Developing a Two-Sided Intervention To Facilitate Shared Decision Making In Haemophilia: Decision Boxes For Clinicians and Brief Patient Decision Aids For Patients
Bibliographic record
Abstract
Abstract Introduction/Background Persons with congenital haemophilia A and B face many complex treatment decisions. Much of the evidence to inform treatment decisions in haemophilia comes from observational, often uncontrolled studies, through which one can establish the efficacy of alternative treatment options, but cannot easily make comparisons to identify optimal treatment strategies. In the absence of evidence-based, 'best' treatment options, patient preferences play an even larger role in decisions regarding therapy. Shared decision making (SDM) is a process where patients and health care providers collaboratively make healthcare related decisions based on (1) the best available evidence, and (2) patient preferences regarding treatment options. In other areas, SDM has been shown to increase the use of treatment options most clearly associated with health benefits, and is associated with increased quality of life and patient satisfaction. Decision aids are interventions that facilitate SDM. The goal of our project was to develop novel, two-sided decision aids, Decision Boxes for physicians and Patient Decision Aids for patients- collectively referred to as decision tools, to facilitate SDM in three complex treatment decisions in haemophilia. Methods Development of the decision tools comprised four phases. Phase one was topic selection through a Delphi process, which was conducted with haemophilia treaters from the Association of Hemophilia Clinic Directors of Canada and patient representatives from the Canadian Hemophilia Society- who are the targeted end-users. Phase two was information identification, by first completing a systematic review for each topic area, then identifying pertinent studies and extracting data. Phase three was prototype creation, by organizing relevant information into a standardized, coherent structure. The decision tool structure was adapted from previously validated framework. Each prototype included: (1) a description of intervention and target population, (2) a statement of the decision to be considered, (3) the benefits and harms of each treatment option, and (4) an appraisal of the evidence. Each decision tool pair comprised the same information, which was presented in a manner appropriate to the target audience. The final phase was iterative testing of the decision tool prototypes with patients, through focus groups, and physicians, through interviews. Results The three topics chosen from eleven proposed topics in the Delphi process were: (1) timing and dosing to commence prophylactic treatment, (2) choice of factor source- either recombinant of plasma-derived, and (3) timing and dosing to commence immune tolerance induction to eradicate factor inhibitory antibodies. From each systematic review, the number of articles used to inform each decision tool pair was as follows: topic one- 21 of 103 articles, topic two- 18 of 185 articles and topic three- 8 of 452 articles. Each physician tool prototype underwent three rounds of review, with three haemophilia specialists reviewing each prototype per round for comprehensibility and usability. Substantial revisions were required after the first two rounds of testing, and only minor revisions were needed after the third. Each patient tool prototype was reviewed in three focus groups- two with haemophilia care support staff and one with haemophilia patients and parents. Testing of the patient tools showed that a high proportion of focus group participants understood the systematic review results informing each specific decision area. The tool prototypes can be accessed through the following link: https://www.dropbox.com/sh/4bc6je7moq6vkad/LwGzSCwqzs Discussion This study provides empirical evidence about a successful process of creating and testing decision aids for haemophilia treatment decisions, thus showing that it is feasible to develop such tools. As well, it provides evidence that physicians' and patients' initial perceptions about the usability of the tools were positive. Future directions will be to conduct a prospective trial to test the practical value and impact on clinical practice of the Decision Boxes and Patient Decision Aids. Disclosures: Athale: Biogen Idec: Graduate Research Internship Award Other. Iorio: Biogen Idec: Research Funding.
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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 | 0.056 | 0.106 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.005 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.017 | 0.002 |
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".