The goal of this pragmatic, embedded clinical trial is to analyze the implementation of Patient Priorities Care in primary care and geriatrics clinics with patients living with dementia or mild cognitive impairment. This study aims are: * demonstrate the feasibility of using the electronic health record to identify a diverse cohort of eligible patients who will engage in a Patient Priorities Care conversation with a trained facilitator. * demonstrate feasibility of pragmatically assessing clinical outcomes using the electronic health record, including a) number of days at home, b) total medications, and c) new referrals to specialist physicians. * examine key feasibility measures across racial, ethnic, and socioeconomic subgroups. Participants will receive a packet of information about Patient Priorities Care from their primary care clinic, in advance of their next upcoming clinic appointment. Individuals who receive a packet will have the opportunity to engage in a conversation about what matters most to them and what their priorities are, with trained facilitators at the clinic.
Study Type
INTERVENTIONAL
Allocation
NA
Purpose
SUPPORTIVE_CARE
Masking
NONE
Enrollment
178
According to patientprioritiescare.org a Patient Priorities Care conversation helps to align healthcare decision-making and care by all clinicians with patients' own health priorities. Patient Priorities Care involves not only the health outcome goals that patients want to achieve, but also their preferences for healthcare.
Eskenazi Health
Indianapolis, Indiana, United States
Indiana University Health Connected Care
Indianapolis, Indiana, United States
University of Texas Health- Houston
Houston, Texas, United States
Documentation of PPC Discussion
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.
Time frame: From enrollment to participating clinic visit
Identification of a Care Partner
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.
Time frame: Baseline and up to 2 months post baseline
Acceptability
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.
Time frame: Baseline and up to 2 months post baseline
Appropriateness
Appropriateness will be assessed via qualitative exit interviews with patients, care partners, and clinicians.
Time frame: Baseline and up to 2 months post baseline
Feasibility of the Intervention
Feasibility will be assessed qualitatively using the description provided by Proctor et al as a guide.
Time frame: Baseline and up to 2 months post baseline
Fidelity to the Intervention
Fidelity will be assessed when select charts are reviewed for adherence to the protocol.
Time frame: Baseline and up to 2 months post baseline
Potential for Future Adoption of Patient Priorities Care Intervention
Assessment of potential for future adoption of the intervention will be conducted via qualitative exit interviews with patients, care partners, and clinicians.
Time frame: Baseline and up to 2 months post baseline
Number of Patient Days at Home
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.
Time frame: 2 months pre and 2 months post baseline
Number of Total Medications
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.
Time frame: 2 months pre and 2 months post baseline
Number of New Referrals to Specialist Physicians
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.
Time frame: 2 months pre and 2 months post baseline
Number of Patients Across Racial, Ethnic, and Socioeconomic Subgroups With Documentation of Patient Priorities Care Discussion in the Electronic Health Record
Evaluation will occur using a previously established natural language processing model to identify patient medical records when a Patient Priorities Care discussion is recorded.
Time frame: 2 months pre and 2 months post baseline
Acceptability Across Racial, Ethnic, and Socioeconomic Subgroups.
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.
Time frame: Baseline and up to 2 months post baseline
Number of Patients With Social Factors Indicated in the Electronic Health Record
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.
Time frame: Baseline and up to 2 months post baseline
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