Developing a Disease Registration System in Order to Collect Scientific and Research-Oriented Data in the Field of Orthopedics: The Case Study of Tehran Shafa Yahyayan Hospital

Knee arthroplasty is one of the most important and growing surgery in orthopedics, with successful results reducing pain and increasing the patient’s mobility. The recording of this procedure is very important for the monitoring of the disease, due to the possibility of its reversibility. This research was conducted with the aim of designing, implementing and evaluating the applicability of the knee replacement surgery registration system in Tehran Shafa Yahyaian Hospital, as the orthopedic hub of the country.

Methods and Materials:

 By forming a multidisciplinary taskforce group and using the Delphi method, and after reviewing relevant texts published by orthopedic societies, the minimum required data was extracted. The modelling and evolution of the system followed the life cycle of information systems, and a prototype of the software was designed on the .NET platform. Finally, machine learning algorithms were used to analyses the primary data.

The data was divided into four categories of patient information: preoperative, intraoperative, postoperative, patient follow-up. The final version of the software was released and piloted at Shafa Hospital. The measurement of user satisfaction with the system was satisfactory. The results obtained from the implementation of the clustering algorithm were consistent with what happened at the bedside.

The development of this platform to other orthopedic centers and hospitals all over the country, adding artificial intelligence and related machine learning algorithms, will play a significant role in the decision-making of the health systems and the orthopedic communities in optimized management of this disease treatment that will lead to support patients better.