The Journal of Arthroplasty Available online 26 November 2014 doi:10.1016/j.arth.2014.11.021 1 A Patient-Specific Predictive Model Increases Preoperative Templating Accuracy in Hip Arthroplasty. Amir Pourmoghaddam, PhD; Marius Dettmer, PhD; Adam M. Freedhand, MD; Brian C. Domingues, BSc.; Stefan W. Kreuzer, MD, MSc. Affiliation: Memorial Bone & Joint Research Foundation, Department of Orthopaedic Surgery, The University of Texas Health Science Center at Houston – Medical School 1140 Business Center Drive, Suite 101 Houston, TX 77043 This is author’s version. For publisher version please visit: http://www.arthroplastyjournal.org/article/S0883-5403(14)00897-3/abstract Abstract: Application of digital radiography during preoperative templating has shown potential to reduce complications in total hip arthroplasty. Digital radiography has significantly improved this process. In this study, we aimed to further improve the digital templating by using a predictive model built on patients’ specific data. The model was significant in improving the accuracy of templating within +/-1 size of acetabular component ( 2 ሺͳ, = Ͷͺሻ = ͳͻ.͵ͳͶ, p<0.0001, =0.604, and odds-ratio: 7.750 (95% CI 2.740-30.220)). We successfully achieved a 99% accuracy within +/- 2 of templated size. Additionally, patient demographics, such as height and weight, have shown significant effects on the predictive model. The outcome of this study may help reducing the costs of health care in the long term by minimizing implant inventory costs for each patient.