To describe a claims-based methodology for constructing new home health stays using traditional Medicare (TM) claims data and Medicare advantage (MA) encounter data.
To demonstrate our methodology's performance, we assessed the percentages of TM and MA beneficiaries with one and two or more stays, and the mean length of a stay (LOS) among home health recipients. We compared 2019 and 2021 results to evaluate the methodology's feasibility pre- and post-implementation of the Patient-Driven Groupings Model (PDGM).
We used 2019 and 2021 TM and MA home health claims and 2019 outcome and assessment information set for a nationally representative 20% sample of Medicare beneficiaries.
In 2019, a lower percentage of MA beneficiaries had new home health stays than TM (5.9% vs. 6.5%). Among home health recipients, approximately 90% had a single stay. The mean LOS in MA was 39 days, compared with 44 days in TM. The statistics from the 2021 data were similar, except that the mean LOS in TM increased to 46 days.
Our claims-based new home health stay methodology is feasible both pre- and post-PDGM and would enable direct comparisons of home health utilization in TM and MA.
Objective: To examine the relationship between mental health provider productivity, staffing levels, and suicide-related events (SREs) among U.S. Veterans receiving care within the Veterans Health Administration (VHA), focusing on therapy and medication management providers.
Data sources/setting: We analyzed administrative data from the Department of Defense and VHA (2014-2018), encompassing 109,376 Veterans who separated from active duty between 2010 and 2017.
Design: A longitudinal design estimated the effects of facility-level provider work rate and staffing on SREs, adjusting for patient and facility characteristics. An instrumental variables (IV) approach addressed potential endogeneity.
Data collection/extraction methods: Data were obtained from the VHA Corporate Data Warehouse and the VHA Survey of Enrollees.
Principal findings: A 1% increase in therapy provider work rate led to a 12.1% increase in SRE probability, regardless of staffing levels. Conversely, a 1% increase in staffing levels led to a 1.6% reduction in SREs, with the largest effect in low-staffed facilities. For medication management providers, work rate had no overall impact on SREs, except in medium-staffed facilities. A 1% increase in staffing levels for medication management providers led to a 1.7% reduction in SREs.
Conclusions: Increased work rates, particularly in low-staffed VHA facilities, may elevate suicide-related risks. In contrast, staffing increases simultaneously improve access and reduce adverse outcomes. Where possible, policymakers should prioritize staffing growth over productivity gains to improve access to mental health clinics and ensure Veteran safety and care quality.
To examine whether hospital eligibility for the 340b drug pricing program reduces prices for clinician-administered drugs in commercial insurance markets and whether effects vary by market competition.
We conducted a quasi-experimental study using a regression discontinuity design that leverages the federal eligibility threshold for 340B participation (disproportionate share hospital [DSH] percentage > 11.75%). The study included non-profit and public acute care hospitals that billed for clinician-administered drugs in the outpatient setting between 2012 and 2014. The primary outcome was hospital-insurer negotiated unit prices for high-spending outpatient drugs. Secondary outcomes included drug volume and revenue.
We analyzed secondary data from the Health Care Cost Institute (HCCI), which includes claims from three national commercial insurers linked to hospital-level characteristics from the Hospital Cost Report Information System (HCRIS) and provider identifiers from the National Plan and Provider Enumeration System (NPPES). The analytic sample comprised 637 hospitals billing 148,037 clinician-administered drug claims for the five drugs with highest total spending.
Hospital 340B eligibility was associated with a $605 reduction (95% CI: −934 to −276) in median unit drug prices, a 25% decrease relative to the mean price among ineligible hospitals at the threshold ($2387). Effects were concentrated in competitive markets (Herfindahl–Hirschman Index [HHI] ≤ 1800), where eligibility was associated with a $793 reduction (95% CI: −1197 to −388), a 32% decrease. In highly concentrated markets, effects were small and statistically insignificant. Price reductions were offset by non-significant increases in drug volume (25%) and neutral effects on drug revenue.
Hospital 340B eligibility reduced commercial drug prices only in competitive markets. These findings suggest that market competition is critical for ensuring that policy-driven hospital cost savings are shared with payers and patients.
Objective: To provide a conceptual framework for understanding ghost networks and propose a new methodology for estimating ghost physician prevalence in health plans' provider directories.
Study setting and design: We focused on providers listed as primary care physicians in Medicare Advantage (MA) plans' provider directories. Our framework categorizes ghost PCPs into general ghosts-those listed as PCPs but unavailable to any Medicare beneficiaries for primary care-and network-specific ghosts-those available to Medicare beneficiaries but inaccessible to enrollees with a certain MA network. We identified general ghosts with multiple data sources. In estimating network-specific ghost prevalence, to separate those who were truly unavailable from those who were accessible but saw no patients simply due to chance, we estimated a logistic model predicting being low-volume among the zero-volume and low-volume PCP-networks.
Data sources and analytic sample: We used the 2019 Ideon MA provider directory data. For physician information, we used the National Plan and Provider Enumeration System National Provider Identifier registry and OneKey Healthcare Industry Database. To estimate the patient volume of listed PCPs, we extracted from the 2019 MA encounter data carrier file beneficiaries' primary care visits to physicians in the office, hospital outpatient, or clinic setting.
Principal findings: We found that 17.5% of the listed PCPs in an average MA network were general ghosts and 11.5% were network-specific ghosts. Health maintenance organization networks listed more ghost PCPs than preferred provider organization (30.5% vs. 26.9%). Networks associated with high star rating contracts had substantially fewer ghost PCPs than those associated with low star rating contracts (26.5% vs. 37.2%). Our methodology for screening for ghost prevalence reduces the penalty on networks offering more choice, such as those serving urban markets.
Conclusions: Policymakers should ensure that provider directories reflect the physicians available to provide care. Our methodology may facilitate targeted network audits.
Objective: To identify the Medicaid eligibility category at delivery and 6 months prior among those with Medicaid and Children's Health Insurance Program (CHIP)-financed births.
Study setting and design: Descriptive analysis of 2018 national Medicaid claims data.
Data sources and analytic sample: We used the 2018 Transformed Medicaid Statistical Information System Analytic Files to assess Medicaid/CHIP eligibility category at the time of birth and 6 months prior during pregnancy among enrollees with Medicaid/CHIP-paid births in 2018, stratifying by age, race/ethnicity, and state.
Principal findings: Just over half (56.2%) of those enrolled in Medicaid/CHIP in 2018 were enrolled in the pregnancy eligibility category at delivery, while 29.5% were enrolled as parents, 8.2% as low-income adults, and 6.1% in other categories. The proportion of pregnant women enrolled via the pregnancy eligibility category varied widely by state, from 11.9% in Kentucky to 97.5% in Texas.
Conclusions: Nearly half of pregnant Medicaid/CHIP enrollees were not enrolled via pregnancy Medicaid eligibility when they delivered. It is important for states to be aware of pregnancy status to apply correct eligibility criteria and benefits for pregnant and postpartum enrollees, including the 12 months of extended postpartum coverage newly available and elected in nearly all states.
Objective: To examine changes in colorectal cancer (CRC) screening rates over time and determine organizational-level factors influencing these shifts.
Study settign and design: This longitudinal study used mixed effects models to analyze data from Federally Qualified Health Centers (FQHCs) in the United States (US). Key organizational-level factors included Patient-Centered Medical Home (PCMH) recognition and duration, hypertension and diabetes management, and center-level characteristics such as racial composition, location, and center volume/size.
Data sources and analytic sample: This study used Uniform Data System (UDS) data from 2017 to 2022 for US-based FQHCs receiving full Public Health Service Section 330 grants and reporting CRC screening measures, excluding school-based centers, US territories, and look-alike centers.
Principal findings: Among the 1282 FQHCs analyzed, CRC screening rates were increasing before the COVID-19 pandemic but declined during and remain below pre-pandemic levels. FQHCs with consistent PCMH recognition reported significantly higher screening rates (β = 8.50, p < 0.001). Screening rates were also positively associated with a higher rate of controlled hypertension (β = 0.354, p < 0.0001) but lower in FQHCs with larger Black patient populations, Southern locations, and smaller center volume/size.
Conclusions: Consistent PCMH recognition and chronic disease management are essential for improving CRC screening rates in FQHCs. By integrating these population health management strategies, FQHCs can proactively address screening disparities. Prioritizing these organizational-level approaches may strengthen healthcare equity and expand CRC screening for historically marginalized communities.
Objective: Quantify racial and ethnic disparities in harm reduction and substance use disorder (SUD) treatment use among people who use drugs and compare estimates using a healthcare disparities measurement method aligned with the Institute of Medicine (IOM) definition of healthcare disparities against other regression approaches.
Study setting and design: 45-minute telephone survey of people who use drugs administered from January 2023 to August 2024 across four US locations (i.e., Milwaukee County, Wisconsin; Flint/Detroit, Michigan; statewide in New Jersey; and Bernalillo County, New Mexico). Service use disparities were estimated using propensity score models with rank-replace methods and compared against standard covariate-adjusted logistic regression models.
Data sources and analytic sample: Survey response data from 1651 respondents who identified as White non-Hispanic (N = 572), Black non-Hispanic (N = 479), Hispanic (N = 453), or American Indian/Alaska Native (N = 147) and had used drugs in the past 30 days. Exposures included respondent demographics, health status, social determinants of health (SDOH), and race/ethnicity. Outcomes included use of any harm reduction services, fentanyl test strip use, naloxone possession, any SUD treatment use, and receipt of buprenorphine, methadone, or naloxone in the past 30 days.
Principal findings: Compared to White non-Hispanic (NH) respondents, Black NH respondents were 17.8 (95% CI: -0.24, -0.12) percentage points less likely to use harm reduction services and 8.8 (95% CI: -0.15, -0.03) points less likely to use SUD treatment. Hispanic respondents were 12.8 percentage points less likely to use any SUD treatment (95% CI: -0.20, -0.06), while American Indian/Alaska Native respondents were 11 percentage points less likely (95% CI: 0.20, -0.02). Standard adjustment models tended to mask or overestimate healthcare disparities relative to rank and replace with propensity scores.
Conclusion: Racial and ethnic disparities in harm reduction and treatment necessitate policy reform. Social determinants adjustment should be performed carefully to prevent inaccurately estimating health disparities.
Objective: To evaluate the impact of California's restricted-scope Medi-Cal program on health insurance coverage and healthcare utilization among undocumented farmworkers.
Study setting and design: We use a difference-in-differences approach to compare undocumented farmworkers in California-where restricted-scope Medi-Cal was expanded in 2014-with those in other states that expanded Medicaid under the Affordable Care Act (ACA) but did not implement a similar program for undocumented workers. The analysis exploits nearly a decade of pretreatment data to assess parallel trends.
Data source and analytic sample: Restricted-access data from the National Agricultural Workers Survey (NAWS), covering farmworkers in the United States from 2001 to 2020, the last year for which data is available. We identify undocumented farmworkers in the NAWS and extract information on health insurance coverage and healthcare utilization, including use of hospitals/emergency rooms and private clinics.
Principal findings: The results show that following the expansion of restricted scope Medi-Cal, the use of institutional healthcare providers (community health centers, hospitals, and emergency rooms) increased by 8.0 percentage points (95% CI: 0.0044, 0.1564) while the use of private clinics decreased for undocumented farmworkers. This is consistent with an 11.6 percentage points (95% CI: 0.0755, 0.1572) increase in restricted Medi-Cal coverage. We also show that the parallel trend assumption holds, lending support to a causal interpretation.
Conclusions: Our results highlight that restricted Medi-Cal expansion increased access to care.
Objective: To examine the association between state Home- and Community-Based Services (HCBS) caregiver payment policies and timely follow-up visits (in-person and telehealth) within 14 days of hospital discharge among Medicare-Medicaid dual-eligible older adults with dementia.
Study setting and design: We categorized state HCBS caregiver payment policies into three groups: no caregiver payment, payment eligible for other friends/family, and payment eligible for two caregiver types (legally responsible relatives or other friends/family). The primary outcome was the mode of follow-up visit within 14 days post-hospital discharge (in-person, telehealth, or no visit). We used multinomial logistic regression with hospital random effects, adjusting for individual- and area-level and HCBS factors. Marginal effects were estimated.
Data sources and analytic sample: We analyzed 2021 Medicare claims data linked with publicly available datasets. The analytic cohort comprised 51,633 dual-eligible Medicare beneficiaries with dementia who were hospitalized and discharged to the community in 2021.
Principal findings: State HCBS caregiver payment policies were significantly associated with the mode of timely follow-up visits. Compared to states without providing caregiver payments, states providing payments to two caregiver types had a 6.8 percentage point higher probability (p < 0.01) of timely in-person visits but a 3.2 percentage point lower probability (p < 0.01) of timely telehealth visits. Similar, though smaller, significant differences were observed between states that provided payments to only other family or friends and those with no caregiver payments. Other HCBS generosity measures, as well as racial, ethnic, and geographic locations, were also associated with the mode of post-discharge visits.
Conclusion: Providing financial support to family caregivers through state HCBS policies may increase the rate of timely post-discharge visits, primarily driven by an increase in in-person visits. The effects were particularly prominent among states that allow payments to both types of caregivers.
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