Protocol for a construct and clinical validation study of MyCog Mobile: a remote smartphone-based cognitive screener for older adults.

INTRODUCTION: Annual cognitive screening in older adults is essential for early detection of cognitive impairment, yet primary care settings face time constraints that present barriers to routine screening. A remote cognitive screener completed on a patient's personal smartphone before a visit has the potential to save primary care clinics time, encourage broader screening practices and increase early detection of cognitive decline. MyCog Mobile is a promising new remote smartphone-based cognitive screening app for primary care settings. We propose a combined construct and clinical validation study of MyCog Mobile. METHODS AND ANALYSIS: We will recruit a total sample of 300 adult participants aged 65 years and older. A subsample of 200 healthy adult participants and a subsample of 100 adults with a cognitive impairment diagnosis (ie, dementia, mild cognitive impairment, cognitive deficits or other memory loss) will be recruited from the general population and specialty memory care centres, respectively. To evaluate the construct validity of MyCog Mobile, the healthy control sample will self-administer MyCog Mobile on study-provided smartphones and be administered a battery of gold-standard neuropsychological assessments. We will compare correlations between performance on MyCog Mobile and measures of similar and dissimilar constructs to evaluate convergent and discriminant validity. To assess clinical validity, participants in the clinical sample will self-administer MyCog Mobile on a smartphone and be administered a Mini-Cog screener and these data will be combined with the healthy control sample. We will then apply several supervised model types to determine the best predictors of cognitive impairment within the sample. Area under the receiver operating characteristic curve, accuracy, sensitivity and specificity will be the primary performance metrics for clinical validity. ETHICS AND DISSEMINATION: The Institutional Review Board at Northwestern University (STU00214921) approved this study protocol. Results will be published in peer-reviewed journals and summaries provided to the study's funders.

Primary care detection of cognitive impairment leveraging health and consumer technologies in underserved US communities: protocol for a pragmatic randomised controlled trial of the MyCog paradigm.

INTRODUCTION: Early identification of cognitive impairment (CI), including Alzheimer's disease and related dementias (ADRD), is a top public health priority. Yet, CI/ADRD is often undetected and underdiagnosed within primary care settings, and in health disparate populations. The MyCog paradigm is an iPad-based, self-administered, validated cognitive assessment based on the National Institutes of Health (NIH) Toolbox Cognition Battery and coupled with clinician decision-support tools that is specifically tailored for CI/ADRD detection within diverse, primary care settings. METHODS AND ANALYSIS: We will conduct a two-arm, primary care practice-randomised (N=24 practices; 45 257 active patients at the proposed practices), pragmatic trial among geographically diverse Oak Street Health sites to test the effectiveness of the MyCog paradigm to improve early detection CI/ADRD among low socioeconomic, black and Hispanic older adults compared with usual care. Participating practices randomised to the intervention arm will impart the MyCog paradigm as a new standard of care over a 3-year implementation period; as the cognitive component for Annual Wellness Visits and for any patient/informant-reported or healthcare provider-suspected cognitive concern. Rates of detected (cognitive test suggesting impairment) and/or diagnosed (relevant International Classification of Diseases-9/10 [ICD-9/10] code) cognitive deficits, impairments or dementias including ADRD will be our primary outcome of study compared between arms. Secondary outcomes will include ADRD severity (ie, mild or later stage), rates of cognitive-related referrals and rates of family member or caregiver involvement in ADRD care planning. We will use generalised linear mixed models to account for clustered study design. Secondary models will adjust for subject, clinic or visit-specific characteristics. We will use mixed-methods approaches to examine fidelity and cost-effectiveness of the MyCog paradigm. ETHICS AND DISSEMINATION: The Institutional Review Board at Advarra has approved the study protocol (Pro00064339). Results will be published in peer-reviewed journals and summaries will be provided to the funders of the study. TRIAL REGISTRATION NUMBER: NCT05607732.

AO Patient Outcomes Center: Design, Implementation, and Evaluation of a Software Application for the Collection of Patient-Reported Outcome Measures in Orthopedic Outpatient Clinics.

BACKGROUND: Patient-reported outcomes are increasingly utilized in routine orthopedic clinical care. Computer adaptive tests (CATs) from the Patient-Reported Outcomes Measurement Information System (PROMIS) offer a brief and precise assessment that is well suited for collection within busy clinical environments. However, software apps that support the administration and scoring of CATs, provide immediate access to patient-reported outcome (PRO) scores, and minimize clinician burden are not widely available. OBJECTIVE: Our objective was to design, implement, and test the feasibility and usability of a Web-based system for collecting CATs in orthopedic clinics. METHODS: AO Patient Outcomes Center (AOPOC) was subjected to 2 rounds of testing. Alpha testing was conducted in 3 orthopedic clinics to evaluate ease of use and feasibility of integration in clinics. Patients completed an assessment of PROMIS CATs and a usability survey. Clinicians participated in a brief semistructured interview. Beta-phase testing evaluated system performance through load testing and usability of the updated version of AOPOC. In both rounds of testing, user satisfaction, bugs, change requests, and performance of PROMIS CATs were captured. RESULTS: Patient feedback supported the ease of use in completing an assessment in AOPOC. Across both phases of testing, clinicians rated AOPOC as easy to use but noted difficulties in integrating a Web-based software application within their clinics. PROMIS CATs performed well; the default assessment of 2 CATs was completed quickly (mean 9.5 items) with a satisfactory range of measurement. CONCLUSION: AOPOC was demonstrated to be an easy-to-learn and easy-to-use software application for patients and clinicians that can be integrated into orthopedic clinical care. The workflow disruption in integrating any type of PRO collection must be addressed if patients' voices are to be better integrated in clinical care.