Convergent parallel mixed-methods study to understand the impact of decision-making for congenital cardiac surgery patients at a tertiary paediatric hospital: a study protocol
Bibliographic record
Abstract
INTRODUCTION: Congenital heart disease (CHD) is the most common congenital condition, often necessitating complex heart surgeries that require careful planning by multidisciplinary teams. Multidisciplinary meetings (MDMs) in CHD care aim to integrate diverse expertise to optimise surgical planning. However, the lack of standardised protocols for conducting these meetings introduces undesirable variability in decision-making processes, potentially impacting patient outcomes. This study addresses the critical gap in understanding which aspects of MDMs should be standardised to ensure consistent, high-quality decision-making while also identifying areas where flexibility is essential to accommodate individual patient needs. The objective is to characterise current MDM practices in CHD care, identify factors contributing to variability and provide insights into how a balance between standardisation and flexibility can improve decision-making and patient outcomes. METHODS AND ANALYSIS: A convergent parallel mixed-methods study design will be used to collect, analyse and interpret quantitative and qualitative data. Data collection will include a blend of naturalistic observations and chart reviews to track patient journeys from surgical planning through to postoperative outcomes. To complement these findings, interviews with healthcare providers will capture subjective perspectives on multidisciplinary decision-making. Additionally, departmental metrics will be collected to contextualise the broader clinical environment. Closed-ended observational and chart review data will be analysed using summary statistics and descriptive analysis (eg, percentages, means) to characterise MDM decision-making. Qualitative data (eg, reflections and learnings) from weekly post-surgical debriefs (called Performance Rounds) and clinician interviews on MDM decision-making will be analysed using a modified Framework Method. ETHICS AND DISSEMINATION: Institutional research ethics approval has been acquired (REB #1000080464). To engage key stakeholders and foster collaborative improvement, study results will be shared in research rounds, where staff attending medical surgical conferences, team huddles, morbidity and mortality reviews, and Performance Rounds will be invited to participate. Targeted meetings with individual clinician groups will further allow for in-depth discussion and valuable feedback on the findings. Finally, the findings from this study are anticipated to make a meaningful contribution to the literature; a manuscript is planned for submission to a peer-reviewed journal.
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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 | 0.086 | 0.076 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.003 | 0.004 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.021 | 0.003 |
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".