Statistical models and implant customization in hip arthroplasty: Seeking patient satisfaction through design

Objectives: This study conducts a systematic literature review to explore the role of statistical models and methods in the design of orthopedic implants, with a specific focus on hip arthroplasty. Through a comprehensive analysis of the scientific literature, it aims to understand the relevance and applicability of these models in implant development and research trends in the field of design. Methods: Data analysis and co-occurrence mapping techniques were employed to investigate the statistical models used as predictors of satisfaction in hip arthroplasty and in implant design. This approach facilitated a detailed and objective assessment of existing literature, revealing key trends and identifying gaps in current knowledge. Key findings: The review's findings underscore a burgeoning interest in implant customization, with a significant emphasis on leveraging statistical techniques for optimal design. The logistic model methodology was applied to analyze a survey of hip surgery specialists, revealing that the physician's age does not influence the decision to use a customized implant. Furthermore, the review highlighted a knowledge gap at the intersection of statistics and design discipline concerning implant customization. Significance: Despite the recognized importance of customization in implant design, there remains a dearth of contributions from the design discipline perspective in the existing literature, indicating substantial room for improvement and the need for interdisciplinary integration. Conclusion: The integration of statistical methods in implant design is crucial, emphasizing the need for multidisciplinary approaches and customization to enhance patient satisfaction. This study provides a foundation for future research that could transform the field of hip arthroplasty through more personalized and effective solutions.