[A survey study towards the opinions of clinicians, patients and care partners regarding computer tools in the memory clinic: sense or nonsense?] / Een vragenlijstonderzoek naar de mening van clinici, patiënten en naasten over computertools in de geheugenpolikliniek: zin of onzin?.

INTRODUCTION: Computer tools based on artificial intelligence could aid clinicians in memory clinics by supporting diagnostic decision-making and communicating diagnosis and prognosis. We aimed to identify preferences of end-users, and barriers and facilitators for using computer tools in memory clinics. METHODS: Between July and October 2020, we invited European clinicians (n=109, age 45±10y; 47% female) to participate in an online questionnaire. A second questionnaire was sent to patients (n=50, age 73±8y, 34% female) with subjective cognitive complaints (SCD, n=21), mild cognitive impairment (MCI, n=16) and dementia (n=13) and care partners (n=46, 65±12y, 54% female). RESULTS: The vast majority (75%) of all participants positively valued the use of computer tools in memory clinics. Facilitating factors included user-friendliness and increased diagnostic accuracy. Barriers included (doubts relating) reliability and validity of the tool and loss of clinical autonomy. The participants believe that tools should be used in addition to the current working method and not as a replacement. DISCUSSION: Our results provide an important step in the iterative process of developing computer tools for memory clinics in co-creation with end-users and could guide successful implementation.

Computerized decision support is an effective approach to select memory clinic patients for amyloid-PET.

BACKGROUND: The use of amyloid-PET in dementia workup is upcoming. At the same time, amyloid-PET is costly and limitedly available. While the appropriate use criteria (AUC) aim for optimal use of amyloid-PET, their limited sensitivity hinders the translation to clinical practice. Therefore, there is a need for tools that guide selection of patients for whom amyloid-PET has the most clinical utility. We aimed to develop a computerized decision support approach to select patients for amyloid-PET. METHODS: We included 286 subjects (135 controls, 108 Alzheimer's disease dementia, 33 frontotemporal lobe dementia, and 10 vascular dementia) from the Amsterdam Dementia Cohort, with available neuropsychology, APOE, MRI and [18F]florbetaben amyloid-PET. In our computerized decision support approach, using supervised machine learning based on the DSI classifier, we first classified the subjects using only neuropsychology, APOE, and quantified MRI. Then, for subjects with uncertain classification (probability of correct class (PCC) < 0.75) we enriched classification by adding (hypothetical) amyloid positive (AD-like) and negative (normal) PET visual read results and assessed whether the diagnosis became more certain in at least one scenario (PPC≥0.75). If this was the case, the actual visual read result was used in the final classification. We compared the proportion of PET scans and patients diagnosed with sufficient certainty in the computerized approach with three scenarios: 1) without amyloid-PET, 2) amyloid-PET according to the AUC, and 3) amyloid-PET for all patients. RESULTS: The computerized approach advised PET in n = 60(21%) patients, leading to a diagnosis with sufficient certainty in n = 188(66%) patients. This approach was more efficient than the other three scenarios: 1) without amyloid-PET, diagnostic classification was obtained in n = 155(54%), 2) applying the AUC resulted in amyloid-PET in n = 113(40%) and diagnostic classification in n = 156(55%), and 3) performing amyloid-PET in all resulted in diagnostic classification in n = 154(54%). CONCLUSION: Our computerized data-driven approach selected 21% of memory clinic patients for amyloid-PET, without compromising diagnostic performance. Our work contributes to a cost-effective implementation and could support clinicians in making a balanced decision in ordering additional amyloid PET during the dementia workup.

Use of a digital tool to support the diagnostic process in memory clinics-a usability study.

BACKGROUND: Both memory clinic professionals and patients see value in digital tools, yet these hardly find their way to clinical practice. We explored the usability of a digital tool to support the diagnostic work-up in daily memory clinic practice. We evaluated four modules that integrate multi-modal patient data (1.cognitive test; cCOG, and 2. MRI quantification; cMRI) into useful diagnostic information for clinicians (3. cDSI) and understandable and personalized information for patients (4. patient report). METHODS: We conducted a mixed-methods study in five Dutch memory clinics. Fourteen clinicians (11 geriatric specialists/residents, two neurologists, one nurse practitioner) were invited to integrate the tool into routine care with 43 new memory clinic patients. We evaluated usability and user experiences through quantitative data from questionnaires (patients, care partners, clinicians), enriched with thematically analyzed qualitative data from interviews (clinicians). RESULTS: We observed wide variation in tool use among clinicians. Our core findings were that clinicians: 1) were mainly positive about the patient report, since it contributes to patient-centered and personalized communication. This was endorsed by patients and care partners, who indicated that the patient report was useful and understandable and helped them to better understand their diagnosis, 2) considered the tool acceptable in addition to their own clinical competence, 3) indicated that the usefulness of the tool depended on the patient population and purpose of the diagnostic process, 4) addressed facilitators (ease of use, practice makes perfect) and barriers (high workload, lack of experience, data unavailability). CONCLUSION: This multicenter usability study revealed a willingness to adopt a digital tool to support the diagnostic process in memory clinics. Clinicians, patients, and care partners appreciated the personalized diagnostic report. More attention to education and training of clinicians is needed to utilize the full functionality of the tool and foster implementation in actual daily practice. These findings provide an important step towards a lasting adoption of digital tools in memory clinic practice.

Communication about diagnosis, prognosis, and prevention in the memory clinic: perspectives of European memory clinic professionals.

BACKGROUND: The paradigm shift towards earlier Alzheimer's disease (AD) stages and personalized medicine creates new challenges for clinician-patient communication. We conducted a survey among European memory clinic professionals to identify opinions on communication about (etiological) diagnosis, prognosis, and prevention, and inventory needs for augmenting communication skills. METHODS: Memory clinic professionals (N = 160) from 21 European countries completed our online survey (59% female, 14 ± 10 years' experience, 73% working in an academic hospital). We inventoried (1) opinions on communication about (etiological) diagnosis, prognosis, and prevention using 11 statements; (2) current communication practices in response to five hypothetical cases (AD dementia, mild cognitive impairment (MCI), subjective cognitive decline (SCD), with ( +) or without ( -) abnormal AD biomarkers); and (3) needs for communication support regarding ten listed communication skills. RESULTS: The majority of professionals agreed that communication on diagnosis, prognosis, and prevention should be personalized to the individual patient. In response to the hypothetical patient cases, disease stage influenced the inclination to communicate an etiological AD diagnosis: 97% would explicitly mention the presence of AD to the patient with AD dementia, 68% would do so in MCI + , and 29% in SCD + . Furthermore, 58% would explicitly rule out AD in case of MCI - when talking to patients, and 69% in case of SCD - . Almost all professionals (79-99%) indicated discussing prognosis and prevention with all patients, of which a substantial part (48-86%) would personalize their communication to patients' diagnostic test results (39-68%) or patients' anamnestic information (33-82%). The majority of clinicians (79%) would like to use online tools, training, or both to support them in communicating with patients. Topics for which professionals desired support most were: stimulating patients' understanding of information, and communicating uncertainty, dementia risk, remotely/online, and with patients not (fluently) speaking the language of the country of residence. CONCLUSIONS: In a survey of European memory clinic professionals, we found a strong positive attitude towards communication with patients about (etiological) diagnosis, prognosis, and prevention, and personalization of communication to characteristics and needs of individual patients. In addition, professionals expressed a need for supporting tools and skills training to further improve their communication with patients.

Young-onset dementia in memory clinics in the Netherlands: Study design and description of PRECODE-GP.

The disease trajectory and healthcare requirements of patients with young-onset dementia (YOD) differ from those of older patients. Accurate data about YOD is crucial to improve diagnosis and optimize care. PRECODE-GP aims to set up a prospective national database of patients with YOD to gain insight into the occurrence and characteristics of patients with YOD in memory clinics in the Netherlands. The national database includes data from dementia patients aged <70 years at diagnosis, collected by local memory clinics (MCs). Data included demographic information, clinical variables, and (etiological) diagnoses. Between July 2019 and December 2022, 781 patients with a mean age of 62±6y at diagnosis (range 37 to 69y) were included from 39 MCs. Most (n = 547,70%) were diagnosed with dementia due to Alzheimer's disease (AD). Patients with Frontotemporal lobe dementia (FTD, n = 87, 11%) were youngest (61±6.0y). Over half (55%) of patients were experiencing symptoms for ≥2 years. We initiated a Dutch national YOD database to improve diagnosis and care for this underrepresented and vulnerable patient group. The database provides a basis for future in-depth studies on YOD.

Optimizing cCOG, a Web-based tool, to detect dementia with Lewy Bodies.

Introduction: Distinguishing dementia with Lewy bodies (DLB) from Alzheimer's disease (AD) is challenging due to overlapping presentations. We adapted a Web-based test tool, cCOG, by adding a visuospatial task and a brief clinical survey and assessed its ability to differentiate between DLB and AD. Methods: We included 110 patients (n = 30 DLB, n = 32 AD dementia, and n = 48 controls with subjective cognitive decline (SCD)). Full cCOG comprises six cognitive subtasks and a survey addressing self-reported DLB core and autonomic features. First, we compared cCOG cognitive tasks to traditional neuropsychological tasks for all diagnostic groups and clinical questions to validated assessments of clinical features in DLB only. Then, we studied the performance of cCOG cognitive tasks and clinical questions, separately and combined, in differentiating diagnostic groups. Results: cCOG cognitive tasks and clinical survey had moderate to strong correlations to standard neuropsychological testing (.61≤ r s ≤ .77) and to validated assessments of clinical features (.41≤ r s ≤ .65), except for fluctuations and REM-sleep behavior disorder (RBD) (r s = .32 and r s = .10). Full cCOG, including both cognitive tasks and brief survey had a diagnostic accuracy (acc) of 0.82 [95% CI 0.73-0.89], with good discrimination of DLB versus AD (acc 0.87 [0.76-0.95]) and DLB versus controls (acc 0.94 [0.86-0.98]). Conclusion: We illustrated that cCOG aids in distinguishing DLB and AD patients by using remote assessment of cognition and clinical features. Our findings pave the way to a funneled, harmonized diagnostic process among memory clinics and, eventually, a more timely and accurate diagnosis of DLB and AD.

Development and design of a diagnostic report to support communication in dementia: Co-creation with patients and care partners.

Introduction: Clear communication of diagnostic test results and dementia diagnosis is challenging yet important to empower patients and care partners. A personalized diagnostic report could support the communication of dementia diagnostics and aid patients' understanding of diagnosis. In this study, we aimed to design a diagnostic report in co-creation with patients and care partners. Methods: We used a mixed-methods approach, combining surveys with focus groups in iteration. Phase 1 consisted of an international survey assessing needs among patients (n = 50) and care partners (n = 46), and phase 2 consisted of focus group meetings (n = 3) to co-create the content and to hands-on co-design the layout of the diagnostic report with patients (n = 7) and care partners (n = 7). Phase 3 validated results from phase 2 in a survey among patients (n = 28) and care partners (n = 12), and phase 4 comprised final feedback by dementia (care) experts (n = 5). Descriptive statistics were used to report quantitative results and directed content analysis was used to analyze qualitative data. Results: Most patients (39/50, 78%) and care partners (38/46, 83%) positively valued a diagnostic report to summarize test results. The report should be brief, straightforward, and comprise results of the diagnostic tests, including brain imaging and information on future expectations. Despite a clear preference for visual display of test results, several visualization options were deemed best and were equally comprehended. Discussion: In this study, we developed a prototype of a personalized patient report through an iterative design process and learned that co-creation is highly valuable to meet the specific needs of end-users.

Assessing the Views of Professionals, Patients, and Care Partners Concerning the Use of Computer Tools in Memory Clinics: International Survey Study.

BACKGROUND: Computer tools based on artificial intelligence could aid clinicians in memory clinics in several ways, such as by supporting diagnostic decision-making, web-based cognitive testing, and the communication of diagnosis and prognosis. OBJECTIVE: This study aims to identify the preferences as well as the main barriers and facilitators related to using computer tools in memory clinics for all end users, that is, clinicians, patients, and care partners. METHODS: Between July and October 2020, we sent out invitations to a web-based survey to clinicians using the European Alzheimer's Disease Centers network and the Dutch Memory Clinic network, and 109 clinicians participated (mean age 45 years, SD 10; 53/109, 48.6% female). A second survey was created for patients and care partners. They were invited via Alzheimer Europe, Alzheimer's Society United Kingdom, Amsterdam Dementia Cohort, and Amsterdam Aging Cohort. A total of 50 patients with subjective cognitive decline, mild cognitive impairment, or dementia (mean age 73 years, SD 8; 17/34, 34% female) and 46 care partners (mean age 65 years, SD 12; 25/54, 54% female) participated in this survey. RESULTS: Most clinicians reported a willingness to use diagnostic (88/109, 80.7%) and prognostic (83/109, 76.1%) computer tools. User-friendliness (71/109, 65.1%); Likert scale mean 4.5, SD 0.7), and increasing diagnostic accuracy (76/109, 69.7%; mean 4.3, SD 0.7) were reported as the main factors stimulating the adoption of a tool. Tools should also save time and provide clear information on reliability and validity. Inadequate integration with electronic patient records (46/109, 42.2%; mean 3.8, SD 1.0) and fear of losing important clinical information (48/109, 44%; mean 3.7, SD 1.2) were most frequently indicated as barriers. Patients and care partners were equally positive about the use of computer tools by clinicians, both for diagnosis (69/96, 72%) and prognosis (73/96, 76%). In addition, most of them thought favorably regarding the possibility of using the tools themselves. CONCLUSIONS: This study showed that computer tools in memory clinics are positively valued by most end users. For further development and implementation, it is essential to overcome the technical and practical barriers of a tool while paying utmost attention to its reliability and validity.