How does context influence collaborative decision-making for health services planning, delivery and evaluation?
Bibliographic record
Abstract
BACKGROUND: Collaboration among researchers (clinician, non-clinician) and decision makers (managers, policy-makers, clinicians), referred to as integrated knowledge translation (IKT), enhances the relevance and use of research, leading to improved decision-making, policies, practice, and health care outcomes. However IKT is not widely practiced due to numerous challenges. This research explored how context influenced IKT as a means of identifying how IKT could be strengthened. METHODS: This research investigated IKT in three health services programs for colon cancer screening, prostate cancer diagnosis, and the treatment of pancreatic cancer. Qualitative methods were used to explore contextual factors that influenced how IKT occurred, and its impact. Data were collected between September 1, 2012 and May 15, 2013 from relevant documents, observation of meetings, and interviews with researchers and decision-makers, analyzed using qualitative methods, and integrated. RESULTS: Data were analyzed from 39 documents, observation of 6 meetings, and 36 interviews. IKT included interaction at meetings, joint undertaking of research, and development of guidelines. IKT was most prevalent in one program with leadership, clear goals, dedicated funding and other infrastructural resources, and an embedded researcher responsible for, and actively engaged in IKT. This program achieved a variety of social, research and health service outcomes despite mixed individual views about the value of IKT and the absence of a programmatic culture of IKT. Participants noted numerous challenges including lack of time and incentives, and recommendations to support IKT. A conceptual framework of factors that influence IKT and associated outcomes was generated, and can be used by others to plan or evaluate IKT. CONCLUSIONS: The findings can be applied by researchers, clinicians, managers or policy-makers to plan or improve collaborative decision-making for health services planning, delivery, evaluation or quality improvement. Further research is needed to explore whether these findings are widespread, and further understand how IKT can be optimized.
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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 | 0.172 | 0.315 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.014 | 0.020 |
| Scholarly communication | 0.030 | 0.020 |
| Open science | 0.004 | 0.023 |
| Research integrity | 0.005 | 0.006 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".