Validity of AHRQ patient safety indicators derived from ICD-10 hospital discharge abstract data (chart review study)

Quan, Hude; Eastwood, Catherine; Cunningham, Ceara Tess; Liu, Mingfu; Flemons, W. Ward; Coster, Carolyn De; Ghali, William A.

doi:10.1136/bmjopen-2013-003716

Cited by 57 publications

(51 citation statements)

References 20 publications

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“…It is possible given this, that the predictive value of the algorithm would be less in populations with lower prevalence of disease. Results will need to be reassessed after introduction of the ICD-10 coding system, which would affect prospective cases of VTE after October 1, 2015[15]. Any algorithm generated for using ICD coding in administrative data will require constant modification and updating over time to account for changes and additions to the ICD codes.…”

Section: Discussionmentioning

confidence: 99%

Improving accuracy of International Classification of Diseases codes for venous thromboembolism in administrative data

Sanfilippo¹,

Wang²,

Gage³

et al. 2015

Thrombosis Research

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BACKGROUND Increasingly, clinicians and researchers are using administrative data for clinical and outcomes research. However, they continue to question the accuracy of using International Classification of Diseases 9th Revision (ICD-9) codes alone to capture diagnoses, especially venous thromboembolism (VTE), in administrative data. OBJECTIVES We tested the hypothesis that incorporation of treatment data and/or common procedural terminology (CPT) codes could improve accuracy of administrative data in detecting VTE. RESEARCH DESIGN Using the Veterans Affairs Central Cancer Registry, we compared three competing algorithms by performing three cross-sectional studies. Algorithm 1 identified patients by ICD-9 codes alone. Algorithm 2 required VTE treatment in addition to ICD-9 codes. Algorithm 3 required a VTE diagnostic CPT code in addition to treatment and ICD-9 criteria. RESULTS The accuracy of ICD-9 codes alone for detection of VTE was marginal, with a PPV of 72%. The PPV was improved to 91% after addition of treatment data (algorithm 2). As compared to algorithm 2, addition of CPT codes (algorithm 3) did not significantly increase the accuracy of detecting VTE (PPV 92%), but decreased sensitivity from 72% to 67%. CONCLUSIONS Accuracy of VTE detection significantly improved with addition of treatment data to ICD-9 codes. This approach should facilitate use of administrative data to assess the incidence, epidemiology, and outcomes of VTE.

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Section: Discussionmentioning

confidence: 99%

Improving accuracy of International Classification of Diseases codes for venous thromboembolism in administrative data

Sanfilippo¹,

Wang²,

Gage³

et al. 2015

Thrombosis Research

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“…This limitation became apparent during our validation study, as there were insufficient cases of pressure ulcers and fall-related injuries identified during 1 fiscal year. In a large validation study of patient safety indicators using administrative hospitalization data, similar challenges in reaching the target sample size for some indicators were reported 41. Fifteen (5.0%) of the 300 randomly selected records were missing one or more key documents.…”

Section: Discussionmentioning

confidence: 80%

Validating administrative data for the detection of adverse events in older hospitalized patients

Ackroyd‐Stolarz¹,

Bowles²,

Giffin³

2014

DHPS

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Older hospitalized patients are at risk of experiencing adverse events including, but not limited to, hospital-acquired pressure ulcers, fall-related injuries, and adverse drug events. A significant challenge in monitoring and managing adverse events is lack of readily accessible information on their occurrence.PurposeThe objective of this retrospective cross-sectional study was to validate diagnostic codes for pressure ulcers, fall-related injuries, and adverse drug events found in routinely collected administrative hospitalization data.MethodsAll patients 65 years of age or older discharged between April 1, 2009 and March 31, 2011 from a provincial academic health sciences center in Canada were eligible for inclusion in the validation study. For each of the three types of adverse events, a random sample of 50 patients whose records were positive and 50 patients whose records were not positive for an adverse event was sought for review in the validation study (n=300 records in total). A structured health record review was performed independently by two health care providers with experience in geriatrics, both of whom were unaware of the patient’s status with respect to adverse event coding. A physician reviewed 40 records (20 reviewed by each health care provider) to establish interrater agreement.ResultsA total of 39 pressure ulcers, 56 fall-related injuries, and 69 adverse drug events were identified through health record review. Of these, 34 pressure ulcers, 54 fall-related injuries, and 47 adverse drug events were also identified in administrative data. Overall, the diagnostic codes for adverse events had a sensitivity and specificity exceeding 0.67 (95% confidence interval [CI]: 0.56–0.99) and 0.89 (95% CI: 0.72–0.99), respectively.ConclusionIt is feasible and valid to identify pressure ulcers, fall-related injuries, and adverse drug events in older hospitalized patients using routinely collected administrative hospitalization data. The information is relatively inexpensive and easy to access with no impact on clinical staff.

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“…We derived our weights using statistical criteria, while clinical knowledge might be needed to determine each comorbidity's value. Since we used codes assigned in routine data, the capture of the comorbidities could be in uenced by other factors, such as physician and nurse documentation, code assignment accuracy, and the possibility that capture of comorbidities is biased towards those for which the Swiss DRG / MDC pays more [46,42]. Moreover, current comorbidity indices are not suitable predictors of patient-centred outcomes like rehabilitation, readmission, fee-for-services while weightings might differ in restricted cohorts, other outcomes and countries [27].…”

Section: Discussionmentioning

confidence: 99%

Comparing Charlson and Elixhauser comorbidity indices with different weightings to predict in-hospital mortality: an analysis of national inpatient data

Sharma

Schwendimann

Endrich

et al. 2020

Preprint

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Background: Understanding how comorbidity measures contribute to patient mortality are essential both to describe patient health status and to adjust for risks and potential confounding. The Charlson and Elixhauser comorbidity indices are well-established for risk adjustment and mortality prediction. Still, a different set of comorbidity weights might improve the prediction of in-hospital mortality. The present study, therefore, aimed to derive a set of new population-based Elixhauser comorbidity weightings, to validate and compare them against those of the Charlson and Elixhauser-based van Walraven weightings in an adult in-patient population-based cohort of general hospitals. Methods: Retrospective analysis was conducted with routine data of 102 Swiss general hospitals (2012–2017) for 6.09 million inpatient cases. To derive the population-based weightings for the Elixhauser comorbidity index, we randomly halved the inpatient data and validated the results of part 1 alongside the established weighting systems in part 2, to predict in-hospital mortality. Charlson and van Walraven weightings were applied to Charlson and Elixhauser comorbidity indices. Derivation and validation of weightings were conducted with generalized additive models adjusted for age, gender and hospital types. Results: Overall, the population-based weights’ c-statistic (0.867, 95% CI: 0.865–0.868) was consistently, yet minimally higher than Elixhauser-van Walraven’s (0.863, 95% CI: 0.862-0.864) and Charlson’s (0.850, 95% CI: 0.849–0.851) in the derivation and validation groups. The net reclassification improvement of new weights improved the predictive performance by 1.6% on the Elixhauser-van Walraven and 4.9% on the Charlson weightings.Conclusions: All weightings confirmed previous results with the national dataset. The new population-based weightings model improved slightly the prediction of in-hospital mortality in Swiss hospitals. The newly derive weights support patient population-based analysis of in-hospital mortality and seek country or specific cohort-based weightings.

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Validity of AHRQ patient safety indicators derived from ICD-10 hospital discharge abstract data (chart review study)

Cited by 57 publications

References 20 publications

Improving accuracy of International Classification of Diseases codes for venous thromboembolism in administrative data

Improving accuracy of International Classification of Diseases codes for venous thromboembolism in administrative data

Validating administrative data for the detection of adverse events in older hospitalized patients

Comparing Charlson and Elixhauser comorbidity indices with different weightings to predict in-hospital mortality: an analysis of national inpatient data

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