A Stakeholder-Engaged Process to Design and Implement the Assessment of Cognitive Complaints Toolkit for Alzheimer’s Disease (ACCT-AD) in Primary Care

A Stakeholder-Engaged Process to Design and Implement the Assessment of Cognitive Complaints Toolkit for Alzheimer’s Disease (ACCT-AD) in Primary Care | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article A Stakeholder-Engaged Process to Design and Implement the Assessment of Cognitive Complaints Toolkit for Alzheimer’s Disease (ACCT-AD) in Primary Care Alissa B. Sideman, Cecilia Alagappan, Ignacia Arteaga, Andrew Breithaupt, and 9 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7134103/v1 This work is licensed under a CC BY 4.0 License Status: Under Revision Version 1 posted 15 You are reading this latest preprint version Abstract Background Dementia is underdiagnosed, particularly in primary care settings where most people receive their healthcare. These is a need for tools to assist with the diagnosis of dementia by primary care clinicians, who greatly outnumber specialists. Objective To describe the collaborative design process, implementation, and lessons learned when developing a new cognitive assessment tool for primary care settings. Design and Participants We used an iterative approach to develop, test, and revise the Assessment of Cognitive Complaints Toolkit for Alzheimer’s Disease (ACCT-AD), and used qualitative and survey-based methods to identify lessons learned from its use in four community primary care practices in California Key Results Lessons learned from implementing the ACCT-AD toolkit in community primary care practices include the importance of stakeholder engagement in the process, assessing and adapting workflow, staffing, and approach; the educational value of the toolkit as a systematic tool, user response to the toolkit, and challenges around workflow, integration, and sustainability. Conclusions The design and implementation of the ACCT-AD toolkit explicitly target workforce constraints that will continue to emerge as demand for cognitive assessment increases. Our approach, which enables primary care clinicians to complete a thorough assessment within their practice, supports building on the strong foundation of the doctor-patient relationship in primary care, and can lead to earlier diagnosis and more efficient referrals. dementia diagnosis primary care cognitive assessment Figures Figure 1 Figure 2 Introduction More than seven million people in the United States live with dementia, and the number is expected to triple in the next thirty years. 1 The health care system currently provides insufficient services to patients facing cognitive decline and is not prepared to address the need for timely and accurate diagnosis of dementia. 2–5 Dementia is underdiagnosed, particularly in primary care (PC) settings where most people receive their healthcare. 6–10 Although primary care clinicians (PCCs) are often the first to see patients with suspected dementia, as many as 66% of patients in PC are not diagnosed in the early stages of the disease. 11–14 Many clinicians do not pursue formal assessment of cognitive complaints, postponing plans to evaluate them or to refer them to specialists, in part due to resource and time constraints, low confidence, and limited availability of specialists. 5,13,15–19 The large numbers of patients needing assessment for cognitive complaints can overwhelm specialty practices and referral centers, leading to delays in assessment. 15,20,21 In one study, the average time between initial symptom recognition and diagnosis was 30 months. 7 Furthermore, even when a referral for specialty evaluation has been made, less than half are completed. 15 Diagnostic delays can be reduced if PCCs perform some of the assessment that would be done by specialists. 22 The diagnosis of dementia relies on recognition of specific symptoms. 23 Alzheimer’s disease (AD), the most common cause of dementia, is usually characterized primarily by memory loss. However, atypical presentations of dementia are characterized by a variety of non-memory symptoms, including language problems, psychiatric symptoms, changes in personality, or movement problems. A critical aspect of dementia diagnosis and care planning is to assess for the presence of these non-memory features. Under-identification of these symptoms is a key reason that many patients with non-AD dementias are misdiagnosed as having AD or a psychiatric illness. 2,24 As new treatments targeted at specific etiologies of dementia are approved, this type of error will have increasing significance. 25,26 These considerations underscore the need for tools to assist with the diagnosis of dementia by PCCs. If PCCs diagnose more patients with the most common form of dementia (AD), and detect features that might suggest atypical causes, this would allow more rapid assessment of cognitive complaints and identification of patients who could be eligible for specific treatments, while facilitating recognition of less common types of dementia that require specialty evaluation. The Assessment of Cognitive Complaints Toolkit for Alzheimer’s Disease (ACCT-AD) In 2018, the ten California Alzheimer’s Disease Centers (CADCs) developed the Assessment of Cognitive Complaints Toolkit for AD (ACCT-AD) to guide PCCs on the history, physical examination, and laboratory and imaging studies for diagnostic evaluation. 27,28 ACCT-AD was developed by a committee of dementia care experts and takes a unique approach by specifying wording for questions and prompts, and providing interpretation of typical answers encountered in clinical practice as consistent with normal aging, consistent with AD or suggestive of a non-Alzheimer’s dementia. The toolkit also supports identification of features that may indicate a non-degenerative dementia, including potentially treatable etiologies for cognitive impairment, such as mood disorders and sleep apnea. It provides example scripts to facilitate the PCC’s discussion of difficult topics such as diagnostic disclosure, driving evaluation and potential cessation, behavioral symptoms, and participation in research. It also includes guidance for billing for different aspects of the diagnostic workup and chronic care management. In July of 2019, UCSF received a five-year grant from the California Department of Public Health to support continued development of the toolkit and to pilot its implementation in community PC practice. This project was implemented in collaboration with two other CADCs: the Alzheimer’s and Memory Center at UCSF Fresno, and the USC/Rancho Los Amigos California Alzheimer’s Center in Los Angeles. Our objective in this manuscript is to share our approach and lessons learned in the implementation of this toolkit. Methods Objectives Our work was designed to support the development, implementation, and evaluation of the ACCT-AD toolkit and optimize its useability by PCCs in these three phases (Figure 1). Research was approved by the Human Subjects Institutional Review Board at the University of California, San Francisco. All participants provided informed consent. (1) Phase 1: Toolkit development and refinement Focus Groups and Feedback Sessions We conducted seven focus groups or one-on-one feedback sessions between 2019 and 2022 with PCCs (internal medicine and family medicine, including Medical Doctors (MDs), Nurse Practitioners (NPs), and Doctors of Osteopathy (DOs)) using a focus group guide developed for this study (Supplementary Material 3). Participants included attendings and trainees. Participants received copies of the toolkit ahead of time. The sessions focused on facilitators and barriers to dementia assessment in their practice, and feedback on the toolkit. Participants reported a lack of systematic approach to diagnosing dementia in their clinics and identified time as the major constraint. They found the toolkit valuable as an educational tool but were concerned about the length and format. They suggested the following modifications: the addition of a self-administered questionnaire, a redesign to make it easier to track patient responses, electronic health record (EHR) integration, and guidance identifying and diagnosing patients with Mild Cognitive Impairment (MCI). Toolkit V2.0 In response to this feedback, as well as ongoing input during the accuracy-testing and PCC recruitment phases, we developed ACCT-AD Toolkit V2.0, (Supplemental Material 1 and 2), which includes several modifications: 1) a revised format that improves usability by dividing the toolkit into three components: the instructions, forms that can be used for documentation of findings from an assessment, and a reference manual for use in interpreting findings, 2) additional materials to support diagnosis of Mild Cognitive Impairment; 3) smart phrases that can be used to document the assessment in the EHR, 4) a pre-visit questionnaire that can be implemented over the phone or online with the patient and a knowledgeable informant prior to the visit; this questionnaire uses simple language to collect the same information as the in-person toolkit, and has been translated into Chinese, Vietnamese, and Spanish. The goal of the pre-visit questionnaire is to streamline the clinician’s in-person work by providing responses to questions in advance. However, because of concerns that the sensitivity of the questions might vary across languages and cultures, we cautioned practices that self-reported responses should be reviewed in person by an experienced member of the practice to ensure that the responses were addressing the area of concern targeted by the question. We also added several educational components related to mild cognitive impairment, vascular cognitive impairment, biomarkers for neurodegenerative disease, and genetic testing for neurodegenerative disease (NDD). (2) Phase 2: Initial implementation We used the training infrastructure of the California Alzheimer’s Disease Centers (CADCs) to provide initial feedback on the use of the toolkit in practice. Each of the CADCs has relationships with local healthcare institutions that have clinical training programs. At UCSF, the Memory and Aging Center conducts a four-week rotation that trains UCSF neurology and psychiatry residents, geriatrics fellows, and medical students. The UCSF-affiliated program in Fresno trains family medicine residents, and the CADC at Rancho Los Amigos, which is affiliated with the University of Southern California, trains family medicine residents from the Charles Drew University associated with Martin Luther King Jr. Hospital. Trainees independently collect the history and physical examination and other data, and then present this information to the attending physician, who provides the final diagnostic assessment. For this project, we asked these trainees to use the toolkit for their assessments and to provide feedback about the toolkit. During the project period, 102 trainees used the toolkit. This phase was utilized to make adjustments to the diagnostic guidance and wording of individual questions as needed. (3) Phase 3: Implementation in community practice Champion identification and workflow assessment We began implementing the toolkit as a quality improvement tool at four community practice sites: Olive View Medical Center in the Los Angeles County Health System, the Central California Faculty Medical Group (CCFMG) in Fresno, Martin Luther King Jr. Hospital in Los Angeles, and the On-Lok Program for All-Inclusive Care for the Elderly (PACE), in the San Francisco Bay Area. These sites were identified based on existing relationships with the study PIs and interest from stakeholders in expanding dementia assessment in their settings. Prior to implementation, two investigators conducted multi-day site visits to meet with key stakeholders and assess existing clinic workflow to identify ways to best fit the toolkit within existing practices. The implementation approach at each site varied based on clinic workflow, but each site was required to retain fidelity to the questions and diagnostic pathway recommended in the toolkit. Clinic directors served as the main liaison between the primary care clinic and the study leadership. They devised a strategy to introduce the toolkit to PCCs within their clinic and met regularly with the study leadership to advise on revisions to the toolkit and study procedures. Individual PCCs were invited to participate in this project on a voluntary basis, and were not given any special accommodations, such as changes in their patient load or schedule. The clinics received funding from the grant to support clinic leadership to meet regularly with the other study personnel to review study progress, and to support staff to facilitate entry of data from the clinic evaluations into the study database. Individual PCCs received small gift cards for entering data into the study database and completing a brief survey developed for this study (Supplementary Material 4). Training Each PCC participated in a 1-hour training presentation on the toolkit. PCCs were also given access to the Montreal Cognitive Assessment (MoCA) training certification program. After receiving feedback from community practitioner stakeholders that it would be helpful to have a regular meeting with neurology experts to discuss toolkit implementation, build community with other sites, present cases, and get insights about challenging cases, we implemented monthly all-site meetings where PCCs presented patient cases they assessed using the Toolkit. Sites reported benefitting from hearing implementation approaches from the other sites involved in the study and getting expert input on challenging cases. Monthly meetings, feedback sessions, surveys, and interviews The monthly all-site meetings included feedback from the PCCs, who suggested potential improvements. We also implemented pre/post surveys about PCC practices, attitudes, and challenges doing dementia diagnosis and care and pre/post interviews or focus groups with PCCs enrolled in the study about approaches to dementia diagnosis, facilitators and barriers to dementia diagnosis and care, training and educational needs, and experiences using the toolkit. We are engaged in ongoing analysis of the information gained from Phase 3 to evaluate and iterate upon the toolkit as needed and to identify common challenges that need to be addressed before more widespread implementation is possible. Community practice accuracy testing A small subset of individuals evaluated in PC also had a second opinion assessment at one of the three expert centers involved in the project. We assessed PCC diagnostic accuracy for these patients by comparing PCC’s diagnosis with that of the expert. Results Implementation Outcomes Between July 2019 and July 2024, the toolkit was used in the PC setting by 22 clinicians (Table 1) to make etiological diagnoses for 137 cases. The toolkit was rated by PCCs as being extremely helpful or somewhat helpful in 94% of the cases (Figure 2), and nearly all felt confident in their diagnosis. Patient demographics and language of assessment are summarized in Table 2. Diagnoses were dementia in 29%, MCI in 47%, and no significant cognitive impairment in 23% (Table 3). Features suggesting atypical neurodegeneration in 14 patients are listed in Table 4. Symptoms were thought to be due to non-neurodegenerative conditions in 35% (most with MCI), and the conditions thought to be contributing are listed in Table 5. Lessons Learned The project successfully implemented this toolkit in four busy PC practices over the course of 5 years. We found that implementation was feasible within PC even though it required additional training and organization of time for assessment that was not always easily available in PC. The lessons, summarized below represent key factors that influenced the success of implementation (Table 6). Lesson 1: Stakeholder engagement . Identification of implementation champions and engaging in iterative stakeholder engagement were critical. PCCs were involved throughout the process in giving us feedback. Many of our champions were clinic directors. We found that the clinic director’s interest and cooperation fostered willingness and greater engagement with the new tool among other clinicians in the practice. Lesson 2: Targeted and responsive educational support during implementation. The need to reinforce the recommended diagnostic approach with changes and additional training quickly became apparent when we found during early, informal case reviews that some PCCs had difficulty separating the severity of the impairment from the potential etiology. PCCs would diagnose patients with dementia when the symptoms suggested AD, even if the severity of the impairment was consistent with mild cognitive impairment (MCI). This prompted a revision of the toolkit to create a new section discussing MCI. In addition, we created a monthly case conference to reinforce the principles of interpretation being promoted in the toolkit. Using a standard template, PCCs presented cases they had assessed in their clinics at meetings that included experts and other PC users. These meetings served to check that the toolkit was guiding appropriate decision-making while educating all users. Lesson 3: Working with clinics to identify how to fit the approach to their workflow 3a. Assessing and adapting workflow and staffing. We found that it was important to support clinic-specific strategies for toolkit implementation. At the start of the study, two researchers did site visits to learn about each site’s workflow and meet with the clinic directors. In some settings, clinic staff or social workers were able to collect pre-visit questionnaires, a model that made it easier to support the PCC during the in-person visit. Some clinicians made adjustments to see patients across multiple visits to complete the toolkit, while others engaged clinical staff to assist with aspects of the toolkit. 3b: Adaptation of cognitive testing. Although the toolkit originally focused on the MoCA, sites also identified tests that were already being used in practice. They highlighted their need to assess patients with low education and who did not speak English. We incorporated additional options for cognitive testing into the toolkit instructions and provided guidance on versions of these tests that had been validated in specific languages and in cohorts with low levels of education. We provided education-specific thresholds to assist with diagnostic assessments. Lesson 4: Value of toolkit 4a. Educational value of the toolkit. PCCs identified many aspects of the toolkit that they found valuable. Many felt the toolkit was useful as an educational tool, helping them think more about differential diagnosis, and whether the problem is normal aging. They felt the toolkit helped them to ask better questions and learn how certain questions and answers pertain to dementia. The toolkit was enthusiastically adopted by one of the sites as a training for family medicine residents. 4b. Usefulness of a systematic tool. PCCs also reported that the toolkit created a systematic approach for knowing what to address with patients while also guiding their diagnostic interpretation. They felt it was helpful to have specific questions and a framework that links specific responses to diagnosis, and they appreciated integration of caregivers. 4c. Patient appreciation of in-depth assessment and education. PCCs also noted that patients and families with whom they had used the toolkit felt that their assessment was thorough, and it created peace of mind for the “worried well”. One PCC reported, “It helped me learn to know what kind of questions to ask and to get to know the patient and their families better.” 4d. Support for a team-based approach. PCCs also appreciated the integration of other clinical team members who could support the diagnostic process. In particular, the pre-visit questionnaire could be administered to patients and care partners by other team members ahead of time, freeing valuable time for PCCs and streamlining the visit because they knew which questions to focus on. Lesson 5: Challenges around workflow, integration, and sustainability We also identified several challenges in the implementation of the toolkit, many related to known barriers in primary care related to time and staffing constraints. PCCs identified the learning curve for use of the toolkit, which takes an investment of time upfront until they are comfortable. Furthermore, practitioners found it challenging to follow up with next steps of the diagnostic process, such as disclosure, treatment recommendations (if any), and referrals to specialist settings, if needed, because of time constraints. The toolkit was best used in a team-based approach, where a staff member in the clinic implemented the pre-visit questionnaire ahead of time, but this required identifying a person in the clinic. In one clinic, this was a medical assistant. However, not all clinics have access to sufficient staffing. At another clinic, the pre-visit questionnaire data was delivered by a non-professional, trained coordinator supported by the research grant. The training and educational background for this individual was similar to that of patient care navigators that have been used for multidisciplinary dementia care models. Some PCCs felt it was challenging to set up visits with patients, as sometimes the toolkit took multiple visits to implement. Those who did not have it incorporated into the EHR felt that it was not streamlined and could have been easier to use if it was integrated, which was done at some sites based on user feedback. Discussion and Next Steps We have described our stakeholder-engaged approach to building a toolkit to support community PCCs in evaluating cognitive and behavioral changes that could represent typical, late-onset dementia due to Alzheimer’s disease. Earlier identification of dementia can lead to faster implementation of management, including treatment of reversible conditions, referrals to specialists in whom this is appropriate, identification of supportive services, and critical planning for those who have mild cognitive changes while they still have capacity. Timely diagnosis has also been associated with reduced costs for healthcare services. 2 As targeted treatments that rely on a specific diagnosis become available, earlier and more accurate diagnosis will become increasingly important. 25,26 Our initial experience with the ACCT-AD toolkit indicates that several components are instrumental for implementation in primary care. The first of these is concrete guidance. Clinical guidelines recommend collecting a patient history, laboratory workup, cognitive screening, and imaging, and often include brief descriptions of atypical dementias. Rarely do they provide guidance on how to collect this history from both the patient and an informant and how to interpret cognitive testing. 16,29,30 We found that PCCs appreciated specific guidance on what questions must be asked, how anticipated responses should be interpreted, and how the history should be integrated with other data to guide diagnosis. Stakeholder engagement was another key element for success. Partnerships between dementia experts and PCCs were utilized to test and amend the toolkit in a user-centered way while maintaining the best-practice principles of dementia diagnosis. Engaging stakeholders early and often in building tools that are feasible in their practice settings is important to set the stage for the rollout of treatment and care innovations. 31,32 Such engagement will continue to be needed as the field rapidly evolves to incorporate new biomarkers and treatments. 22,33,34 The design and implementation of the toolkit explicitly target workforce constraints that will continue to emerge as demand for cognitive assessment increases. 22 Our approach, which enables PCCs to complete a thorough assessment within their practice supports more efficient referrals, including identifying patients that may not need a referral to dementia specialists. For example, 40 percent of the cases evaluated in this project were thought to be cognitively normal or were identified as having a non-neurodegenerative disorder that needed to be addressed. For those referred to dementia specialist, the assessment supported by the toolkit ensures that the evaluation up to that point has been complete, making the questions that need to be addressed by the specialist more focused. Use of this toolkit therefore represents a strategy to improve the efficiency of the health system in the evaluation of persons with cognitive changes. Use of this toolkit can be considered as part of a larger strategy to create networks of dementia-proficient community practices through programs such as Project ECHO for dementia, which supports dementia diagnosis and care through case conferences similar to those implemented for this project. 35 A shared diagnostic framework, implemented through a common instrument that PCCs endorse, can provide the foundation for such networks. Common approaches for assessment would improve communication among clinicians and with patients and set the stage for rapidly disseminating new developments that affect diagnosis and care for neurodegenerative diseases. As potential treatments and options for diagnostic testing evolve, this network can serve as a resource for disseminating knowledge. This workforce innovation has the potential to improve health service delivery for people with dementia. Limitations Although the results of this pilot program are encouraging, there are many outstanding questions. Most patients seen in PC for this project were not evaluated by experts, so that the accuracy of PCC diagnoses could not be determined for most of the patients. Accuracy of diagnosis using this tool might vary considerably depending on the experience of the clinician and patient factors. In addition, although the pre-visit questionnaire can potentially improve efficiency of assessment, the sensitivity and specificity of these questions, particularly in diverse clinical settings, has not been established, so that review by a trained staff member is required. These issues will be addressed in a project recently funded by the National Institute on Aging (1R01AG085689-01A1). Declarations Ethics Approval and Consent to Participate This study was approved by the Institutional Review Board at the University of California, San Francisco #17-24024, and research participants provided their consent to participate. This study adhered to the Declaration of Helsinki. Consent for Publication Not applicable. Availability of Data and Materials The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request. Competing Interests There are no conflicts of interest to report. Funding This work was supported by the California Department of Public Health Alzheimer’s Disease Program Grant (#18-10612), the National Institute on Aging (R01AG085689; R01AG087166, and K01AG059840). Authors’ Contributions Alissa Sideman: design, funding acquisition, methodology, data collection, analysis, interpretation, writing (original draft, review, editing); Cecilia Alagappan: design, methodology, data collection, formal analysis, writing (review, editing); Ignacia Arteaga: interpretation, writing (original draft, review, editing); Andrew Breithaupt: analysis, interpretation, writing (original draft, review, editing); Sahar Soleymani: data collection, interpretation, writing (review); Hrishikesh Belani data collection, interpretation, writing (review); Teresa Pham: data collection, interpretation, writing (review); Sunny Pak: data collection, interpretation, writing (review), Teresa Sigala: data collection, interpretation, writing (review); Jason Gravano: methodology, data collection, interpretation, writing (review, editing); Loren Alving: design, funding acquisition, methodology, data collection, formal analysis, writing (review, editing); Freddi Segal-Gidan: design, funding acquisition, methodology, data collection, formal analysis, writing (review, editing); Howie Rosen: design, funding acquisition, methodology, data collection, formal analysis, writing (original draft, review, editing). 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Demographics for 137 Cases Diagnosed in Primary Care Age Education Language of Assessment >65 67% College or more 25% Spanish 56% <65 33% High School 23% English 23% Middle School 13% Cantonese 6% Elementary School 32% Mandarin 2% No Formal Education 7% Other 3% Table 3. Diagnoses for 137 Cases Diagnosed in Primary Care Syndrome N (%) Suspected Cause N (%) Dementia 40 (29%) Typical AD 23 (58%) Atypical Neurodegenerative 14 (35%) Non-Degenerative 8% Not enough symptoms to choose 0 Mild Cognitive Impairment 65 (47%) Typical AD 3 (5%) Atypical Neurodegenerative 0 Non-Degenerative 45 (69%) Not enough symptoms to choose 18 (28%) No Significant Cognitive Impairment 32 (23%) Table 4. Atypical Features in 14 Patients with Atypical Neurodegenerative Syndromes Symptoms Not Typically Seen in Alzheimer’s Disease 21% Early Age of Onset 14% Rapidly Progressive 14% Motor Features 16% Not specified 44% Table 5. Identified Conditions in 48 Patients with Non-Neurodegenerative Syndromes Depression or Other Psychiatric Condition 75% Sleep Apnea 35% Cerebrovascular Changes 17% Hearing or Visual Impairment 16% Laboratory Abnormalities 6% Table 6. Lessons Learned 1. Stakeholder engagement 2. Targeted and responsive educational support during implementation 3. Working with clinics to identify how to fit the approach to their workflow 3a. Assessing and adapting workflow and staffing 3b. Adaptation of cognitive testing. 4. Value of the toolkit 4a. Educational value 4b. Usefulness as a systematic tool 4c. Patient appreciation of in-depth assessment and education 4d. Support for a team-based approach 5. Challenges around workflow, integration, and sustainability Additional Declarations No competing interests reported. Supplementary Files SupplementaryMaterial1ToolkitQuestionnaire.pdf SupplementaryMaterial2ToolkitInterpretationManual.pdf SupplementaryMaterial3FocusGroupGuide.docx SupplementaryMaterial4QualtricsSurvey.pdf Cite Share Download PDF Status: Under Revision Version 1 posted Editorial decision: Revision requested 09 Nov, 2025 Reviews received at journal 04 Nov, 2025 Reviews received at journal 29 Oct, 2025 Reviewers agreed at journal 19 Oct, 2025 Reviewers agreed at journal 17 Oct, 2025 Reviewers agreed at journal 16 Oct, 2025 Reviewers agreed at journal 14 Oct, 2025 Reviews received at journal 21 Sep, 2025 Reviewers agreed at journal 29 Aug, 2025 Reviewers agreed at journal 24 Aug, 2025 Reviewers invited by journal 25 Jul, 2025 Editor assigned by journal 24 Jul, 2025 Editor invited by journal 23 Jul, 2025 Submission checks completed at journal 22 Jul, 2025 First submitted to journal 22 Jul, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7134103","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":491596517,"identity":"313b2cd3-5cba-4dae-b05a-522d1d2b6f2d","order_by":0,"name":"Alissa B. 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09:39:15","extension":"docx","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":15323,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryMaterial3FocusGroupGuide.docx","url":"https://assets-eu.researchsquare.com/files/rs-7134103/v1/4dfac74148c28fa9cc622d35.docx"},{"id":87813315,"identity":"1da3808e-70e8-46ed-b53c-23331c8aa85d","added_by":"auto","created_at":"2025-07-29 09:39:15","extension":"pdf","order_by":4,"title":"","display":"","copyAsset":false,"role":"supplement","size":160218,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryMaterial4QualtricsSurvey.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7134103/v1/e54d601298ae28be56681225.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"\u003cp\u003eA Stakeholder-Engaged Process to Design and Implement the Assessment of Cognitive Complaints Toolkit for Alzheimer’s Disease (ACCT-AD) in Primary Care\u003c/p\u003e","fulltext":[{"header":"Introduction","content":"\u003cp\u003eMore than seven million people in the United States live with dementia, and the number is expected to triple in the next thirty years.\u003csup\u003e1\u003c/sup\u003e The health care system currently provides insufficient services to patients facing cognitive decline and is not prepared to address the need for timely and accurate diagnosis of dementia.\u003csup\u003e2–5\u003c/sup\u003e\u003c/p\u003e\n\u003cp\u003eDementia is underdiagnosed, particularly in primary care (PC) settings where most people receive their healthcare.\u003csup\u003e6–10\u003c/sup\u003e Although primary care clinicians (PCCs) are often the first to see patients with suspected dementia, as many as 66% of patients in PC are not diagnosed in the early stages of the disease.\u003csup\u003e11–14\u003c/sup\u003e Many clinicians do not pursue formal assessment of cognitive complaints, postponing plans to evaluate them or to refer them to specialists, in part due to resource and time constraints, low confidence, and limited availability of specialists.\u003csup\u003e5,13,15–19\u003c/sup\u003e\u003c/p\u003e\n\u003cp\u003eThe large numbers of patients needing assessment for cognitive complaints can overwhelm specialty practices and referral centers, leading to delays in assessment.\u003csup\u003e15,20,21\u003c/sup\u003e In one study, the average time between initial symptom recognition and diagnosis was 30 months.\u003csup\u003e7\u003c/sup\u003e Furthermore, even when a referral for specialty evaluation has been made, less than half are completed.\u003csup\u003e15\u003c/sup\u003e Diagnostic delays can be reduced if PCCs perform some of the assessment that would be done by specialists.\u003csup\u003e22\u003c/sup\u003e\u003c/p\u003e\n\u003cp\u003eThe diagnosis of dementia relies on recognition of specific symptoms.\u003csup\u003e23\u003c/sup\u003e Alzheimer’s disease (AD), the most common cause of dementia, is usually characterized primarily by memory loss. However, atypical presentations of dementia are characterized by a variety of non-memory symptoms, including language problems, psychiatric symptoms, changes in personality, or movement problems. A critical aspect of dementia diagnosis and care planning is to assess for the presence of these non-memory features. Under-identification of these symptoms is a key reason that many patients with non-AD dementias are misdiagnosed as having AD or a psychiatric illness.\u003csup\u003e2,24\u003c/sup\u003e As new treatments targeted at specific etiologies of dementia are approved, this type of error will have increasing significance.\u003csup\u003e25,26\u003c/sup\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThese considerations underscore the need for tools to assist with the diagnosis of dementia by PCCs. If PCCs diagnose more patients with the most common form of dementia (AD), and detect features that might suggest atypical causes, this would allow more rapid assessment of cognitive complaints and identification of patients who could be eligible for specific treatments, while facilitating recognition of less common types of dementia that require specialty evaluation.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eThe Assessment of Cognitive Complaints Toolkit for Alzheimer’s Disease (ACCT-AD)\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIn 2018, the ten California Alzheimer’s Disease Centers (CADCs) developed the Assessment of Cognitive Complaints Toolkit for AD (ACCT-AD) to guide PCCs on the history, physical examination, and laboratory and imaging studies for diagnostic evaluation.\u003csup\u003e27,28\u003c/sup\u003e ACCT-AD was developed by a committee of dementia care experts and takes a unique approach by specifying wording for questions and prompts, and providing interpretation of typical answers encountered in clinical practice as consistent with normal aging, consistent with AD or suggestive of a non-Alzheimer’s dementia. The toolkit also supports identification of features that may indicate a non-degenerative dementia, including potentially treatable etiologies for cognitive impairment, such as mood disorders and sleep apnea. It provides example scripts to facilitate the PCC’s discussion of difficult topics such as diagnostic disclosure, driving evaluation and potential cessation, behavioral symptoms, and participation in research. It also includes guidance for billing for different aspects of the diagnostic workup and chronic care management.\u003c/p\u003e\n\u003cp\u003eIn July of 2019, UCSF received a five-year grant from the California Department of Public Health to support continued development of the toolkit and to pilot its implementation in community PC practice. This project was implemented in collaboration with two other CADCs: the Alzheimer’s and Memory Center at UCSF Fresno, and the USC/Rancho Los Amigos California Alzheimer’s Center in Los Angeles. Our objective in this manuscript is to share our approach and lessons learned in the implementation of this toolkit.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003e\u003cem\u003eObjectives\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eOur work was designed to support the development, implementation, and evaluation of the ACCT-AD toolkit and optimize its useability by PCCs in these three phases (Figure 1). Research was approved by the Human Subjects Institutional Review Board at the University of California, San Francisco. All participants provided informed consent.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e(1) Phase 1: Toolkit development and refinement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eFocus Groups and Feedback Sessions\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eWe conducted seven focus groups or one-on-one feedback sessions between 2019 and 2022 with PCCs (internal medicine and family medicine, including Medical Doctors (MDs), Nurse Practitioners (NPs), and Doctors of Osteopathy (DOs)) using a focus group guide developed for this study (Supplementary Material 3). Participants included attendings and trainees. Participants received copies of the toolkit ahead of time. The sessions focused on facilitators and barriers to dementia assessment in their practice, and feedback on the toolkit. Participants reported a lack of systematic approach to diagnosing dementia in their clinics and identified time as the major constraint. They found the toolkit valuable as an educational tool but were concerned about the length and format. They suggested the following modifications: the addition of a self-administered questionnaire, a redesign to make it easier to track patient responses, electronic health record (EHR) integration, and guidance identifying and diagnosing patients with Mild Cognitive Impairment (MCI).\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eToolkit V2.0\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eIn response to this feedback, as well as ongoing input during the accuracy-testing and PCC recruitment phases, we developed ACCT-AD Toolkit V2.0, (Supplemental Material 1 and 2), which includes several modifications: 1) a revised format that improves usability by dividing the toolkit into three components: the instructions, forms that can be used for documentation of findings from an assessment, and a reference manual for use in interpreting findings, 2) additional materials to support diagnosis of Mild Cognitive Impairment; 3) smart phrases that can be used to document the assessment in the EHR, 4) a pre-visit questionnaire that can be implemented over the phone or online with the patient and a knowledgeable informant prior to the visit; this questionnaire uses simple language to collect the same information as the in-person toolkit, and has been translated into Chinese, Vietnamese, and Spanish. The goal of the pre-visit questionnaire is to streamline the clinician’s in-person work by providing responses to questions in advance. However, because of concerns that the sensitivity of the questions might vary across languages and cultures, we cautioned practices that self-reported responses should be reviewed in person by an experienced member of the practice to ensure that the responses were addressing the area of concern targeted by the question. We also added several educational components related to mild cognitive impairment, vascular cognitive impairment, biomarkers for neurodegenerative disease, and genetic testing for neurodegenerative disease (NDD).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e(2)\u003c/strong\u003e \u003cstrong\u003ePhase 2: Initial implementation\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe used the training infrastructure of the California Alzheimer’s Disease Centers (CADCs) to provide initial feedback on the use of the toolkit in practice. Each of the CADCs has relationships with local healthcare institutions that have clinical training programs. At UCSF, the Memory and Aging Center conducts a four-week rotation that trains UCSF neurology and psychiatry residents, geriatrics fellows, and medical students. The UCSF-affiliated program in Fresno trains family medicine residents, and the CADC at Rancho Los Amigos, which is affiliated with the University of Southern California, trains family medicine residents from the Charles Drew University associated with Martin Luther King Jr. Hospital. Trainees independently collect the history and physical examination and other data, and then present this information to the attending physician, who provides the final diagnostic assessment. For this project, we asked these trainees to use the toolkit for their assessments and to provide feedback about the toolkit. During the project period, 102 trainees used the toolkit. This phase was utilized to make adjustments to the diagnostic guidance and wording of individual questions as needed.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e(3) Phase 3: Implementation in community practice\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eChampion identification and workflow assessment\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eWe began implementing the toolkit as a quality improvement tool at four community practice sites: Olive View Medical Center in the Los Angeles County Health System, the Central California Faculty Medical Group (CCFMG) in Fresno, Martin Luther King Jr. Hospital in Los Angeles, and the On-Lok Program for All-Inclusive Care for the Elderly (PACE), in the San Francisco Bay Area. These sites were identified based on existing relationships with the study PIs and interest from stakeholders in expanding dementia assessment in their settings. Prior to implementation, two investigators conducted multi-day site visits to meet with key stakeholders and assess existing clinic workflow to identify ways to best fit the toolkit within existing practices. The implementation approach at each site varied based on clinic workflow, but each site was required to retain fidelity to the questions and diagnostic pathway recommended in the toolkit. Clinic directors served as the main liaison between the primary care clinic and the study leadership. They devised a strategy to introduce the toolkit to PCCs within their clinic and met regularly with the study leadership to advise on revisions to the toolkit and study procedures. Individual PCCs were invited to participate in this project on a voluntary basis, and were not given any special accommodations, such as changes in their patient load or schedule. The clinics received funding from the grant to support clinic leadership to meet regularly with the other study personnel to review study progress, and to support staff to facilitate entry of data from the clinic evaluations into the study database. Individual PCCs received small gift cards for entering data into the study database and completing a brief survey developed for this study (Supplementary Material 4).\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eTraining\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eEach PCC participated in a 1-hour training presentation on the toolkit. PCCs were also given access to the Montreal Cognitive Assessment (MoCA) training certification program. After receiving feedback from community practitioner stakeholders that it would be helpful to have a regular meeting with neurology experts to discuss toolkit implementation, build community with other sites, present cases, and get insights about challenging cases, we implemented monthly all-site meetings where PCCs presented patient cases they assessed using the Toolkit. Sites reported benefitting from hearing implementation approaches from the other sites involved in the study and getting expert input on challenging cases.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eMonthly meetings, feedback sessions, surveys, and interviews\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThe monthly all-site meetings included feedback from the PCCs, who suggested potential improvements. We also implemented pre/post surveys about PCC practices, attitudes, and challenges doing dementia diagnosis and care and pre/post interviews or focus groups with PCCs enrolled in the study about approaches to dementia diagnosis, facilitators and barriers to dementia diagnosis and care, training and educational needs, and experiences using the toolkit. We are engaged in ongoing analysis of the information gained from Phase 3 to evaluate and iterate upon the toolkit as needed and to identify common challenges that need to be addressed before more widespread implementation is possible.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eCommunity practice accuracy testing\u003c/em\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eA small subset of individuals evaluated in PC also had a second opinion assessment at one of the three expert centers involved in the project. We assessed PCC diagnostic accuracy for these patients by comparing PCC’s diagnosis with that of the expert.\u0026nbsp;\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cstrong\u003eImplementation Outcomes\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eBetween July 2019 and July 2024, the toolkit was used in the PC setting by 22 clinicians (Table 1) to make etiological diagnoses for 137 cases. The toolkit was rated by PCCs as being extremely helpful or somewhat helpful in 94% of the cases (Figure 2), and nearly all felt confident in their diagnosis. Patient demographics and language of assessment are summarized in Table 2. Diagnoses were dementia in 29%, MCI in 47%, and no significant cognitive impairment in 23% (Table 3). Features suggesting atypical neurodegeneration in 14 patients are listed in Table 4. Symptoms were thought to be due to non-neurodegenerative conditions in 35% (most with MCI), and the conditions thought to be contributing are listed in Table 5.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eLessons Learned\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe project successfully implemented this toolkit in four busy PC practices over the course of 5 years. We found that implementation was feasible within PC even though it required additional training and organization of time for assessment that was not always easily available in PC. The lessons, summarized below represent key factors that influenced the success of implementation (Table 6).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eLesson 1:\u003c/strong\u003e \u003cstrong\u003eStakeholder engagement\u003c/strong\u003e. Identification of implementation champions and engaging in iterative stakeholder engagement were critical. PCCs were involved throughout the process in giving us feedback. Many of our champions were clinic directors. We found that the clinic director’s interest and cooperation fostered willingness and greater engagement with the new tool among other clinicians in the practice.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eLesson 2:\u003c/strong\u003e \u003cstrong\u003eTargeted and responsive educational support during implementation.\u0026nbsp;\u003c/strong\u003eThe need to reinforce the recommended diagnostic approach with changes and additional training quickly became apparent when we found during early, informal case reviews that some PCCs had difficulty separating the severity of the impairment from the potential etiology. PCCs would diagnose patients with dementia when the symptoms suggested AD, even if the severity of the impairment was consistent with mild cognitive impairment (MCI). This prompted a revision of the toolkit to create a new section discussing MCI. In addition, we created a monthly case conference to reinforce the principles of interpretation being promoted in the toolkit. Using a standard template, PCCs presented cases they had assessed in their clinics at meetings that included experts and other PC users. These meetings served to check that the toolkit was guiding appropriate decision-making while educating all users.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eLesson 3:\u003c/strong\u003e \u003cstrong\u003eWorking with clinics to identify how to fit the approach to their workflow\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3a.\u003c/strong\u003e \u003cstrong\u003eAssessing and adapting workflow and staffing.\u003c/strong\u003e We found that it was important to support clinic-specific strategies for toolkit implementation. At the start of the study, two researchers did site visits to learn about each site’s workflow and meet with the clinic directors. In some settings, clinic staff or social workers were able to collect pre-visit questionnaires, a model that made it easier to support the PCC during the in-person visit. Some clinicians made adjustments to see patients across multiple visits to complete the toolkit, while others engaged clinical staff to assist with aspects of the toolkit.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3b: Adaptation of cognitive testing.\u003c/strong\u003e Although the toolkit originally focused on the MoCA, sites also identified tests that were already being used in practice. They highlighted their need to assess patients with low education and who did not speak English. We incorporated additional options for cognitive testing into the toolkit instructions and provided guidance on versions of these tests that had been validated in specific languages and in cohorts with low levels of education. We provided education-specific thresholds to assist with diagnostic assessments.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eLesson 4:\u003c/strong\u003e \u003cstrong\u003eValue of toolkit\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e4a. Educational value of the toolkit.\u0026nbsp;\u003c/strong\u003ePCCs identified many aspects of the toolkit that they found valuable. Many felt the toolkit was useful as an educational tool, helping them think more about differential diagnosis, and whether the problem is normal aging. They felt the toolkit helped them to ask better questions and learn how certain questions and answers pertain to dementia. The toolkit was enthusiastically adopted by one of the sites as a training for family medicine residents.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e4b. Usefulness of a systematic tool.\u0026nbsp;\u003c/strong\u003ePCCs also reported that the toolkit created a systematic approach for knowing what to address with patients while also guiding their diagnostic interpretation. They felt it was helpful to have specific questions and a framework that links specific responses to diagnosis, and they appreciated integration of caregivers.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e4c. Patient appreciation of in-depth assessment and education.\u0026nbsp;\u003c/strong\u003ePCCs also noted that patients and families with whom they had used the toolkit felt that their assessment was thorough, and it created peace of mind for the “worried well”. One PCC reported, “It helped me learn to know what kind of questions to ask and to get to know the patient and their families better.”\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e4d. Support for a team-based approach.\u0026nbsp;\u003c/strong\u003ePCCs also appreciated the integration of other clinical team members who could support the diagnostic process. In particular, the pre-visit questionnaire could be administered to patients and care partners by other team members ahead of time, freeing valuable time for PCCs and streamlining the visit because they knew which questions to focus on.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eLesson 5: Challenges around workflow, integration, and sustainability\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe also identified several challenges in the implementation of the toolkit, many related to known barriers in primary care related to time and staffing constraints. PCCs identified the learning curve for use of the toolkit, which takes an investment of time upfront until they are comfortable. Furthermore, practitioners found it challenging to follow up with next steps of the diagnostic process, such as disclosure, treatment recommendations (if any), and referrals to specialist settings, if needed, because of time constraints. The toolkit was best used in a team-based approach, where a staff member in the clinic implemented the pre-visit questionnaire ahead of time, but this required identifying a person in the clinic. In one clinic, this was a medical assistant. However, not all clinics have access to sufficient staffing. At another clinic, the pre-visit questionnaire data was delivered by a non-professional, trained coordinator supported by the research grant. The training and educational background for this individual was similar to that of patient care navigators that have been used for multidisciplinary dementia care models. Some PCCs felt it was challenging to set up visits with patients, as sometimes the toolkit took multiple visits to implement. Those who did not have it incorporated into the EHR felt that it was not streamlined and could have been easier to use if it was integrated, which was done at some sites based on user feedback. \u0026nbsp;\u0026nbsp;\u003c/p\u003e"},{"header":"Discussion and Next Steps ","content":"\u003cp\u003eWe have described our stakeholder-engaged approach to building a toolkit to support community PCCs in evaluating cognitive and behavioral changes that could represent typical, late-onset dementia due to Alzheimer\u0026rsquo;s disease. Earlier identification of dementia can lead to faster implementation of management, including treatment of reversible conditions, referrals to specialists in whom this is appropriate, identification of supportive services, and critical planning for those who have mild cognitive changes while they still have capacity. Timely diagnosis has also been associated with reduced costs for healthcare services.\u003csup\u003e2\u003c/sup\u003e As targeted treatments that rely on a specific diagnosis become available, earlier and more accurate diagnosis will become increasingly important.\u003csup\u003e25,26\u003c/sup\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eOur initial experience with the ACCT-AD toolkit indicates that several components are instrumental for implementation in primary care. The first of these is concrete guidance. Clinical guidelines recommend collecting a patient history, laboratory workup, cognitive screening, and imaging, and often include brief descriptions of atypical dementias. Rarely do they provide guidance on how to collect this history from both the patient and an informant and how to interpret cognitive testing.\u003csup\u003e16,29,30\u003c/sup\u003e We found that PCCs appreciated specific guidance on what questions must be asked, how anticipated responses should be interpreted, and how the history should be integrated with other data to guide diagnosis. Stakeholder engagement was another key element for success. Partnerships between dementia experts and PCCs were utilized to test and amend the toolkit in a user-centered way while maintaining the best-practice principles of dementia diagnosis. Engaging stakeholders early and often in building tools that are feasible in their practice settings is important to set the stage for the rollout of treatment and care innovations.\u003csup\u003e31,32\u003c/sup\u003e Such engagement will continue to be needed as the field rapidly evolves to incorporate new biomarkers and treatments.\u003csup\u003e22,33,34\u003c/sup\u003e\u003c/p\u003e\n\u003cp\u003eThe design and implementation of the toolkit explicitly target workforce constraints that will continue to emerge as demand for cognitive assessment increases.\u003csup\u003e22\u003c/sup\u003e Our approach, which enables PCCs to complete a thorough assessment within their practice supports more efficient referrals, including identifying patients that may not need a referral to dementia specialists. For example, 40 percent of the cases evaluated in this project were thought to be cognitively normal or were identified as having a non-neurodegenerative disorder that needed to be addressed. For those referred to dementia specialist, the assessment supported by the toolkit ensures that the evaluation up to that point has been complete, making the questions that need to be addressed by the specialist more focused. Use of this toolkit therefore represents a strategy to improve the efficiency of the health system in the evaluation of persons with cognitive changes. \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u003c/p\u003e\n\u003cp\u003eUse of this toolkit can be considered as part of a larger strategy to create networks of dementia-proficient community practices through programs such as Project ECHO for dementia, which supports dementia diagnosis and care through case conferences similar to those implemented for this project.\u003csup\u003e35\u003c/sup\u003e A shared diagnostic framework, implemented through a common instrument that PCCs endorse, can provide the foundation for such networks. Common approaches for assessment would improve communication among clinicians and with patients and set the stage for rapidly disseminating new developments that affect diagnosis and care for neurodegenerative diseases. As potential treatments and options for diagnostic testing evolve, this network can serve as a resource for disseminating knowledge. This workforce innovation has the potential to improve health service delivery for people with dementia.\u003c/p\u003e\n\u003cp\u003eLimitations\u003c/p\u003e\n\u003cp\u003eAlthough the results of this pilot program are encouraging, there are many outstanding questions. Most patients seen in PC for this project were not evaluated by experts, so that the accuracy of PCC diagnoses could not be determined for most of the patients. Accuracy of diagnosis using this tool might vary considerably depending on the experience of the clinician and patient factors. In addition, although the pre-visit questionnaire can potentially improve efficiency of assessment, the sensitivity and specificity of these questions, particularly in diverse clinical settings, has not been established, so that review by a trained staff member is required. These issues will be addressed in a project recently funded by the National Institute on Aging (1R01AG085689-01A1).\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003e\u003cem\u003eEthics Approval and Consent to Participate\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was approved by the Institutional Review Board at the University of California, San Francisco #17-24024, and research participants provided their consent to participate. This study adhered to the Declaration of Helsinki.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eConsent for Publication\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eAvailability of Data and Materials\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eCompeting Interests\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThere are no conflicts of interest to report.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eFunding\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work was supported by the California Department of Public Health Alzheimer’s Disease Program Grant (#18-10612), the National Institute on Aging (R01AG085689; R01AG087166, and K01AG059840).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eAuthors’ Contributions\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAlissa Sideman: design, funding acquisition, methodology, data collection, analysis, interpretation, writing (original draft, review, editing); Cecilia Alagappan: design, methodology, data collection, formal analysis, writing (review, editing);\u0026nbsp;Ignacia Arteaga: interpretation, writing (original draft, review, editing); Andrew Breithaupt: analysis, interpretation, writing (original draft, review, editing); Sahar Soleymani: data collection, interpretation, writing (review); Hrishikesh Belani data collection, interpretation, writing (review); Teresa Pham: data collection, interpretation, writing (review); Sunny Pak: data collection, interpretation, writing (review), Teresa Sigala: data collection, interpretation, writing (review); Jason Gravano: methodology, data collection, interpretation, writing (review, editing); Loren Alving: design, funding acquisition, methodology, data collection, formal analysis, writing (review, editing); Freddi Segal-Gidan: design, funding acquisition, methodology, data collection, formal analysis, writing (review, editing); Howie Rosen: design, funding acquisition, methodology, data collection, formal analysis, writing (original draft, review, editing).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eAcknowledgments\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe thank members of the California Alzheimer’s Disease Centers who contributed to the development of the AIDDPCC Toolkit.\u0026nbsp;\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAlzheimer\u0026rsquo;s Association. 2023 Alzheimer\u0026rsquo;s disease facts and figures. \u003cem\u003eAlzheimers Dement.\u003c/em\u003e \u003cstrong\u003e19\u003c/strong\u003e, 1598\u0026ndash;1695 (2023).\u003c/li\u003e\n\u003cli\u003eHappich, M. \u003cem\u003eet al.\u003c/em\u003e Excess Costs Associated with Possible Misdiagnosis of Alzheimer\u0026rsquo;s Disease Among Patients with Vascular Dementia in a UK CPRD Population. \u003cem\u003eJ. 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Cancer Educ.\u003c/em\u003e \u003cstrong\u003e37\u003c/strong\u003e, 1486\u0026ndash;1495 (2022).\u003c/li\u003e\n\u003cli\u003eHampel, H. \u003cem\u003eet al.\u003c/em\u003e Blood-based biomarkers for Alzheimer\u0026rsquo;s disease: Current state and future use in a transformed global healthcare landscape. \u003cem\u003eNeuron\u003c/em\u003e \u003cstrong\u003e111\u003c/strong\u003e, 2781\u0026ndash;2799 (2023).\u003c/li\u003e\n\u003cli\u003eBoxer, A. L. \u0026amp; Sperling, R. Accelerating Alzheimer\u0026rsquo;s therapeutic development: The past and future of clinical trials. \u003cem\u003eCell\u003c/em\u003e \u003cstrong\u003e186\u003c/strong\u003e, 4757\u0026ndash;4772 (2023).\u003c/li\u003e\n\u003cli\u003eSideman, A. B. \u003cem\u003eet al.\u003c/em\u003e Strengthening Primary Care Workforce Capacity in Dementia Diagnosis and Care: A Qualitative Study of Project Alzheimer\u0026rsquo;s Disease\u0026ndash;ECHO. \u003cem\u003eMed. Care Res. Rev.\u003c/em\u003e 10775587241251868 (2024) doi:10.1177/10775587241251868.\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Tables","content":"\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"3\" valign=\"top\" style=\"width: 100%;\"\u003e\n \u003cp\u003eTable 1. Clinicians Using the Toolkit in \u0026nbsp; \u0026nbsp; Primary Care Practice\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 22.2222%;\"\u003e\n \u003cp\u003eSite\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 37.5%;\"\u003e\n \u003cp\u003eNumber of Clinicians\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 40.2778%;\"\u003e\n \u003cp\u003eNumber of Patients\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 22.2222%;\"\u003e\n \u003cp\u003eOlive View\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 37.5%;\"\u003e\n \u003cp\u003e11 (X MD, X NP)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 40.2778%;\"\u003e\n \u003cp\u003e99\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 22.2222%;\"\u003e\n \u003cp\u003eCCFMG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 37.5%;\"\u003e\n \u003cp\u003e1 MD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 40.2778%;\"\u003e\n \u003cp\u003e26\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 22.2222%;\"\u003e\n \u003cp\u003eOn Lok\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 37.5%;\"\u003e\n \u003cp\u003e10 (X MD, X NP)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 40.2778%;\"\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"6\" valign=\"top\" style=\"width: 100%;\"\u003e\n \u003cp\u003eTable 2. Demographics for 137 Cases Diagnosed in Primary Care\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 19.8413%;\"\u003e\n \u003cp\u003eAge\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 43.254%;\"\u003e\n \u003cp\u003eEducation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 36.9048%;\"\u003e\n \u003cp\u003eLanguage of Assessment\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 10.9127%;\"\u003e\n \u003cp\u003e\u0026gt;65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.92857%;\"\u003e\n \u003cp\u003e67%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 32.5397%;\"\u003e\n \u003cp\u003eCollege or more\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.7143%;\"\u003e\n \u003cp\u003e25%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.2381%;\"\u003e\n \u003cp\u003eSpanish\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.6667%;\"\u003e\n \u003cp\u003e56%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 10.9127%;\"\u003e\n \u003cp\u003e\u0026lt;65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.92857%;\"\u003e\n \u003cp\u003e33%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 32.5397%;\"\u003e\n \u003cp\u003eHigh School\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.7143%;\"\u003e\n \u003cp\u003e23%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.2381%;\"\u003e\n \u003cp\u003eEnglish\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.6667%;\"\u003e\n \u003cp\u003e23%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 10.9127%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.92857%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 32.5397%;\"\u003e\n \u003cp\u003eMiddle School\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.7143%;\"\u003e\n \u003cp\u003e13%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.2381%;\"\u003e\n \u003cp\u003eCantonese\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.6667%;\"\u003e\n \u003cp\u003e6%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 10.9127%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.92857%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 32.5397%;\"\u003e\n \u003cp\u003eElementary School\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.7143%;\"\u003e\n \u003cp\u003e32%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.2381%;\"\u003e\n \u003cp\u003eMandarin\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.6667%;\"\u003e\n \u003cp\u003e2%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 10.9127%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.92857%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 32.5397%;\"\u003e\n \u003cp\u003eNo Formal Education\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.7143%;\"\u003e\n \u003cp\u003e7%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.2381%;\"\u003e\n \u003cp\u003eOther\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.6667%;\"\u003e\n \u003cp\u003e3%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"672\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"4\" valign=\"top\" style=\"width: 100%;\"\u003e\n \u003cp\u003eTable 3. Diagnoses for 137 Cases Diagnosed in Primary Care\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 29.4643%;\"\u003e\n \u003cp\u003eSyndrome\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12.5%;\"\u003e\n \u003cp\u003eN (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 39.2857%;\"\u003e\n \u003cp\u003eSuspected Cause\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.75%;\"\u003e\n \u003cp\u003eN (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"4\" valign=\"top\" style=\"width: 100%;\"\u003e\n \u003cp\u003eDementia\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 29.4643%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12.5%;\"\u003e\n \u003cp\u003e40 (29%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 39.2857%;\"\u003e\n \u003cp\u003eTypical AD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.75%;\"\u003e\n \u003cp\u003e23 (58%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 29.4643%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12.5%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 39.2857%;\"\u003e\n \u003cp\u003eAtypical Neurodegenerative\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.75%;\"\u003e\n \u003cp\u003e14 (35%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 29.4643%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12.5%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 39.2857%;\"\u003e\n \u003cp\u003eNon-Degenerative\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.75%;\"\u003e\n \u003cp\u003e8%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 29.4643%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12.5%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 39.2857%;\"\u003e\n \u003cp\u003eNot enough symptoms to choose\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.75%;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"4\" valign=\"top\" style=\"width: 100%;\"\u003e\n \u003cp\u003eMild Cognitive Impairment\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 29.4643%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12.5%;\"\u003e\n \u003cp\u003e65 (47%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 39.2857%;\"\u003e\n \u003cp\u003eTypical AD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.75%;\"\u003e\n \u003cp\u003e3 (5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 29.4643%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12.5%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 39.2857%;\"\u003e\n \u003cp\u003eAtypical Neurodegenerative\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.75%;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 29.4643%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12.5%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 39.2857%;\"\u003e\n \u003cp\u003eNon-Degenerative\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.75%;\"\u003e\n \u003cp\u003e45 (69%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 29.4643%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12.5%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 39.2857%;\"\u003e\n \u003cp\u003eNot enough symptoms to choose\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.75%;\"\u003e\n \u003cp\u003e18 (28%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"4\" valign=\"top\" style=\"width: 100%;\"\u003e\n \u003cp\u003eNo Significant Cognitive Impairment\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 29.4643%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12.5%;\"\u003e\n \u003cp\u003e32 (23%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 39.2857%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.75%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 100%;\"\u003e\n \u003cp\u003eTable 4. Atypical Features in 14 Patients with Atypical Neurodegenerative Syndromes\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 77%;\"\u003e\n \u003cp\u003eSymptoms Not Typically Seen in Alzheimer\u0026rsquo;s Disease\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23%;\"\u003e\n \u003cp\u003e21%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 77%;\"\u003e\n \u003cp\u003eEarly Age of Onset\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23%;\"\u003e\n \u003cp\u003e14%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 77%;\"\u003e\n \u003cp\u003eRapidly Progressive\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23%;\"\u003e\n \u003cp\u003e14%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 77%;\"\u003e\n \u003cp\u003eMotor Features\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23%;\"\u003e\n \u003cp\u003e16%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 77%;\"\u003e\n \u003cp\u003eNot specified\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23%;\"\u003e\n \u003cp\u003e44%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 100%;\"\u003e\n \u003cp\u003eTable 5. Identified Conditions in 48 Patients with Non-Neurodegenerative Syndromes\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 53%;\"\u003e\n \u003cp\u003eDepression or Other Psychiatric Condition\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47%;\"\u003e\n \u003cp\u003e75%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 53%;\"\u003e\n \u003cp\u003eSleep Apnea\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47%;\"\u003e\n \u003cp\u003e35%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 53%;\"\u003e\n \u003cp\u003eCerebrovascular Changes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47%;\"\u003e\n \u003cp\u003e17%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 53%;\"\u003e\n \u003cp\u003eHearing or Visual Impairment\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47%;\"\u003e\n \u003cp\u003e16%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 53%;\"\u003e\n \u003cp\u003eLaboratory Abnormalities\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47%;\"\u003e\n \u003cp\u003e6%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 100%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTable 6. Lessons Learned\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 100%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e1.\u0026nbsp;\u003c/strong\u003eStakeholder engagement\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 100%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2.\u0026nbsp;\u003c/strong\u003eTargeted and responsive educational support during implementation\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 100%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e3.\u0026nbsp;\u003c/strong\u003eWorking with clinics to identify how to fit the approach to their workflow\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e3a.\u0026nbsp;\u003c/strong\u003eAssessing and adapting workflow and staffing\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e3b.\u0026nbsp;\u003c/strong\u003eAdaptation of cognitive testing.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 100%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e4.\u0026nbsp;\u003c/strong\u003eValue of the toolkit\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e4a.\u0026nbsp;\u003c/strong\u003eEducational value\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e4b.\u0026nbsp;\u003c/strong\u003eUsefulness as a systematic tool\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e4c.\u0026nbsp;\u003c/strong\u003ePatient appreciation of in-depth assessment and education\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e4d.\u0026nbsp;\u003c/strong\u003eSupport for a team-based approach\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 100%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e5.\u0026nbsp;\u003c/strong\u003eChallenges around workflow, integration, and sustainability\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-primary-care","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"famp","sideBox":"Learn more about [BMC Primary Care](https://bmcprimcare.biomedcentral.com/)","snPcode":"","submissionUrl":"https://author-welcome.nature.com/12875","title":"BMC Primary Care","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"dementia, diagnosis, primary care, cognitive assessment","lastPublishedDoi":"10.21203/rs.3.rs-7134103/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7134103/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eDementia is underdiagnosed, particularly in primary care settings where most people receive their healthcare. These is a need for tools to assist with the diagnosis of dementia by primary care clinicians, who greatly outnumber specialists.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eObjective\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTo describe the collaborative design process, implementation, and lessons learned when developing a new cognitive assessment tool for primary care settings.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDesign and Participants\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe used an iterative approach to develop, test, and revise the Assessment of Cognitive Complaints Toolkit for Alzheimer’s Disease (ACCT-AD), and used qualitative and survey-based methods to identify lessons learned from its use in four community primary care practices in California\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eKey Results\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eLessons learned from implementing the ACCT-AD toolkit in community primary care practices include the importance of stakeholder engagement in the process, assessing and adapting workflow, staffing, and approach; the educational value of the toolkit as a systematic tool, user response to the toolkit, and challenges around workflow, integration, and sustainability.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe design and implementation of the ACCT-AD toolkit explicitly target workforce constraints that will continue to emerge as demand for cognitive assessment increases. Our approach, which enables primary care clinicians to complete a thorough assessment within their practice, supports building on the strong foundation of the doctor-patient relationship in primary care, and can lead to earlier diagnosis and more efficient referrals.\u003c/p\u003e","manuscriptTitle":"A Stakeholder-Engaged Process to Design and Implement the Assessment of Cognitive Complaints Toolkit for Alzheimer’s Disease (ACCT-AD) in Primary Care","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-07-29 09:39:08","doi":"10.21203/rs.3.rs-7134103/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-11-09T10:48:41+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-11-05T04:43:43+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-10-29T17:25:36+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"337518876234326118870409240332450106689","date":"2025-10-19T14:27:35+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"62788068305636170679438236607156374435","date":"2025-10-17T17:16:11+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"212074928432367087402797389226109695402","date":"2025-10-16T13:44:12+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"316264259584032482295916911051571609009","date":"2025-10-14T16:11:49+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-09-22T01:25:37+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"330435244855695100638869285512739441615","date":"2025-08-29T11:34:20+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"209977316304014837331209762684050018033","date":"2025-08-24T16:44:49+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-07-25T04:19:10+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-07-24T07:14:44+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-07-23T05:16:37+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-07-22T22:32:29+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Primary Care","date":"2025-07-22T22:29:50+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-primary-care","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"famp","sideBox":"Learn more about [BMC Primary Care](https://bmcprimcare.biomedcentral.com/)","snPcode":"","submissionUrl":"https://author-welcome.nature.com/12875","title":"BMC Primary Care","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"7d654dee-174b-4e27-8e74-e90035492a2e","owner":[],"postedDate":"July 29th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"in-revision","subjectAreas":[],"tags":[],"updatedAt":"2026-05-19T11:23:34+00:00","versionOfRecord":[],"versionCreatedAt":"2025-07-29 09:39:08","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7134103","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7134103","identity":"rs-7134103","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}