Literature DB >> 33720372

Assessment of Extractability and Accuracy of Electronic Health Record Data for Joint Implant Registries.

Nicholas J Giori1,2, John Radin1, Alison Callahan3, Jason A Fries3,4, Eni Halilaj5, Christopher Ré4, Scott L Delp5, Nigam H Shah3, Alex H S Harris1,6.   

Abstract

Importance: Implant registries provide valuable information on the performance of implants in a real-world setting, yet they have traditionally been expensive to establish and maintain. Electronic health records (EHRs) are widely used and may include the information needed to generate clinically meaningful reports similar to a formal implant registry.
Objectives: To quantify the extractability and accuracy of registry-relevant data from the EHR and to assess the ability of these data to track trends in implant use and the durability of implants (hereafter referred to as implant survivorship), using data stored since 2000 in the EHR of the largest integrated health care system in the United States. Design, Setting, and Participants: Retrospective cohort study of a large EHR of veterans who had 45 351 total hip arthroplasty procedures in Veterans Health Administration hospitals from 2000 to 2017. Data analysis was performed from January 1, 2000, to December 31, 2017. Exposures: Total hip arthroplasty. Main Outcomes and Measures: Number of total hip arthroplasty procedures extracted from the EHR, trends in implant use, and relative survivorship of implants.
Results: A total of 45 351 total hip arthroplasty procedures were identified from 2000 to 2017 with 192 805 implant parts. Data completeness improved over the time. After 2014, 85% of prosthetic heads, 91% of shells, 81% of stems, and 85% of liners used in the Veterans Health Administration health care system were identified by part number. Revision burden and trends in metal vs ceramic prosthetic femoral head use were found to reflect data from the American Joint Replacement Registry. Recalled implants were obvious negative outliers in implant survivorship using Kaplan-Meier curves. Conclusions and Relevance: Although loss to follow-up remains a challenge that requires additional attention to improve the quantitative nature of calculated implant survivorship, we conclude that data collected during routine clinical care and stored in the EHR of a large health system over 18 years were sufficient to provide clinically meaningful data on trends in implant use and to identify poor implants that were subsequently recalled. This automated approach was low cost and had no reporting burden. This low-cost, low-overhead method to assess implant use and performance within a large health care setting may be useful to internal quality assurance programs and, on a larger scale, to postmarket surveillance of implant performance.

Entities:  

Year:  2021        PMID: 33720372      PMCID: PMC7961313          DOI: 10.1001/jamanetworkopen.2021.1728

Source DB:  PubMed          Journal:  JAMA Netw Open        ISSN: 2574-3805


  13 in total

1.  The International Consortium of Orthopaedic Registries: overview and summary.

Authors:  Art Sedrakyan; Elizabeth W Paxton; Charlotte Phillips; Robert Namba; Tadashi Funahashi; Thomas Barber; Thomas Sculco; Douglas Padgett; Timothy Wright; Danica Marinac-Dabic
Journal:  J Bone Joint Surg Am       Date:  2011-12-21       Impact factor: 5.284

2.  Kaiser Permanente National Total Joint Replacement Registry: aligning operations with information technology.

Authors:  Elizabeth W Paxton; Maria C S Inacio; Monti Khatod; Eric J Yue; Robert S Namba
Journal:  Clin Orthop Relat Res       Date:  2010-10       Impact factor: 4.176

3.  Data for registry and quality review can be retrospectively collected using natural language processing from unstructured charts of arthroplasty patients.

Authors:  Romil F Shah; Stefano Bini; Thomas Vail
Journal:  Bone Joint J       Date:  2020-07       Impact factor: 5.082

4.  External Determinants of Veterans' Utilization of VA Health Care.

Authors:  Amresh D Hanchate; Austin B Frakt; Nancy R Kressin; Amal Trivedi; Amy Linsky; Hassen Abdulkerim; Kelly L Stolzmann; David C Mohr; Steven D Pizer
Journal:  Health Serv Res       Date:  2018-07-31       Impact factor: 3.402

5.  Maintaining a hip registry for 25 years. Mayo Clinic experience.

Authors:  D J Berry; M Kessler; B F Morrey
Journal:  Clin Orthop Relat Res       Date:  1997-11       Impact factor: 4.176

6.  Incremental inputs improve the automated detection of implant loosening using machine-learning algorithms.

Authors:  Romil F Shah; Stefano A Bini; Alejandro M Martinez; Valentina Pedoia; Thomas P Vail
Journal:  Bone Joint J       Date:  2020-06       Impact factor: 5.082

7.  Snorkel: Rapid Training Data Creation with Weak Supervision.

Authors:  Alexander Ratner; Stephen H Bach; Henry Ehrenberg; Jason Fries; Sen Wu; Christopher Ré
Journal:  Proceedings VLDB Endowment       Date:  2017-11

8.  Excessive distal migration of fiber-mesh coated femoral stems.

Authors:  Thomas Baad-Hansen; Søren Kold; Niels Olsen; Finn Christensen; Kjeld Søballe
Journal:  Acta Orthop       Date:  2011-04-19       Impact factor: 3.717

9.  Enhanced Quality Measurement Event Detection: An Application to Physician Reporting.

Authors:  Suzanne R Tamang; Tina Hernandez-Boussard; Elsie Gyang Ross; Gregory Gaskin; Manali I Patel; Nigam H Shah
Journal:  EGEMS (Wash DC)       Date:  2017-05-30

10.  Medical device surveillance with electronic health records.

Authors:  Alison Callahan; Jason A Fries; Christopher Ré; James I Huddleston; Nicholas J Giori; Scott Delp; Nigam H Shah
Journal:  NPJ Digit Med       Date:  2019-09-25
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  1 in total

1.  The relative proportion of comorbidities among rhinitis and rhinosinusitis patients and their impact on visit burden.

Authors:  Mikko Nuutinen; Annina Lyly; Paula Virkkula; Maija Hytönen; Elmo Saarentaus; Antti Mäkitie; Aarno Palotie; Paulus Torkki; Jari Haukka; Sanna Toppila-Salmi
Journal:  Clin Transl Allergy       Date:  2022-07-21       Impact factor: 5.657

  1 in total

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