Fostering Shared Decision-Making Between Patients and Health Care Professionals in Clinical Practice Guidelines: Protocol for a Project to Develop and Test a Tool for Guideline Developers
Bibliographic record
Abstract
BACKGROUND: Clinical practice guidelines (CPGs) are designed to assist health care professionals in medical decision-making, but they often lack effective integration of shared decision-making (SDM) principles to reflect patient values and preferences, particularly in the context of preference-sensitive CPG recommendations. To address this shortcoming and foster SDM through CPGs, the integration of patient decision aids (PDAs) into CPGs has been proposed as an important strategy. However, methods for systematically identifying and prioritizing CPG recommendations relevant to SDM and related decision support tools are currently lacking. OBJECTIVE: The aim of the project is to develop (1) a tool for systematically identifying and prioritizing CPG recommendations for which SDM is considered particularly relevant and (2) a platform for PDAs to support practical SDM implementation. METHODS: The project consists of 6 work packages (WPs). It is embedded in the German health care context but has an international focus. In WP 1, we will conduct a scoping review in bibliographic databases and gray literature sources to identify methods used to foster SDM via PDAs in the context of CPGs. In WP 2, we will conduct semistructured interviews with CPG experts to better understand the concepts of preference sensitivity and identify strategies for fostering SDM through CPGs. WP 3, a modified Delphi study including surveys and focus groups with SDM experts, aims to define and operationalize preference sensitivity. Based on the results of the Delphi study, we will develop a methodology for prioritizing key questions in CPGs. In WP 4, the tool will be developed. A list of relevant items to identify CPG recommendations for which SDM is most relevant will be created, tested, and iteratively refined, accompanied by the development of a user manual. In WP 5, a platform for creating and digitizing German-language PDAs will be developed to support the practical application of SDM during clinical encounters. WP 6 will conclude the project by testing the tool with newly developed and revised CPGs. RESULTS: The Brandenburg Medical School Ethics Committee approved the project (165122023-ANF). An international multidisciplinary advisory board is involved to guide the tool development on CPGs and SDM. Patient partners are involved throughout the project, considering the essential role of the patient perspective in SDM. As of February 20, 2024, we are currently assessing literature references to determine eligibility for inclusion in the scoping review (WP 1). We expect the project to be completed by December 31, 2026. CONCLUSIONS: The tool will enable CPG developers to systematically incorporate aspects of SDM into CPG development, thereby providing guideline-based support for the patient-practitioner interaction. Together, the tool for CPGs and the platform for PDAs will create a systematic link between CPGs, SDM, and PDAs, which may facilitate SDM in clinical practice. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/57611.
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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 | 0.098 | 0.091 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.003 | 0.004 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.005 | 0.005 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.004 | 0.006 |
| Research integrity | 0.006 | 0.007 |
| Insufficient payload (model declined to judge) | 0.046 | 0.014 |
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".