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Many older adults manage multiple chronic conditions requiring adherence to multidrug regimens, yet half are non-adherent, increasing their risk of hospitalization for poorly controlled chronic conditions. Few studies have investigated whether caregivers support medication-related behaviors of community-dwelling older adults. We interviewed 97 patient-caregiver dyads participating in a cognitive aging cohort study to identify factors associated with caregiver assistance in managing multidrug regimens. Patients completed a neuropsychological battery covering five cognitive domains. Health literacy and patient activation were measured using the Newest Vital Sign and Consumer Health Activation Index, respectively. Caregivers reported their medication-related involvement. Predictors of involvement in medication-related tasks were examined using logistic regression models. Patients were on average 71 years old, managing 4 comorbidities and prescribed 5 medications. The majority were female (73%) and identified as Black (46%) or White (47%). Caregivers’ mean age was 65 years; half were female (53%), were predominantly spouses (57%) or children (26%), and lived with the patient (61%). 31% of caregivers ordered patients’ prescribed medications, 40% helped manage their medications, and 50% spoke with the patient’s clinician about their clinical care. Cognitive impairment (OR 2.60, 95% CI 1.08-6.25), limited health literacy (OR 2.97, 95% CI 1.26-6.97), and ≥3 comorbidities (OR 2.14, 95% CI 1.06-9.30) were associated with medication management assistance. Patient activation, gender, cohabitation, or relationship were not associated. These findings suggest that caregivers are assisting with older adults’ medication management and should be included in clinical discussions about medication management, especially among patients with cognitive impairment, low health literacy or multimorbidities.

Early detection of Cognitive impairment (CI) is imperative to identify potentially treatable underlying conditions or provide supportive services when due to progressive conditions such as Alzheimer’s Disease. While primary care settings are ideal for identifying CI, it frequently goes undetected. We developed ‘MyCog’, a brief technology-enabled, 2-step assessment to detect CI and dementia in primary care settings. We piloted MyCog in 80 participants 65 and older recruited from an ongoing cognitive aging study. Cases were identified either by a documented diagnosis of dementia or mild cognitive impairment (MCI) or based on a comprehensive cognitive battery. Administered via an iPad, Step 1 consists of a single self-report item indicating concern about memory or other thinking problems and Step 2 includes two cognitive assessments from the NIH Toolbox: Picture Sequence Memory (PSM) and Dimensional Change Card Sorting (DCCS). 39%(31/80) participants were considered cognitively impaired. Those who expressed concern in Step 1 (n=52, 66%) resulted in a 37% false positive and 3% false negative rate. With the addition of the PSM and DCCS assessments in Step 2, the paradigm demonstrated 91% sensitivity, 75% specificity and an area under the ROC curve (AUC)=0.82. Steps 1 and 2 had an average administration time of

As the age of the US population increases, so does cognitive impairment (CI); therefore early detection of CI is critical for ensuring its appropriate management. As part of a NINDS Consortium to detect CI and dementia in primary care (DetectCID), we are implementing and evaluating a brief 2-step CI detection paradigm (MyCog), that can be delivered in clinics with diverse populations via the electronic health record (step 1) and iPad (step 2). We conducted focus groups with 25 clinicians and administrative leaders from academic and community primary care practices to 1) understand how CI is being assessed, and 2) evaluate the feasibility of implementing the MyCog paradigm into existing primary care workflows. Several key themes emerged from the discussions. No proactive detection strategy for CI was regularly used outside of the Medicare Annual Wellness Visits (AWV); variable assessments including the Minicog, MoCA, or MMSE were used to fulfill the AWV requirement. Regarding the feasibility of our MyCog Paradigm, our 2-step process was positively received, with the brief case-finding step 1 satisfying AWV requirements and replacing the longer assessments currently being used. Clinicians preferred that step 2 be self-administered due to limited clinician time for wellness visits, and highlighted logistical challenges such as room availability and storage and maintenance of the iPad. Overall, clinicians felt that the identification of CI was valuable and supported standardization, but indicated regular case finding was unlikely without clear guidance on clinical decision-making.