Receiving home care forms and the risk for emergency department visits in community-dwelling Dutch older adults, a retrospective cohort study using national data.

BACKGROUND: Older adults receiving home care have a higher risk of visiting the emergency department (ED) than community-dwelling older adults not receiving home care. This may result from a higher incidence of comorbidities and reduced functional autonomy in home care recipients. Since people receive different types of home care because of their different comorbidities and autonomy profiles, it is possible that distinguishing between the form of home care can help identify subpopulations with different risks for ED visits and help develop targeted interventions. This study aimed to compare the risk of visiting the ED in older adults receiving different forms of home care with those living at home without receiving home care in a national cohort in one year. METHODS: A retrospective cohort study using claims data collected in 2019 on the Dutch population aged ≥ 65 years (N = 3,314,440) was conducted. Participants were classified as follows: no claimed home care (NO), household help (HH), personal care (PC), HH + PC, and nursing home care at home (NHH). The primary outcome was the number of individuals that visited the ED. Secondary outcomes were the number of individuals whose home care changed, who were institutionalized, or who died. Exploratory logistic regression was applied. RESULTS: There were 2,758,093 adults in the NO group, 131,260 in the HH group, 154,462 in the PC group, 96,526 in the HH + PC group, and 34,612 in the NHH group. More ED visits were observed in the home care groups than in the NO group, and this risk increased to more than two-fold for the PC groups. There was a significant change to a more intensive form of home care, institutionalization, or death in all groups. CONCLUSIONS: Distinguishing between the form of home care older adults receive identifies subpopulations with different risks for ED visits compared with community-dwelling older adults not receiving home care on a population level. Home care transitions are frequent and mostly involve more intensive care or death. Although older adults not receiving home care have a lower risk of ED visits, they contribute most to the absolute volume of ED visits.

Implementing online group model building to unravel complex geriatric problems, a methodological description.

BACKGROUND: Group model building (GMB), is a qualitative focus group like study design from the field of system dynamics, that leads a group of topic experts (often key stakeholders of a problem), through a set of scripted activities to create a conceptual model of their shared view on this problems' key contributing factors and their interactions. By offering a specific step wise approach to the complexity of a problem, GMB has provided better understanding and overview of complex problems across different scientific domains, in addition to traditional research methods. As the development of geriatric syndromes and organization of geriatric care are often complex issues that are difficult to research, understand and resolve, GMB might be a useful methodology to better address these issues. This study aimed to describe the methodology of online GMB using a geriatric case study. METHODS: Four online GMB sessions were designed by two clinician researchers. A GMB methodology expert was consulted for optimal design. Scriptapedia scripts formed the core of the sessions. These scripts were adapted to the online format. Experts were recruited purposefully and included seven local health care professionals, one patient representative and one healthcare insurance data analyst. The outcome was a conceptual model of older adults' emergency department visits, which was discussed in a separate article. RESULTS: During implementation of these four sessions, the sessions were adjusted and two extra (non-scripted) sessions were added because defining unambiguous contributing factors to the geriatric case was challenging for the experts. Paraphrasing, categorizing, iterative plenary reflection, and reserving extra time were used to help experts overcome this challenge. All sessions were held in April and May 2021. CONCLUSION: This study shows that GMB can help unravel complex problems in geriatrics, both pathophysiological as organizational, by creating step wise overview of their key contributing factors and interactions. Furthermore, it shows that GMB can be used by clinicians, researchers and health policy makers to better understand complex geriatric problems. Moreover, this paper can help to overcome specific implementational challenges in the geriatric field.

A causal loop diagram of older persons' emergency department visits and interactions of its contributing factors: a group model building approach.

PURPOSE: Understanding the etiology of older persons' emergency department (ED) visits is highly needed. Many contributing factors have been identified, however, the role their interactions play remains unclear. Causal loop diagrams (CLDs), as conceptual models, can visualize these interactions and therefore may elucidate their role. This study aimed to better understand why people older than 65 years of age visit the ED in Amsterdam by capturing the interactions of contributing factors as perceived by an expert group in a CLD through group model building (GMB). METHODS: Six qualitative online focus group like sessions, known as GMB, were conducted with a purposefully recruited interdisciplinary expert group of nine that resulted in a CLD that depicted their shared view. RESULTS: The CLD included four direct contributing factors, 29 underlying factors, 66 relations between factors and 18 feedback loops. The direct factors included, 'acute event', 'frailty', 'functioning of the healthcare professional' and 'availability of alternatives for the ED'. All direct factors showed direct as well as indirect contribution to older persons' ED visits in the CLD through interaction. CONCLUSION: Functioning of the healthcare professional and availability of alternatives for the ED were considered pivotal factors, together with frailty and acute event. These factors, as well as many underlying factors, showed extensive interaction in the CLD, thereby contributing directly and indirectly to older persons' ED visits. This study helps to better understand the etiology of older persons' ED visits and in specific the way contributing factors interact. Furthermore, its CLD can help to find solutions for the increasing numbers of older adults in the ED.

Reduced Waiting Times by Preference-Based Allocation of Patients to Nursing Homes.

OBJECTIVES: The long waiting times for nursing homes can be reduced by applying advanced waiting-line management. In this article, we implement a preference-based allocation model for older adults to nursing homes, evaluate the performance in a simulation setting for 2 case studies, and discuss the implementation in practice. DESIGN: Simulation study. SETTING AND PARTICIPANTS: Older adults requiring somatic nursing home care, from an urban region (Rotterdam) and a rural region (Twente) in the Netherlands. METHODS: Data about nursing homes and capacities for the 2 case studies were identified. A set of preference profiles was defined with aims regarding waiting time preferences and flexibility. Guidelines for implementation of the model in practice were obtained by addressing the tasks of all stakeholders. Thereafter, the simulation was run to compare the current practice with the allocation model based on specified outcome measures about waiting times and preferences. RESULTS: We found that the allocation model decreased the waiting times in both case studies. Compared with the current practice policy, the allocation model reduced the waiting times until placement by at least a factor of 2 (from 166 to 80 days in Rotterdam and 178 to 82 days in Twente). Moreover, more of the older adults ended up in their preferred nursing home and the aims of the distinct preference profiles were satisfied. CONCLUSIONS AND IMPLICATIONS: The results show that the allocation model outperforms commonly used waiting-line policies for nursing homes, while meeting individual preferences to a larger extent. Moreover, the model is easy to implement and of a generic nature and can, therefore, be extended to other settings as well (eg, to allocate older adults to home care or daycare). Finally, this research shows the potential of mathematical models in the care domain for older adults to face the increasing need for cost-effective solutions.