TY - JOUR
T1 - Assessing the views of professionals, patients, and care partners concerning the use of computer tools in memory clinics
T2 - International survey study
AU - van Gils, Aniek M.
AU - Visser, Leonie N.C.
AU - Hendriksen, Heleen M.A.
AU - Georges, Jean
AU - Muller, Majon
AU - Bouwman, Femke H.
AU - van der Flier, Wiesje M.
AU - Rhodius-Meester, Hanneke F.M.
N1 - Funding Information: Research of the Alzheimer’s Center Amsterdam is part of the neurodegeneration research program of Amsterdam Neuroscience. The Vrije Universiteit Medical Center Alzheimer Center is supported by the Stichting Alzheimer Nederland and Stichting Vrije Universiteit Medical Center Fonds. The clinical database structure was developed with funding from the Stichting Dioraphte. The collaboration project Dementia diagnostics using Artificial Intelligence (light weighted computer tool for local memory clinics; project number LSHM19123-HSGF) is cofunded by the public–private partnership allowance made available by Health-Holland, Top Sector Life Sciences and Health, to stimulate public–private partnerships. The chair of WMVDF is supported by the Pasman Stichting. WMVDF and LNCV are recipients of ABOARD (A personalized medicine approach for Alzheimer disease), which is a public–private partnership receiving funding from ZonMW (number 73305095007) and Health-Holland, Top Sector Life Sciences and Health (public–private partnership allowance; number LSHM20106). LNCV is supported by a fellowship grant received from Alzheimer Nederland (WE.15-2019-05). WF, LNV and JG are recipients of the EU Joint Programme - Neurodegenerative Disease Research (JPND) project EURO-FINGERS (ZonMW-Memorabel #733051102) which is supported through the following funding organizations under the aegis of Joint Programme-Neurodegenerative Disease: Finland, Academy of Finland; Germany, Federal Ministry of Education and Research; Spain, National Institute of Health Carlos III; Luxemburg, National Research Fund; Hungary, National Research, Development and Innovation Office; The Netherlands, Netherlands Organisation for Health Research and Development; Sweden, Swedish Research Council (grant agreement INTER/JPND/19/BM/14012609). These funding sources were not involved in the study design, collection, analysis, and interpretation of data; in the writing of the report; and in the decision to submit the paper for publication. Funding Information: HFMRM performs contract research for Combinostics; all funding is paid to her institution. WMVDF performs contract research for Biogen. Research programs of WMVDF have been funded by ZorgOnderzoek Nederland, area of Medical Sciences, Dutch Research Council, European Union Framework Programmes, Alzheimer Nederland, Cardiovascular Onderzoek Nederland, Gieskes-Strijbis fonds, Pasman Stichting, Boehringer Ingelheim, Piramal Neuroimaging, Combinostics, Roche BV, AVID. She has been an invited speaker at Boehringer Ingelheim and Biogen. All funding is paid to her institution. FHB performs contract research for Optina Dx and Optos, she has been an invited speaker at Roche and has been invited for expert testimony at Biogen. All funding is paid to her institution. All other coauthors report no conflicts of interest. Publisher Copyright: ©Aniek M van Gils, Leonie NC Visser, Heleen MA Hendriksen, Jean Georges, Majon Muller, Femke H Bouwman, Wiesje M van der Flier, Hanneke FM Rhodius-Meester.
PY - 2021/12/3
Y1 - 2021/12/3
N2 - 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.
AB - 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.
KW - Artificial intelligence
KW - Clinical decision support systems
KW - Communication
KW - Dementia
KW - Diagnosis
KW - Diagnostic testing
KW - Prognosis
UR - http://www.scopus.com/inward/record.url?scp=85120962266&partnerID=8YFLogxK
U2 - https://doi.org/10.2196/31053
DO - https://doi.org/10.2196/31053
M3 - Article
C2 - 34870612
SN - 2561-326X
VL - 5
JO - JMIR formative research
JF - JMIR formative research
IS - 12
M1 - e31053
ER -