BACKGROUND: Transitional hospital-to-home care programs support safe and timely transition from acute care settings back into the community. Case-mix systems that classify transitional care clients into groups based on their resource utilization can assist with care planning, calculating reimbursement rates in bundled care funding models, and predicting health human resource needs. This study evaluated the fit and relevance of the Resource Utilization Groups version III for Home Care (RUG-III/HC) case-mix classification system in transitional care programs in Ontario, Canada.
METHODS: We conducted a retrospective analysis of clinical assessment data and administrative billing records from a cohort of clients (n = 1,680 care episodes) in transitional home care programs in Ontario. We classified care episodes into established RUG-III/HC groups based on clients\' clinical and functional characteristics and calculated four case-mix indices to describe care relative resource utilization in the study sample. Using these indices in linear regression models, we evaluated the degree to which the RUG-III/HC system can be used to predict care resource utilization.
RESULTS: A majority of transitional home care clients are classified as being Clinically complex (41.6%) and having Reduced physical functions (37.8%). The RUG-III/HC groups that account for the largest share of clients are those with the lowest hierarchical ranking, indicating low Activities of Daily Living limitations but a range of Instrumental Activities of Daily Living limitations. There is notable heterogeneity in the distribution of clients in RUG-III/HC groups across transitional care programs. The case-mix indices reflect decreasing hierarchical resource use within but not across RUG-III/HC categories. The RUG-III/HC predicts 23.34% of the variance in resource utilization of combined paid and unpaid care time.
CONCLUSIONS: The distribution of clients across RUG-III/HC groups in transitional home care programs is remarkably different from clients in long-stay home care settings. Transitional care programs have a higher proportion of Clinically complex clients and a lower proportion of clients with Reduced physical function. This study contributes to the development of a case-mix system for clients in transitional home care programs which can be used by care managers to inform planning, costing, and resource allocation in these programs.

Behavioral health (BH) concerns are prevalent among residents (eg, depression, anxiety, and insomnia), family care partners (eg, depression and burden), and staff (eg, burnout and depression) in nursing home-based post-acute and subacute care, referred to as skilled nursing facility (SNF) care. When untreated, BH concerns can lead to negative care outcomes, including limited functional improvements, longer lengths of stay, and elevated risk of rehospitalization and mortality. Despite the high clinical need, the field lacks evidence and consensus regarding an optimal model of BH services and roles for BH clinicians in SNFs. Developing such a model can inform the testing of BH interventions that best align with clinical operations, moving the field toward answering questions regarding the effectiveness and implementation of BH services in SNFs. Evidence-based BH models from the primary care literature include coordinated, colocated, and integrated care, each of which present potential benefits and challenges for the SNF setting. In this special article, we argue that an integrated model of BH services in SNFs may (1) increase access to and engagement with BH; (2) strengthen positive biopsychosocial resident outcomes and quality of care; and (3) prevent or improve BH concerns among stakeholders involved in resident care, including family care partners and staff. From our evidence-based discussion, we propose a Stepped-Care Model of Integrated BH for SNFs that can help clarify the scope of practice and clinical roles for licensed BH clinicians in this setting (eg, psychologists, clinical social workers, master\'s-level counselors). We conclude with a discussion of policy and research implications with a focus on potential policy changes that may be necessary for BH integration in SNFs. Future research to establish feasibility, clinical benefit (eg, efficacy, effectiveness), and financial justification for our proposed model is needed. This article can serve as a guide for such future research endeavors.

UNASSIGNED: Post-acute care is fast developing in China, yet a payment system for post-acute care has not been established. As stroke is the leading cause of mortality and disability in China, patients constitute a large share of post-acute-care patients among all hospitalized patients. This study was to identify the cost determinants and establish a case-mix classification of the post-acute care system for stroke patients in China.
UNASSIGNED: A total of 5401 post-acute stroke patients in seven hospitals of Jinhua City from January 2018 to December 2020 were selected. Demographic characteristics, medical status, functional measures (eg, the Barthel Index, Mini-Mental State Examination, Gugging Swallowing Screen, Hamilton Depression Scale), and cost data were extracted. Generalized linear model (GLM) and quantile regression (QR) were conducted to determine the predictors of cost, and a case-mix classification model was established using the decision-tree analysis.
UNASSIGNED: The GLM regression revealed that gender, tracheostomy, complication or comorbidity (CC), activities of daily living (ADL), and cognitive impairment were the main variables significantly affecting the hospitalization expenses of post-acute stroke patients. The QR model showed that the gender, tracheostomy and CC factors had a more significant impact on per diem costs on the upper quantiles. In contrast, cognitive impairment had a more substantial effect on the lower quantiles, and ADL significantly impacted the central quantile. Using tracheostomy, CC, and ADL as node variables of the regression tree, 12 classes were generated. The case-mix classification performed reliably and robustly, as measured by the reduction in the variation statistic (RIV=0.46) and class-specific coefficients of variation (CV less than 1.0; range: 0.18-0.81).
UNASSIGNED: QR has strengths in comprehensively identifying cost predictors across cost groups. Tracheostomy, CC, and ADL significantly can predict the expenses of post-acute care for stroke patients. The established case-mix classification system can inform the future payment policy of post-acute care in China.

In Canada, alternate-level-of-care (ALC) beds in hospitals may be used when patients who do not require the intensity of services provided in an acute care setting are waiting to be discharged to a more appropriate care setting. However, when there is a lack of care options for patients waiting to be discharged, it contributes to prolonged hospital stays and bottlenecks in the health care system manifested as \"hallway medicine.\" We examined the effectiveness of a function-focused transitional care program, the Sub-Acute care for Frail Elderly (SAFE) Unit, in reducing the length of stay (LOS) in hospital, as well as post-discharge acute care use and continuity of care.
Case-control study.
A 450-bed nursing home located in Ontario, Canada, where the SAFE Unit is based. The study population included frail, older patients aged 60 years and older who received care in the SAFE Unit between March 1, 2018, and February 28, 2019 (n = 153) to controls comprising of other hospitalized patients (n = 1773).
We linked facility-level to provincial health administrative databases on hospital admissions and emergency department (ED) visits, and the Ontario Health Insurance Plan claims database for physician billings to investigated the LOS during the index hospitalization, 30-day odds of post-discharge ED visits, hospital readmission, and follow-up with family physicians.
SAFE patients had a median hospital LOS of 13 days [interquartile range (IQR): 8-19 days], with 75% having fewer than 1 day in an ALC bed. In comparison, the median LOS in the control group was 15 days (IQR: 10-24 days), with one-third of those days spent in an ALC bed (median: 5 days, IQR: 3-10 days). SAFE patients were more likely (64.1%) to be discharged home than control patients (46.3%). Both groups experienced similar 30-day odds of ED visits, hospital readmission and follow-up with a family physician.
Frail older individuals in the SAFE Unit experienced shorter hospital stays, were less likely to be discharged to settings other than home and had similar 30-day acute care outcomes as control patients post-discharge.

Administrative records such as Medicare fee-for-service (FFS) claims provide accurate information on services paid for by Medicare. However, the increasing availability of electronic health records means many researchers may be inclined to rely on data coded in hospital information systems rather than claims. The current quality and accuracy of hospital reports on the use of post-acute care (PAC) services are not known.
This study examined differences in the PAC use between hospital discharge status recorded on Medicare Provider and Analysis Review inpatient hospital records and claims for PAC services.
In addition to assessments of the three types of Medicare-reimbursed PAC (home health agency [HHA], skilled nursing facility [SNF], and inpatient rehabilitation facility [IRF]), the analysis also considered home without PAC services as a default discharge location.
The analysis was conducted using data for FFS beneficiaries who participated in the Medicare Current Beneficiary Survey and had one or more inpatient hospitalizations from 2006 to 2011.
This study measured discrepancies between hospital-reported discharges to PAC and PAC use based on Medicare claims.
The study found that, on average, 27.9% of hospital reports of discharging to Medicare-covered PAC services were not substantiated by Medicare PAC claims. Among all the discharge pathways, discharging to HHAs had the highest discrepancy rate (29.6%), followed by IRFs (14.7%) and SNFs (13.8%).
The study results call for cautions about the extent to which the reported discharge locations on hospital claims may differ from actual PAC services used. Assuming that Medicare FFS claims were complete and accurate, researchers using the discharge status reported on Medicare hospital claims should be aware of possible measurement errors when using hospital-reported discharge locations. J Am Geriatr Soc 68:847-851, 2020.

Report cards on provider performance are intended to improve consumer decision-making and address information gaps in the market for quality. However, inadequate risk adjustment of report-card measures often biases comparisons across providers. We test whether going to a skilled nursing facility (SNF) with a higher star rating leads to better quality outcomes for a patient. We exploit variation over time in the distance from a patient\'s residential ZIP code to SNFs with different ratings to estimate the causal effect of admission to a higher-rated SNF on health care outcomes, including mortality. We found that patients who go to higher-rated SNFs achieved better outcomes, supporting the validity of the SNF report card ratings.

The RUG-III case-mix system is a method of grouping patients in long-term and post-acute care settings. RUG-III groups patients by relative per diem resource consumption and may be used as the basis for prospective payment systems to ensure that facility reimbursement is commensurate with patient acuity. Since RUG-III\'s development in 1994, more than a dozen international staff time measurement studies have been published to evaluate the utility of the case-mix system in a variety of diverse health care environments around the world. This overview of the literature summarizes the results of these RUG-III validation studies and compares the performance of the algorithm across countries, patient populations, and health care environments. Limitations of the RUG-III validation literature are discussed for the benefit of health system administrators who are considering implementing RUG-III and next-generation resource utilization group case-mix systems.