Development and early findings of a semiautomated arthroplasty registry in a multi-institutional healthcare networkIsabella Florissi, Vincent Philip Galea, Nicholas Sauder, Yhan Colon Iban, Marilyn Heng, Fraz K. Ahmed, Henrik Malchau, Charles R. Bragdon
The primary aim of this paper was to outline the processes involved in building the Partners Arthroplasty Registry (PAR), established in April 2016 to capture baseline and outcome data for patients undergoing arthroplasty in a regional healthcare system. A secondary aim was to determine the quality of PAR’s data. A tertiary aim was to report preliminary findings from the registry and contributions to quality improvement initiatives and research up to March 2019.
Structured Query Language was used to obtain data relating to patients who underwent total hip or knee arthroplasty (THA and TKA) from the hospital network’s electronic medical record (EMR) system to be included in the PAR. Data were stored in a secure database and visualized in dashboards. Quality assurance of PAR data was performed by review of the medical records. Capture rate was determined by comparing two months of PAR data with operating room schedules. Linear and binary logistic regression models were constructed to determine if length of stay (LOS), discharge to a care home, and readmission rates improved between 2016 and 2019.
The PAR captured 16,163 THAs and TKAs between April 2016 and March 2019, performed in seven hospitals by 110 surgeons. Manual comparison to operating schedules showed a 100% capture rate. Review of the records was performed for 2,603 random operations; 2,298 (88.3%) had complete and accurate data. The PAR provided the data for three abstracts presented at international conferences and has led to preoperative mental health treatment as a quality improvement initiative in the participating institutions. For primary THA and TKA surgeries, the LOS decreased significantly (p < 0.001) and the rate of home discharge increased significantly (p < 0.001) between 2016 and 2019. Readmission rates did not correlated with the date of surgery (p = 0.953).
The PAR has high rates of coverage (the number of patients treated within the Partners healthcare network) and data completion and can be used for both research purposes and quality improvement. The same method of creating a registry that was used in the PAR can be applied to hospitals using similar EMR systems.
Cite this article: Bone Joint J 2020;102-B(7 Supple B):90–98.