Regular ArticleEvaluation of the predictive value of ICD-9-CM coded administrative data for venous thromboembolism in the United States☆
Introduction
Increasingly, epidemiologic studies are using “administrative” hospital discharge data to identify patients with important vascular outcome events, such as deep-vein thrombosis or pulmonary embolism, which together comprise venous thromboembolism (VTE). Administrative data are computerized records that are gathered for some administrative purpose, but contain information that can be used for other purposes as well. In the United States (US), the Uniform Claim and Billing Form 04 (UB-04) requires International Classification of Diseases, 9th Revision, Clinical Modification (ICD-9-CM) coding. The Joint Commission (TJC- the regulatory agency that oversees licensing of hospitals), the Agency for Healthcare Research and Quality (AHRQ - the US agency charged with improving the quality, safety, efficiency, and effectiveness of health care), and the Centers for Medicare & Medicaid Services (CMS) have launched quality measurement, quality improvement, and pay-for-performance initiatives that require identification of patients with acute VTE using a set of specific ICD-9-CM codes in hospital discharge records [1]. Researchers interested in vascular outcomes who use administrative data rely on ICD-9-CM codes to define presence or absence of acute VTE [2], [3], [4], [5], [6].
Prior to October 2009, there were twenty ICD-9-CM codes for VTE in non-pregnant patients, including 3 codes for pulmonary embolism, 10 codes for ‘thrombophlebitis’ (451 series) and 7 codes for ‘other venous thrombosis or embolism’ (453 series) [7]. In addition, there are several codes for pregnancy-related VTE (671 series) [8]. ICD-9-CM coding rules are evolving, as evidenced by the creation in October 2004 of 3 new codes that specify deep-vein thrombosis in the leg, thigh, or calf, and the creation in October 2009 of 21 new codes that specify additional locations and the acuity of VTE [9]. In addition, an ‘indicator’ to specify if a condition was present-on-admission (POA) was introduced in New York and California in the 1990s [10], and since October 2007 is required by CMS. This indicator should theoretically aid in the identification of hospital-acquired acute VTE events (i.e., not present-on-admission) [3], [4].
Only a few studies have retrospectively analyzed the positive predictive value of VTE codes. An early study showed that the most commonly used codes, when present in the principal position (specific for the condition that occasioned hospital admission), had very high positive predictive value for acute VTE (i.e., approximately 95%) [11]. However, other studies have reported that VTE codes in any position (principal or secondary) have much lower predictive value for acute VTE, in the range of 70-75%. In a multisite prospective cohort study, Cushman et al reported that the predictive value of any VTE code was 68% (95%CI: 63-74) [12]. More recently, Arnason et al [13] at a single hospital, and Heckbert et al [14], from the Women's Health Initiative, reported positive predictive values of 74% (95%CI: 64-82) and 78% (95%CI: 70-85), respectively. In another study using data from CMS, the predictive value of coding for deep vein thrombosis was 72% [15]. Finally, Zhan and coworkers analyzed the predictive value of ICD-9-CM coding for post-operative VTE using Medicare data and found a predictive value of only 29% for VTE [16]. These published studies have generally analyzed the predictive value of a group of VTE codes for any acute VTE event, not strictly lower extremity deep-vein thrombosis OR pulmonary embolism.
The aim of this study was to analyze a large sample of records from a wide array of hospitals throughout the United States to determine the predictive value of individual ICD-9-CM codes located in the principal position versus a secondary position for either any acute VTE or acute lower extremity deep-vein thrombosis or pulmonary embolism. Our objectives were to provide the ICD-9-CM Coordination and Maintenance Committee with the information necessary to enable them to restructure VTE codes in a more logical can comprehensive fashion, and to inform researchers and quality improvement professionals who use VTE codes for surveillance purposes about the predictive value of individual ICD-9-CM VTE codes [17].
Section snippets
Methods
The present study represents the compilation of three independent chart abstraction efforts by the University of California, Davis Medical Center (UCDMC), the University HealthSystem Consortium (UHC), and The Joint Commission (TJC). Because the research goals and abstraction methods were similar across projects, the first and last authors, who were involved in all three projects, decided to pool the data in order to enhance reliability. The UHC project also aimed to estimate the false negative
Results
The demographic characteristics of the samples from UCDMC, TJC and the two UHC subgroups (medical and surgical) that had a VTE code are shown in Table 1. The Joint Commission (N = 2052) sample had a median age that was 10 years older than both the UCDMC (N = 413) and UHC samples (N = 991), and the percentage of women in the TJC sample was also higher.
Discussion
All hospitals in the United States collect coded patient discharge data, which are used for a multitude of purposes [22] and are submitted to state health organizations and to various vendors, including The Joint Commission. The American Health Information Management Association recognizes that “the collection of accurate and complete coded data is critical to healthcare delivery, research, public reporting, reimbursement, and policy-making. The integrity of coded data and the ability to turn
Conflict of interest statement
The authors have no actual or potential conflict of interest specifically they have no financial, personal or other relationships with other people or organizations within three years of beginning the work submitted that could inappropriately influence their work.
Acknowledgment
This study was supported, in part, by a contract (290-04-0020, Support for Quality Indicators) with the Agency for Healthcare Research and Quality and, in part, by the Hibbard E Williams Endowment for General Medicine at UCDMC.
References (28)
- et al.
Clinical Validation of the AHRQ Postoperative Venous Thromboembolism Patient Safety Indicator
Jt Comm J Qual Patient Saf
(2009) - et al.
How often are potential patient safety events present on admission?
Jt Comm J Qual Patient Saf
(Mar 2008) - et al.
ICD-9-CM codes poorly indentified venous thromboembolism during pregnancy
J Clin Epidemiol
(2004) - et al.
Deep vein thrombosis and pulmonary embolism in two cohorts: the longitudinal investigation of thromboembolism etiology
Am J Med
(Jul 1 2004) - et al.
Accuracy of coding for possible warfarin complications in hospital discharge abstracts
Thromb Res
(2006) - et al.
The validity of ICD-9-CM codes in identifying postoperative deep vein thrombosis and pulmonary embolism
Jt Comm J Qual Patient Saf
(Jun 2007) Venous Thromboembolism (VTE) Core Measure Set - Last Updated 4/2009
(2009)- et al.
Identifying in-hospital venous thromboembolism (VTE): a comparison of claims-based approaches with the Rochester Epidemiology Project VTE cohort
Med Care
(Feb 2008) - et al.
Validity of selected AHRQ Patient Safety Indicators based on VA National Surgical Quality Improvement Program Data
Health Serv Res
(2009) - et al.
How Valid is the ICD-9-CM Based AHRQ Patient Safety Indicator for Postoperative Venous Thromboembolism?
Med Care
(Sep 25 2009)
Impact of diagnosis-timing indicators on measures of safety, comorbidity, and case mix groupings from administrative data sources
Med Care
Incidence and time course of thromboembolic outcomes following total hip or knee arthroplasty
Arch Intern Med
Cited by (0)
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Presented at the International Society of Thrombosis and Haemostasis Meeting, July 16, 2009, Boston, MA.