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The validity of International Classification of Diseases, Ninth Revision, Clinical Modification diagnosis codes for identifying patients hospitalized for COPD exacerbations.

ABSTRACT: 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.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.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%).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.

SUBMITTER: Stein BD

PROVIDER: S-EPMC3251268 | biostudies-other | 2012 Jan

REPOSITORIES: biostudies-other

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Project description:BackgroundAdministrative health claims data have been used for research in neuro-ophthalmology, but the validity of International Classification of Diseases (ICD) codes for identifying neuro-ophthalmic conditions is unclear.Evidence acquisitionWe performed a systematic literature review to assess the validity of administrative claims data for identifying patients with neuro-ophthalmic disorders. Two reviewers independently reviewed all eligible full-length articles and used a standardized abstraction form to identify ICD code-based definitions for 9 neuro-ophthalmic conditions and their sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV). A quality assessment of eligible studies was also performed.ResultsEleven articles that met criteria for inclusion are as follows: 3 studies of idiopathic intracranial hypertension (PPV 54%-91% and NPV 74%-85%), 2 studies of giant cell arteritis (sensitivity 30%-96% and PPV 94%), 3 studies of optic neuritis (sensitivity 76%-99%, specificity 83%-100%, PPV 25%-100%, and NPV 98%-100%), 1 study of neuromyelitis optica (sensitivity 60%, specificity 100%, PPV 43%-100%, and NPV 98%-100%), 1 study of ocular motor cranial neuropathies (PPV 98%-99%), and 2 studies of myasthenia gravis (sensitivity 53%-97%, specificity 99%-100%, PPV 5%-90%, and NPV 100%). No studies met eligibility criteria for nonarteritic ischemic optic neuropathy, thyroid eye disease, and blepharospasm. Approximately 45.5% provided only one measure of diagnostic accuracy. Complete information about the validation cohorts, inclusion/exclusion criteria, data collection methods, and expertise of those reviewing charts for diagnostic accuracy was missing in 90.9%, 72.7%, 81.8%, and 36.4% of studies, respectively.ConclusionsFew studies have reported the validity of ICD codes for neuro-ophthalmic conditions. The range of diagnostic accuracy for some disorders and study quality varied widely. This should be taken into consideration when interpreting studies of neuro-ophthalmic conditions using administrative claims data.

Project description:To examine the validity of the International Classification of Diseases, 10th revision (ICD-10) codes for hyponatraemia in the nationwide population-based Danish National Registry of Patients (DNRP) among inpatients of all ages.Population-based validation study.All somatic hospitals in the North and Central Denmark Regions from 2006 through 2011.Patients of all ages admitted to hospital (n=819 701 individual patients) during the study period. The patient could be included in the study more than once, and our study did not restrict to patients with serum sodium measurements (total of n=2 186 642 hospitalisations).We validated ICD-10 discharge diagnoses of hyponatraemia recorded in the DNRP, using serum sodium measurements obtained from the laboratory information systems (LABKA) research database as the gold standard. One sodium value <135 mmol/L measured at any time during hospitalisation confirmed the diagnosis. We estimated sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) for ICD-10 codes for hyponatraemia overall and for cut-off points for increasing hyponatraemia severity.An ICD-10 code for hyponatraemia was recorded in the DNRP in 5850 of the 2 186 642 hospitalisations identified. According to laboratory measurements, however, hyponatraemia was present in 306 418 (14%) hospitalisations. Sensitivity of hyponatraemia diagnoses was 1.8% (95% CI 1.7% to 1.8%). For sodium values <115 mmol/L, sensitivity was 34.3% (95% CI 32.6% to 35.9%). The overall PPV was 92.5% (95% CI 91.8% to 93.1%) and decreased with increasing hyponatraemia severity. Specificity and NPV were high for all cut-off points (?99.8% and ?86.2%, respectively). Patients with hyponatraemia without a corresponding ICD-10 discharge diagnosis were younger and had higher Charlson Comorbidity Index scores than patients with hyponatraemia with a hyponatraemia code in the DNRP.ICD-10 codes for hyponatraemia in the DNRP have high specificity but very low sensitivity. Laboratory test results, not discharge diagnoses, should be used to ascertain hyponatraemia.

Project description:Administrative databases are increasingly used in research studies to capture clinical outcomes such as sepsis. This systematic review and meta-analysis examines the accuracy of International Classification of Diseases, 10th revision (ICD-10), codes for identifying sepsis in adult and pediatric patients.Data sourcesWe searched MEDLINE, EMBASE, Web of Science, CENTRAL, Epistemonikos, and McMaster Superfilters from inception to September 7, 2021.Study selectionWe included studies that validated the accuracy of sepsis ICD-10 codes against any reference standard.Data extractionThree authors, working in duplicate, independently extracted data. We conducted meta-analysis using a random effects model to pool sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV). We evaluated individual study risk of bias using the Quality Assessment of Diagnostic Accuracy Studies tool and assessed certainty in pooled diagnostic effect measures using the Grading of Recommendations Assessment, Development, and Evaluation framework.Data synthesisThirteen eligible studies were included in the qualitative synthesis and the meta-analysis. Eleven studies used manual chart review as the reference standard, and four studies used registry databases. Only one study evaluated pediatric patients exclusively. Compared with the reference standard of detailed chart review and/or registry databases, the pooled sensitivity for sepsis ICD-10 codes was 35% (95% CI, 22-48, low certainty), whereas the pooled specificity was 98% (95% CI: 98-99, low certainty). The PPV for ICD-10 codes ranged from 9.8% to 100% (median, 72.0%; interquartile range [IQR], 50.0-84.7%). NPV ranged from 54.7% to 99.1% (median, 95.9%; interquartile range, 85.5-98.3%).ConclusionsSepsis is undercoded in administrative databases. Future research is needed to explore if greater consistency in ICD-10 code definitions and enhanced quality measures for ICD-10 coders can improve the coding accuracy of sepsis in large databases.

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The validity of International Classification of Diseases, Ninth Revision, Clinical Modification diagnosis codes for identifying patients hospitalized for COPD exacerbations.

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