Trial Outcomes & Findings for Patient Priorities Care Among Persons Living With Mild Cognitive Impairment and Dementia (NCT NCT06001775)

Recruitment from clinics and data collection between 08/31/2023 - 02/15/2025

Participants enrolled when PPC packet mailed. Care partners were not enrolled.

Patient Priorities Care Among Persons Living With Mild Cognitive Impairment and Dementia

Review of the electronic health record will be used to assess for the presence of documentation of patient priorities care for each enrolled patient. Documentation can occur from enrollment through enrolled patient's visit with the participating physician in clinic. Enrollment (mailing of packet) occurred from two months prior to scheduled appointment with participating physician to clinic appointment. Documentation of discussion could occur from two months prior up to within 24 hours of clinic appointment with participating physician.

Identification of a care partner for 50% of eligible persons living with dementia and mild cognitive impairment. Care partners will be identified based on information provided by the patient, the electronic health record, and the clinical team.

Acceptability will be assessed using Sekhon's Theoretical Framework of Acceptability (TFA) to qualitatively assess acceptability, which includes meeting definitions outlined within the framework, represented by seven component constructs: affective attitude, burden, perceived effectiveness, ethicality, intervention coherence, opportunity costs, and self-efficacy.

Appropriateness will be assessed via qualitative exit interviews with patients, care partners, and clinicians.

Feasibility will be assessed qualitatively using the description provided by Proctor et al as a guide.

Fidelity will be assessed when select charts are reviewed for adherence to the protocol.

Assessment of potential for future adoption of the intervention will be conducted via qualitative exit interviews with patients, care partners, and clinicians.

Review of the electronic health record will be used to assess for hospital visits, emergency room visits, or nursing home admissions. Number of patient days at home will be further evaluated across racial, ethnic, and socioeconomic subgroups to detect any differences.

Review of the electronic health record will be used to assess the medication list total at 2 months pre and post baseline. Number of total medications will be further evaluated across racial, ethnic, and socioeconomic subgroups to detect any differences.

Review of the electronic health record to identify the number of referrals to specialists at 2 months pre and post baseline. Number of new referrals to specialist physicians will be further evaluated across racial, ethnic, and socioeconomic subgroups to detect any differences.

Evaluation will occur using a previously established natural language processing model to identify patient medical records when a Patient Priorities Care discussion is recorded.

Acceptability effects will be further evaluated across racial, ethnic, and socioeconomic subgroups. We will utilize Sekhon et al's Theoretical Framework of Acceptability (TFA) to qualitatively assess acceptability, which includes meeting definitions outlined within the framework, represented by seven component constructs: affective attitude, burden, perceived effectiveness, ethicality, intervention coherence, opportunity costs, and self-efficacy.

Established algorithms for detecting social factors that may influence patient care priorities, such as housing instability, financial insecurity, or transportation concerns will be deployed. These algorithms have been previously created and validated across the care spectrum and will be deployed at the primary site in current form on the established natural language processing platform at Regenstrief Institute. Similar data will be manually extracted using keywords from the primary site for the secondary site. All available clinical notes for the recruited cohort will be annotated by the software as either positive or negative for the social factors. This can then be incorporated into analyses.

Number of eligible patients enrolled across racial, ethnic and socioeconomic subgroups.