Cast or Nail? Using a Preference-Based Tool for Shared Decision-Making in Pediatric Femoral Shaft Fracture Treatment

Abstract

Background: Femoral shaft fractures are common injuries in children 2 to 7 years of age, with treatments ranging from casting to flexible intramedullary nails (FIN). Each treatment has unique attributes and outcomes are overall similar. Given equivalent outcomes, we hypothesized that a shared decision-making process, using adaptive conjoint analysis (ACA), can be used to assess individual family situations to determine ultimate treatment choice. Methods: An interactive survey incorporating an ACA exercise to elicit the preferences of individuals was created. Amazon Mechanical Turk was used to recruit survey respondents simulating the at-risk population. Basic demographic information and family characteristics were collected. Sawtooth Software was utilized to generate relative importance values of five treatment attributes and determine subjects’ ultimate treatment choice. Student’s t-test or Wilcoxon rank sum test was used to compare relative importance between groups. Results: The final analysis included 186 subjects with 147 (79%) choosing casting as their ultimate treatment choice, while 39 (21%) chose FIN. Need for second surgery had the highest overall average relative importance (42.0), followed by a chance of serious complications (24.6), time away from school (12.9), effort required by caregivers (11.0), and return to activities (9.6). Most respondents (85%) indicated the generated relative importance of attributes aligned “very well or well” with their preferences. For those who chose casting instead of FIN, the need for secondary surgery (43.9 vs. 34.8, P<0.001) and the chance of serious complications (25.9 vs. 19.6, P<0.001) were the most important factors. In addition, returning to activities, the burden to caregivers, and time away from school were all significantly more important to those choosing surgery versus casting (12.6 vs. 8.7 P<0.001, 12.6 vs. 9.8 P=0.014, 16.6 vs. 11.7 P<0.001, respectively). Conclusions: Our decision-making tool accurately identified subjects’ treatment preferences and appropriately aligned them with a treatment decision. Given the increased emphasis on shared decision-making in health care, this tool may have the potential to improve shared decision-making and family understanding, leading to improved satisfaction rates and overall outcomes. Level of Evidence: Level—III.