Integrating shared decision-making into primary care: lessons learned from a multi-centre feasibility randomized controlled trial
Bibliographic record
Abstract
BACKGROUND: MyDiabetesPlan is a web-based, interactive patient decision aid that facilitates patient-centred, diabetes-specific, goal-setting and shared decision-making (SDM) with interprofessional health care teams. OBJECTIVE: Assess the feasibility of (1) conducting a cluster randomized controlled trial (RCT) and (2) integrating MyDiabetesPlan into interprofessional primary care clinics. METHODS: We conducted a cluster RCT in 10 interprofessional primary care clinics with patients living with diabetes and at least two other comorbidities; half of the clinics were assigned to MyDiabetesPlan and half were assigned to usual care. To assess recruitment, retention, and resource use, we used RCT conduct logs and financial account summaries. To assess intervention fidelity, we used RCT conduct logs and website usage logs. To identify barriers and facilitators to integration of MyDiabetesPlan into clinical care across the IP team, we used audiotapes of clinical encounters in the intervention groups. RESULTS: One thousand five hundred and ninety-seven potentially eligible patients were identified through searches of electronic medical records, of which 1113 patients met the eligibility criteria upon detailed chart review. A total of 425 patients were randomly selected; of these, 213 were able to participate and were allocated (intervention: n = 102; control: n = 111), for a recruitment rate of 50.1%. One hundred and fifty-one patients completed the study, for a retention rate of 70.9%. A total of 5745 personnel-hours and $6104 CAD were attributed to recruitment and retention activities. A total of 179 appointments occurred (out of 204 expected appointments-two per participant over the 12-month study period; 87.7%). Forty (36%), 25 (23%), and 32 (29%) patients completed MyDiabetesPlan at least twice, once, and zero times, respectively. Mean time for completion of MyDiabetesPlan by the clinician and the patient during initial appointments was 37 min. From the clinical encounter transcripts, we identified diverse strategies used by clinicians and patients to integrate MyDiabetesPlan into the appointment, characterized by rapport building and individualization. Barriers to use included clinician-related, patient-related, and technical factors. CONCLUSION: An interprofessional approach to SDM using a decision aid was feasible. Lower than expected numbers of diabetes-specific appointments and use of MyDiabetesPlan were observed. Addressing facilitators and barriers identified in this study will promote more seamless integration into clinical care. Trial registration Clinicaltrials.gov Identifier: NCT02379078. Date of Registration: February 11, 2015. Protocol version: Version 1; February 26, 2015.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.100 | 0.126 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.005 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.005 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".