Health Services Research最新文献

Objective: To assess how patient and caregiver factors influence caregiver readiness for hospital discharge in palliative care patients.

Study setting and design: This transitional care study uses cross-sectional data from a randomized controlled trial conducted from 2018 to 2023 testing an intervention for caregivers of hospitalized adult patients with a serious or life-limiting illness who received a palliative care consult prior to transitioning out of the hospital.

Data sources and analytical sample: Caregiver readiness was measured with the Family Readiness for Hospital Discharge Scale (n = 231). Caregiver demographic, intra- and interpersonal factors were self-reported. Patient demographic, comorbidity score, and risk score for complicated discharge planning were extracted from electronic health records. Stepwise regression models estimated variance explained (r²) in caregiver readiness for patient hospital discharge.

Principal findings: Patient demographics and complexity were not statistically associated with caregiver readiness for discharge. Caregiver depressive symptoms, poor caregiver-patient relationship quality, and fewer hours spent caregiving prior to hospitalization explained 29% of the variance in caregiver readiness.

Conclusions: Reliance on patient data may not be sufficient for explaining caregiver readiness for discharge. Assessing caregiver factors may be a better alternative for identifying caregivers at risk for low discharge readiness and those in need of additional support.

Trial registration: ClinicalTrials.gov on November 13, 2017, (No. NCT03339271).

Objectives: To explore how the Medicaid continuous coverage requirement and unwinding process was implemented in three states with diverse existing policy environments and implications for the implementation of post-emergency 12-month postpartum extensions.

Data sources: State data on unwinding performance and qualitative in-depth interviews with 48 stakeholders and patient-facing healthcare workers in Texas, New York and New Jersey.

Study design: State Medicaid stakeholders and patient-facing healthcare workers in each state were interviewed with the goal of gaining insights into: (1) How the continuous coverage requirement was implemented; (2) What effects continuous coverage had on access to care for postpartum mothers; (3) How states are implementing the pandemic unwinding and postpartum extensions.

Data collection/extraction: Interviews were recorded and took place over Zoom between September 2022 and March 2024. Interview transcripts were analyzed thematically using an open coding approach.

Principal findings: The study found that low awareness of the continuous coverage requirement blunted potential benefits: little changed in practice in recommended patient care or follow-up procedures. Differences in state unwinding approaches reflected differential state capacity to minimize procedural disenrollment and political incentives to either rapidly reduce or maintain Medicaid rolls. Based on these findings, we describe how political will, state capacity and policy legacies interact to either increase or decrease administrative burdens associated with program enrollment/re-enrollment.

Conclusions: While the continuous coverage requirement in theory applies equally across US states, its implementation was inconsistent and influenced by state capacity and political objectives creating differential experiences across states. To ensure that postpartum Medicaid coverage extensions have maximal impact on improving maternal health, states should develop improved communication strategies to ensure that providers and community-based organizations are aware of coverage changes and leverage available flexibilities to increase use of administrative renewal and ensure smooth coverage transitions.

Objective: To understand how Medicare Advantage (MA) networks impact utilization patterns and plan choices, using the 2019 discontinuation of MA 1876 Cost plans as a natural experiment.

Study setting and design: We study 1876 Cost plans, MA plans for which out-of-network care is covered through traditional Medicare (TM) and many of which CMS discontinued in 2019. We characterize the proportion of Cost plan enrollees who utilized out-of-network care in 2018 from different types of medical specialties. We then study how enrollees in discontinued plans selected into new plans in 2019. We use regression analysis to characterize whether higher risk enrollees selected into TM at higher rates.

Data sources and analytic sample: We identify discontinued plans using public MA plan data. We employ administrative Medicare enrollment and TM claims data to identify 2018 enrollees of discontinued plans, their 2018 out-of-network utilization, and their subsequent 2019 enrollment decisions.

Principal findings: Among Cost plan enrollees, 69% utilized non-emergency room related care out of network in 2018. Out-of-network utilization was distributed across several types of specialties: 43% of Cost plan enrollees had at least one out-of-network claim with a primary care physician and over 20% had a claim with a medical specialist, surgical specialist, or nurse practitioner. We find evidence of adverse selection among enrollees of discontinued Cost plans in 2019. Conditional on one's 2018 Cost plan and county of residence, a standard deviation increase in risk score was on average associated with a 26.35% (95% CI, 25.57%-27.12%) increased likelihood of enrolling in TM.

Conclusion: The high rate of out-of-network utilization suggests that MA enrollees value access to care outside of standard MA networks. Subsequent selection patterns indicate that preferences for broader networks and subsequent enrollment in TM is highest among higher risk enrollees, suggesting limited networks may induce extensive margin selection.

Objective: To estimate associations between Wisconsin Medicaid's Prenatal Care Coordination (PNCC) program and infant mortality.

Data sources and study setting: We analyzed birth records, Medicaid claims, and infant death records for all resident and in-state Medicaid-paid live deliveries during 2010-2018.

Study design: We measured PNCC exposure during pregnancy dichotomously (none; any) and categorically (none; assessment/care plan only; service receipt). Our outcome was infant mortality (death at age < 365 days). Adjusted binary logit regressions and propensity score weighted regressions tested associations between PNCC receipt and infant mortality, and we estimated probabilities and average marginal effects of infant mortality. We also executed regressions with interactions on maternal race/ethnicity to determine if associations varied across Black non-Hispanic (NH), Hispanic, and White NH births.

Data collection/extraction methods: Our sample consisted of 231,540 Medicaid-paid births during 2010-2018. PNCC is only available to pregnant Medicaid beneficiaries.

Principal findings: Infant mortality was lower among PNCC assessment/care plan only births (5.0 deaths/1000 births) and PNCC service receipt births (6.1 deaths/1000 births) relative to non-PNCC births (6.8 deaths/1000 births). This pattern was consistent in Black NH and Hispanic subgroups, but infant mortality did not vary by PNCC among White NH deliveries. Overall, adjusted binary logit regressions indicated that the probabilities of infant mortality were 0.70% for no PNCC and 0.53% for any PNCC, yielding an average marginal effect of -0.17 percentage points (95% confidence interval -0.22 percentage points, -0.11 percentage points). This association did not vary by PNCC exposure level. PNCC-infant mortality associations were significantly stronger for Black NH births relative to White NH births. Results were consistent in propensity score weighted regressions.

Conclusions: PNCC during pregnancy is associated with a lower probability of infant mortality, particularly in Black NH families. The benefit of PNCC on infant mortality may not depend on receiving services beyond care planning.

Objective: To characterize health insurance gap patterns related to age-19 Medicaid and age-26 commercial age-eligibility cutoffs.

Study setting and design: This descriptive analysis spans 2014-2018, after Affordable Care Act implementation, but before COVID-19 emergency provisions. We defined insurance gaps as ≥3 consecutive months without observed enrollment, preceded and followed by ≥1 month of enrollment and stratified results by insurance source and clinical severity (e.g., with chronic, complex, or disabling conditions or not).

Data sources and analytic sample: The Colorado all-payer claims database provided data for enrollees aged 10-29, 52% (649,346) of whom were initially Medicaid insured, whereas 47% (576,596) were commercially insured.

Principal findings: The percent of enrollees with insurance gaps peaks within six months of turning age-19 and age-26-at 8.9% Medicaid and 8.7% commercial, respectively. The percentage point difference between ages 27-28 and 11-18 was 3.3 percentage points higher for prior Medicaid recipients (p < 0.001) and 2.2 percentage points greater for prior commercial enrollees (p < 0.001). Relative to the other clinical severity groups, young adults with disabling health conditions who were initially Medicaid insured had the lowest peak gap rate, 5.7%, compared with 10.5% among the previously commercially insured; this latter finding was sensitive to gap specification.

Conclusions: Young adults would likely benefit from greater attention to age-19 and age-26 health insurance "unwinding."

Objective: To examine the extent of segregation between hospitals for Medicare beneficiaries by race, ethnicity, and dual-eligible status over time.

Data sources and study setting: We used Medicare inpatient hospital provider data for fee-for-service (FFS) beneficiaries, and the Dartmouth Atlas of Health Care from 2013 to 2021 nationwide, for hospital referral regions (HRRs), and for and hospital service areas (HSAs).

Study design: We conducted time trend analysis with dissimilarity indices (DIs) for Black (DI-Black), Hispanic (DI-Hispanic), non-White (including Black, Hispanic, and other non-White) (DI-non-White), and dual-eligible (DI-Dual) beneficiaries. DIs between hospitals were contextualized and correlated with population compositions and residential DIs.

Data collection/extraction methods: We included 3177 hospitals with more than 250 Medicare FFS beneficiaries discharged per year. We cross-linked data on hospital-level patient race, ethnicity, and dual-eligible status with geographic data and examined time trends using linear mixed models.

Principal findings: Nationwide DIs ranged from 0.23 to 0.53. HRRs and HSAs generally had low segregation (DI medians: 0.08-0.19, highest among Black, then non-White, Hispanic, and dual-eligible beneficiaries). However, some HRRs and HSAs had moderate or high segregation (DI-Black >0.30 in 19.1% of HRRs and 5.8% of HSAs; DI-non-White >0.30 for two HRRs with high American Indian/Alaska Native populations). Time trends indicated small declines in segregation from 2013 to 2021 (0.15%-0.30% per year; all p < 0.001). DI-Dual correlated moderately with non-White populations.

Conclusions: For Medicare FFS, we observe generally low and slightly declining levels of segregation across HRRs and HSAs, with notable exceptions. Improving race reporting and contextualizing select areas of higher segregation with their hospital and residential population compositions can help frame and understand health inequities. Interpretation of HRR-level DI may require additional historical, demographic, and spatial context due to its potential to oversimplify, overstate, or obscure segregation. Future work should identify drivers and mitigators of segregation, including sorting patterns among health systems.

Objective: To examine the effects of data breach incidents on healthcare quality and to explore potential mechanisms.

Data source: Hospital-level data breach reports from the U.S. Department of Health and Human Services and patient-level hospitalization records from Florida State Inpatient Database during 2013-2017.

Study design: We employ a propensity score matching difference-in-difference model to estimate changes in a patient's emergency department (ED) door-to-hospital admission hours, days to undergo principal procedure after admission, length of stay days, and in-hospital mortality rates following data breaches. We compare the health information technology (HIT) functionalities of breached and non-breached hospitals during both pre and post periods.

Data collection/extraction methods: Our primary analysis covers 1,295,537 records of inpatients admitted through the EDs of 12 hospitals.

Principal findings: Data breaches are associated with long-term improvements in healthcare quality, particularly in the timeliness of patient care and acute myocardial infarction (AMI) mortality. Over time, patients experience a reduction of 0.56 h in ED door-to-hospital admission time (95% confidence interval [CI]: -1.04 to -0.06 h) and a decrease of 0.18 days in time to undergo the principal procedure after hospital admission (95% CI: -0.23 to -0.13 days). Additionally, AMI patients experience a one percentage point reduction in in-hospital mortality (95% CI: -2 to -0.06 percentage points), while mortality rates for other patient groups remain unchanged. Hospitals affected by data breaches show long-term advancements in their HIT functionalities.

Conclusions: Hospital data breach incidents are associated with improved healthcare quality. This improvement may be attributed to hospitals' enhanced functionality of HIT.

Objective: To examine the association of Massachusetts Medicaid Accountable Care Organization (ACO) implementation with changes in mental health care utilization in the postpartum period.

Study setting and design: We examine care for people with a birth covered by Medicaid or private insurance. We used a difference-in-differences design to compare differences before and after Medicaid ACO implementation for those with Medicaid versus those with private insurance. The primary outcome was a binary measure of having at least one outpatient mental health care visit in the 6 months postpartum. We estimated linear probability models controlling for age, prenatal mental illness, pregnancy complications, birth mode, and ZIP code characteristics.

Data sources and analytic sample: Data are from the Massachusetts All-Payer Claims Database. The analytic sample included Massachusetts residents with a live birth between July 1, 2016, and September 30, 2019, with complete data.

Principal findings: 107,813 births were included (53.0% Medicaid, 47.0% private). 7.8% of these had at least one outpatient mental health visit in the 6 months postpartum, with similar rates among those with Medicaid versus those with private insurance pre-ACO implementation (7.9% Medicaid versus 7.7% private). An increase in utilization among privately insured individuals and a decrease among Medicaid beneficiaries post-ACO implementation was observed. Regression-adjusted difference-in-differences estimates indicate that Medicaid ACO implementation was associated with a 1.3 percentage point [pp] decrease (95% confidence interval: 1.3 pp, -0.5 pp; p < 0.01) in the probability of having an outpatient mental health visit for those with Medicaid.

Conclusions: Medicaid ACO implementation was associated with decreases in use of outpatient mental health care in the postpartum period among people with Medicaid, overall and compared to those with private insurance. Future research should determine whether this increased disparity in mental health care utilization persists with maturation of the ACO delivery model.

Objective: To assess mental health related outcomes of Recipe4Health, a multisectoral social care partnership implementing produce prescriptions with or without group medical visits (GMVs).

Study setting and design: Recipe4Health was implemented at five community health centers from 2020 to 2023. Primary care teams referred patients with food insecurity and/or nutrition-sensitive chronic conditions (e.g., diabetes, depression) to 16 weeks of Food Farmacy (produce prescriptions) with the option of GMV participation. We used a convergent mixed-methods design including survey and interview data.

Data sources and analytic sample: We conducted (1) participant surveys pre- and post-intervention and (2) semi-structured interviews with Recipe4Health participants and partner organization staff. Linear mixed effects models examined changes in mental health and related outcomes. Interviews were analyzed using codebook thematic analysis.

Principal findings: Program participants were middle-aged, primarily women, and from diverse racial/ethnic backgrounds (majority Latine and Black). At baseline, moderate or severe depression and/or anxiety symptoms were reported by 77/188 (41%) of Food Farmacy-only participants, and 113/284 (40%) of Food Farmacy +GMV participants. Among Food Farmacy-only participants, post-intervention depression and anxiety symptoms significantly improved only among those who did not have baseline depression/anxiety (PHQ9: -1.7 [95% CI: -2.8, -0.6]; GAD7: -1.8 [95% CI: -2.9, -0.8]). Among Food Farmacy +GMV participants, mental health symptoms improved regardless of baseline mental health; among those with baseline depression/anxiety: PHQ9: -2.4 (95% CI: -3.6, -1.2); GAD7: -0.9 (95% CI: -2.0, 0.1); among those without: PHQ9: -2.2 (95% CI: -3.2, -1.2); GAD7: -2.2 (95% CI: -3.1, -1.2). Improvements in social needs (food insecurity, loneliness) and health-related behaviors (fruit/vegetable intake, physical activity) varied by intervention arm and baseline depression/anxiety symptom level. In interviews, staff and patients endorsed produce prescriptions for improving nutrition and food insecurity, and GMVs for increasing social support.

Conclusion: Social care interventions providing vegetables and fruit, with or without group medical visits, may concurrently address mental health symptoms and social needs.

Objective: To evaluate the completeness and quality of Medicaid comprehensive managed care (CMC) data in national MAX/TAF research files.

Study setting and design: This observational study compared CMC with fee-for-service (FFS) enrollee data in 2001-2019 Medicaid MAX/TAF inpatient, outpatient, and pharmacy files. Completeness was assessed as the proportion of enrollees with any claim and mean claims per enrollee with any claim. Quality was assessed as the proportion of inpatient and outpatient claims with primary diagnosis and procedure codes and the proportion of prescription drug claims with fill dates, National Drug Codes (NDC), days supplied, and quantity dispensed. Acceptable ranges for each study measure were defined as the national FFS mean ± 2 standard deviations.

Data sources and analytic sample: We analyzed secondary data on 45 states from 2001 to 2013 (MAX) and 50 states and DC from 2014 to 2019 (TAF). The sample included adults aged 18-64 with continuous calendar-year enrollment who were eligible for full Medicaid benefits and ineligible for Medicare. We determined CMC enrollment rates and assessed data completeness and quality among state-years with ≥10% CMC penetration, comparing CMC with FFS enrollees.

Principal findings: Across 891 state-years, 194,364,647 enrollees met inclusion criteria. Of 540 state-years (60.6%) with ≥10% CMC enrollment, CMC data were largely comparable to national FFS distributions for all inpatient (n = 430; 79.6%), outpatient (n = 467, 86.5%), and prescription (n = 459, 85.0%) completeness criteria and for all inpatient (n = 449, 83.1%), outpatient (n = 511, 94.6%), and prescription (n = 528, 97.8%) quality criteria. Overall completeness (92.3%) and quality (84.6%) improved substantially by 2019.

Conclusions: Completeness and quality of CMC data were largely comparable to FFS data, with increasing state-years meeting criteria over time. Further research on national Medicaid populations should assess and address differences in data completeness and quality by plan type across states, over time, and in relation to specific study samples and measures of interest.