Chest
Volume 141, Issue 1, January 2012, Pages 87-93
Journal home page for Chest

Original Research
COPD
The Validity of International Classification of Diseases, Ninth Revision, Clinical Modification Diagnosis Codes for Identifying Patients Hospitalized for COPD Exacerbations

https://doi.org/10.1378/chest.11-0024Get rights and content

Background

Acute exacerbations of COPD (AE-COPD) are a leading cause of hospitalizations in the United States. To estimate the burden of disease (eg, prevalence and cost), identify opportunities to improve care quality (eg, performance measures), and conduct observational comparative effectiveness research studies, various algorithms based on the International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) codes have been used to identify patients with COPD. However, the validity of these algorithms remains unclear.

Methods

We compared the test characteristics (sensitivity, specificity, positive predictive value, and negative predictive value) of four different coding algorithms for identifying patients hospitalized for an exacerbation of COPD with chart review (reference standard) using a stratified probability sample of 200 hospitalizations at two urban academic medical centers. Sampling weights were used when calculating prevalence and test characteristics.

Results

The prevalence of COPD exacerbations (based on the reference standard) was 7.9% of all hospitalizations. The sensitivity of all ICD-9-CM algorithms was very low and varied by algorithm (12%-25%), but the negative predictive value was similarly high across algorithms (93%-94%). The specificity was > 99% for all algorithms, but the positive predictive value varied by algorithm (81%-97%).

Conclusions

Algorithms based on ICD-9-CM codes will undercount hospitalizations for AE-COPD, and as many as one in five patients identified by these algorithms may be misidentified as having a COPD exacerbation. These findings suggest that relying on ICD-9-CM codes alone to identify patients hospitalized for AE-COPD may be problematic.

Section snippets

Materials and Methods

In the COPD-ARTIFACT (Administrative Data to Identify COPD or Heart Failure) study, hospital discharge databases at two academic health centers affiliated with different universities in Chicago were used to select a stratified probability sample of 200 adults admitted between November 2005 and October 2006. Inclusion criteria were age ≥ 25 years and hospital admission to a medical service (Fig 1); this lower boundary for age was used based on previous studies.17, 18 To avoid gaps in chart

Patient Characteristics

Of the 49,239 patients (hospital 1, 28,643; hospital 2, 20,596) admitted during the study period, 8,790 met eligibility criteria (hospital 1, 5,602; hospital 2, 3,188). Based on the reference standard, the prevalence (using sampling weights) of hospitalizations for AE-COPD was 7.9% (Table 2). As expected, the prevalence of AE-COPD in stratum 1 (81.2%) was higher than in stratum 2 (26.0%) or stratum 3 (4.0%). Only 20.8% of patients hospitalized for AE-COPD had a documented spirometry in the

Discussion

About one in 13 hospitalized patients in this study (7.9%) had AE-COPD. We demonstrated that algorithms based on ICD-9-CM codes vary in their ability to distinguish patients admitted for AE-COPD from those who are not. The sensitivity of all four ICD-9-CM algorithms was poor, but they were generally better if a combination of primary and secondary diagnosis codes were used. The PPVs varied across algorithms and favored the approach that relies on a primary diagnosis of COPD exacerbation

Acknowledgments

Author contributions: Dr Stein had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.

Dr Stein: contributed to study design, data analysis and interpretation, and preparation of the manuscript.

Dr Bautista: contributed to the study design, data analysis and interpretation, and preparation of the manuscript.

Dr Schumock: contributed to the study design, data analysis and interpretation, and preparation of the

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  • Cited by (0)

    Funding/Support: This work was supported by the National Institutes of Health [HL07605, HL101618] and the Agency for Healthcare Research and Quality [HS016967, HS017894].

    Reproduction of this article is prohibited without written permission from the American College of Chest Physicians (http://www.chestpubs.org/site/misc/reprints.xhtml).

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