A systematic review of case-mix models for home health care payment: Making sense of variation

Embracing Reablement as an Essential Support Approach for Dementia Care in the 21st Century: A Position Paper

The World Health Organization (WHO) recognizes the right of individuals with dementia and their family caregivers to access interventions that enhance their participation in society. Reablement is an approach that enables older people to participate in meaningful daily and social activities. Over the past decade, a growing body of evidence has underscored reablement as a promising approach within dementia care, including positive outcomes for people with dementia and their family caregivers, and cost-effectiveness. However, the dissemination of knowledge about and practical implementation of reablement remain slow. This position paper, authored by the ReableDEM research network, aims to address key issues related to implementing reablement in dementia care. To expedite the adoption of reablement within dementia care, we propose five critical areas of focus: 1) Changing the attitudes and expectations of stakeholders (eg health and social care staff, policy makers, funders) - encouraging people to think about dementia as a disability from a biopsychosocial perspective; 2) Disrupting health and social care - A radical change is needed in the way services are organized so that they are more holistic, personalized and resource-oriented; 3) Investing in capacity-building and creating a supportive environment - the workforce needs to be trained and supported to implement reablement in dementia care; 4) Involving, educating and supporting family caregivers - services and staff that are equipped to provide reablement will be better able to involve family caregivers and the person's social network; 5) Providing robust evidence about reablement in dementia care by conducting high-quality research with long-term follow-up.

Resource Utilization Groups in transitional home care: validating the RUG-III/HC case-mix system in hospital-to-home care programs

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.

Identifying client characteristics to predict homecare use more accurately: a Delphi-study involving nurses and homecare purchasing specialists

Background

Case-mix based prospective payment of homecare is being implemented in several countries to work towards more efficient and client-centred homecare. However, existing models can only explain a limited part of variance in homecare use, due to their reliance on health- and function-related client data. It is unclear which predictors could improve predictive power of existing case-mix models. The aim of this study was therefore to identify relevant predictors of homecare use by utilizing the expertise of district nurses and health insurers.

Methods

We conducted a two-round Delphi-study according to the RAND/UCLA Appropriateness Method. In the first round, participants assessed the relevance of eleven client characteristics that are commonly included in existing case-mix models for predicting homecare use, using a 9-Point Likert scale. Furthermore, participants were also allowed to suggest missing characteristics that they considered relevant. These items were grouped and a selection of the most relevant items was made. In the second round, after an expert panel meeting, participants re-assessed relevance of pre-existing characteristics that were assessed uncertain and of eleven suggested client characteristics. In both rounds, median and inter-quartile ranges were calculated to determine relevance.

Results

Twenty-two participants (16 district nurses and 6 insurers) suggested 53 unique client characteristics (grouped from 142 characteristics initially). In the second round, relevance of the client characteristics was assessed by 12 nurses and 5 health insurers. Of a total of 22 characteristics, 10 client characteristics were assessed as being relevant and 12 as uncertain. None was found irrelevant for predicting homecare use. Most of the client characteristics from the category ‘Daily functioning’ were assessed as uncertain. Client characteristics in other categories – i.e. ‘Physical health status’, ‘Mental health status and behaviour’, ‘Health literacy’, ‘Social environment and network’, and ‘Other’ – were more frequently considered relevant.

Conclusion

According to district nurses and health insurers, homecare use could be predicted better by including other more holistic predictors in case-mix classification, such as on mental functioning and social network. The challenge remains, however, to operationalize the new characteristics and keep stakeholders on board when developing and implementing case-mix classification for homecare prospective payment.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12913-022-07733-9.

Predictors of district nursing care utilisation for community-living people in the Netherlands: an exploratory study using claims data

OBJECTIVE

To explore predictors of district nursing care utilisation for community-living (older) people in the Netherlands using claims data. To cope with growing demands in district nursing care, knowledge about the current utilisation of district nursing care is important.

SETTING

District nursing care as a part of primary care.

PARTICIPANTS

In this nationwide study, claims data were used from the Dutch risk adjustment system and national information system of health insurers. Samples were drawn of 5500 pairs of community-living people using district nursing care (cases) and people not using district nursing care (controls) for two groups: all ages and aged 75+ years (total N=22 000).

OUTCOME MEASURES

The outcome was district nursing care utilisation and the 114 potential predictors included predisposing factors (eg, age), enabling factors (eg, socioeconomic status) and need factors (various healthcare costs). The random forest algorithm was used to predict district nursing care utilisation. The performance of the models and importance of predictors were calculated.

RESULTS

For the population of people aged 75+ years, most important predictors were older age, and high costs for general practitioner consultations, aid devices, pharmaceutical care, ambulance transportation and occupational therapy. For the total population, older age, and high costs for pharmaceutical care and aid devices were the most important predictors.

CONCLUSIONS

People in need of district nursing care are older, visit the general practitioner more often, and use more and/or expensive medications and aid devices. Therefore, close collaboration between the district nurse, general practitioner and the community pharmacist is important. Additional analyses including data regarding health status are recommended. Further research is needed to provide an evidence base for district nursing care to optimise the care for those with high care needs, and guide practice and policymakers' decision-making.