Abstract
Identifying when and how often decisions are made based on high-quality evidence can inform the development of evidence-based treatment plans and care pathways, which have been shown to improve quality of care and patient safety. Evidence to guide decision-making, national guidelines and clinical pathways for many conditions in pediatric orthopedic surgery are limited. This study investigated decision-making rationale and quantified the evidence supporting decisions made by pediatric orthopedic surgeons in an outpatient clinic. We recorded decisions made by eight pediatric orthopedic surgeons in an outpatient clinic and the surgeon's reported rationale behind the decisions. Surgeons categorized the rationale for each decision as one or a combination of 12 possibilities (e.g. 'Experience/anecdote,' 'First principles,' 'Trained to do it,' 'Arbitrary/instinct,' 'General study,' 'Specific study'). Out of 1150 total decisions, the most frequent decisions were follow-up scheduling, followed by bracing prescription/removal. The most common decision rationales were 'First principles' (n = 310, 27.0%) and 'Experience/anecdote' (n = 253, 22.0%). Only 17.8% of decisions were attributed to scientific studies, with 7.3% based on studies specific to the decision. As high as 34.6% of surgical intervention decisions were based on scientific studies, while only 10.4% of follow-up scheduling decisions were made with studies in mind. Decision category was significantly associated with a basis in scientific studies: surgical intervention and medication prescription decisions were more likely to be based on scientific studies than all other decisions. With increasing emphasis on high value, evidence-based care, understanding the rationale behind physician decision-making can educate physicians, identify common decisions without supporting evidence and help create clinical care pathways in pediatric orthopedic surgery. Decisions based on evidence or consensus between surgeons can inform pathways and national guidelines that minimize unwarranted variation in care and waste. Decision support tools and aids could also be implemented to guide these decisions.
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