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Adverse drug events in German hospital routine data: A validation of International Classification of Diseases, 10th revision (ICD-10) diagnostic codes.

ABSTRACT: Adverse drug events (ADEs) during hospital stays are a significant problem of healthcare systems. Established monitoring systems lack completeness or are cost intensive. Routinely assigned International Statistical Classification of Diseases and Related Health Problems (ICD) codes could complement existing systems for ADE identification. To analyze the potential of using routine data for ADE detection, the validity of a set of ICD codes was determined focusing on hospital-acquired events.The study utilized routine data from four German hospitals covering the years 2014 and 2015. A set of ICD, 10th Revision, German Modification (ICD-10-GM) diagnoses coded most frequently in the routine data and identified as codes indicating ADEs was analyzed. Data from psychiatric and psychotherapeutic departments were excluded. Retrospective chart review was performed to calculate positive predictive values (PPV) and sensitivity.Of 807 reviewed ADE codes, 91.2% (95%-confidence interval: 89.0, 93.1) were identified as disease in the medical records and 65.1% (61.7, 68.3) were confirmed as ADE. For code groups being predominantly hospital-acquired, 78.5% (73.7, 82.9) were confirmed as ADE, ranging from 68.5% to 94.4% dependent on the ICD code. However, sensitivity of inpatient ADEs was relatively low. 49.7% (45.2, 54.2) of 495 identified hospital-acquired ADEs were coded as disease in the routine data, from which a subgroup of 12.1% (9.4, 15.3) was coded as drug-associated disease.ICD codes from routine data can provide an important contribution to the development and improvement of ADE monitoring systems. Documentation quality is crucial to further increase the PPV, and actions against under-reporting of ADEs in routine data need to be taken.

SUBMITTER: Kuklik N

PROVIDER: S-EPMC5667751 | biostudies-literature | 2017

REPOSITORIES: biostudies-literature

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Adverse drug events in German hospital routine data: A validation of International Classification of Diseases, 10th revision (ICD-10) diagnostic codes.

Kuklik Nils N Stausberg Jürgen J Jöckel Karl-Heinz KH

PloS one 20171102 11

<h4>Objective</h4>Adverse drug events (ADEs) during hospital stays are a significant problem of healthcare systems. Established monitoring systems lack completeness or are cost intensive. Routinely assigned International Statistical Classification of Diseases and Related Health Problems (ICD) codes could complement existing systems for ADE identification. To analyze the potential of using routine data for ADE detection, the validity of a set of ICD codes was determined focusing on hospital-acqui ...[more]

PMID: 29095926

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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.

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:PURPOSE:We previously developed and validated informatic algorithms that used International Classification of Diseases 9th revision (ICD9)-based diagnostic and procedure codes to detect the presence and timing of cancer recurrence (the RECUR Algorithms). In 2015, ICD10 replaced ICD9 as the worldwide coding standard. To understand the impact of this transition, we evaluated the performance of the RECUR Algorithms after incorporating ICD10 codes. METHODS:Using publicly available translation tables along with clinician and other expertise, we updated the algorithms to include ICD10 codes as additional input variables. We evaluated the performance of the algorithms using gold standard recurrence measures associated with a contemporary cohort of patients with stage I to III breast, colorectal, and lung (excluding IIIB) cancer and derived performance measures, including the area under the receiver operating curve, average absolute prediction error, and correct classification rate. These values were compared with the performance measures derived from the validation of the original algorithms. RESULTS:A total of 659 colorectal, 280 lung, and 2,053 breast cancer cases were identified. Area under the receiver operating curve derived from the updated algorithms was 89.0% (95% CI, 82.3% to 95.7%), 88.9% (95% CI, 79.3% to 98.2%), and 80.5% (95% CI, 72.8% to 88.2%) for the colorectal, lung, and breast cancer algorithms, respectively. Average absolute prediction errors for recurrence timing were 2.7 (SE, 11.3%), 2.4 (SE, 10.4%), and 5.6 months (SE, 21.8%), respectively, and timing estimates were within 6 months of actual recurrence for more than 80% of colorectal, more than 90% of lung, and more than 50% of breast cancer cases using the updated algorithm. CONCLUSION:Performance measures derived from the updated and original algorithms had overlapping confidence intervals, suggesting that the ICD9 to ICD10 transition did not affect the RECUR Algorithm performance.

Dataset Information

Adverse drug events in German hospital routine data: A validation of International Classification of Diseases, 10th revision (ICD-10) diagnostic codes.

Publications

Adverse drug events in German hospital routine data: A validation of International Classification of Diseases, 10th revision (ICD-10) diagnostic codes.

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