Seven-State Study of Assisted Living and Healthcare Providers’ Responses to COVID-19

COVID-19 has inordinately affected assisted living (AL), such that the proportion of fatalities to cases has been 21% in AL versus 2.5% for the general population. Understanding how AL administrators and medical and mental health providers have responded to COVID-19 can inform health care going forward. Using a seven-state stratified random sample of 250 communities, administrators were interviewed and providers completed questionnaires regarding COVID-19 practices. Preliminary data indicate that 79%, 44%, and 62% of administrators reported serving meals in rooms to segregate residents, using telemedicine, and providing extra pay for staff, respectively. Perceived use/effectiveness of practices differed based on dementia case-mix (e.g., face coverings, social distancing). Providers reported less access to patients (82%), more telehealth (63%), and less ability to provide care (43%). However, they uniformly reported high confidence in AL staff ability to prevent (94%) and respond to outbreaks (96%). Discussion will summarize points important for future care.

Current mHealth Use in Dutch Dementia Care: A Guide to Action!

Objective: To report underlying factors that hinder or advance mHealth implementation and use in Dutch dementia care. Methods: 44 dementia experts (healthcare professionals, informal caregivers, dementia case managers, and researchers) completed a questionnaire as part of a wider Delphi study to share their experiences with, thoughts on, and proposals for mHealth use in Dutch dementia care. A SWOT-framework is used to categorize the experiences, thoughts and proposals. Results: Four strengths, twelve weaknesses, thirteen opportunities and six threats for the current use of mHealth in Dutch dementia care were identified. Conclusion: Identified weaknesses highlight the importance for a guide for action for everyone involved in design and implementing mHealth for older adults with dementia. It is critical to raise awareness of mHealth’s availability, improve its design, and continue to address the needs of older adults with dementia.

Resource allocation decision-making in dementia care with and without budget constraints: a qualitative analysis

Introduction: Health systems in many different countries have increasingly been reorienting the delivery of dementia care to home and community care settings. This paper provides information on how health and social care professionals (HSCPs) in Ireland make decisions on resource allocation for people with dementia living at home and how resource constraints affect their decisions and choices. Methods: The study employed a balance of care approach to assess resource allocation across six dementia case types, ranging from low to high needs. Decision-making workshops were held with 24 HSCPs from a range of backgrounds. Participants were asked to allocate services and supports across dementia case types in two scenarios: allocation with and without a budget constraint. Nominal group technique was used to structure discussions around resource allocation in both scenarios. Thematic analysis was applied to analyse the qualitative data using a general inductive approach. Results: The following themes influenced allocative deliberations: whose needs are being met; what needs are identified; decision making context; decision making process; and allocation outcomes. Participants used ‘decision rules’ or heuristics to help them make decisions under fixed budget rules. Conclusions: Freedom from a budget constraint allowed HSCPs to consider a broader range of services and to take a more expansive view on what needs should be considered, with a particular emphasis on adopting a proactive, preventative approach to the allocation of resources. The effect of the budget constraint overall was to narrow all considerations, using heuristics to limit the type of needs addressed and the range of services and supports provided. The consequences were a largely reactive, less personalised system of care. The findings emphasise the need for an integrated and comprehensive assessment process that is more concerned with individualised responses rather than relying on existing models of care alone.

Developing a Plan for the Sustainable Implementation of an Electronic Health Intervention (Partner in Balance) to Support Caregivers of People With Dementia: Case Study

Background Given the increasing use of digital interventions in health care, understanding how best to implement them is crucial. However, evidence on how to implement new academically developed interventions in complex health care environments is lacking. This case study offers an example of how to develop a theory-based implementation plan for Partner in Balance, an electronic health (eHealth) intervention to support the caregivers of people with dementia. Objective The specific objectives of this study were to (1) formulate evidence-based implementation strategies, (2) develop a sustainable business model, and (3) integrate these elements into an implementation plan. Methods This case study concerns Partner in Balance, a blended care intervention to support the caregivers of people with dementia, which is effective in improving caregiver self-efficacy, quality of life, and experienced control. The large-scale implementation of Partner in Balance took place in local dementia case-management services, local care homes, dementia support groups, and municipalities. Experiences from real-life pilots (n=22) and qualitative interviews with national stakeholders (n=14) were used to establish an implementation plan consisting of implementation strategies and a business model. Results The main finding was the need for a business model to facilitate decision-making from potential client organizations, who need reliable pricing information before they can commit to training coaches and implementing the intervention. Additionally, knowledge of the organizational context and a wider health care system are essential to ensure that the intervention meets the needs of its target users. Based on these findings, the research team formulated implementation strategies targeted at the engagement of organizations and staff, dissemination of the intervention, and facilitation of long-term project management in the future. Conclusions This study offers a theory-based example of implementing an evidence-based eHealth intervention in dementia health care. The findings help fill the knowledge gap on the eHealth implementation context for evidence-based eHealth interventions after the trial phase, and they can be used to inform individuals working to develop and sustainably implement eHealth.