Health Services Research最新文献

Objective: To evaluate whether the Preventive Health Inventory (PHI)-a virtual care management intervention addressing hypertension and diabetes management implemented nationally in the Veterans Health Administration (VHA)-was delivered equitably among racial/ethnic groups and if existing inequities in hypertension and diabetes outcomes changed following PHI receipt.

Data sources and study setting: We used data from the VHA Corporate Data Warehouse among Veterans enrolled in primary care nationally from February 28, 2021 to March 31, 2022.

Study design: We used logistic regression to evaluate PHI receipt and hypertension and diabetes outcomes after PHI implementation among Veterans with hypertension and/or diabetes. We conducted unadjusted analyses and analyses adjusting for clinic fixed effects using dummy variables.

Data collection/extraction methods: We identified Veterans engaged in primary care with documented race/ethnicity and hypertension and/or diabetes diagnoses in all months during the study period.

Principle findings: Prior to PHI, Non-Hispanic Black (NHB) (42.2%) and Hispanic (39.5%) Veterans were less likely to have controlled hypertension vs. Non-Hispanic White (NHW) Veterans (47.5%); NHB Veterans (32.9%) were more likely to have uncontrolled diabetes vs. NHW Veterans (25.1%). Among 1,805,658 Veterans, 5.7% NHW (N = 68,744), 5.6% NHB (N = 22,580), 10.2% Hispanic (N = 13,313), 6.2% Asian/Pacific Islander/Native Hawaiian (N = 1868), 5.1% American Indian/Native Alaskan (N = 744), and 5.6% multiple races or other race (N = 1647) Veterans received PHI. We found no significant racial inequities in PHI receipt in unadjusted and adjusted models. Hypertension and diabetes measures improved more in the intervention group compared with the group who did not receive the intervention. There were no new or worsened inequities after PHI, and in pre-/post-intervention analysis, among NHB Veterans, the inequity in uncontrolled diabetes improved by 1.9 percentage points (95% CI 0.2, 3.6).

Conclusions: Our findings suggest the PHI intervention was equitably deployed across race/ethnicity groups without significantly impacting most existing inequities in diabetes and hypertension.

Objective: To develop, deploy, and evaluate a national, electronic health record (EHR)-based dashboard to support safe prescribing of biologic and targeted synthetic disease-modifying agents (b/tsDMARDs) in the United States Veterans Affairs Healthcare System (VA).

Data sources and study setting: We extracted and displayed hepatitis B (HBV), hepatitis C (HCV), and tuberculosis (TB) screening data from the EHR for users of b/tsDMARDs using PowerBI (Microsoft) and deployed the dashboard to VA facilities across the United States in 2022; we observed facilities for 44 weeks post-deployment.

Study design: We examined the association between dashboard engagement by healthcare personnel and the percentage of patients with all screenings complete (HBV, HCV, and TB) at the facility level using an interrupted time series. Based on frequency of sessions, facilities were grouped into high- and low/none-engagement categories. We modeled changes in complete screening pre- and post-deployment of the dashboard.

Data collection methods: All VA facilities were eligible for inclusion; excluded facilities participated in design of the dashboard or had <20 patients receiving b/tsDMARDs. Session counts from facility personnel were captured using PowerBI audit log data. Outcomes were assessed weekly based on EHR data extracted via the dashboard itself.

Principal findings: Totally 117 facilities (serving a total of 41,224 Veterans prescribed b/tsDMARDs) were included. Before dashboard deployment, across all facilities, 61.5% of patients had all screenings complete, which improved to 66.3% over the course of the study period. The largest improvement (15 percentage points, 60.3%-75.3%) occurred among facilities with high engagement (post-intervention difference in outcome between high and low/none-engagement groups was 0.17 percentage points (pp) per week, 95% confidence interval (0.04 pp, 0.30 pp); p = 0.01).

Conclusions: We observed significant improvements in screening for latent infections among facilities with high engagement with the dashboard, compared with those with fewer sessions.

Objective: To examine wealth-related inequalities in self-reported health status among older population in the United States and 14 European countries.

Data sources and study setting: We used secondary individual-level data from Health and Retirement Survey (HRS) and the Survey of Health, Ageing, and Retirement in Europe (SHARE) in 2011 and 2019.

Study design: In this cross-sectional study, we used two waves from HRS (wave 10 and 14) and SHARE (wave 4 and 8) to compare wealth-related health inequality across countries, age groups, and birth cohorts. We estimated Wagstaff concentration indices to measure these inequalities across three age groups (50-59, 60-69, 70-79) and two birth cohorts (1942-1947, 1948-1953) in the US and 14 European countries.

Data collection/extraction methods: We performed secondary analysis of survey data.

Principal findings: Focusing on older population, we found evidence of wealth-related inequalities in self-reported health status across several high-income countries, with the US demonstrating higher levels of inequality than its European counterparts. The magnitude of these inequalities with respect to wealth remained unchanged over the study period across all countries. Our findings also suggest that wealth-related health inequalities differ at different stages of workforce engagement, especially in the United States. This could be explained either by potential redistributive effects of retirement or by uneven survivor effect, as less wealthy may drop out of the observations at a greater rate partly due to their poorer health.

Conclusions: Wealth-related inequalities in self-reported health status are strong and persistent across countries. Our results suggest that there is meaningful variation across high-income countries in health-wealth dynamics that merits further investigation to better understand whether certain health or welfare systems are more equitable. They also highlight the need to consider social policy and wealth redistribution mechanisms as strategies for improving population health among the less wealthy, in the United States and elsewhere.

Objective: The objective of this analysis was to evaluate the effect of resident program training size on clinician productivity and turnover in the Veterans Health Administration (VHA), the largest education and training platform for medical professionals in the United States.

Data sources: We retrieved administrative data on training programs and training facilities from the VA Office of Academic Affiliations and the VHA Corporate Data Warehouse. Data on primary care physician shortage areas were retrieved from the Health Resources and Services Administration.

Study design: We used a quasi-experimental instrumental variables 2SLS design and constructed an exogenous predicted training allocation treatment variable as a function of the total national training program allocation. The outcome was clinical staff productivity and turnover. Secondary analyses stratified results using Health Professional Shortage Areas data (HPSA).

Data collection/extraction methods: Data were obtained for a national dataset of 141 VHA medical facilities and 26 specialties that hosted training programs across 11 years from 2011 to 2021 (N = 132,177).

Principal findings: Instrumental variables results showed that on average, an increase of one training slot in a specialty leads to a decrease of 0.039 visits per standardized clinic day (p < 0.001) and a 0.02 percentage point increase in turnover (p < 0.001). The direction of this association varied by specialty: while psychiatry and psychology specialties saw a decline in productivity, fields such as primary care and cardiology experienced an increase in productivity. HPSA stratified results indicate that negative effects on productivity and turnover are driven by areas with little to no primary care physician shortage, whereas shortage areas experienced a small increase in productivity and no effect on turnover.

Conclusions: This quasi-experimental evaluation indicates that resident training program size is associated with reduced productivity and increased turnover in specialties such as psychiatry and in facilities with high baseline productivity. However, in specialties like primary care and cardiology, as well as areas with shortages of primary care, larger training programs are associated with increased productivity.

Objective: To determine the barriers transgender and gender nonconforming (TGNC) adults face when accessing or receiving healthcare in the United States.

Data sources and study setting: Primary data were collected between September 2022 and March 2023 from a purposive sample of TGNC adults (N = 116 participants) using an online survey with a series of open-ended and closed-ended questions.

Study design: Thematic analysis was employed to extract and analyze participants' responses to an open-ended question about challenges they experienced when accessing or receiving healthcare. Two members of the research team conducted qualitative data analyses using Dedoose. The quality of each analysis was subsequently reviewed by a third research team member.

Data collection/extraction methods: Data were collected from responses to one open-ended question that asked about participants' healthcare barriers as a TGNC individual.

Principal findings: Five main themes surrounding healthcare barriers emerged from the content analysis: (1) acceptability, (2) accommodation, (3) affordability, (4) availability, and (5) accessibility. First, participants who noted acceptability issues reported explicit discriminatory treatment from providers, providers not using their chosen names and pronouns (e.g., misgendering), and provider refusal to provide gender-affirming care. Second, participants who experienced accommodation challenges identified provider medical training gaps on TGNC patient needs and administrative barriers to care. Third, participants explained affordability issues due to a lack of adequate health insurance coverage. Fourth, participants described availability challenges with accessing hormone therapy prescriptions. Finally, participants noted accessibility issues with obtaining TGNC-specific care at LGBTQ+-affirming clinics.

Conclusions: There is a growing interest in the needs of TGNC adults within healthcare settings. This requires that health policies are enacted to ensure that TGNC adults have access to healthcare that is accommodating and accepting/affirming. Study findings may provide insight into the potential impact of current legislation on transgender access and availability.