Validation of claims‐based diagnostic and procedure codes for cardiovascular and gastrointestinal serious adverse events in a commercially‐insured population

Wahl, Peter; Rodgers, Keith; Schneeweiß, Sebastian; Gage, Brian F.; Butler, Javed; Wilmer, Charles; Nash, Marshall; Esper, Gregory J.; Gitlin, Norman; Osborn, Neal; Short, Louise J.; Bohn, Rhonda L.

doi:10.1002/pds.1924

Cited by 156 publications

(128 citation statements)

References 13 publications

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“…Disease surveillance and quality‐of‐care studies frequently use information from administrative claims databases, such as Medicare, by identifying patients with specific conditions based on International Classification of Diseases, Ninth Revision, Clinical Modification (ICD‐9‐CM) codes. Studies comparing the accuracy of ICD‐9‐CM codes with medical record review find variations in agreement depending on code selection,2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18 as well as patient characteristics, such as age, race/ethnicity,10, 11 sex,11 and length of hospitalization 3. Aside from teaching hospital status10 and hospital departments,16 potential variations in accuracy based on other hospital characteristics are largely unknown.…”

Section: Introductionmentioning

confidence: 99%

Accuracy of ICD‐9‐CM Codes by Hospital Characteristics and Stroke Severity: Paul Coverdell National Acute Stroke Program

Chang

Lichtman

Goldstein

et al. 2016

JAHA

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BackgroundEpidemiological and health services research often use International Classification of Diseases, Ninth Revision, Clinical Modification (ICD‐9‐CM) codes to identify patients with clinical conditions in administrative databases. We determined whether there are systematic variations between stroke patient clinical diagnoses and ICD‐9‐CM codes, stratified by hospital characteristics and stroke severity.Methods and ResultsWe used the records of patients discharged from hospitals participating in the Paul Coverdell National Acute Stroke Program in 2013. Within this stroke‐enriched cohort, we compared agreement between the attending physician's clinical diagnosis and principal ICD‐9‐CM code and determined whether disagreements varied by hospital characteristics (presence of a stroke unit, stroke team, number of hospital beds, and hospital location). For patients with a documented National Institutes of Health Stroke Scale score at admission, we assessed whether diagnostic agreement varied by stroke severity. Agreement was generally high (>89%); differences between the physician diagnosis and ICD‐9‐CM codes were primarily attributed to discordance between ischemic stroke and transient ischemic attack (TIA), and subarachnoid and intracerebral hemorrhage. Agreement was higher for patients in metropolitan hospitals with stroke units, stroke teams, and >200 beds (all P<0.001). Agreement was lowest (60.3%) for rural hospitals with ≤200 beds and without stroke units or teams. Agreement was also lower for milder (94.9%) versus more‐severe (96.4%) ischemic strokes (P<0.001).ConclusionsWe identified disagreements in stroke/TIA coding by hospital characteristics and stroke severity, particularly for milder ischemic strokes. Such systematic variations in ICD‐9‐CM coding practices can affect stroke case identification in epidemiological studies and may have implications for hospital‐level quality metrics.

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Section: Introductionmentioning

confidence: 99%

Accuracy of ICD‐9‐CM Codes by Hospital Characteristics and Stroke Severity: Paul Coverdell National Acute Stroke Program

Chang

Lichtman

Goldstein

et al. 2016

JAHA

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“…In this regard, high specificity of the outcome is preferable to high sensitivity, as the relative risk estimates are unbiased when specificity approaches 100% [123]. It has been shown that claims data can identify cardiovascular endpoints with very high specificity, resulting in relatively small potential for bias associated with misclassification of the outcome [124][125][126][127][128]. Among the evaluated literature, few explorative analyses assessed the potential effect of outcome misclassification on the study estimates [68,70].…”

Section: Other Issuesmentioning

confidence: 99%

Observational studies of the association between glucose-lowering medications and cardiovascular outcomes: addressing methodological limitations

et al. 2014

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Background Recent years have witnessed a growing body of observational literature on the association between glucose-lowering treatments and cardiovascular disease. However, many of the studies are based on designs or analyses that inadequately address the methodological challenges involved. Methods We reviewed recent observational literature on the association between glucose-lowering medications and cardiovascular outcomes and assessed the design and analysis methods used, with a focus on their ability to address specific methodological challenges. We describe and illustrate these methodological issues and their impact on observed associations, providing examples from the reviewed literature. We suggest approaches that may be employed to manage these methodological challenges.Results From the evaluation of 81 publications of observational investigations assessing the association between glucose-lowering treatments and cardiovascular outcomes, we identified the following methodological challenges: 1) handling of temporality in administrative databases; 2) handling of risks that vary with time and treatment duration; 3) definitions of the exposure risk window; 4) handling of exposures that change over time; and 5) handling of confounding by indication. Most of these methodological challenges may be suitably addressed through application of appropriate methods. Conclusions/interpretation Observational research plays an increasingly important role in the evaluation of the clinical effects of diabetes treatment. Implementation of appropriate research methods holds the promise of reducing the potential for spurious findings and the risk that the spurious findings will mislead the medical community about risks and benefits of diabetes medications.

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“…The PPV of this algorithm is 86%, which is comparable to other peer-reviewed algorithms. 16 Other bleeding was defined as genitourinary bleeding, hemopericardium, hemoperitoneum, hemarthrosis, epistaxis, hemoptysis, hemorrhage from throat, and unspecified hemorrhage. 15 Ischemic stroke was defined based on the presence of ICD-9-CM codes 434.xx (occlusion of cerebral arteries) and 436.xx (acute but illdefined cerebrovascular disease) as the primary discharge diagnosis in any inpatient claim following the index date.…”

Section: Definition Of Outcomesmentioning

confidence: 99%

Comparative effectiveness of direct oral anticoagulants and warfarin in patients with cancer and atrial fibrillation

et al. 2018

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Validation of claims‐based diagnostic and procedure codes for cardiovascular and gastrointestinal serious adverse events in a commercially‐insured population

Abstract: The results suggest that, for certain adverse events, claims data can serve as the basis for pharmacoepidemiology research and drug safety surveillance in the US.

Cited by 156 publications

References 13 publications

Accuracy of ICD‐9‐CM Codes by Hospital Characteristics and Stroke Severity: Paul Coverdell National Acute Stroke Program

Accuracy of ICD‐9‐CM Codes by Hospital Characteristics and Stroke Severity: Paul Coverdell National Acute Stroke Program

Observational studies of the association between glucose-lowering medications and cardiovascular outcomes: addressing methodological limitations

Comparative effectiveness of direct oral anticoagulants and warfarin in patients with cancer and atrial fibrillation

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