Low Accuracy of Diagnostic Codes to Identify Anterior Cruciate Ligament Tear in Orthopaedic Database Research

Thomas L. Sanders, Ayoosh Pareek, Vishal S. Desai, Timothy Hewett, Bruce A Levy, Michael J. Stuart, Diane L. Dahm, Aaron Krych

Research output: Contribution to journalArticle

4 Citations (Scopus)

Abstract

Background: Database research is being used in orthopaedic literature with increased regularity. The main limitation of database research is the absence of diagnosis and treatment verification afforded by medical chart review. This absence may limit the accuracy of some conclusions and recommendations produced by database research. Hypothesis/Purpose: The purpose was to describe the accuracy of 1 database (Rochester Epidemiology Project) used in orthopaedic research to detect isolated anterior cruciate ligament (ACL) tears and to discuss the limitations of database research. It was hypothesized that diagnostic codes alone are unlikely to be accurate in identifying patients with ACL tears. Study Design: Cohort study (diagnosis); Level of evidence, 2. Methods: A population-based historical cohort study was performed with the Rochester Epidemiology Project database. All subjects had International Classification of Diseases, Ninth Revision, diagnosis codes consistent with ACL tears between January 1, 1990, and December 31, 2010. The medical records of all subjects were reviewed in detail to confirm the accuracy of diagnosis and gather data on injury type, laterality, associated meniscal injuries, magnetic resonance imaging findings, and treatment details. Results: A total of 3494 patients had codes consistent with ACL tears, and 2288 of them were confirmed through chart review to have an isolated ACL tear (65.5%). Among these were 1841 patients (52.7%) with an ACL tear within 1 year of injury and an additional 447 (12.8%) with an ACL tear >1 year from injury. Thirty-nine patients (1.1%) had a partial ACL tear diagnosed on magnetic resonance imaging, 48 (1.4%) had an isolated posterior cruciate ligament tear, and 22 (0.6%) had a combined ACL–posterior cruciate ligament injury. Twenty-four patients (0.7%) had ACL reconstruction before the study period. The remaining 1073 patients (30.7%) had diagnostic codes consistent with an ACL tear but did not have a cruciate ligament injury. Conclusion: This study demonstrates low accuracy with the use of diagnostic codes alone to identify an ACL tear. Database studies offer unique benefits to the medical literature, but the inherent limitations should be taken into account when these data are used to counsel patients, dictate clinical management, or make health care policy decisions. Information from a health care database is most accurate when accompanied by verification of diagnosis, treatment, and outcomes with medical chart review.

Original languageEnglish (US)
JournalAmerican Journal of Sports Medicine
DOIs
StateAccepted/In press - Jan 1 2018

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Orthopedics
Databases
Research
Wounds and Injuries
Ligaments
Epidemiology
Cohort Studies
Magnetic Resonance Imaging
Anterior Cruciate Ligament Injuries
Posterior Cruciate Ligament
Delivery of Health Care
Anterior Cruciate Ligament Reconstruction
International Classification of Diseases
Health Policy
Medical Records
Therapeutics
Population

Keywords

  • anterior cruciate ligament
  • epidemiology
  • knee

ASJC Scopus subject areas

  • Orthopedics and Sports Medicine
  • Physical Therapy, Sports Therapy and Rehabilitation

Cite this

Low Accuracy of Diagnostic Codes to Identify Anterior Cruciate Ligament Tear in Orthopaedic Database Research. / Sanders, Thomas L.; Pareek, Ayoosh; Desai, Vishal S.; Hewett, Timothy; Levy, Bruce A; Stuart, Michael J.; Dahm, Diane L.; Krych, Aaron.

In: American Journal of Sports Medicine, 01.01.2018.

Research output: Contribution to journalArticle

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abstract = "Background: Database research is being used in orthopaedic literature with increased regularity. The main limitation of database research is the absence of diagnosis and treatment verification afforded by medical chart review. This absence may limit the accuracy of some conclusions and recommendations produced by database research. Hypothesis/Purpose: The purpose was to describe the accuracy of 1 database (Rochester Epidemiology Project) used in orthopaedic research to detect isolated anterior cruciate ligament (ACL) tears and to discuss the limitations of database research. It was hypothesized that diagnostic codes alone are unlikely to be accurate in identifying patients with ACL tears. Study Design: Cohort study (diagnosis); Level of evidence, 2. Methods: A population-based historical cohort study was performed with the Rochester Epidemiology Project database. All subjects had International Classification of Diseases, Ninth Revision, diagnosis codes consistent with ACL tears between January 1, 1990, and December 31, 2010. The medical records of all subjects were reviewed in detail to confirm the accuracy of diagnosis and gather data on injury type, laterality, associated meniscal injuries, magnetic resonance imaging findings, and treatment details. Results: A total of 3494 patients had codes consistent with ACL tears, and 2288 of them were confirmed through chart review to have an isolated ACL tear (65.5{\%}). Among these were 1841 patients (52.7{\%}) with an ACL tear within 1 year of injury and an additional 447 (12.8{\%}) with an ACL tear >1 year from injury. Thirty-nine patients (1.1{\%}) had a partial ACL tear diagnosed on magnetic resonance imaging, 48 (1.4{\%}) had an isolated posterior cruciate ligament tear, and 22 (0.6{\%}) had a combined ACL–posterior cruciate ligament injury. Twenty-four patients (0.7{\%}) had ACL reconstruction before the study period. The remaining 1073 patients (30.7{\%}) had diagnostic codes consistent with an ACL tear but did not have a cruciate ligament injury. Conclusion: This study demonstrates low accuracy with the use of diagnostic codes alone to identify an ACL tear. Database studies offer unique benefits to the medical literature, but the inherent limitations should be taken into account when these data are used to counsel patients, dictate clinical management, or make health care policy decisions. Information from a health care database is most accurate when accompanied by verification of diagnosis, treatment, and outcomes with medical chart review.",
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AU - Sanders, Thomas L.

AU - Pareek, Ayoosh

AU - Desai, Vishal S.

AU - Hewett, Timothy

AU - Levy, Bruce A

AU - Stuart, Michael J.

AU - Dahm, Diane L.

AU - Krych, Aaron

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N2 - Background: Database research is being used in orthopaedic literature with increased regularity. The main limitation of database research is the absence of diagnosis and treatment verification afforded by medical chart review. This absence may limit the accuracy of some conclusions and recommendations produced by database research. Hypothesis/Purpose: The purpose was to describe the accuracy of 1 database (Rochester Epidemiology Project) used in orthopaedic research to detect isolated anterior cruciate ligament (ACL) tears and to discuss the limitations of database research. It was hypothesized that diagnostic codes alone are unlikely to be accurate in identifying patients with ACL tears. Study Design: Cohort study (diagnosis); Level of evidence, 2. Methods: A population-based historical cohort study was performed with the Rochester Epidemiology Project database. All subjects had International Classification of Diseases, Ninth Revision, diagnosis codes consistent with ACL tears between January 1, 1990, and December 31, 2010. The medical records of all subjects were reviewed in detail to confirm the accuracy of diagnosis and gather data on injury type, laterality, associated meniscal injuries, magnetic resonance imaging findings, and treatment details. Results: A total of 3494 patients had codes consistent with ACL tears, and 2288 of them were confirmed through chart review to have an isolated ACL tear (65.5%). Among these were 1841 patients (52.7%) with an ACL tear within 1 year of injury and an additional 447 (12.8%) with an ACL tear >1 year from injury. Thirty-nine patients (1.1%) had a partial ACL tear diagnosed on magnetic resonance imaging, 48 (1.4%) had an isolated posterior cruciate ligament tear, and 22 (0.6%) had a combined ACL–posterior cruciate ligament injury. Twenty-four patients (0.7%) had ACL reconstruction before the study period. The remaining 1073 patients (30.7%) had diagnostic codes consistent with an ACL tear but did not have a cruciate ligament injury. Conclusion: This study demonstrates low accuracy with the use of diagnostic codes alone to identify an ACL tear. Database studies offer unique benefits to the medical literature, but the inherent limitations should be taken into account when these data are used to counsel patients, dictate clinical management, or make health care policy decisions. Information from a health care database is most accurate when accompanied by verification of diagnosis, treatment, and outcomes with medical chart review.

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