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. 2025 Aug 12;15(8):e099080.
doi: 10.1136/bmjopen-2025-099080.

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

Affiliations

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

Leyi Yin et al. BMJ Open. .

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.

Keywords: Cardiac surgery; Clinical Decision-Making; Congenital heart disease; Paediatric cardiac surgery; Paediatric cardiology; Paediatric intensive & critical care.

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Conflict of interest statement

Competing interests: None declared.

Figures

Figure 1
Figure 1. Diagram of a systems approach when observing decision-making by multi-disciplinary heart centre teams. SEIPS, Systems Engineering in Patient Safety.
Figure 2
Figure 2. Modified MODe used to evaluate decision-making MDMs. The original version of the Metric for the Observation of Decision-Making in cancer MDT tool consisted of 13 items rated on a five-point Likert scale regarding predefined observable anchor behaviours. To adapt the tool to paediatric congenital cardiac surgery, the categories were adjusted. Other features of the tool, such as the five-point Likert scale and equivalent observable anchor behaviours, were kept the same. MDM, multidisciplinary meeting.
Figure 3
Figure 3. Example framework matrix of clinician interviews. Data items will be sorted by Systems Engineering in Patient Safety category (theme), decision-making metrics (subtheme and code) and staff interview.

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