While internet search engines have been the primary information source for patients’ questions, artificial intelligence large language models like ChatGPT are trending towards becoming the new primary source. The purpose of this study was to determine if ChatGPT can answer patient questions about total hip (THA) and knee arthroplasty (TKA) with consistent accuracy, comprehensiveness, and easy readability. We posed the 20 most Google-searched questions about THA and TKA, plus ten additional postoperative questions, to ChatGPT. Each question was asked twice to evaluate for consistency in quality. Following each response, we responded with, “Please explain so it is easier to understand,” to evaluate ChatGPT’s ability to reduce response reading grade level, measured as Flesch-Kincaid Grade Level (FKGL). Five resident physicians rated the 120 responses on 1 to 5 accuracy and comprehensiveness scales. Additionally, they answered a “yes” or “no” question regarding acceptability. Mean scores were calculated for each question, and responses were deemed acceptable if ≥ four raters answered “yes.”Aims
Methods
The aim of this study is to assess the impact of a pilot enhanced recovery after surgery (ERAS) programme on length of stay (LOS) and post-discharge resource usage via service evaluation and cost analysis. Between May and December 2019, 100 patients requiring hip or knee arthroplasty were enrolled with the intention that each would have a preadmission discharge plan, a preoperative education class with nominated helper, a day of surgery admission and mobilization, a day one discharge, and access to a 24/7 dedicated helpline. Each was matched with a patient under the pre-existing pathway from the previous year.Aims
Methods
