The Medicare Care Choices Model was associated with reductions in disparities in the use of hospice care for Medicare beneficiaries with terminal illness.

OBJECTIVE: To assess the effects of the Medicare Care Choices Model (MCCM) on disparities in hospice use and quality of end-of-life care for Medicare beneficiaries from underserved groups-those from racial and ethnic minority groups, dually eligible for Medicare and Medicaid, or living in rural areas. DATA SOURCES AND STUDY SETTING: Medicare enrollment and claims data from 2013 to 2021 for terminally ill Medicare fee-for-service beneficiaries nationwide. STUDY DESIGN: Through MCCM, terminally ill enrolled Medicare beneficiaries received supportive and palliative care services from hospice providers concurrently with curative treatments. Using a matched comparison group, we estimated subgroup-specific effects on hospice use, days at home, and aggressive treatment and multiple emergency department visits in the last 30 days of life. DATA COLLECTION/EXTRACTION METHODS: The sample included decedent Medicare beneficiaries enrolled in MCCM and a matched comparison group from the same geographic areas who met model eligibility criteria at time of enrollment: having a diagnosis of cancer, congestive heart failure, chronic obstructive pulmonary disease, or HIV/AIDS; living in the community; not enrolled in the Medicare hospice benefit in the previous 30 days; and having at least one hospital stay and three office visits in the previous 12 months. PRINCIPAL FINDINGS: Eligible beneficiaries from underserved groups were underrepresented in MCCM. MCCM increased enrollees' hospice use and the number of days at home and reduced aggressive treatment among all subgroups analyzed. MCCM also reduced disparities in hospice use by race and ethnicity and dual eligibility by 4.1 (90% credible interval [CI]: 1.3-6.1) and 2.4 (90% CI: 0.6-4.4) percentage points, respectively. It also reduced disparities in having multiple emergency department visits for rural enrollees by 1.3 (90% CI: 0.1-2.7) percentage points. CONCLUSIONS: MCCM increased hospice use and quality of end-of-life care for model enrollees from underserved groups and reduced disparities in hospice use and having multiple emergency department visits.

Medicare Care Choices Model Improved End-Of-Life Care, Lowered Medicare Expenditures, And Increased Hospice Use.

The Medicare Care Choices Model (MCCM) tested a new option for eligible Medicare beneficiaries to receive conventional treatment for terminal conditions along with supportive and palliative care from participating hospice providers. Using claims data, we estimated differences in average outcomes from enrollment to death between deceased MCCM enrollees and matched comparison beneficiaries who received usual services covered by original Medicare. Enrollees were 15 percentage points less likely to receive an aggressive life-prolonging treatment at the end of life and spent more than five more days at home. MCCM also reduced net Medicare expenditures by 13 percent, decreased inpatient admissions by 26 percent, reduced outpatient emergency department visits by 12 percent, and increased hospice use by 18 percentage points. Although the Centers for Medicare and Medicaid Services did not expand the model, given concerns about generalizability, these results provide evidence that MCCM is a promising approach to transforming care delivery at the end of life.

Reducing Acute Hospitalizations at High-Performing CPC+ Primary Care Practice Sites: Strategies, Activities, and Facilitators.

PURPOSE: Despite evidence suggesting that high-quality primary care can prevent unnecessary hospitalizations, many primary care practices face challenges in achieving this goal, and there is little guidance identifying effective strategies for reducing hospitalization rates. We aimed to understand how practices in the Comprehensive Primary Care Plus (CPC+) program substantially reduced their acute hospitalization rate (AHR) over 2 years. METHODS: We used Bayesian analyses to identify the CPC+ practice sites having the highest probability of achieving a substantial reduction in the adjusted Medicare AHR between 2016 and 2018 (referred to here as AHR high performers). We then conducted telephone interviews with 64 respondents at 14 AHR high-performer sites and undertook within- and cross-case comparative analysis. RESULTS: The 14 AHR high performers experienced a 6% average decrease (range, 4% to 11%) in their Medicare AHR over the 2-year period. They credited various care delivery activities aligned with 3 strategies for reducing AHR: (1) improving and promoting prompt access to primary care, (2) identifying patients at high risk for hospitalization and addressing their needs with enhanced care management, and (3) expanding the breadth and depth of services offered at the practice site. They also identified facilitators of these strategies: enhanced payments through CPC+, prior primary care practice transformation experience, use of data to identify high-value activities for patient subgroups, teamwork, and organizational support for innovation. CONCLUSIONS: The AHR high performers observed that strengthening the local primary care infrastructure through practice-driven, targeted changes in access, care management, and comprehensiveness of care can meaningfully reduce acute hospitalizations. Other primary care practices taking on the challenging work of reducing hospitalizations can learn from CPC+ practices and may consider similar strategies, selecting activities that fit their context, personnel, patient population, and available resources.

Cox Regression Models with Functional Covariates for Survival Data.

We extend the Cox proportional hazards model to cases when the exposure is a densely sampled functional process, measured at baseline. The fundamental idea is to combine penalized signal regression with methods developed for mixed effects proportional hazards models. The model is fit by maximizing the penalized partial likelihood, with smoothing parameters estimated by a likelihood-based criterion such as AIC or EPIC. The model may be extended to allow for multiple functional predictors, time varying coefficients, and missing or unequally-spaced data. Methods were inspired by and applied to a study of the association between time to death after hospital discharge and daily measures of disease severity collected in the intensive care unit, among survivors of acute respiratory distress syndrome.

Duration of oral endotracheal intubation is associated with dysphagia symptoms in acute lung injury patients.

PURPOSE: The purpose of this study is to evaluate demographic and clinical factors associated with self-reported dysphagia after oral endotracheal intubation and mechanical ventilation in patients with acute lung injury (ALI). MATERIALS AND METHODS: This is a prospective cohort study of 132 ALI patients who had received mechanical ventilation via oral endotracheal tube. RESULTS: The primary outcome was binary, whether clinically important symptoms of dysphagia at hospital discharge were reported by patients, using the Sydney Swallowing Questionnaire score 200 or more. Of 132 patients, 29% reported clinically important symptoms of dysphagia. Of 18 relevant demographic and clinical variables, only 2 were found to be independently associated with clinically important symptoms of dysphagia in a multivariable logistic regression model: upper gastrointestinal comorbidity (odds ratio, 2.82; 95% confidence interval, 1.09-7.26) and duration of oral endotracheal intubation (odds ratio, 1.79; [95% confidence interval, 1.15-2.79] per day for first 6 days, after which additional days of intubation were not associated with a further increase in the odds of dysphagia). CONCLUSIONS: In ALI survivors, patient-reported, postexubation dysphagia at hospital discharge was significantly associated with upper gastrointestinal comorbidity and a longer duration of oral endotracheal intubation during the first 6 days of intubation.

Variable-Domain Functional Regression for Modeling ICU Data.

We introduce a class of scalar-on-function regression models with subject-specific functional predictor domains. The fundamental idea is to consider a bivariate functional parameter that depends both on the functional argument and on the width of the functional predictor domain. Both parametric and nonparametric models are introduced to fit the functional coefficient. The nonparametric model is theoretically and practically invariant to functional support transformation, or support registration. Methods were motivated by and applied to a study of association between daily measures of the Intensive Care Unit (ICU) Sequential Organ Failure Assessment (SOFA) score and two outcomes: in-hospital mortality, and physical impairment at hospital discharge among survivors. Methods are generally applicable to a large number of new studies that record a continuous variables over unequal domains.

Does intensive care unit severity of illness influence recall of baseline physical function?

PURPOSE: The aim of this study is to evaluate if severity of illness in the intensive care unit influences patients' retrospective recall of their baseline physical function from before hospital admission. MATERIALS AND METHODS: This is a prospective cohort study of 193 acute lung injury survivors who, before hospital discharge, retrospectively reported their prehospitalization physical function using the Short Form 36 quality of life survey. RESULTS: Four measures were used to evaluate intensive care unit (ICU) severity of illness: (1) Acute Physiology and Chronic Health Evaluation II Acute Physiologic Score at ICU admission, (2) Lung Injury Score at acute lung injury diagnosis, (3) Sequential Organ Failure Assessment score at study enrollment, and (4) maximum daily Sequential Organ Failure Assessment score during the entire ICU stay. In multivariable linear regression analysis, no measure of severity of illness was associated with prehospitalization physical function. Education level significantly modified the relationship between ICU severity of illness and baseline physical function with lower educational attainment having a stronger association with baseline physical function. CONCLUSION: Intensive care unit severity of illness was not associated with patients' retrospectively recalled baseline physical function. Patients with a lower level of education may be more influenced by ICU severity of illness, but the magnitude of this effect may not be clinically meaningful.