Health Services Research最新文献

Objective: To determine the feasibility of integrating Medicare Advantage (MA) admissions into the Centers for Medicare & Medicaid Services (CMS) hospital outcome measures through combining Medicare Advantage Organization (MAO) encounter- and hospital-submitted inpatient claims.

Data sources and study setting: Beneficiary enrollment data and inpatient claims from the Integrated Data Repository for 2018 Medicare discharges.

Study design: We examined timeliness of MA claims, compared diagnosis and procedure codes for admissions with claims submitted both by the hospital and the MAO (overlapping claims), and compared demographic characteristics and principal diagnosis codes for admissions with overlapping claims versus admissions with a single claim.

Data collection/extraction methods: We combined hospital- and MAO-submitted claims to capture MA admissions from all hospitals and identified overlapping claims. For admissions with only an MAO-submitted claim, we used provider history data to match the National Provider Identifier on the claim to the CMS Certification Number used for reporting purposes in CMS outcome measures.

Principal findings: After removing void and duplicate claims, identifying overlapped claims between the hospital- and MAO-submitted datasets, restricting claims to acute care and critical access hospitals, and bundling same admission claims, we identified 5,078,611 MA admissions. Of these, 76.1% were submitted by both the hospital and MAO, 14.2% were submitted only by MAOs, and 9.7% were submitted only by hospitals. Nearly all (96.6%) hospital-submitted claims were submitted within 3 months after a one-year performance period, versus 85.2% of MAO-submitted claims. Among the 3,864,524 admissions with overlapping claims, 98.9% shared the same principal diagnosis code between the two datasets, and 97.5% shared the same first procedure code.

Conclusions: Inpatient MA data are feasible for use in CMS claims-based hospital outcome measures. We recommend prioritizing hospital-submitted over MAO-submitted claims for analyses. Monitoring, data audits, and ongoing policies to improve the quality of MA data are important approaches to address potential missing data and errors.

Objective: To assess differences in hospitals' collection and use of data on patients' health-related social needs (HRSN) by availability of programs or strategies in place to address patients' HRSN and social determinants of health (SDOH) of communities.

Data sources: The 2021 American Hospital Association Annual Survey and 2022 Information Technology (IT) Supplement.

Study design: This cross-sectional study described hospitals' engagement in screening and the availability of programs or strategies to address nine different HRSN. We assessed differences in screening rates and uses of data collected through screening among hospitals with and without programs or strategies in place to address HRSN or SDOH using Chi-squared tests of independence.

Data collection/extraction methods: Analyses were restricted to IT Supplement respondents with complete data for social needs questions asked in the Annual Survey (N = 1997).

Principal findings: In 2022, hospitals used social needs data collected through screening for various purposes including discharge planning and clinical decision-making at their hospital as well as to refer patients to needed resources and assess community-level needs. Hospitals with a program or strategy in place had higher rates of screening across all domains and higher rates of using of data collected through screening for uses involving exchange or coordination with external entities.

Conclusions: Collection of social needs data may help inform the development of programs or strategies to address HRSN and SDOH, which in turn can enable providers to screen for these needs and use the data in the near term for care delivery and in the long term to address community and population needs.

Objective: To determine the budget impact of implementing multidisciplinary complex pain clinics (MCPCs) for Veterans Health Administration (VA) patients living with complex chronic pain and substance use disorder comorbidities who are on risky opioid regimens.

Data sources and study setting: We measured implementation costs for three MCPCs over 2 years using micro-costing methods. Intervention and downstream costs were obtained from the VA Managerial Cost Accounting System from 2 years prior to 2 years after opening of MCPCs.

Study design: Staff at the three VA sites implementing MCPCs were supported by Implementation Facilitation. The intervention cohort was patients at MCPC sites who received treatment based on their history of chronic pain and risky opioid use. Intervention costs and downstream costs were estimated with a quasi-experimental study design using a propensity score-weighted difference-in-difference approach. The healthcare utilization costs of treated patients were compared with a control group having clinically similar characteristics and undergoing the standard route of care at neighboring VA medical centers. Cancer and hospice patients were excluded.

Data collection/extraction methods: Activity-based costing data acquired from MCPC sites were used to estimate implementation costs. Intervention and downstream costs were extracted from VA administrative data.

Principal findings: Average Implementation Facilitation costs ranged from $380 to $640 per month for each site. Upon opening of three MCPCs, average intervention costs per patient were significantly higher than the control group at two intervention sites. Downstream costs were significantly higher at only one of three intervention sites. Site-level differences were due to variation in inpatient costs, with some confounding likely due to the COVID-19 pandemic. This evidence suggests that necessary start-up investments are required to initiate MCPCs, with allocations of funds needed for implementation, intervention, and downstream costs.

Conclusions: Incorporating implementation, intervention, and downstream costs in this evaluation provides a thorough budget impact analysis, which decision-makers may use when considering whether to expand effective programming.

Objective: To describe a learning health care system research process designed to increase buprenorphine prescribing for the treatment of opioid use disorder (OUD) in rural primary care settings within U.S. Department of Veterans Affairs (VA) treatment facilities.

Data sources and study setting: Using national administrative data from the VA Corporate Data Warehouse, we identified six rural VA health care systems that had improved their rate of buprenorphine prescribing within primary care from 2015 to 2020 (positive deviants). We conducted qualitative interviews with leaders, clinicians, and staff involved in buprenorphine prescribing within primary care from these sites to inform the design of an implementation strategy.

Study design: Qualitative interviews to inform implementation strategy development.

Data collection/extraction methods: Interviews were audio-recorded, transcribed verbatim, and coded by a primary coder and secondary reviewer. Analysis utilized a mixed inductive/deductive approach. To develop an implementation strategy, we matched clinical needs identified within interviews with resources and strategies participants had utilized to address these needs in their own sites.

Principal findings: Interview participants (n = 30) identified key clinical needs and strategies for implementing buprenorphine in rural, primary care settings. Common suggestions included the need for clinical mentorship or a consult service, buprenorphine training, and educational resources. Building upon interview findings and in partnership with a clinical team, we developed an implementation strategy composed of an engaging case-based training, an audit and feedback process, and educational resources (e.g., Buprenorphine Frequently Asked Questions, Rural Care Model Infographic).

Conclusions: We describe a learning health care system research process that leveraged national administrative data, health care provider interviews, and clinical partnership to develop an implementation strategy to encourage buprenorphine prescribing in rural primary care settings.

Objective: To examine skilled nursing facility (SNF) staffing shortages across job roles during the COVID-19 pandemic. We aimed to capture the perspectives of leaders on the breadth of staffing shortages and their implications on staff that stayed throughout the pandemic in order to provide recommendations for policies and practices used to strengthen the SNF workforce moving forward.

Study setting and design: For this qualitative study, we engaged a purposive national sample of SNF leaders (n = 94) in one-on-one interviews between January 2021 and December 2022.

Data source and analytic sample: Using purposive sampling (i.e., Centers for Medicare & Medicaid quality rating, region, ownership) to capture variation in SNF organizations, we conducted in-depth, semi-structured qualitative interviews, guided a priori by the Institute of Medicine's Model of Healthcare System Framework. Interviews were conducted via phone, audio-recorded, and transcribed. Rigorous rapid qualitative analysis was used to identify emergent themes, patterns, and relationships.

Principal findings: SNF leaders consistently described staffing shortages spanning all job roles, including direct care (e.g., activities, nursing, social services), support services (e.g., laundry, food, environmental services), administrative staff, and leadership. Ascribed sources of shortages were multidimensional (e.g., competing salaries, family caregiving needs, burnout). The impact of shortages was felt by all staff that stayed. In addition to existing job duties, those remaining staff experienced re-distribution of essential day-to-day operational tasks (e.g., laundry) and allocation of new COVID-19 pandemic-related activities (e.g., screening). Cross-training was used to cover a wide range of job duties, including patient care.

Conclusions: Policies are needed to support SNF staff across roles beyond direct care staff. These policies must address the system-wide drivers perpetuating staffing shortages (i.e., pay differentials, burnout) and leverage strategies (i.e., cross-training, job role flexibility) that emerged from the pandemic to ensure a sustainable SNF workforce that can meet patient needs.

Objective: To systematically review Medicaid policies state-by-state for gender-affirming surgery coverage.

Data sources and study setting: Primary data were collected for each US state utilizing the LexisNexis legal database, state legislature publications, and Medicaid manuals.

Study design: A cross-sectional study evaluating Medicaid coverage for numerous gender-affirming surgeries.

Data collection/extraction methods: 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.

Principal findings: 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.

Conclusions: 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.

Objective: To evaluate the impact on rural Veterans' access to social work services of a Department of Veterans Affairs (VA) national program to increase social work staffing, by Veterans' rurality, race, and complex care needs.

Data sources and study setting: Data obtained from VA Corporate Data Warehouse, including sites that participated in the social work program between October 1, 2016 and September 30, 2021.

Study design: The study outcome was monthly number of Veterans per 1000 individuals with 1+ social work encounters. We used difference-in-differences to estimate the program effect on urban, rural, and highly rural Veterans. Among rural and highly rural Veterans, we stratified by race (American Indian or Alaskan Native, Asian, Black, Native Hawaiian or Other Pacific Islander, and White) and complex care needs (homelessness, high hospitalization risk, and dementia).

Data collection: We defined a cohort of 740,669 Veterans (32,434,001 monthly observations) who received primary care at a participating site.

Principal findings: Average monthly social work use was 8.7 Veterans per 1000 individuals. The program increased access by 49% (4.3 per 1000; 95% confidence interval, 2.2-6.3). Rural Veterans' social work access increased by 57% (5.0; 3.6-6.3). Among rural/highly rural Veterans, the program increased social work access for those with high hospitalization risk by 63% (24.5; 18.2-30.9), and for Veterans experiencing homelessness, 35% (13.4; 5.2-21.7). By race, the program increased access for Black Veterans by 53% (6.1; 2.1-10.2) and for Asian Veterans by 82% (5.1; 2.2-7.9).

Conclusions: At rural VA primary care sites with social work staffing below recommended levels, Black and Asian Veterans and those experiencing homelessness and high hospitalization risk may have unmet needs warranting social work services.