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PPO 17-026 – HSR Study

PPO 17-026
Early Identification of Poorly Performing Joint Replacements
Nicholas J. Giori, MD PhD
VA Palo Alto Health Care System, Palo Alto, CA
Palo Alto, CA
Funding Period: March 2018 - February 2019
Joint replacement surgery is the most common inpatient surgery in the Veterans Health Administration (VHA). 14,349 primary joint replacement cases were performed in the VHA system in 2015. About 5% are reoperated by 10 years for failure or infection, but poor implants have a much higher reoperation rate (17-25% by 5 years for the DePuy ASR XL). Failed joint replacements result in personal and financial hardship for veteran patients and is costly for the VHA (about $38,000 per episode). As implant designs and techniques evolve, some changes improve patient pain and function, reduce complications, and improve longevity, while other changes have the opposite effect. These changes in outcome often take many years to become evident.

To limit harm to patients and costs for the health care system, it is imperative that we improve our ability to monitor the performance of implants and to identify poor implants earlier than is now possible. Currently, the United States Food and Drug Administration (FDA) monitors the performance of implants using several inputs, but none derive information directly from medical records. Medical records are a rich source of information on device performance and could provide a comprehensive view that includes prosthetic-related complications and the pain and function of the patient. Such a comprehensive view may allow early identification of poorly performing implants even before they end up being revised, potentially sparing many patients from receiving them.

Our purpose is to extract and evaluate joint replacement prosthesis implantation and explantation information from the VA Corporate Data Warehouse (CDW). Aim 1: Determine trends in national hip replacement implant use and regional variation in the VA from 2000 to 2016. Aim 2: Build a level 1 registry of hip replacement implants in the VA system.

Aim 1: We will retrieve implant-specific information from the CDW across the VHA over time, including Operative Date, Station, CPT code, Prosthesis Vendor, Prosthesis Model, Prosthesis Size, and Prosthesis Name. After evaluating the quality and completeness of these records across the VHA over time, we will characterize implantation practices for each station and each calendar year.

Aim 2: A level 1 registry consists of patient demographics, hospital, surgeon, and procedure-related data including the laterality of surgery, dates of surgery, and implant utilized. Part (a) of this aim will focus on extracting laterality information for both index surgery and any subsequent reoperations from unstructured fields to directly link index surgeries to any corresponding reoperations. This will tell us how long the joint prosthesis lasted before a reoperation was needed. Part (b) of the aim will require analysis of unstructured data to determine which component of the joint replacement was problematic and removed. By completing this aim, we will generate reports on the individual component survivorship free of reoperation or removal for each of the implants used across the VA health care system.


The VHA is the nation's largest integrated health care system and was among the earliest adopters of the electronic health record (EHR). The VHA EHR is unique, and may be used to create a VA joint implant registry. This could improve joint replacement practice and care across the VA health care system. In addition, a VA joint replacement registry could act to support a national implant surveillance system by computationally extracting and aggregating individual prosthetic data for use by the FDA.

External Links for this Project

NIH Reporter

Grant Number: I21HX002413-01A1

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None at this time.

DRA: Other Conditions, Prosthetics, Orthotics, and Assistive Technology, Aging, Older Veterans' Health and Care
DRE: Research Infrastructure, TRL - Applied/Translational, Treatment - Observational
Keywords: Electronic Health Record, Knowledge Integration, Surveillance
MeSH Terms: none

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