Medical Care最新文献

Background: Understanding whether patients' preferences for physicians are influenced by racial or ethnic concordance is crucial for balancing patient care satisfaction and health care workforce diversity.

Objectives: To investigate whether patients' preferences for physicians are influenced by racial or ethnic concordance and whether these preferences are reflected in the availability of physicians by race.

Research design: A patient-focused randomized online experiment was conducted to evaluate preferences for physicians while a physician-focused randomized field experiment was conducted to evaluate physician availability by race. The patient-focused experiment involved respondents selecting primary care physicians, while the physician-focused field experiment was conducted on a random sample of primary care physicians in Texas, which reports physician race.

Results: White respondents preferred White physicians by 10 percentage points (ppts) (95% CI: 0.048-0.157, P <0.01). Hispanic respondents favored Hispanic physicians by 27 ppts (95% CI: 0.148-0.398, P <0.01) while Black respondents favored Black physicians by 15 ppts (95% CI: -0.013 to 0.395, P =0.07). Overall, White physicians were preferred by 4.8 ppts (95% CI: 0.004-0.092, P =0.030) at the expense of Asian physicians, who were less preferred by 9.2 ppts (95% CI: -0.187 to 0.003, P =0.06). These findings are consistent with the physician-focused field experiment where Asian physicians offered appointments 3 days sooner than White providers (95% CI: -6.1 to 0.1 days, P =0.05).

Conclusion: We find that concordance preferences for physicians varied by race. Some patients may be dissatisfied if these preferences are not met while some physicians may face unequal employment outcomes if they are met.

Background: Despite national attention to address disparities in health care, significant language-based health inequities exist in the United States.

Objectives: To evaluate whether readmissions for patients with limited English proficiency (LEP) are associated with the LEP volume of the hospital and to determine whether and to what extent the effect of hospital LEP volume on readmissions for LEP patients is conditional on the hospitals' nurse work environment.

Research design: Cross-sectional analysis using 3 data sources from 2016: New Jersey Discharge Data Collection System, RN4CAST-US survey, and American Hospital Association Annual Survey.

Subjects: A total of 424,745 patients, 9.2% of which were defined as having LEP (n=38,906), in 68 hospitals.

Measures: The RN4CAST survey utilized the Practice Environment Scale of the Nursing Work Index to measure nurses' ratings of their hospitals' nurse work environment. The outcome variable was 7-day readmissions, representing a potentially avoidable re-visit to the hospital. Hospital LEP volume was measured as the percentage of index admissions of LEP patients.

Results: In the fully adjusted stratified model, in hospitals with poor work environments, a 10-percentage point increase in LEP volume was significantly associated with 6% higher odds of a 7-day readmission for LEP patients [OR=1.06, 95% CI (1.04-1.08), P <0.001]. In hospitals with favorable environments, a 10-percentage point increase in LEP volume was associated with 2% higher odds of a 7-day readmission; however, this difference was not statistically significant [OR=1.02, 95% CI (0.99-1.06)].

Conclusion: Readmission disparities were greatest in hospitals serving higher proportions of patients with LEP; however, the disparities were rendered insignificant in hospitals with the favorable nurse work environments.

Background: Post-acute care (PAC) utilization following sepsis hospitalization remains understudied, particularly concerning racial and ethnic and urban-rural disparities.

Objectives: To examine trends and disparities in PAC utilization after sepsis hospitalization, focusing on race, ethnicity, and rurality.

Methods: A comprehensive search of databases (PubMed, CINAHL, Embase, Web of Science, and Scopus) was conducted for eligible studies using data through March 2020. The Social Ecological Model guided the review.

Results: Eleven studies met inclusion criteria. Our synthesis found a discontinuous increase in PAC use, with a shift from home discharges toward greater use of nursing homes and home health care after 2006. White patients had higher PAC utilization than racial and ethnic minority individuals. Rural and urban non-teaching hospitals discharged more sepsis survivors to long-term care hospitals, while urban teaching hospitals had more discharges to HHC.

Conclusion: This review establishes a pre-reform, pre-pandemic baseline for PAC utilization among sepsis survivors. Despite overall gains, disparities in PAC utilization persist by race, ethnicity, and hospital type. As payment and care delivery models have evolved since 2016, future research should leverage this historical baseline to assess the impact of new policies on equitable PAC access for sepsis survivors.

Background: Prior studies at the national level indicate that primary care wait times exceeded the 20-day veterans Health Administration (VA) wait time standards set for primary care. Longer wait times were also reported for Black and Hispanic versus White veterans.

Objectives: Examine variation in wait time for primary care at the facility level by race and ethnicity over time and determine whether differences are due to within-facility differences (ie, at the same facility) or between-facility differences (ie, differences in facilities used).

Research design: Observational study using VA and Community Care (CC) data from Fiscal Year (FY) FY2021 to FY2023.

Subjects: All veterans (n=642,180) who had an outpatient primary care consult in VA or CC.

Measures: Wait time for an outpatient primary care consult.

Methods: We used multivariate regression models calculated using all 3 FYs combined and separately by FY models to predict consult wait times. We then used the Kitagawa decomposition to partition differences in mean adjusted wait times between Hispanic/Black veterans and White veterans into within-facility differences and between-facility differences.

Results: Overall, Hispanic veterans waited on average 6.7 days longer than White veterans, attributed to longer wait times within the same facility. Black veterans waited 1.2 days less than White veterans, partially accounted for by their higher use of facilities with shorter wait times for all veterans. Within-facility results were reasonably stable across FYs.

Conclusions: Continued investigation at the local level is important for ensuring timely access to primary care for all racial and ethnic groups.

Background: The Affordable Care Act (ACA) aimed to simplify plan choice and provide affordable health insurance. However, the complexity and cost-sharing features of ACA plans may undermine its goals.

Objectives: To examine the affordability and choice set of all individual ACA health insurance plans, and the cost implications for taxpayers.

Design: Cross-sectional study.

Subjects: ACA marketplace plans nationwide.

Measures: We analyzed choice set, total premiums, and total deductibles for all plans in all US ACA markets using 2023 HIX Compare data, Small Area Health Insurance Estimates, and American Community Survey data. We evaluated affordability for persons with incomes above 400% of the Federal Poverty Line (FPL), for whom ACA premium tax subsidies are set to expire, defining premiums ≥10% of annual income as unaffordable.

Results: In 97% of US counties, ACA consumers were offered >= 25 ACA plans, and 40% of counties offered >127 plans. Presubsidy, the median (IQR) Bronze plan premium was $4160 ($3636-4866), with a median (IQR) deductible of $7500 ($5300-$9700). The median (IQR) Silver plan premium was $5057 ($4430-5892), with a median (IQR) deductible of $2000 ($0-6800). Among persons with income at 400% of FPL, 98.6% of markets had ≥75% of their plans with unaffordable premiums for a 2-adult household, and 97.0% of markets had ≥75% of plans with unaffordable premiums for a 50-year-old individual should subsidies expire.

Conclusions: Excessive plan choice creates significant challenges for consumers in selecting appropriate coverage. The magnitude of premiums and deductibles is unsustainable due to the financial burdens they place on the individual ACA consumer and/or the American taxpayer.

Background: Medicare Advantage (MA) encounter data became available for research in 2019; data quality concerns remain.

Objectives: We evaluated the consistency of ICD-10-CM comorbidity coding between MA and Fee-For-Service (FFS) data.

Methods: We used round 7 (2017) of the National Health and Aging Trends Study (NHATS) linked to Medicare enrollment, MA encounter, and FFS claims (2016-2017). We included participants continuously enrolled in MA or FFS for 1 year before round 7. Comorbidities were identified using ICD-10-CM codes from the Gagne combined comorbidity index. Demographic, socioeconomic, and clinical covariates from NHATS for FFS beneficiaries were standardized to resemble those for MA beneficiaries. We estimated crude and standardized comorbidity prevalence differences (PDs) between MA and FFS beneficiaries.

Results: Among 5158 beneficiaries (MA: 40%, FFS: 60%), MA beneficiaries were more likely to be Black, Hispanic, and socioeconomically disadvantaged. After standardization, comorbidity prevalence was similar between groups. Peripheral vascular disorder (PD=7.2%, 95% CI: 3.8%-10.6%) and renal failure (PD=3.7%, 95% CI: 0.9%-6.5%) were more common in MA beneficiaries; fluid/electrolyte disorders (PD=-3.2%, 95% CI: -5.5 to -1.0%) and deficiency anemias (PD=-5.0%, 95% CI: -7.6 to -2.3%) were more common in FFS beneficiaries. Other PDs were less than 3 percentage points.

Conclusions: Discrepancies in comorbidity prevalence may reflect true differences or coding variations influenced by provider incentives, documentation standards, or diagnostic priorities. Comorbidity prevalence was largely consistent between MA encounters and FFS claims, supporting the reliability of MA encounter data for aging research. Additional validation studies should address remaining discrepancies.

Background: Understanding patients' experiences with diagnosis is crucial for improving care. Clarifying how best to ask about these experiences is an essential step in doing so.

Objective: To elicit and then categorize diagnostic problems and mistakes in a national, population-based survey.

Methods: Drawing from a nationally representative panel, respondents were asked whether they had experienced (directly or as a care partner) a diagnostic problem or mistake in the last 4 years. They then classified the experience as a mistake, a problem only, or a combination of both. Respondents who experienced multiple problems and mistakes reported on their most memorable experience. We compared responses among those reporting a problem, a mistake, or a combination of both.

Results: A third [1216/3684 (33.0%)] of screened households reported diagnostic problems or mistakes involving themselves [697/3684 (18.9%)] or someone close to them [519/3684 (14.1%)]. A plurality [448/3684 (12.2%)] categorized these as a mistake, 382 (10.4%) as a problem, and 371 (10.1%) as both. Experiences reported as problems versus mistakes were equally likely to be associated with harmful consequences and concrete clinician responses. The distribution of problems and mistakes across the 3 categories did not significantly differ when reported by patients versus care partners, though there were checkered differences in the reported impact.

Conclusions: Whether labeled as problems or mistakes, diagnostic experiences reported by patients and care partners are accompanied by substantial emotional, physical, and financial impacts. Responding to this full range of patient experiences is important for guiding improvements in diagnostic quality within learning health systems.

Background: Patient Safety Indicators (PSIs) derived from administrative data are widely used for monitoring and improving hospital care quality. However, the validity of ICD-10-based PSI algorithms remains uncertain, particularly in terms of their sensitivity and specificity.

Objectives: To evaluate the diagnostic performance of ICD-10-CA-based algorithms for identifying fifteen PSIs using chart review as the reference standard.

Research design: Multicenter retrospective cohort validation study.

Subjects: A random sample of 10,665 adult patients admitted to 4 acute care hospitals in Calgary, Alberta, between January 1, 2017, and March 31, 2022.

Measures: Fifteen PSIs were identified using ICD-10-CA codes and validated against detailed chart reviews. Diagnostic performance was measured using sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and overall accuracy. Analyses were stratified by diagnosis code type and relevant patient characteristics.

Results: Among 10,665 patients, 1688 had at least one PSI confirmed by chart review. ICD-10-CA coding detected any PSI with 67.0% sensitivity (95% CI, 64.7%-69.2%), 72.8% specificity (95% CI, 71.8%-73.7%), 31.6% PPV (95% CI, 30.1%-33.1%), 92.2% NPV (95% CI, 91.5%-92.8%), and 71.8% accuracy (95% CI, 71.0%-72.7%). Restricting PSIs to conditions that occurred after admission (limited diagnosis type II code) improved specificity (95.7%; 95% CI, 95.3%-96.1%) and PPV (56.5%; 95% CI, 53.2%-59.7%) but reduced sensitivity (29.6%; 95% CI, 27.4%-31.8%). Validity varied by PSI and patient characteristics, with higher sensitivity and PPV among older adults, males, and those with greater comorbidity, longer hospital and ICU stays, 30-day readmission, or in-hospital death.

Conclusions: ICD-10 coded administrative data demonstrate high specificity and NPV but varied sensitivity and PPV in identifying PSIs. Restricting to type II codes improves PPV but reduces sensitivity. Tailoring coding strategies to specific surveillance or quality improvement goals is critical.