benefits may stem from the finding that many plans were already at parity pre-MHPAEA. Future policy focus in mental health may shift to slowing growth in cost-sharing for all health services.

Objective: To examine factors associated with accurate reporting of private and public health insurance coverage. Data sources: Minnesota health plan enrollment records provided the sample for the Comparing Health Insurance Measurement Error (CHIME) study, a survey conducted in 2015 that randomly assigned enrollees to treatments that included health insurance questions from the American Community Survey (ACS) or the redesigned Current Population Survey Annual Social and Economic Supplement (CPS). Study design: Reverse record check study that compared CHIME study survey responses to enrollment records of coverage type (direct purchase on and off the Marketplace, Medicaid, or MinnesotaCare), service use, subsidy receipt, and duration of coverage from a major insurer. Data collection methods: Using matched enrollment and CHIME survey data and logistic regression, we examined correlates of accurate insurance type reporting, including characteristics of the insurance coverage, the covered individual, respondent, and family. Principal findings: Reporting accuracy across treatment and coverage type is high (77%–84%). As with past research, accurate reporting of public insurance is higher for people with characteristics consistent with eligibility for public insurance for both survey treatments. For the ACS treatment, reports of direct purchase insurance are more accurate for enrollees who receive a premium subsidy. Conclusions: Given the complexity of health insurance measurement and frequently changing policy environment, differences in reporting accuracy across treatments or coverage types are not surprising. Several results have important implications for data editing and modeling routines. First, adding premium and subsidy questions in federal surveys should prove useful given the finding that subsidy receipt is associated with reporting accuracy. Second, across both survey treatments, people whose opportunity structures (race, ethnicity, and income) match public program eligibility are accurate reporters of this coverage. This evidence supports using these commonly collected demographic variables in simulation, imputation, and editing routines. [ABSTRACT FROM AUTHOR]

ObjectiveTo estimate health care expenditure trends among young adults ages 19-25 before and after the 2010 implementation of the Affordable Care Act (ACA) provision that extended eligibility for dependent private health insurance coverage.Data sourcesNationally representative Medical Expenditure Panel Survey data from 2008 to 2012.Study designWe conducted repeated cross-sectional analyses and employed a difference-in-differences quantile regression model to estimate health care expenditure trends among young adults ages 19-25 (the treatment group) and ages 27-29 (the control group).Principal findingsOur results show that the treatment group had 14 percent lower overall health care expenditures and 21 percent lower out-of-pocket payments compared with the control group in 2011-2012. The overall reduction in health care expenditures among young adults ages 19-25 in years 2011-2012 was more significant at the higher end of the health care expenditure distribution. Young adults ages 19-25 had significantly higher emergency department costs at the 10th percentile in 2011-2012. Differences in the trends of costs of private health insurance and doctor visits are not statistically significant.ConclusionsIncreased health insurance enrollment as a consequence of the ACA provision for dependent coverage has successfully reduced spending and catastrophic expenditures, providing financial protections for young adults.

Objective: To discuss and develop difference‐in‐difference estimators for categorical outcomes and apply them to estimate the effect of the Affordable Care Act's Medicaid expansion on insurance coverage. Data Sources: Secondary analysis of Survey on Income and Program Participation (SIPP) data on health insurance coverage types before (January 2013) and after (December 2015) Medicaid expansion in 39 US states (19 expansion and 20 non‐expansion). Study Design: We develop difference‐in‐difference methods for repeated measures (panel data) of categorical outcomes. We discuss scale‐dependence of DID assumptions for marginal and transition effect estimates and specify a new target estimand: the difference between outcome category transitions under treatment versus no treatment. We establish causal assumptions about transitions that are sufficient to identify this and a marginal target estimand. We contrast the marginal estimands identified by the transition approach versus an additive assumption only about marginal evolution. We apply both the marginal and transition approaches to estimate the effects of Medicaid expansion on health insurance coverage types (employer‐sponsored; other private, non‐group; public; and uninsured). Data Extraction: We analyzed 16,027 individual survey responses from people aged 18–62 years in the 2014 SIPP panel. Principal Findings: We show that the two identifying assumptions are equivalent (on the scale of the marginals) if either the baseline marginal distributions are identical or the marginals are constant in both groups. Applying our transitions approach to the SIPP data, we estimate a differential increase in transitions from uninsured to public coverage and differential decreases in transitions from uninsured to private, non‐group coverage and in remaining uninsured. Conclusions: By comparing the assumption that marginals are evolving in parallel to an assumption about transitions across outcome values, we illustrate the scale‐dependence of difference‐in‐differences. Our application shows that studying transitions can illuminate nuances obscured by changes in the marginals. [ABSTRACT FROM AUTHOR]

ObjectiveTo predict changes in wage growth for health care workers based on projections of insurance enrollment from the Affordable Care Act (ACA).Data sourcesEnrollment data came from three large employers and a sampling of premiums from ehealthinsurance.com. Information on state Medicaid eligibility rules and costs were from the Kaiser Family Foundation. National predictions were based on the MEPS and Medicare Current Beneficiary surveys. Bureau of Labor Statistics data were used to estimate employment.Study designWe projected health insurance enrollment by plan type using a health plan choice model. Using claims data, we measured the services demanded for each plan choice and year. Projections of labor demand were based on current output/input ratios. Changes in wages resulting from changes in labor demand from 2014 to 2021 were based on labor supply and demand elasticities.Principal findingsExpenditures required to retain and grow the health care workforce will increase substantially. Wages will increase most for professions with the greatest training requirements (physicians and registered nurses). The largest impact will be felt in 2015.ConclusionsProjected wage increases for health care workers may drive substantial growth in insurance premiums and reduce the affordability of health insurance.

ObjectiveTo evaluate the effects of state insurance mandates requiring insurance plans to cover Pap tests, the standard screening for cervical cancer that is recommended for nearly all adult women.Data sourcesIndividual-level data on 600,000 women age 19-64 from the CDC's Behavioral Risk Factor Surveillance System.Study designTwenty-four states adopted state mandates requiring private insurers in the state to cover Pap tests from 1988 to 2000. We performed a difference-in-differences analysis comparing within-state changes in Pap test rates before and after adoption of a mandate, controlling for the associated changes in other states that did not adopt a mandate.Principal findingsDifference-in-differences estimates indicated that the Pap test mandates significantly increased past 2-year cervical cancer screenings by 1.3 percentage points, with larger effects for Hispanic and non-Hispanic white women. These effects are plausibly concentrated among insured women.ConclusionsMandating more generous insurance coverage for even inexpensive, routine services with already high utilization rates such as Pap tests can significantly further increase utilization.

Objective: To (1) characterize change in type of insurance coverage among childhood cancer survivors from diagnosis to survivorship and (2) examine whether insurance change is associated with cancer‐related follow‐up care utilization. Data Sources: Participants in this study were derived from the Project Forward study, a population‐based, observational study of childhood cancer survivors in Los Angeles County that used California Cancer Registry data to identify participants. Study Design: Multivariable logistic regression models incorporating survey nonresponse weights estimated the change in the marginal predicted probabilities of insurance change and survivorship care, adjusting for demographic, socioeconomic, and clinical covariates and clustering by treating hospital. Data Collection/Extraction Methods: Study participants were diagnosed with cancer who were younger than age 20 years while living in Los Angeles County from 1996 to 2010 and were older than the age 18 years at the time of survey participation, from 2015 to 2017 (N = 1106). Principal Findings: Most participants were 18–26 years of age, male, diagnosed before 2004, Hispanic/Latino race/ethnicity, single, without children, highly educated, not employed full time, and lived with their parents at survey. Almost half (N = 529) of participants experienced insurance change from diagnosis to survivorship. Insurance change was associated with insurance coverage at diagnosis, as those who were uninsured were most likely to experience change and gain coverage during survivorship (by 51 percentage points [ppt], standard error [SE] of 0.05). Survivors who experienced any change had decreased probability of reporting a recent cancer‐related follow‐up care visit, a disparity that was magnified for those who lost insurance coverage (−5 ppt, SE 0.02 for those who gained coverage; −15 ppt, SE 0.04 for those who lost coverage). Conclusions: Insurance coverage change was associated with lower cancer‐related follow‐up care utilization. Indeed, survivors who experienced any insurance coverage change had decreased probability of having a cancer‐related follow‐up care visit, and this was magnified for those who lost their insurance coverage. [ABSTRACT FROM AUTHOR]

ObjectiveTo compare physicians' self-reported willingness to provide new patient appointments with the experience of research assistants posing as either a Medicaid beneficiary or privately insured person seeking a new patient appointment.Data sources/study settingSurvey administered to California physicians and telephone calls placed to a subsample of respondents.Study designCross-sectional comparison.Data collection/extraction methodsAll physicians whose California licenses were due for renewal in June or July 2013 were mailed a survey, which included questions about acceptance of new Medicaid and new privately insured patients. Subsequently, research assistants using a script called the practices of a stratified random sample of 209 primary care physician respondents in an attempt to obtain a new patient appointment. By design, half of the physicians selected for the telephone validation reported on the survey that they accepted new Medicaid patients and half indicated that they did not.Principal findingsThe percentage of callers posing as Medicaid patients who could schedule new patient appointments was 18 percentage points lower than the percentage of physicians who self-reported on the survey that they accept new Medicaid patients. Callers were also less likely to obtain appointments when they posed as patients with private insurance.ConclusionsPhysicians overestimate the extent to which their practices are accepting new patients, regardless of insurance status.

Objective: To describe physicians' variation in de-adopting concurrent statin and fibrate therapy for type 2 diabetic patients following a reversal in clinical evidence.Data Sources: We analyzed 2007-2015 claims data from OptumLabs® Data Warehouse, a longitudinal, real-world data asset with de-identified administrative claims and electronic health record data.Study Design: We modeled fibrate use among Medicare Advantage and commercially insured type 2 diabetic statin users before and after the publication of the ACCORD lipid trial, which found statins and fibrates were no more effective than statins alone in reducing cardiovascular events among type 2 diabetic patients. We modeled fibrate use trends with physician random effects and physician characteristics such as age and specialty.Data Extraction: We identified patient-year-quarters with one year of continuous insurance enrollment, type 2 diabetes diagnoses, and fibrate use. We designated the physician most responsible for patients' diabetes care based on evaluation and management visits and prescriptions of glucose-lowering drugs.Principal Findings: Fibrate use increased by 0.12 percentage points per quarter among commercial patients (95% CI, 0.10 to 0.14) and 0.17 percentage points per quarter among Medicare Advantage patients (95% CI, 0.13 to 0.20) before the trial and then decreased by 0.16 percentage points per quarter among commercial patients (95% CI, -0.18 to -0.15) and 0.05 percentage points per quarter among Medicare Advantage patients (95% CI, -0.06 to -0.03) after the trial. However, 45% of physicians treating commercial patients and 48% of physicians treating Medicare Advantage patients had positive trends in prescribing following the trial. Physicians' characteristics did not explain their variation (pseudo R2  = 0.000).Conclusion: On average, physicians decreased fibrate prescribing following the ACCORD lipid trial. However, many physicians increased prescribing following the trial. Observable physician characteristics did not explain variations in prescribing. Future research should examine whether physicians vary similarly in other de-adoption settings. [ABSTRACT FROM AUTHOR]

ObjectiveTo assess the impact of a pharmacy benefit change on mail order pharmacy (MOP) uptake.Data sources/study settingRace-stratified, random sample of diabetes patients in an integrated health care delivery system.Study designIn this natural experiment, we studied the impact of a pharmacy benefit change that conditionally discounted medications if patients used MOP and prepaid two copayments. We compared MOP uptake among those exposed to the benefit change (n = 2,442) and the reference group with no benefit change (n = 8,148), and estimated differential MOP uptake across social strata using a difference-in-differences framework.Data collection/extraction methodsAscertained MOP uptake (initiation among previous nonusers).Principal findingsThirty percent of patients started using MOP after receiving the benefit change versus 9 percent uptake among the reference group (p < .0001). After adjustment, there was a 26 percentage point greater MOP uptake (benefit change effect). This benefit change effect was significantly smaller among patients with inadequate health literacy (15 percent less), limited English proficiency (14 percent less), and among Latinos and Asians (24 and 16 percent less compared to Caucasians).ConclusionsConditionally discounting medications delivered by MOP effectively stimulated MOP uptake overall, but it unintentionally widened previously existing social gaps in MOP use because it stimulated less MOP uptake in vulnerable populations.

ObjectiveTo investigate the determinants and quality of coverage decisions among uninsured choosing plans in a hypothetical health insurance marketplace.Study settingTwo samples of uninsured individuals: one from an Internet-based sample comprised largely of young, healthy, tech-savvy individuals (n = 276), and the other from low-income, rural Virginians (n = 161).Study designWe assessed whether health insurance comprehension, numeracy, choice consistency, and the number of plan choices were associated with participants' ability to choose a cost-minimizing plan, given their expected health care needs (defined as choosing a plan costing no more than $500 in excess of the total estimated annual costs of the cheapest plan available).Data collectionPrimary data were collected using an online questionnaire.Principal findingsUninsured who were more numerate showed higher health insurance comprehension; those with more health insurance comprehension made choices of health insurance plans more consistent with their stated preferences; and those who made choices more concordant with their stated preferences were less likely to choose a plan that cost more than $500 in excess of the cheapest plan available.ConclusionsIncreasing health insurance comprehension and designing exchanges to facilitate plan comparison will be critical to ensuring the success of health insurance marketplaces.

Objective: To assess changes in physicians' provision of care to duals (low-income individuals with Medicare and Medicaid) in response to a policy that required Medicaid to fully pay Medicare's cost sharing for office visits with these patients. This policy-a provision of the Affordable Care Act-effectively increased payments for office visits with duals by 0%-20%, depending on the state, in 2013 and 2014.Data Sources: Fee-for-service claims for a 5% random sample of Medicare beneficiaries in 2010-2016.Study Design: We conducted a difference-in-differences analysis to compare changes in office visits among Qualified Medicare Beneficiaries (QMBs)-the largest subpopulation of duals for whom payment rates were affected by this policy-to changes among other low-income Medicare beneficiaries for whom payment rates were unaffected (pooled across all states). Next, we conducted a triple-differences analysis that compared changes between QMBs and other low-income beneficiaries in 33 states with payment rate increases of approximately 20% to analogous changes in 14 states without payment increases.Data Collection: The study included administrative Medicare enrollment and claims data for QMBs and a comparison group of other low-income Medicare beneficiaries (1 914 073 beneficiary-years from 2010 to 2016).Principal Findings: Nationally, we did not find a differential increase in office visits among QMBs versus other low-income beneficiaries that coincided with this payment change. In the triple-differences analysis, we did not observe a greater increase in visits among QMBs vs other low-income beneficiaries in states where the policy resulted in large (approximately 20%) increases in payment rates vs states where payment rates were unaffected (triple-differences estimate: -0.12 annual visits, 95% CI: -0.28, 0.04; P = 0.15).Conclusions: Physicians' provision of care to low-income Medicare beneficiaries may not be responsive to short-run payment changes. [ABSTRACT FROM AUTHOR]

Objective: To provide evidence on the effects of expansions to private and public insurance programs on adolescent specialty substance use disorder (SUD) treatment use.Data Source/study Setting: The Treatment Episodes Data Set (TEDS), 1996 to 2017.Study Design: A quasi-experimental difference-in-differences design using observational data.Data Collection: The TEDS provides administrative data on admissions to specialty SUD treatment.Principal Findings: Expansions of laws that compel private insurers to cover SUD treatment services at parity with general health care increase adolescent admissions by 26% (P < .05). These increases are driven by nonintensive outpatient admissions, the most common treatment episodes, which rise by 30% (P < .05) postparity law. In contrast, increases in income eligibility for public insurance targeting those 6-18 years old are not statistically associated with SUD treatment.Conclusions: Private insurance expansions allow more adolescents to receive SUD treatment, while public insurance income eligibility expansions do not appear to influence adolescent SUD treatment. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Objective: To identify the association between insulin out-of-pocket costs (OOPC) and adherence to insulin in Medicare Advantage (MA) patients., Data Sources and Study Setting: The study is based on Optum Labs Data Warehouse, a longitudinal, real-world data asset with de-identified administrative claims and electronic health record data., Study Design: Using descriptive and multivariable logistic regression analyses, we identified the likelihood of patients with diabetes having ≥60 consecutive days between an expected insulin fill date and the actual fill date (refill lapse) by OOPC, categorized by $0, >$0-$20 (reference), >$20-$35, >$35-$50, and > $50 per 30-day supply., Data Collection/extraction Methods: The study included MA enrollees with type 1 or type 2 diabetes and prescription claims for insulin between 2014 and 2018., Principal Findings: Those with average insulin OOPC per 30-day supply >$35 or $0 were more likely to have an insulin refill lapse versus OOPC of >$0 to $20, with odds ratios ranging 1.18 (95% CI 1.13-1.22) to 1.74 (95% CI 1.66-1.83) depending on OOPC group and diabetes type., Conclusions: Capping average insulin OOPC at $35 per 30-day supply may help avoid cost-related insulin non-adherence in MA patients; efforts to address non-cost barriers to medication adherence remain important., (© 2023 The Authors. Health Services Research published by Wiley Periodicals LLC on behalf of Health Research and Educational Trust.)

Objective: To examine whether physicians in tiered physician networks where tier assignments are based on "intensity" of care, which is the quantity of resources used per-episode of care, change their intensity after learning detailed information about how their intensity compares to their peers., Data Sources: Administrative data on intensity and quality at the physician-episode level for all physicians included in a tiered physician network offered through the Massachusetts Group Insurance Commission (GIC) in 2010-2015. Data on physicians' share of revenue from GIC patients from the 2012 Massachusetts All-Payer Claims Database., Study Design: For 21,086 physicians in seven specialties, we estimate the impact of the dissemination of detailed intensity performance information in 2014 on physician intensity per episode of care overall and decomposed into physician services, facility, and pharmaceutical subcomponents. Intensity outcomes were measured using a standardized price schedule. Using a difference-in-differences regression, we compared physicians with high exposure to the tiered network via a large share of their revenue coming from GIC patients ("GIC share") to physicians who were less exposed. Measures of intensity of care and GIC share were log-transformed, and models controlled for physician-episode type fixed effects., Data Extraction Methods: We linked GIC share to administrative data using National Provider Identifier., Principal Findings: There were no statistically significant differences in total intensity of care with the informational intervention for physicians in procedure-based specialties (-0.12 elasticity of intensity per episode with respect to GIC patient share, 95% CI -0.30 to 0.06) or in relationship-based specialties (0.09, 95% CI -0.15 to 0.33). There were also no differences in intensity of subcomponents of care following the intervention., Conclusions: Tiered network incentives had no detectable impact on intensity of care that physicians provided to patients., (© 2023 Health Research and Educational Trust.)

Objective: The Affordable Care Act allows insurers to charge up to 50% higher premiums to tobacco users, making tobacco use the only behavioral factor that can be used to rate premiums in the nongroup insurance market. Some states have set more restrictive limits on rating for tobacco use, and several states have outlawed tobacco premium surcharges altogether. We examined the impact of state level tobacco surcharge policy on health insurance enrollment decisions among smokers.Study Design: We compared insurance enrollment in states that did and did not allow tobacco surcharges, using a difference-in-difference approach to compare the policy effects among smokers and nonsmokers. We also used geographic variation in tobacco surcharges to examine how the size of the surcharge affects insurance coverage, again comparing smokers to nonsmokers.Data Collection: We linked data from two components of the Current Population Survey-the 2015 and 2019 Annual Social and Economic Supplement and the Tobacco Use Supplement, which we combined with data on marketplace plan premiums. We also collected qualitative data from a survey of smokers who did not have insurance through an employer or public program.Principal Findings: Allowing a tobacco surcharge reduced insurance enrollment among smokers by 4.0 percentage points (P = .01). Further, smokers without insurance through an employer or public program were 9.0 percentage points less likely (P < .01) to enroll in a nongroup plan if they were subject to a tobacco surcharge. In states with surcharges, enrollment among smokers was 3.4 percentage points lower (P < .01) for every 10 percentage point increase in the tobacco surcharge.Conclusions: Tobacco use is the largest cause of preventable illness in the United States. State tobacco surcharge policy may have a substantial impact on whether tobacco users choose to remain insured and consequently their ability to receive care critical for preventing and treating tobacco-related disease. [ABSTRACT FROM AUTHOR]

Objectives: To examine changes in carve-out financial requirements (copayments, coinsurance, use of deductibles, and out-of-pocket maxima) following the Mental Health Parity and Addiction Equity Act (MHPAEA).Data Source/study Setting: Specialty mental health benefit design information for employer-sponsored carve-out plans from a national managed behavioral health organization's claims processing engine (2008-2013).Study Design: This pre-post study reports linear and logistic regression as the main analysis.Data Collection/extraction Methods: NA.Principal Findings: Copayments for in-network emergency room (-$44.9, 95% CI: -78.3, -11.5; preparity mean: $56.2), outpatient services (eg, individual psychotherapy: -$7.4, 95% CI: -10.5, -4.2; preparity mean: $17.8), and out-of-network coinsurance for emergency room (-11 percentage points, 95% CI: -16.7, -5.4; preparity mean: 38.8 percent) and outpatient (eg, individual psychotherapy: -5.8 percentage points, 95% CI: -10.0, -1.6; preparity mean 41.0 percent) decreased. Probability of family OOP maxima use (29 percentage points, 95% CI: 19.3, 38.6; preparity mean: 36 percent) increased. In-network outpatient coinsurance increased (eg, individual psychotherapy: 4.5 percentage points, 95% CI: 1.1, 7.9; preparity mean: 2.7 percent), as did probability of use of family deductibles (15 percentage points, 95% CI: 6.1, 23.3; preparity mean: 38 percent).Conclusions: MHPAEA was associated with increased generosity in most financial requirements observed here. However, increased use of deductibles may have reduced generosity for some patients. [ABSTRACT FROM AUTHOR]

Objective: To estimate the impact of the major components of the ACA (Medicaid expansion, subsidized Marketplace plans, and insurance market reforms) on health care access and self‐assessed health during the first 2 years of the Trump administration (2017 and 2018). Data Source: The 2011‐2018 waves of the Behavioral Risk Factor Surveillance System (BRFSS), with the sample restricted to nonelderly adults. The BRFSS is a commonly used data source in the ACA literature due to its large number of questions related to access and self‐assessed health. In addition, it is large enough to precisely estimate the effects of state policy interventions, with over 300 000 observations per year. Design: We estimate difference‐in‐difference‐in‐differences (DDD) models to separately identify the effects of the private and Medicaid expansion portions of the ACA using an identification strategy initially developed in Courtemanche et al (2017). The differences come from: (a) time, (b) state Medicaid expansion status, and (c) local area pre‐2014 uninsured rates. We examine ten outcome variables, including four measures of access and six measures of self‐assessed health. We also examine differences by income and race/ethnicity. Principal Findings: Despite changes in ACA administration and the political debate surrounding the ACA during 2017 and 2018, including these fourth and fifth years of postreform data suggests continued gains in coverage. In addition, the improvements in reported excellent health that emerged with a lag after ACA implementation continued during 2017 and 2018. Conclusions: While gains in access and self‐assessed health continued in the first 2 years of the Trump administration, the ongoing debate at both the federal and state level surrounding the future of the ACA suggests the need to continue monitoring how the law impacts these and many other important outcomes over time. [ABSTRACT FROM AUTHOR]

Objective: To add to the evidence base on causal linkages between health insurance coverage and health status, controlling for sociodemographic factors, by analyzing longitudinal data. Data Source: Secondary data from the Panel Study of Income Dynamics (PSID), 2009‐17, which is a longitudinal, multigenerational study covering a wide array of socioeconomic topics that began in 1968 but has only recently begun collecting useful information on individual health insurance. Study Design: 2017 data on self‐reported health status, work limitations, and death were analyzed as outcomes based upon the degree of exposure to health insurance in 2011‐17. All variables were collected biannually for four years beginning in 2011. Having health insurance at each point in time was, in turn, modeled as a function of several sociodemographic factors. Data Extraction Methods: Data were downloaded using the crosswalk tool available at the PSID website. Because individual health insurance questions were only asked of heads and spouses in households beginning in 2011, we analyzed only these records. Principal Findings: Among respondents who were not in fair or poor health in 2009, each additional 2 years of subsequent reported insurance coverage reduced the chance of reporting fair or poor health in 2017 by 10 percent; however, this effect was not present for black respondents. Conclusions: Our results suggest that the effect of health insurance on health status may compound over time, although unevenly by race. Since people who report fair or poor health status represent the bulk of utilization and spending, our findings provide evidence in support of viewing coverage expansions as investments that will pay dividends in the form of lower utilization over time. More work is needed to produce detailed estimates of cost savings, which may in turn influence policy, as well as to understand and address the source of racial disparity. [ABSTRACT FROM AUTHOR]

ObjectiveTo compare drug costs and adherence among Medicare beneficiaries with the standard Part D coverage gap versus supplemental gap coverage in 2006.Data sourcesPharmacy data from Medicare Advantage Prescription Drug (MAPD) plans.Study designParallel analyses comparing beneficiaries aged 65+ with diabetes in an integrated MAPD with a gap versus no gap (n=28,780); and in a network-model MAPD with a gap versus generic-only coverage during the gap (n=14,984).Principal findingsDrug spending was 3 percent (95 percent confidence interval [CI]: 1-4 percent) and 4 percent (CI: 1-6 percent) lower among beneficiaries with a gap versus full or generic-only gap coverage, respectively. Out-of-pocket expenditures were 189 percent higher (CI: 185-193 percent) and adherence to three chronic drug classes was lower among those with a gap versus no gap (e.g., odds ratio=0.83, CI: 0.79-0.88, for oral diabetes drugs). Annual out-of-pocket spending was 14 percent higher (CI: 10-17 percent) for beneficiaries with a gap versus generic-only gap coverage, but levels of adherence were similar.ConclusionsAmong Medicare beneficiaries with diabetes, having the Part D coverage gap resulted in lower total drug costs, but higher out-of-pocket spending and worse adherence compared with having no gap. Having generic-only coverage during the gap appeared to confer limited benefits compared with having no gap coverage.

Objective: To provide new evidence on the effects of large-scale public health insurance expansions, associated with the Affordable Care Act (ACA), on the availability of specialty mental health care treatment in the United States. We measure availability with the probability that a provider accepts Medicaid.Data Source/study Setting: The National Mental Health Services Survey (N-MHSS) 2010-2018.Study Design: A quasi-experimental differences-in-differences design using observational data.Data Collection: The N-MHSS provides administrative data on the universe of specialty mental health care providers in the United States. Response rates are above 90 percent in all years. Data cover 85 019 provider/year observations.Principal Findings: ACA-Medicaid expansion increases the probability that a provider accepts Medicaid by 1.69 percentage points, 95 percent confidence interval: [0.0017,0.0321], which corresponds to an increase from 87.27 percent pre-expansion to 90.27 percent postexpansion in expansion states or a 1.94 percent increase. We observe spillovers to Medicare, although this finding is sensitive to specification.Conclusions: This study provides evidence on the impact of ACA-Medicaid expansion on accepted forms of payment for specialty mental health care treatment. Findings suggest that expansion increases availability of providers who deliver valuable care for enrollees with severe mental illness. These findings may help policy makers reflecting on the future directions of the US health care delivery system. [ABSTRACT FROM AUTHOR]

Objective: To examine the association of a national insurer's reference-based pricing (RBP), program for outpatient advanced imaging-a benefit design to encourage patients to choose lower-price facilities.Data Source/study Setting: Administrative and medical claims data for three self-insured employers that introduced RBP and a comparison group without RBP.Study Design: Difference-in-difference comparison of pre-RBP (2014) and post-RBP (2015-6) care between intervention and comparison groups.Data Collection/extraction Method: We identified 137 680 imaging procedures (4602 intervention group; 133 078 comparison group) in 2014-2016.Principal Findings: In the first post-RBP year (2015), there was no change in choice of facility; by the second year, RBP-exposed enrollees were 21.9 pp (95% CI: 18.5, 25.3) more likely to choose a lower-priced facility and net prices were $101.05 (95% CI: -$130.65, -$71.46), a difference of 8.1 percent lower. RBP was associated with higher patient out-of-pocket spending in the first post-RBP year ($31.82; 95% CI: $10.91, $52.73). There was no change in utilization, and higher-priced providers did not lower prices in the postperiod. Net savings represented 0.3 percent of outpatient spending.Conclusions: Reference-based pricing for advanced imaging was associated with a shift to lower-priced facilities, but net impact on outpatient spending was modest. Patients paid increased out-of-pocket costs, though the amount declined after the first year of the program. [ABSTRACT FROM AUTHOR]

Objective: To compare different methods of indexing health care service prices for the commercially insured population across geographic markets.Data Sources: Health Care Cost Institute commercial claims data from 2012 to 2016.Study Design: We compare price indices computed using methods with differing levels of computational intensity: weighted-average versus regression-based methods. We separately compute indices of the prices paid for set of common inpatient and set of common outpatient services in different markets across the United States using each type of method. We subsequently examined the variation of and correlations between the resulting index values.Data Collection/extraction Methods: We computed health care service price indices separately using samples of inpatient and outpatient facility claims from 2012 to 2016 across 112 Core-Based Statistical Areas. Within each category of services, claims were limited to members under the age of 65 with employer-sponsored insurance. Both samples were limited to a common set of services that made up nearly 80 percent of the service use in the full sample every year.Principal Findings: We found that the methods studied produced highly correlated price indices (r > .94) with similar distributions across years for both inpatient and outpatient services.Conclusions: Our findings suggest that weighted-average methods, which are much less computationally intensive, will generate results similar to regression-based methods. [ABSTRACT FROM AUTHOR]

Objective: To examine the relationship between insurer market structure, health plan quality, and health insurance premiums in the Medicare Advantage (MA) program.Data Sources/study Setting: Administrative data files from the Centers for Medicare and Medicaid Services, along with other secondary data sources.Study Design: Trends in MA market concentration from 2008 to 2017 are presented, alongside logistic and linear regression models examining MA plan quality and premiums as a function of insurer market structure for 2011.Data Collection/extraction Methods: Data are publicly available.Principal Findings: MA plans that tend to operate in more concentrated MA markets have a higher predicted probability of receiving a high-quality health plan rating. Operating in more concentrated MA markets was also found to be associated with higher premiums. Among plans that tend to operate in very concentrated MA markets, high-quality MA plans were associated with premiums as much as two times higher than premiums associated with lower-quality plans.Conclusions: Any policies directed at enhancing insurer competition should consider implications for health plan quality, which may be very different than the implications for enrollee premiums. [ABSTRACT FROM AUTHOR]

Objective: To analyze factors associated with changes in prescription drug use and expenditures in the United States from 1999 to 2016, a period of rapid growth, deceleration, and resumed above-average growth.Data Sources/study Setting: The Medical Expenditure Panel Survey (MEPS), containing household and pharmacy information on over five million prescription drug fills.Study Design: We use nonparametric decomposition to analyze drug use, average payment per fill, and per capita expenditure, tracking the contributions over time of socioeconomic characteristics, health status and treated conditions, insurance coverage, and market factors surrounding the patent cycle.Data Collection/extraction Methods: Medical Expenditure Panel Survey data were combined with information on drug approval dates and patent status.Principal Findings: Per capita utilization increased by nearly half during 1999-2016, with changes in health status and treated conditions accounting for four-fifths of the increase. In contrast, per capita expenditures more than doubled, with individual characteristics only explaining one-third of the change. Other drivers of spending during this period include the changing pipeline of new drugs, drugs losing exclusivity, and changes in generic competition.Conclusions: Long-term trends in treated conditions were the fundamental drivers of medication use, whereas factors involving the patent cycle accelerated and decelerated spending growth relative to trends in use. [ABSTRACT FROM AUTHOR]

Objectives: To compare existing algorithms for classifying screening vs diagnostic colonoscopies and to quantify the increase in screening colonoscopy rates when Medicare began reimbursement in 2001 and when the Affordable Care Act (ACA) eliminated cost-sharing.Data Sources: Twenty percent random sample of fee-for-service (FFS) Medicare claims, 2000-2012.Study Design: Using recent administrative codes as tarnished gold standards, we examined the sensitivity and specificity of five published algorithms for classifying colonoscopies and calculated annual screening colonoscopy rates. We estimated the change in rates after Medicare began reimbursement and used difference-in-differences analysis to estimate the effects of eliminating cost-sharing by comparing states with and without a mandate to cover screening colonoscopy prior to the ACA.Findings: Model-based algorithms have higher sensitivity (0.53-0.99) than expert-based algorithms (0.35-0.39), but lower specificity (0.43-0.65 vs 0.79-0.88). All algorithms detected increases in screening from both Medicare's reimbursement change (range: 24-93/10 000) and the 2011 cost-sharing change (range: 1.1-34/10 000). Difference-in-difference estimates of the ACA's effect varied from 51 to 155 tests per 10 000 depending on the algorithm.Conclusions: Screening colonoscopy rates increased after eliminating cost-sharing in 2011, but the increase's size varied depending on the algorithm used to classify the indication. Improvements are needed in Medicare coding for screening. [ABSTRACT FROM AUTHOR]

Objective: To test whether a change from a telephone to mail and Internet survey in January 2018 affected the sample composition and uninsured estimates in the Gallup-Sharecare Well-Being Index.Data Sources: Gallup-Sharecare Well-Being Index (2013-2018).Study Design: Regression discontinuity analysis identified changes after the survey redesign in the estimated U.S. uninsured rate (adults 18-64) and in the sample's demographic composition.Principal Findings: After the survey redesign, the estimated uninsured rate fell 5.3 percentage points (P < 0.001), respondents were older and disproportionately white, more likely to have a college degree, and had higher average incomes. These changes were modestly reduced by survey weights.Conclusions: The shift to a mail survey (with a web option) led to an older, more educated sample with fewer minorities, and a significant break in trend in the estimated uninsured rate. [ABSTRACT FROM AUTHOR]

Objective: This commentary summarizes the methods and topics addressed in the special issue of HSR focused on linkage of United States Department of Veterans Affairs (VA) and non-VA datasets. The issue illustrates that researchers are increasingly linking diverse datasets as a valuable method for obtaining outcomes, treatments, and covariates to evaluate and examine health care delivery that includes non-VA services. The issue serves as a reference to VA and non-VA investigators alike who employ data linkage methods to address high-impact clinical and health policy evaluations that span different care systems and different datasets. [ABSTRACT FROM AUTHOR]

Objectives: To determine dementia prevalence and costs attributable to dementia using Veterans Health Administration (VHA) data with and without Medicare data.Data Sources: VHA inpatient, outpatient, purchased care and other data and Medicare enrollment, claims, and assessments in fiscal year (FY) 2013.Study Design: Analyses were conducted with VHA data alone and with combined VHA and Medicare data. Dementia was identified from a VHA sanctioned list of ICD-9 diagnoses. Attributable cost of dementia was estimated using recycled predictions.Data Collection: Veterans age 65 and older who used VHA and were enrolled in Traditional Medicare in FY 2013 (1.9 million).Principal Findings: VHA records indicated the prevalence of dementia in FY 2013 was 4.8 percent while combined VHA and Medicare data indicated the prevalence was 7.4 percent. Attributable cost of dementia to VHA was, on average, $10,950 per veteran per year (pvpy) using VHA alone and $6,662 pvpy using combined VHA and Medicare data. Combined VHA and Medicare attributable cost of dementia was $11,285 pvpy. Utilization attributed to dementia using VHA data alone was lower for long-term institutionalization and higher for supportive care services than indicated in combined VHA and Medicare data.Conclusions: Better planning for clinical and cost-efficient care requires VHA and Medicare to share data for veterans with dementia and likely more generally. [ABSTRACT FROM AUTHOR]

Objective: To examine the association of dual use of both Veterans Health Administration (VHA) and Medicare benefits with high-risk opioid prescriptions among Veterans aged 65 years and older with a musculoskeletal disorder diagnosis.Data Sources/study Setting: Data were obtained from the VA Musculoskeletal Disorder (MSD) cohort and national Medicare claims data from 2008 to 2010.Study Design: We conducted a retrospective analysis of Veterans enrolled in Medicare to examine the association of dual use with long-term opioid use (>90 days of prescription opioids/year) and overlapping opioid prescriptions. Multivariable logistic regression was performed adjusting for demographic and clinical characteristics.Data Collection/extraction Methods: We identified 21,111 Veterans enrolled in Medicare who entered the MSD cohort in 2008 and received an opioid prescription in 2010. We linked VHA data with Medicare claims data to identify opioid prescriptions for these Veterans in 2010.Principal Findings: As compared to Veterans who used only VHA or Medicare, Veterans with dual use of VHA and Medicare were significantly more likely to be prescribed long-term opioid therapy (OR = 4.61 (95 percent CI 4.05-5.25) and were also found to have higher median number of opioid prescriptions and higher odds of overlapping opioid prescriptions in 1 year. Patients reporting moderate-to-severe pain, non-white-race/ethnicity, and higher scoring on the Charlson comorbidity index had significantly higher odds of long-term opioid prescriptions.Conclusions: Among Veterans aged 65 years or older, dual use of both VHA and Medicare was associated with higher odds of long-term opioid therapy. Our findings suggest there may be benefit to combining VHA and non-VHA electronic health record data to minimize exposure to high-risk opioid prescribing. [ABSTRACT FROM AUTHOR]

Objective: To estimate the effect of Medicare use on the receipt of outpatient services from 2001 through 2015 for a cohort of Veterans Administration (VA) users who became age-eligible for Medicare in 1998-2000.Data Sources/study Setting: VA administrative data linked with Medicare claims for veterans who participated in the 1999 Large Health Survey of Enrolled Veterans.Study Design: We coded each veteran as VA-reliant or Medicare-reliant based on the number of visits in each system and compared the health and social risk factors between VA-reliant and Medicare-reliant veterans. We used bivariate probit and instrumental variables models to estimate the association between a veteran's reliance on Medicare and the receipt of outpatient procedures in Medicare and the VA.Principal Findings: Veterans who chose to rely on the VA (n = 4,317) had substantially worse social and health risk factors than Medicare-reliant veterans (n = 2,567). Medicare reliance was associated with greater use of outpatient services for 24 of the 28 types of services considered. Instrumental variable estimates found significant effects of Medicare reliance on receipt of advanced imaging and cardiovascular testing.Conclusions: Expanded access to fee-for-service care in the community may be expensive, while the VA will likely continue to care for the most vulnerable veterans. [ABSTRACT FROM AUTHOR]

Objective: Up to 70 percent of patients who receive care through Veterans Health Administration (VHA) facilities also receive care from non-VA providers. Using applied classification techniques, this study sought to improve understanding of how elderly VA patients use VA services and complementary use of non-VA care.Methods: The study included 1,721,900 veterans age 65 and older who were enrolled in VA and Medicare during 2013 with at least one VA encounter during 2013. Outpatient and inpatient encounters and medications received in VA were classified, and mutually exclusive patient subsets distinguished by patterns of VA service use were derived empirically using latent class analysis (LCA). Patient characteristics and complementary use of non-VA care were compared by patient subset.Results: Five patterns of VA service use were identified that were distinguished by quantity of VA medical and specialty services, medication complexity, and mental health services. Low VA Medical users tend to be healthier and rely on non-VA services, while High VA users have multiple high cost illnesses and concentrate their care in the VA.Conclusions: VA patients distinguished by patterns of VA service use differ in illness burden and the use of non-VA services. This information may be useful for framing efforts to optimize access to care and care coordination for elderly VA patients. [ABSTRACT FROM AUTHOR]

Objective: To examine the relationship between antihypertensive drug deintensification and recurrent falls in long-term care.Data Sources/settings: Department of Veterans Affairs (VA) inpatient, outpatient, and purchased care data, Minimum Data Set assessments from VA nursing homes (NHs), and Medicare claims from fiscal years 2010 - 2015.Study Design: We identified NH residents with evidence of overaggressive antihypertensive treatment, defined as systolic blood pressure (SBP) 80-120 and an index fall. Recurrent fall, hospitalization, and mortality within 30 days were compared between veterans whose antihypertensive medications were deintensified versus those whose antihypertensive medications were not using propensity score methods (PSM).Principal Findings: Among 2,212 NH residents with possibly overaggressive antihypertensive treatment, 11 percent experienced antihypertensive drug deintensification. Lower blood pressure, >1 antihypertensive drug, no congestive heart failure, fracture from index fall, and older age were associated with higher likelihood of deintensification. Antihypertensive deintensification was associated with statistically significant (p-value < .01) lower risk of recurrent fall among residents with SBP 80-100 (marginal effect = -11.4 percent; PSM = -13.6 percent) and higher risk of death among residents with SBP 101-120 (marginal effect = 2.1 percent, p-value = .07; with PSM = 4.3 percent, p-value = .04).Conclusions: Results provide some needed evidence and guidelines for deintensifying antihypertensive medication among frail older residents; since hypertension is prevalent among 54 percent of NH residents, the potential impact of new evidence is great. [ABSTRACT FROM AUTHOR]

Objective: To determine whether skilled nursing facilities (SNFs) chosen by health systems to participate in preferred provider networks exhibited differences in quality, costs, and patient outcomes relative to other SNFs after accounting for differences in case mix.Data Sources: Medicare provider and claims data, 2012 and 2013.Study Design: We compared SNFs included in preferred networks relative to other SNFs in the same market, prior to the establishment of preferred provider networks.Data Extraction Methods: We linked the SNFs in our sample to facility characteristics and quality data. We identified SNF admissions and hospitalizations in claims data and limited the analysis to patients discharged from the hospitals in our sample. We obtained patient characteristics from Medicare summary files and the preceding hospital stay.Principal Findings: Preferred SNFs exhibited better performance across publicly reported quality measures. Patients admitted to preferred SNFs exhibited shorter stays, lower Medicare payments, and lower probability of SNF readmission relative to nonpreferred SNFs.Conclusions: Our results imply that health systems selected SNFs with lower resource use and better performance on quality measures. Thus, the trend toward preferred provider networks could have implications for Medicare spending and patient health. [ABSTRACT FROM AUTHOR]

Objective: Examine the impact of the 2011 shortage of the drug cytarabine on patient receipt and timeliness of induction treatment for Acute Myeloid Leukemia (AML).Study Design: A retrospective cohort was utilized to examine odds of receipt of inpatient induction chemotherapy and time to first dose across major (N = 105) and moderate (N = 316) shortage time periods as compared to a nonshortage baseline (N = 1,147).Data Collection/extraction Methods: De-identified patient data from 2008 to 2011 Surveillance, Epidemiology, and End Results (SEER) were linked to 2007-2013 Medicare claims and 2007-2013 Hospital Characteristics.Principal Findings: Compared to prior nonshortage time period, patients diagnosed during a major drug shortage were 47 percent less likely (p < .05) to receive inpatient chemotherapy within 14 days of diagnosis. Patients who were younger, had a lower Charlson Comorbidity score, and for whom AML was a first primary cancer were prioritized across all periods.Conclusions: Period of major shortage of a generic oncolytic, without an equivalent therapeutic substitute, reduced timely receipt of induction chemotherapy treatment. More favorable economic and regulatory policies for generic drug suppliers might result in greater availability of essential, older generic drug products that face prolonged or chronic shortage. [ABSTRACT FROM AUTHOR]

Objective: Given the tremendous growth in assisted living (AL) over the past 20 years, it is important to understand how expansion has affected the demand for long-term care (LTC) provided in nursing homes (NHs). We estimated the effect of a change in county-level AL beds on the prevalence of private-pay residents and private-pay resident days at the NH-level.Data Sources: National census of large AL providers (25+ beds), and Minimum Data Set combined with Medicare enrollment records and claims from 2007 and 2014.Study Design: Retrospective longitudinal analysis of LTC markets.Principal Findings: Mean AL beds per county increased from 285 to 324, while NHs exhibited a decrease in private-pay residents (20.1 to 17.7 percent) and resident days (21.3 to 17.5 percent). An increase of 1,000 AL beds at the county level is associated with a reduction of 0.44 percentage points in private-pay resident days but is not significantly associated with percent of private-pay residents.Conclusions: These results suggest that increases in AL capacity have potentially allowed NH residents to delay or decrease their privately financed lengths of stay. As demand for AL continues to grow, it will be important to assess the effects on other LTC sectors. [ABSTRACT FROM AUTHOR]

Objective: To characterize the nature and degree of hospitals' efforts to collaborate with skilled nursing facilities (SNFs) and associated patient outcomes.Data Sources/study Setting: Qualitative data were collected through 138 interviews with staff in 16 hospitals and 25 SNFs in eight markets across the United States in 2015. Quantitative data include Medicare claims data for the 290,603 patients discharged from those 16 hospitals between 2008 and 2015.Study Design/data Collection: Semi-structured interviews with hospital and SNF staff were coded and used to classify hospitals' collaboration efforts with SNFs into high versus low collaboration hospitals, and risk-adjusted, claims-based hospital readmission rates from SNF were compared.Principal Findings: Hospital collaboration efforts were defined as establishing SNF partners, transition management initiatives, and hospital staff visits to SNFs. High collaboration hospitals were more likely to send patients to SNFs (as opposed to home, home with home health, or other PAC settings), sent a higher share of patients to high quality SNFs, and had fewer hospital readmissions from SNF sooner than did low collaboration hospitals.Conclusions: Although collaboration with SNF requires significant administrative and clinical time investment, it is associated with positive patient outcomes. [ABSTRACT FROM AUTHOR]

Objective: To determine whether Medicare's Nonpayment Program was associated with decline in venous thromboembolism (VTE) following hip and knee replacements; and whether the decline was greater among hospitals at risk of larger financial losses from the Program.Data Sources: State Inpatient Database for New York (NY) from 2005 to 2013.Study Design: The primary outcome was an occurrence of VTE. Medicare Utilization Ratio (MUR), which is the proportion of inpatient days in a hospital that is financed by Medicare, represented a hospital's financial sensitivity. We used hierarchical logistic regressions with difference-in-differences estimation to study the Program effects.Principal Findings: A total of 98,729 hip replacement and 111,361 knee replacement stays were identified. For hip replacement, the Program was associated with significant reduction (Range: 44% to 53%) in VTE incidence among hospitals in MUR quartiles 2 to 4. For knee replacement, the Program was associated with significant reduction (47%) in VTE incidence only among quartile 2 hospitals.Conclusion: Implementation of the Program was associated with a reduction in VTE, especially for hip replacements, in higher MUR hospitals. Payment reforms such as Medicare's Nonpayment Program that withhold payments for complications are effective and should be continued. [ABSTRACT FROM AUTHOR]