Geographic Variation in One-Year Recurrent Ischemic Stroke Rates for Elderly Medicare Beneficiaries in the USA

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Abstract

Background: While geographic disparities in stroke mortality are well documented, there are no data describing geographic variation in recurrent stroke. Accordingly, we evaluated geographic variations in 1-year recurrent ischemic stroke rates in the USA with adjustment for patient characteristics. Methods: One-year recurrent stroke rates for ischemic stroke (International Classification of Diseases, 9th Revision codes 433, 434 and 436) following hospital discharge were calculated by county for all fee-for-service Medicare beneficiaries from 2000 to 2002. The rates were standardized and smoothed using a bayesian conditional autoregressive model that was risk-standardized for patients’ age, gender, race/ethnicity, prior hospitalizations, Deyo comorbidity score, acute myocardial infarction, congestive heart failure, diabetes, hypertension, dementia, cancer, chronic obstructive pulmonary disease and obesity. Results: The overall 1-year recurrent stroke rate was 9.4% among 895,916 ischemic stroke patients (mean age: 78 years; 56.6% women; 86.6% White, 9.7% Black and 1.2% Latino/Hispanic). The rates varied by geographic region and were highest in the South and in parts of the West and Midwest. Regional variation was present for all racial/ethnic subgroups and persisted after adjustment for individual patient characteristics. Conclusions: Almost 1 in 10 hospitalized ischemic stroke patients was readmitted for an ischemic stroke within 1 year. There was heterogeneity in recurrence patterns by geographic region. Further work is needed to understand the reasons for this regional variability.

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Assessing validity of ICD-9-CM and ICD-10 administrative data in recording clinical conditions in a unique dually coded database.

Hude Quan, Bing Li, L. Duncan Saunders … (2008)

The goal of this study was to assess the validity of the International Classification of Disease, 10th Version (ICD-10) administrative hospital discharge data and to determine whether there were improvements in the validity of coding for clinical conditions compared with ICD-9 Clinical Modification (ICD-9-CM) data. We reviewed 4,008 randomly selected charts for patients admitted from January 1 to June 30, 2003 at four teaching hospitals in Alberta, Canada to determine the presence or absence of 32 clinical conditions and to assess the agreement between ICD-10 data and chart data. We then re-coded the same charts using ICD-9-CM and determined the agreement between the ICD-9-CM data and chart data for recording those same conditions. The accuracy of ICD-10 data relative to chart data was compared with the accuracy of ICD-9-CM data relative to chart data. Sensitivity values ranged from 9.3 to 83.1 percent for ICD-9-CM and from 12.7 to 80.8 percent for ICD-10 data. Positive predictive values ranged from 23.1 to 100 percent for ICD-9-CM and from 32.0 to 100 percent for ICD-10 data. Specificity and negative predictive values were consistently high for both ICD-9-CM and ICD-10 databases. Of the 32 conditions assessed, ICD-10 data had significantly higher sensitivity for one condition and lower sensitivity for seven conditions relative to ICD-9-CM data. The two databases had similar sensitivity values for the remaining 24 conditions. The validity of ICD-9-CM and ICD-10 administrative data in recording clinical conditions was generally similar though validity differed between coding versions for some conditions. The implementation of ICD-10 coding has not significantly improved the quality of administrative data relative to ICD-9-CM. Future assessments like this one are needed because the validity of ICD-10 data may get better as coders gain experience with the new coding system.

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Accuracy of Medicare claims-based diagnosis of acute myocardial infarction: estimating positive predictive value on the basis of review of hospital records.

Yuka Kiyota, Sebastian Schneeweiss, Robert J Glynn … (2004)

Many cardiovascular epidemiologic studies rely on diagnosis codes in health care claims databases. Despite important changes in the care and diagnosis of acute myocardial infarction (AMI), the validity of hospital discharge diagnosis codes for AMI in the US Medicare system has not been recently examined. Our objective was to examine the accuracy of International Classification of Diseases--ninth revision--Clinical Modifications (ICD-9-CM) discharge diagnosis codes and diagnosis-related groups (DRG) codes for AMI in a Medicare claims database. We sampled hospitalization episodes from Medicare beneficiaries in Pennsylvania during 1999, 2000, or both. We used Medicare data to identify patients with hospitalizations containing indicators of AMI (ICD-9-CM diagnosis codes 410.X0 and 410.X1 or DRG codes 121, 122, and 123). Hospital records for these episodes were reviewed by trained abstractors using World Health Organization criteria for diagnosing AMI. We then calculated the positive predictive value of Medicare claims-based definitions of AMI. Of 2200 hospitalization episodes with Medicare diagnosis codes suggestive of AMI, 2022 hospital records (91.9%) were obtained. The positive predictive value for a primary Medicare claims-based definition was 94.1% (95% CI, 93.0%-95.2%). Positive predictive values for alternative claims-based definitions ranged slightly, with the definition including DRG codes and length-of-stay restrictions yielding the highest positive predictive value, 95.4% (95% CI, 94.3%-96.4%). Subjects with a history of myocardial infarction had a significantly lower positive predictive value than subjects without a history of myocardial infarction (88.1% vs 94.6%, P <.001). In this study, we observed high positive predictive values for a Medicare claims-based diagnosis of AMI and a diagnosis based on structured hospital record review.

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The accuracy of Medicare's hospital claims data: progress has been made, but problems remain.

D Malenka, J Barón, Simon E. Fisher … (1992)

Health care databases provide a widely used source of data for health care research, but their accuracy remains uncertain. We analyzed data from the 1985 National DRG Validation Study, which carefully reabstracted and reassigned ICD-9-CM diagnosis and procedure codes from a national sample of 7050 medical records, to determine whether coding accuracy had improved since the Institute of Medicine studies of the 1970s and to assess the current coding accuracy of specific diagnoses and procedures. We defined agreement as the proportion of all reabstracted records that had the same principal diagnosis or procedure coded on both the original (hospital) record and on the reabstracted record. We also evaluated coding accuracy in 1985 using the concepts of diagnostic test evaluation. Overall, the percentage of agreement between the principal diagnosis on the reabstracted record and the original hospital record, when analyzed at the third digit, improved from 73.2% in 1977 to 78.2% in 1985. However, analysis of the 1985 data demonstrated that the accuracy of diagnosis and procedure coding varies substantially across conditions. Although some diagnoses and all major surgical procedures that we examined were accurately coded, the variability in the accuracy of diagnosis coding poses a problem that must be overcome if claims-based research is to achieve its full potential.

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Author and article information

Journal

Journal ID (publisher-id): NED

Journal ID (nlm-ta): Neuroepidemiology

Journal ID (doi): 10.1159/issn.0251-5350

Title: Neuroepidemiology

Publisher: S. Karger AG

ISSN (Print): 0251-5350

ISSN (Electronic): 1423-0208

Publication date Subscription-year: 2010

Publication date (Print): February 2010

Publication date (Electronic): 13 January 2010

Volume: 34

Issue: 2

Pages: 123-129

Affiliations

Divisions of ^aChronic Disease Epidemiology and ^bBiostatistics, Department of Epidemiology and Public Health, and ^cCenter for Perinatal, Pediatric and Environmental Epidemiology, Department of Epidemiology and Public Health, Yale University School of Medicine, New Haven, Conn., ^dDepartment of Medicine (Neurology), Duke Stroke Center, Center for Clinical Health Policy Research, Duke University and Durham VAMC, Durham, N.C., ^eDepartment of Biostatistics, School of Public Health, University of Alabama at Birmingham, Birmingham, Ala., and ^fDepartment of Preventive Medicine, Feinberg School of Medicine, Northwestern University, Chicago, Ill., USA

Article

Publisher ID: 274804 Pmcid ID: PMC2837886 Other ID: Neuroepidemiology 2010;34:123–129

DOI: 10.1159/000274804

PMC ID: PMC2837886

PubMed ID: 20068358

SO-VID: dbc1dd78-0718-4a37-aa2a-990f93e17203

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Copyright: All rights reserved. No part of this publication may be translated into other languages, reproduced or utilized in any form or by any means, electronic or mechanical, including photocopying, recording, microcopying, or by any information storage and retrieval system, without permission in writing from the publisher. Drug Dosage: The authors and the publisher have exerted every effort to ensure that drug selection and dosage set forth in this text are in accord with current recommendations and practice at the time of publication. However, in view of ongoing research, changes in government regulations, and the constant flow of information relating to drug therapy and drug reactions, the reader is urged to check the package insert for each drug for any changes in indications and dosage and for added warnings and precautions. This is particularly important when the recommended agent is a new and/or infrequently employed drug. Disclaimer: The statements, opinions and data contained in this publication are solely those of the individual authors and contributors and not of the publishers and the editor(s). The appearance of advertisements or/and product references in the publication is not a warranty, endorsement, or approval of the products or services advertised or of their effectiveness, quality or safety. The publisher and the editor(s) disclaim responsibility for any injury to persons or property resulting from any ideas, methods, instructions or products referred to in the content or advertisements.

History

Date received : 12 July 2009

Date accepted : 10 November 2009

Page count

Figures: 2, Tables: 2, References: 36, Pages: 7

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Geographic Variation in One-Year Recurrent Ischemic Stroke Rates for Elderly Medicare Beneficiaries in the USA

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Karger: Neurology and Neuroscience

Most cited references 22

Assessing validity of ICD-9-CM and ICD-10 administrative data in recording clinical conditions in a unique dually coded database.

Accuracy of Medicare claims-based diagnosis of acute myocardial infarction: estimating positive predictive value on the basis of review of hospital records.

The accuracy of Medicare's hospital claims data: progress has been made, but problems remain.

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