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Lessons learned from managing a prospective, private practice joint replacement registry: a 25-year experience
Joshua T Carothers1, Richard E White, Krishna R Tripuraneni
1New Mexico Orthopaedics, Center for Joint Replacement, 201 Cedar SE, Suite 6600, Albuquerque, NM 87106, USA. carothersjt@nmortho.net
Clinical Orthopaedics and Related Research
|September 6, 2012
Summary
Managing a joint replacement registry (JRR) presents challenges. This study found poor patient followup and incomplete data capture in a long-term registry for hip and knee replacements, indicating a need for improved methods.
Area of Science:
- Orthopedic surgery
- Health informatics
- Biostatistics
Background:
- A private practice joint replacement registry (JRR) was established in 1984 to prospectively track patients undergoing total hip arthroplasty (THA) and total knee arthroplasty (TKA).
- Limited literature exists on managing such databases and their long-term utility for research questions.
Purpose of the Study:
- To determine the followup rate for THA and TKA patients in the JRR.
- To identify factors influencing patient followup.
- To evaluate the JRR model's data capture success, identify areas for improvement, and assess associated maintenance costs.
Main Methods:
- Clinical and radiographic data were collected from 12,047 primary THA and TKA patients since 1984.
- A prospective database was utilized for data entry at routine followup intervals.
- Database analysis assessed followup rates, data completeness, patient variable effects on followup, and management costs.
Main Results:
- Followup rates were consistently poor across all time intervals post-surgery, worsening over time.
- Younger patients (<70 years) and those experiencing complications showed higher followup frequencies.
- Challenges in data capture and significant database management expenses were identified.
Conclusions:
- Managing a joint replacement registry is difficult, characterized by poor followup and incomplete data.
- Future registries may benefit from newer technologies to enhance patient tracking, data capture efficiency, and cost control.
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