Healthcare Needs Patterns and Pattern-Predicting Factors in Dementia: Results of the Comprehensive, Computerized Unmet Needs Assessment from the Randomized, Controlled Interventional Trial InDePendent.

Background: Determining unmet need patterns and associated factors in primary care can potentially specify assessment batteries and tailor interventions in dementia more efficiently. Objective: To identify latent unmet healthcare need patterns and associated sociodemographic and clinical factors. Methods: This Latent Class Analysis (LCA) includes n = 417 community-dwelling people living with dementia. Subjects completed a comprehensive, computer-assisted face-to-face interview to identify unmet needs. One-hundred-fifteen predefined unmet medical, medication, nursing, psychosocial, and social care needs were available. LCA and multivariate logistic regressions were performed to identify unmet needs patterns and patient characteristics belonging to a specific pattern, respectively. Results: Four profiles were identified: [1] "few needs without any psychosocial need" (n = 44 (11%); mean: 7.4 needs), [2] "some medical and nursing care needs only" (n = 135 (32%); 9.7 needs), [3] "some needs in all areas" (n = 139 (33%); 14.3 needs), and [4] "many medical and nursing needs" (n = 99 (24%); 19.1 needs). Whereas the first class with the lowest number of needs comprised younger, less cognitively impaired patients without depressive symptoms, the fourth class had the highest number of unmet needs, containing patients with lower health status, less social support and higher comorbidity and depressive symptoms. Better access to social care services and higher social support reduced unmet needs, distinguishing the second from the third class (9.7 versus 14.3 needs). Conclusions: Access to the social care system, social support and depressive symptoms should be assessed, and the patient's health status and comorbidities monitored to more comprehensively identify unmet needs patterns and more efficiently guide tailored interventions.

Sociodemographic and Clinical Characteristics of People Living with Dementia and Their Associations with Unmet Healthcare Needs: Insights from the Baseline Assessment of the InDePendent Study.

Background: The healthcare needs of People living with Dementia (PlwD) (such as Alzheimer's disease) are often unmet. Information about the needs of community-dwelling PlwD and their association with sociodemographic and clinical characteristics is needed to fill the knowledge gap regarding factors influencing unmet needs among PlwD and to conduct a comprehensive needs assessment to develop tailored interventions. Objective: To describe sociodemographic and clinical characteristics of the InDePendent study population with particular reference to determinants of unmet needs. Methods: We analyzed baseline data of the multi-centre cluster-randomized controlled trial (InDePendent) using descriptive statistics to describe patients' sociodemographic and clinical characteristics and Poisson regression models to predict unmet needs, separated by sex. Data were collected personally via face-to-face interviews. Results: Most of the n = 417 participating PlwD were mild to moderately cognitively impaired, were not depressed, had an average of 10.8 diagnoses, took 6.7 medications, and had, on average, 2.4 unmet needs (62% of PlwD had at least one unmet need) measured by the Camberwell Assessment of Need for the Elderly (CANE). Low social support, a high body-mass-index, a lower education, functional impairment, and worse health status were associated with more unmet needs, regardless of sex. In women, higher unmet needs were associated with more depressive symptoms, a poor financial situation, living alone and not being recently treated by a general practitioner. In males, unmet needs increased with the number of medications taken. Conclusions: PlwD had a broad array of unmet healthcare needs, indicating primary healthcare provision improvement potentials. The results underscore the significance of early assessment of patient's clinical characteristics and unmet needs as a basis for individualized gender-sensible intervention strategies.∥ClinicalTrials.gov Identifier: NCT04741932, Registered on February 5, 2021.