Medical Care最新文献

Objective: The association between participation in a behavioral weight intervention and health expenditures has not been well characterized. We compared Veterans Affairs (VA) expenditures of individuals participating in MOVE!, a VA behavioral weight loss program, and matched comparators 2 years before and 2 years after MOVE! initiation.

Methods: Retrospective cohort study of Veterans who had one or more MOVE! visits in 2008-2017 who were matched contemporaneously to up to 3 comparators with overweight or obesity through sequential stratification on an array of patient characteristics, including sex. Baseline patient characteristics were compared between the two cohorts through standardized mean differences. VA expenditures in the 2 years before MOVE! initiation and 2 years after initiation were modeled using generalized estimating equations with a log link and distribution with variance proportional to the standard deviation (gamma).

Results: MOVE! participants (n=499,696) and comparators (n=1,336,172) were well-matched, with an average age of 56, average body mass index of 35, and similar total VA expenditures in the fiscal year before MOVE! initiation ($9662 for MOVE! participants and $10,072 for comparators, standardized mean difference=-0.019). MOVE! participants had total expenditures that were statistically lower than matched comparators in the 6 months after initiation but modestly higher in the 6 months to 2 years after initiation, though differences were small in magnitude (1.0%-1.6% differences).

Conclusions: The VA's system-wide behavioral weight intervention did not realize meaningful short-term health care cost savings for participants.

Background: The magnitude of the relationship between ambulatory care fragmentation and subsequent total health care costs is unclear.

Objective: To determine the association between ambulatory care fragmentation and total health care costs.

Research design: Longitudinal analysis of 15 years of data (2004-2018) from the national Reasons for Geographic and Racial Differences in Stroke (REGARDS) study, linked to Medicare fee-for-service claims.

Subjects: A total of 13,680 Medicare beneficiaries who are 65 years and older.

Measures: We measured ambulatory care fragmentation in each calendar year, defining high fragmentation as a reversed Bice-Boxerman Index ≥0.85 and low as <0.85. We used generalized linear models to determine the association between ambulatory care fragmentation in 1 year and total Medicare expenditures (costs) in the following year, adjusting for baseline demographic and clinical characteristics, a time-varying comorbidity index, and accounting for geographic variation in reimbursement and inflation.

Results: The average participant was 70.9 years old; approximately half (53%) were women. One-fourth (26%) of participants had high fragmentation in the first year of observation. Those participants had a median of 9 visits to 6 providers, with the most frequently seen provider accounting for 29% of visits. By contrast, participants with low fragmentation had a median of 8 visits to 3 providers, with the most frequently seen provider accounting for 50% of visits. High fragmentation was associated with $1085 more in total adjusted costs per person per year (95% CI $713 to $1457) than low fragmentation.

Conclusions: Highly fragmented ambulatory care in 1 year is independently associated with higher total costs the following year.

Objectives: To examine Black-White patient differences in mortality and other hospital outcomes among Veterans treated in Veterans Affairs (VA) and non-VA hospitals.

Background: Lower hospital mortality has been documented in older Black patients relative to White patients, yet the mechanisms have not been determined. Comparing other hospital outcomes and multiple hospital systems may help inform the reasons for these differences.

Methods: Repeated cross-sectional analysis of hospitalization records was conducted for Veterans discharged in VA and non-VA hospitals from January 1, 2013 to December 31, 2017 in 11 states. Hospital outcomes included 30-day mortality, 30-day readmissions, inpatient costs, and length of stay. Hospitalizations were for acute myocardial infarction, coronary artery bypass graft surgery, gastrointestinal bleeding, heart failure, pneumonia, and stroke. Differences in outcomes were estimated between Black and White patients for VA and non-VA hospitals and age groups younger than 65 years or 65 years and older in regression models adjusting for patient and hospital factors.

Results: There were a total of 459,574 study patients. Older Black patients had lower adjusted mortality for acute myocardial infarction, gastrointestinal bleeding, heart failure, and pneumonia. Adjusted probability of readmission was higher and adjusted mean length of stay and costs were greater for older Black patients relative to White patients in non-VA hospitals for several conditions. Fewer differences were observed in younger patients and in VA hospitals.

Conclusion: While older Black patients had lower mortality, other outcomes compared poorly with White patients. Differences were not fully explained by observable patient and hospital factors although social determinants may contribute to these differences.

Background: Over 12 million Americans are dually enrolled in Medicare and Medicaid. These individuals experience over twice as many hospitalizations for chronic diseases such as coronary artery disease and diabetes compared with Medicare-only patients. Nurse practitioners (NPs) are well-positioned to address the care needs of dually-enrolled patients, yet NPs often work in unsupportive clinical practice environments. The purpose of this study was to examine the association between the NP primary care practice environment and hospitalization disparities between dually-enrolled and Medicare-only patients with chronic diseases.

Methods: Using secondary cross-sectional data from the Nurse Practitioner Primary Care Organizational Climate Questionnaire and Medicare claims files, we examined 135,648 patients with coronary artery disease and/or diabetes (20.0% dually-eligible, 80.0% Medicare-only), cared for in 450 practices employing NPs across 4 states (PA, NJ, CA, FL) in 2015. We compared dually-enrolled patients' odds of being hospitalized when cared for in practice environments characterized as poor, mixed, and good based on practice-level Nurse Practitioner Primary Care Organizational Climate Questionnaire scores.

Results: After adjusting for patient and practice characteristics, dually-enrolled patients in poor practice environments had the highest odds of being hospitalized compared with their Medicare-only counterparts [odds ratio (OR): 1.48, CI: 1.37, 1.60]. In mixed environments, dually-enrolled patients had 27% higher odds of a hospitalization (OR: 1.27, CI: 1.12, 1.45). However, in the best practice environments, hospitalization differences were nonsignificant (OR: 1.02, CI: 0.85, 1.23).

Conclusions: As policymakers look to improve outcomes for dually-enrolled patients, addressing a modifiable aspect of care delivery in NPs' clinical practice environment is a key opportunity to reduce hospitalization disparities.

Objectives: To examine the association of prestroke continuity of care (COC) with postdischarge health care utilization and expenditures.

Study population: The study population included 2233 patients with a diagnosis of stroke or a transient ischemic attack hospitalized in one of 41 hospitals in North Carolina between March 2016 and July 2019 and discharged directly home from acute care.

Methods: COC was assessed from linked Centers for Medicare and Medicaid Services Medicare claims using the Modified, Modified Continuity Index. Logistic regressions and 2-part models were used to examine the association of prestroke primary care COC with postdischarge health care utilization and expenditures.

Results: Relative to patients in the first (lowest) COC quartile, patients in the second and third COC quartiles were more likely [21% (95% CI: 8.5%, 33.5%) and 33% (95% CI: 20.5%, 46.1%), respectively] to have an ambulatory care visit within 14 days. Patients in the highest COC quartile were more likely to visit a primary care provider but less likely to see a stroke specialist. Highest as compared with lowest primary care COC quartile was associated with $45 lower (95% CI: $14, $76) average expenditure for ambulatory care visits within 30 days postdischarge. Patients in the highest, as compared with the lowest, primary care COC quartile were 36% less likely (95% CI: 8%, 64%) to be readmitted within 30 days postdischarge and spent $340 less (95% CI: $2, $678) on unplanned readmissions.

Conclusions: These findings underscore the importance of primary care COC received before stroke hospitalization to postdischarge care and expenditures.

Objective: Health care overuse is pervasive in countries with advanced health care delivery systems. We hypothesize that effective interventions to reduce low-value care that targets patients or clinicians are mediated by psychological and cognitive processes that change behaviors and that interventions targeting these processes are varied. Thus, we performed a scoping review of experimental studies of interventions, including the interventions' objectives and characteristics, to reduce low-value care that targeted psychological and cognitive processes.

Methods: We systematically searched databases for experimental studies of interventions to change cognitive orientations and affective states in the setting of health care overuse. Outcomes included observed overuse or a stated intention to use services. We used existing frameworks for behavior change and mechanisms of change to categorize the interventions and the mediating processes.

Results: Twenty-seven articles met the inclusion criteria. Sixteen studied the provision of information to patients or clinicians, with most providing cost information. Six studies used educational interventions, including the provision of feedback about individual practice. Studies rarely used counseling, behavioral nudges, persuasion, and rewards. Mechanisms for behavior change included gain in knowledge or confidence and motivation by social norms.

Conclusions: In this scoping review, we found few experiments testing interventions that directly target the psychological and cognitive processes of patients or clinicians to reduce low-value care. Most studies provided information to patients or clinicians without measuring or considering mediating factors toward behavior change. These findings highlight the need for process-driven experimental designs, including trials of behavioral nudges and persuasive language involving a trusting patient-clinician relationship, to identify effective interventions to reduce low-value care.

Background: Evidence of higher hospital volume being associated with improved outcomes for patients undergoing total knee replacement (TKR) is mostly based on arbitrary distribution-based thresholds.

Objective: We aimed to define outcome-based volume thresholds using data from a national database.

Methods: We used the MedPAR Limited Data Set inpatient data from 2010-2015 to identify patients who had undergone primary TKR. Surgical and TKR specific complications occurring within the index hospitalization and all-cause readmission within 90 days were considered adverse events. We derived an average annual TKR case volume for each hospital and applied the stratum-specific likelihood ratio method to determine volume categories indicative of a similar likelihood of 90-day post-operative complications. Hierarchical multivariable logistic regression with a random intercept for hospital nested within study year and adjusted for patient and hospital characteristics was performed to determine if these volume thresholds were still associated with the odds of 90-day readmission for complications after adjustment.

Results: SSLR analysis yielded 4 hospital volume categories based on the likelihood of 90-day postoperative complications: 1-31 (low), 32-127 (medium), 128-248 (high), and 429+ (very high) TKRs performed per year. The results of the hierarchical multivariable logistic regression showed significantly increased odds of 90-day complications at lower volume categories. Sensitivity analyses confirmed our main findings.

Conclusions: This study is the first to provide national-level volume categories that are evidence-based. Publicizing these thresholds may enhance quality measures available to patients, providers, and payors.

Objective: Length of stay (LOS) is an important metric for the organization and scheduling of care activities. This study sought to propose a LOS prediction method based on deep learning using widely available administrative data from acute and emergency care and compare it with other methods.

Patients and methods: All admissions between January 1, 2011 and December 31, 2019, at 6 university hospitals of the Hospices Civils de Lyon metropolis were included, leading to a cohort of 1,140,100 stays of 515,199 patients. Data included demographics, primary and associated diagnoses, medical procedures, the medical unit, the admission type, socio-economic factors, and temporal information. A model based on embeddings and a Feed-Forward Neural Network (FFNN) was developed to provide fine-grained LOS predictions per hospitalization step. Performances were compared with random forest and logistic regression, with the accuracy, Cohen kappa, and a Bland-Altman plot, through a 5-fold cross-validation.

Results: The FFNN achieved an accuracy of 0.944 (CI: 0.937, 0.950) and a kappa of 0.943 (CI: 0.935, 0.950). For the same metrics, random forest yielded 0.574 (CI: 0.573, 0.575) and 0.602 (CI: 0.601, 0.603), respectively, and 0.352 (CI: 0.346, 0.358) and 0.414 (CI: 0.408, 0.422) for the logistic regression. The FFNN had a limit of agreement ranging from -2.73 to 2.67, which was better than random forest (-6.72 to 6.83) or logistic regression (-7.60 to 9.20).

Conclusion: The FFNN was better at predicting LOS than random forest or logistic regression. Implementing the FFNN model for routine acute care could be useful for improving the quality of patients' care.

Background: Between 2004 and 2019, the US hospital industry reversed the 21-year decline in its share of national health spending.

Objective: To measure and explain changes in hospital utilization, cost, charges, and inpatient case mix.

Data sources: Principal sources were the American Hospital Association annual survey, the National Inpatient Sample, and the Healthcare Cost Reporting Information System. The study included all US community hospitals (n=5141 in 2019).

Analytic approach: We used factor decomposition to separate the impacts of population, utilization, unit cost, and charge markups on the growth in cost and charges for inpatient and outpatient care nationwide and for each state. For unit cost, we separated the impacts of input price inflation and treatment intensity. To measure the inpatient case mix, we applied an all-patient diagnosis-related groups algorithm.

Results: Between 2004 and 2019, charges more than tripled to $4.11 trillion. The cost more than doubled to $911 billion. For inpatient care, discharges fell 5%, discharges per person fell 15%, cost per discharge increased 88%, and charge markups rose 43%. For outpatient care, visits rose 36%, visits per person rose 21%, cost per visit rose 119%, and charge markups rose 52%. Treatment intensity increased by 33% per discharge and 55% per visit. Nationwide, the inpatient case mix increased by 34%, reflecting sicker patients and better clinical documentation.

Conclusions: We quantified 3 important trends: rapid growth in outpatient visits, increased treatment intensity, and sustained increases in markups. Increased treatment intensity was the largest factor behind $491 billion in hospital cost growth between 2004 and 2019.