Health Services Research最新文献

Objective: To qualitatively explore the reasons health professionals decide to practice in rural areas.

Study setting and design: Exploratory, cross-sectional, semi-structured qualitative interview and focus group study using thematic analysis with a convenience sample of health professionals in rural Minnesota. Interviews and focus groups were conducted virtually and in person, respectively, between August 2023 and March 2024.

Data sources and analytic sample: Primary interview and focus group data were collected from 19 individual interviews and 3 focus groups (n = 16) with health professionals in rural Minnesota. Interview and focus group recordings were transcribed, deductively coded, and analyzed using constant comparison.

Principal findings: Rural health professionals cited autonomy and breadth of practice and patient connection as rewarding and challenging components of practice that were distinctly rural. Barriers to recruitment and retention of rural health professionals included lack of housing (especially rental and short-term) and accessible childcare. Potentially promising considerations when recruiting and retaining health professionals include loan forgiveness programs, the appeal of increasing racial and ethnic diversity in rural areas, and the ease of community health advocacy efforts.

Conclusion: Our findings suggest that to recruit and retain rural health professionals, stakeholders could highlight autonomy and patient connection, reduce childcare and housing barriers, and explore community strengths such as racial/ethnic diversity and opportunities for advocacy.

Objective: To examine differences between patients treated in integrated systems of care and patients treated outside of such systems during the COVID pandemic in the use of primary and preventive care, emergency services, inpatient services, and mortality.

Data sources and study setting: Data are used from all enrollees in traditional Medicare aged 66 and older.

Study design: Difference-in-differences estimates are calculated from the pre-COVID time period (January 2019-February 2020) to the initial COVID time period (March-May 2020) and the ongoing COVID time period (June 2020-December 2021) for patients treated by primary care physicians working in a health system versus not, and by the type of health system.

Data collection/extraction methods: Medicare claims data are used to measure monthly claims for office and telehealth visits, mammography, colon cancer screening, inpatient/emergency department visits, and death. Patients are assigned to primary care physicians using common algorithms. Physician membership in a health system is determined from a previously generated dataset.

Principal findings: Relative to the pre-COVID period, patients treated in health systems fared no better in maintaining primary care access than patients treated outside of such systems (DID estimate on receipt of office care or telehealth visit = -4%; p < 0.001). In the ongoing COVID time period, non-COVID mortality rose by less in health systems (DID estimate = -0.9%; p < 0.001) and health system patients experienced a greater decline in the use of the emergency department (DID estimate = -1.2%; p < 0.001) and emergency/urgent inpatient care for non-COVID conditions less (DID estimate = -0.7%; p < 0.001).

Conclusion: Health systems were associated with reduced occurrence of death and adverse medical events, although the effect magnitudes are modest. This reduction appears unrelated to the use of primary care and should be considered in the context of our evolving understanding of the advantages and disadvantages of health systems.

Objective: To evaluate whether COVID-19-related nurse aide training and licensing relaxation policies improved staffing shortages in nursing homes.

Study setting and design: Staffing shortages have been a long-standing concern in nursing homes, and states are experimenting with different approaches to enhance nurse aide staffing. We use the latest quasi-experimental difference-in-differences methods to evaluate the effect of relaxing training and licensing requirements in 19 states (treatment group) relative to the 31 states that did not implement such policies (control group). We analyze the combined effect of relaxing both training and licensing requirements, as well as the impact of relaxing each policy separately.

Data sources and analytic sample: We obtain quarterly data on nursing home characteristics, including adjusted nurse aide hours per resident day (HPRD) from 2019 to 2023 from Care Compare, a federal website with quality information on all Medicare/Medicaid-certified nursing homes. After excluding outliers of staffing data (nurse aide HPRD > 5.25, or nurse aide HPRD = 0), our final analytical sample had 278,170 observations.

Principal findings: The average nurse aide HPRD is 2.30 in the treatment group and 2.26 in the control group. Using the difference-in-differences regression analyses, we find no significant effect of the relaxation of training and licensing requirements on nurse aide levels (average treatment effect: -0.0001; p = 0.99). Similarly, separate analyses of training and licensing relaxation policies suggest that neither policy significantly impacts nurse aide staffing. Results are consistent when we adjust for staffing requirements, wage increase policies, and nursing home characteristics.

Conclusions: Our findings suggest that the relaxation of training and licensing requirements may not lead to improved nurse aide staffing levels in nursing homes. Policymakers need to consider other strategies to address persistent staffing shortages in nursing homes.

Objective: To examine the trend in Immune Checkpoint Inhibitor (ICI) use before and after FDA approval in 2015 for patients with metastatic non-small cell lung cancer (NSCLC), and whether vertical integration of oncologists affected ICI use.

Study setting and design: We conducted a retrospective cohort study of patients with metastatic NSCLC from 21 population-based cancer registries in the United States. We measured whether patients' treating oncologists were vertically integrated based on ≥ 10% of total services billed through hospital outpatient departments. We described the percentage of ICI recipients annually in 2010-2019, stratified by oncologists' integration status each year. In the post-FDA approval period (2015-2019), we used difference-in-differences (DID) modeling to compare the probability of patients' receiving ICI before and after oncologists became integrated relative to those whose oncologists remained non-integrated.

Data sources and analytic sample: Using the SEER-Medicare linkage, we identified Medicare Fee-For-Service beneficiaries aged ≥ 65.5 years diagnosed with metastatic NSCLC in 2010-2019 and followed them from diagnosis until ICI receipt, death, or end of 2019.

Principal findings: The overall percentage of patients receiving ICI increased from 0% before 2015 to 4.0% in 2015, and further increased to 29.2% in 2019. The percent of ICI recipients was higher among integrated (6.9%) than non-integrated oncologists (2.0%, p < 0.001) in 2015, but by 2017 adoption rates converged (19.8% vs. 19.8%, p = 0.91). DID analysis showed non-significant changes in the probability of ICI use after oncologists became integrated (1.7 percentage points, 95% CI = -1.0 to 4.4) relative to oncologists who remained non-integrated.

Conclusions: Integrated oncologists were quicker to adopt ICIs in the first year after FDA approval, but this lead was not sustained over time. Vertically integrating into health systems was not associated with significant changes in ICI use. Further research is needed on the factors influencing equitable dissemination of novel cancer therapies across practice settings.

Objective: To examine the relationship between the COVID-19 pandemic and the preexisting gender mental health gap in symptoms as well as service utilization.

Study setting and design: Using repeated cross-sectional data, the study compares the gender mental health gap between American female and male college students before and after the start of the COVID-19 pandemic. Adjustments are made for preexisting trends. The study constructs an overall index of poor mental health, based on self-reported symptoms and service utilization related to anxiety, depression, and eating disorders. The gender mental health gap is also broken into the gender symptoms gap and the gender service utilization gap; each is analyzed separately by race, ethnicity, and sexuality.

Data sources and analytic sample: The study draws on secondary data from the National College Health Assessment Surveys from fall 2015 to fall 2022 and focuses on young American college students, ages 18-25 years old.

Principal findings: The gender mental health gap, measured using the overall index of poor mental health, increased by 15.6% [95% CI: 5.67-25.6]. The gender symptom gap in eating disorders increased by 38.8% [95% CI: 24.4-53.1] and is consistently observed across race, ethnicity, and sexuality, except among non-Hispanic Asian students. Minimal to no long-term significant differences are observed for the gender symptom gap in anxiety and depression. The gender service utilization gap, on the other hand, increased for all illnesses, with slight increases for anxiety and depression.

Conclusions: The COVID-19 pandemic was accompanied by an exacerbation of the already existing rise in eating disorders among female college students. In symptoms of anxiety and depression, the gap between women and men stayed constant during the pandemic. Action is required to understand and address the factors that led to a rise in the symptoms of eating disorders among women.

Objective: To explore the experiences of patients who found and/or connected to social care via a community resource referral system named "Resourceful" (linked with FindHelp.org) linked to a health system's electronic health record.

Study setting and design: The mixed-methods study was co-designed and conducted using community-based participatory processes by a team of researchers at a multi-state health system (Minnesota, North Dakota, Wisconsin) and community members with lived experience addressing unmet social needs. Study participants were individuals referred to, connected to, or delivered social care through Resourceful in the health system's service area. Quantitative surveys were emailed to 780 patients and 38 healthcare workers (HCWs) tied to closed-loop referrals between 8/2022 and 2/2023. Qualitative interview invites were emailed to 19 patient survey respondents wanting to interview, and the five HCWs and 12 community-based organizations (CBOs) involved in their social care experience. Descriptive statistics analyzed sociodemographic and patient experience variables developed via the participatory process. We coded qualitative data using thematic analysis, extracting thematic factors informing survey responses.

Data sources and analytic sample: We collected primary data from online surveys and semi-structured phone interviews.

Principal findings: Usable survey responses from 62 patients and 14 HCWs were analyzed. Most respondents agreed on some level that their experience using Resourceful strengthened patient trust (patients:66%, HCWs:86%), improved communication about what patients need to be healthy (patients:61%, HCWs:57%), provided "helpful help" reducing social care barriers (patients:56%, HCWs:93%), and enhanced person-centeredness (patients:60%, HCWs:79%). Qualitative analysis yielded six thematic factors corresponding to 23 actionable takeaways potentially important for using CRRS to improve the seeker experience of social care: resource/service environment; platform access/usability/utilization; helper integration/coordination/continuity; helpful help; reliable sources/partnerships; responsive relationships.

Conclusions: Differences in the perceptions of patient experiences involving resourceful were observed between patients and HCWs/CBOs. Thematic factors clarified these differences and how to improve patient experiences with closed-loop referrals.

Objective: To determine whether Medicaid coverage of healthcare services provided within schools affects the supply of school-based health clinics.

Data sources and study setting: We combine nationwide data spanning 2012-2020 on Federally Qualified Health Centers delivering health services within school settings with state policy information on Medicaid expansion to school-based healthcare.

Study design: Until 2014, the federal "Free Care Rule" restricted school-based health centers from using Medicaid funding to provide health services unless these services were part of the student's Individual Education Plan. In 2014, the Centers for Medicare & Medicaid Services reversed the free care rule, allowing states to opt in to authorizing Medicaid reimbursement for comprehensive health services delivered in schools to Medicaid-enrolled students. We compared the number of federally qualified school-based health centers in states that expanded their Medicaid policies in response to the free care rule reversal to that of states that did not expand their Medicaid programs to reimburse for school-based health services in a staggered difference-in-differences analysis. We also adjusted the analysis for other important measures that may independently affect school-based healthcare provision and funding decisions.

Data collection: The number of health centers delivering services in schools comes from the Health Resources & Services Administration. State Medicaid coverage policy information comes from the Healthy Schools Campaign.

Principal findings: Expanding Medicaid coverage to comprehensive school-based healthcare increased the number of Federally Qualified Health Centers providing services in school settings by about 13.42 (p = 0.035, 95% CI: 0.94, 25.90). This increase represents a relative rise of 39%. However, these results are sensitive to specifications.

Conclusions: Local educational entities, school health providers, and public health professionals are responsive to financial incentives to provide services to Medicaid-enrolled children within schools. Recent federal legislation has the potential to increase financial incentives and offer complementarities to prior state-level policy changes.

Objective: To examine the impact of two interventions aimed at increasing the adoption of social risk screening in community health centers (CHCs).

Study setting and design: Intervention CHCs were in one of three groups, which received either: (1) tailored practice facilitation-focused social risk screening implementation supports; (2) financial incentives for screening; and (3) both practice facilitation and financial incentives in staggered order. A group of control clinics was identified through propensity score matching and a difference-in-difference analysis compared effects across groups.

Data sources and analytic sample: Using electronic health record data, we calculated monthly rates of social risk screening (per 100 adult patients) at 32 intervention clinics (19 practice facilitation supports only, 6 financial incentives only, 7 both financial incentives and practice facilitation supports), and 32 control clinics.

Principal findings: Compared to control clinics, clinics in any intervention group had a greater increase in average monthly social risk screenings from pre- to post-intervention that was maintained over the 24 months following intervention (difference-in-difference: 4.66, 95% CI: 0.89, 8.43). In the primary analysis, clinics engaged in both interventions increased screening rates when practice facilitation implementation supports were added to financial incentives (12 months 3.70, 95% CI: 0.34, 7.07; 24 months 4.18, 95% CI: -0.01, 8.87); adding financial incentives to practice facilitation supports resulted in increased screening rates but did not reach statistical significance.

Conclusions: This study is the first to compare different interventions intended to bolster CHCs' social risk screening activities. As social risk screening becomes increasingly tied to US policy and payment structures, it is critical to identify strategies that can support implementation in settings serving underserved populations. Our findings suggest modest impacts of both financial incentives and practice facilitation supports.

Objective: To assess the utility of using discrete primary care electronic health record (EHR) data to identify social risk referrals in a national network of community-based clinics.

Data sources and study setting: Primary data were abstracted from the OCHIN network EHR (June 2016 to February 2022) of 1459 community-based clinics across the United States.

Study design: Structured data elements included 913 commonly used smartphrases and 53 procedure codes that were considered potential indicators of social risk referrals. Using stratified purposive sampling, we compared these discrete data with clinical notes to assess concordance of social risk referral documentation, and of the prevalence, types, and outcomes of such referrals.

Data collection/extraction methods: Smartphrases were classified into three categories (likely, possible, or unlikely to indicate a social risk referral); 50 chart notes were sampled for each of the 25 most frequently used smartphrases in each category, and for 53 of the most frequently used procedure codes. A total of 6104 chart notes were reviewed.

Principal findings: In 59% of chart notes where discrete data suggested a social risk referral occurred, there was no documentation of this in the note. Primary domains addressed were food insecurity (38%), financial stress (18%) and housing needs (18%). Common referral activities included providing contact information (26%), help with assistance applications (17%), and direct provision of resources (16%). Documentation indicated the patient received resources in 29% of notes.

Conclusions: EHR documentation of social risk referrals in structured data fields is inconsistent. Further work should establish best practices, especially given emerging policies that tie payments to documentation of social risk screening and intervention provision. Community health centers may struggle to use data elements such as smartphrases and procedure codes to monitor and report on their social risk referrals until standardized coding practices are established and effectively implemented.