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      Accuracy of routinely collected hospital administrative discharge data and death certificate ICD-10 diagnostic coding in progressive supranuclear palsy and corticobasal syndrome: a systematic review and validation study

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          Abstract

          Background

          We conducted a systematic review to identify existing ICD-10 coding validation studies in progressive supranuclear palsy and corticobasal syndrome [PSP/CBS]) and, in a new study, evaluated the accuracy of ICD-10 diagnostic codes for PSP/CBS in Scottish hospital inpatient and death certificate data.

          Methods

          Original studies that assessed the accuracy of specific ICD-10 diagnostic codes in PSP/CBS were sought. Separately, we estimated the positive predictive value (PPV) of specific codes for PSP/CBS in inpatient hospital data (SMR01, SMR04) compared to clinical diagnosis in four regions. Sensitivity was assessed in one region due to a concurrent prevalence study. For PSP, the consistency of the G23.1 code in inpatient and death certificate coding was evaluated across Scotland.

          Results

          No previous ICD-10 validation studies were identified. 14,767 records (SMR01) and 1497 records (SMR04) were assigned the candidate ICD-10 diagnostic codes between February 2011 and July 2019. The best PPV was achieved with G23.1 (1.00, 95% CI 0.93–1.00) in PSP and G23.9 in CBS (0.20, 95% CI 0.04–0.62). The sensitivity of G23.1 for PSP was 0.52 (95% CI 0.33–0.70) and G31.8 for CBS was 0.17 (95% CI 0.05–0.45). Only 38.1% of deceased G23.1 hospital-coded cases also had this coding on their death certificate: the majority (49.0%) erroneously assigned the G12.2 code.

          Discussion

          The high G23.1 PPV in inpatient data shows it is a useful tool for PSP case ascertainment, but death certificate coding is inaccurate. The PPV and sensitivity of existing ICD-10 codes for CBS are poor due to a lack of a specific code.

          Supplementary Information

          The online version contains supplementary material available at 10.1007/s00415-024-12280-w.

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          Most cited references17

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          What are the Read Codes?

          The Read Codes were initially developed by a general practitioner, Dr James Read from Loughborough, in the early 1980s and rapidly gained acceptance by general practitioners as a popular and useful mechanism for storing structured information about patients in individual, patient-based records, which were beginning to become popular in a few general practices at the time. This short article aims to explain the past and future development of the coding system in the National Health Service as a whole.
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            Accuracy of Electronic Health Record Data for Identifying Stroke Cases in Large-Scale Epidemiological Studies: A Systematic Review from the UK Biobank Stroke Outcomes Group

            Objective Long-term follow-up of population-based prospective studies is often achieved through linkages to coded regional or national health care data. Our knowledge of the accuracy of such data is incomplete. To inform methods for identifying stroke cases in UK Biobank (a prospective study of 503,000 UK adults recruited in middle-age), we systematically evaluated the accuracy of these data for stroke and its main pathological types (ischaemic stroke, intracerebral haemorrhage, subarachnoid haemorrhage), determining the optimum codes for case identification. Methods We sought studies published from 1990-November 2013, which compared coded data from death certificates, hospital admissions or primary care with a reference standard for stroke or its pathological types. We extracted information on a range of study characteristics and assessed study quality with the Quality Assessment of Diagnostic Studies tool (QUADAS-2). To assess accuracy, we extracted data on positive predictive values (PPV) and—where available—on sensitivity, specificity, and negative predictive values (NPV). Results 37 of 39 eligible studies assessed accuracy of International Classification of Diseases (ICD)-coded hospital or death certificate data. They varied widely in their settings, methods, reporting, quality, and in the choice and accuracy of codes. Although PPVs for stroke and its pathological types ranged from 6–97%, appropriately selected, stroke-specific codes (rather than broad cerebrovascular codes) consistently produced PPVs >70%, and in several studies >90%. The few studies with data on sensitivity, specificity and NPV showed higher sensitivity of hospital versus death certificate data for stroke, with specificity and NPV consistently >96%. Few studies assessed either primary care data or combinations of data sources. Conclusions Particular stroke-specific codes can yield high PPVs (>90%) for stroke/stroke types. Inclusion of primary care data and combining data sources should improve accuracy in large epidemiological studies, but there is limited published information about these strategies.
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              Development and use of reporting guidelines for assessing the quality of validation studies of health administrative data.

              Validation of health administrative data for identifying patients with different health states (diseases and conditions) is a research priority, but no guidelines exist for ensuring quality. We created reporting guidelines for studies validating administrative data identification algorithms and used them to assess the quality of reporting of validation studies in the literature. Using Standards for Reporting of Diagnostic accuracy (STARD) criteria as a guide, we created a 40-item checklist of items with which identification accuracy studies should be reported. A systematic review identified studies that validated identification algorithms using administrative data. We used the checklist to assess the quality of reporting. In 271 included articles, goals and data sources were well reported but few reported four or more statistical estimates of accuracy (36.9%). In 65.9% of studies reporting positive predictive value (PPV)/negative predictive value (NPV), the prevalence of disease in the validation cohort was higher than in the administrative data, potentially falsely elevating predictive values. Subgroup accuracy (53.1%) and 95% confidence intervals for accuracy measures (35.8%) were also underreported. The quality of studies validating health states in the administrative data varies, with significant deficits in reporting of markers of diagnostic accuracy, including the appropriate estimation of PPV and NPV. These omissions could lead to misclassification bias and incorrect estimation of incidence and health services utilization rates. Use of a reporting checklist, such as the one created for this study by modifying the STARD criteria, could improve the quality of reporting of validation studies, allowing for accurate application of algorithms, and interpretation of research using health administrative data. Copyright © 2011 Elsevier Inc. All rights reserved.
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                Author and article information

                Contributors
                diane.swallow@abdn.ac.uk
                Journal
                J Neurol
                J Neurol
                Journal of Neurology
                Springer Berlin Heidelberg (Berlin/Heidelberg )
                0340-5354
                1432-1459
                12 April 2024
                12 April 2024
                2024
                : 271
                : 6
                : 2929-2937
                Affiliations
                Institute of Applied Health Sciences, University of Aberdeen, ( https://ror.org/016476m91) Polwarth Building, Foresterhill, Aberdeen, AB25 2ZD UK
                Author information
                http://orcid.org/0000-0002-0994-3561
                Article
                12280
                10.1007/s00415-024-12280-w
                11136796
                38609666
                b1ed9204-b353-4672-b427-9749732b80c2
                © The Author(s) 2024

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 9 February 2024
                : 25 February 2024
                Funding
                Funded by: FundRef http://dx.doi.org/10.13039/501100000589, Chief Scientist Office;
                Award ID: CAF/PSP/16/01
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/100011707, PSP Association;
                Award ID: CAF/PSP/16/01
                Award Recipient :
                Categories
                Original Communication
                Custom metadata
                © Springer-Verlag GmbH Germany, part of Springer Nature 2024

                Neurology
                progressive supranuclear palsy,corticobasal degeneration,positive predictive value,sensitivity,icd-10 diagnostic codes,death certificate

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