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Background: Dementia diagnostics can often be performed in primary care, yet older persons with memory complaints are frequently referred to memory clinics (MCs)., Aim: To compare diagnostic information in general practitioner (GP) referral letters of patients with and without an eventual dementia diagnosis., Design & Setting: Retrospective cohort study in a Dutch academic geriatric MC., Method: We collected electronic health record (EHR) data of consecutive patients aged≥65 referred by their GP between 2016-2020. EHR data included patient characteristics, diagnostic information in referral letters, ancillary investigations performed at the MC, and established diagnoses. Chi-square tests were applied to compare groups., Results: Of 651 patients included, the average age was 78.0 (SD: 6.8), and 348 (53.5%) were diagnosed with dementia. Most people with dementia were diagnosed without ancillary investigations (235/348, 67.5%). In GP referral letters of people with dementia compared with people without dementia, a collateral history, any physical examination, a differential diagnosis including dementia, an MMSE score, interference with daily functioning, and decline from previous levels of functioning were mentioned more often. Furthermore, the more diagnostic criteria mentioned in the referral letter, the more often dementia was diagnosed at the MC (no criteria: 35.4%, one criterion: 47.3%, two criteria: 53.4%, three criteria: 69.9%, four or five criteria: 83.3%)., Conclusion: GPs often correctly mention diagnostic information and dementia criteria in referral letters of people with dementia, and they are often diagnosed without ancillary investigations. This suggests that referral is often unnecessary, and GPs can be empowered to diagnose dementia themselves., (Copyright © 2024, The Authors.)

Introduction: Care integration in primary elderly care is suboptimal. Validated instruments are needed to enable the implementation of integrated primary care. We aimed to assess construct validity of the Rainbow Model of Integrated Care measurement tool (RMIC-MT) for healthcare professionals working in an integrated primary elderly care setting in the Netherlands., Methods: In a cross-sectional study, the RMIC-MT, a 36-item questionnaire covering all domains of the Rainbow Model of Integrated Care (RMIC), was sent out to local networks of primary elderly care professionals. Confirmatory factor analysis with maximum likelihood estimation was used for the validation of the factor structure of the RMIC-MT. Model fit was assessed by the chi-square test and fit indices., Results: The RMIC-MT was completed by 323 professionals, primarily general practitioners, community nurses, practice nurses, and case managers. Confirmatory factor analysis and corresponding fit indices showed moderate to good fit, thereby confirming a nine factor model with a total of 36 items., Conclusions: The RMIC-MT is promising for the primary elderly care setting in the Netherlands. It can be used for evaluating integrated care initiatives in a primary care setting, thereby contributing to implementation of integrated primary elderly care., Competing Interests: The authors have no competing interests to declare., (Copyright: © 2023 The Author(s).)