Accuracy of routinely-collected healthcare data for identifying motor neurone disease cases: A systematic review.
<h4>Background</h4>Motor neurone disease (MND) is a rare neurodegenerative condition, with poorly understood aetiology. Large, population-based, prospective cohorts will enable powerful studies of the determinants of MND, provided identification of disease cases is sufficiently accurate....
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Public Library of Science (PLoS)
2017-01-01
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| Series: | PLoS ONE |
| Online Access: | https://doi.org/10.1371/journal.pone.0172639 |
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| author | Sophie Horrocks Tim Wilkinson Christian Schnier Amanda Ly Rebecca Woodfield Kristiina Rannikmäe Terence J Quinn Cathie L M Sudlow |
| author_facet | Sophie Horrocks Tim Wilkinson Christian Schnier Amanda Ly Rebecca Woodfield Kristiina Rannikmäe Terence J Quinn Cathie L M Sudlow |
| author_sort | Sophie Horrocks |
| collection | DOAJ |
| description | <h4>Background</h4>Motor neurone disease (MND) is a rare neurodegenerative condition, with poorly understood aetiology. Large, population-based, prospective cohorts will enable powerful studies of the determinants of MND, provided identification of disease cases is sufficiently accurate. Follow-up in many such studies relies on linkage to routinely-collected health datasets. We systematically evaluated the accuracy of such datasets in identifying MND cases.<h4>Methods</h4>We performed an electronic search of MEDLINE, EMBASE, Cochrane Library and Web of Science for studies published between 01/01/1990-16/11/2015 that compared MND cases identified in routinely-collected, coded datasets to a reference standard. We recorded study characteristics and two key measures of diagnostic accuracy-positive predictive value (PPV) and sensitivity. We conducted descriptive analyses and quality assessments of included studies.<h4>Results</h4>Thirteen eligible studies provided 13 estimates of PPV and five estimates of sensitivity. Twelve studies assessed hospital and/or death certificate-derived datasets; one evaluated a primary care dataset. All studies were from high income countries (UK, Europe, USA, Hong Kong). Study methods varied widely, but quality was generally good. PPV estimates ranged from 55-92% and sensitivities from 75-93%. The single (UK-based) study of primary care data reported a PPV of 85%.<h4>Conclusions</h4>Diagnostic accuracy of routinely-collected health datasets is likely to be sufficient for identifying cases of MND in large-scale prospective epidemiological studies in high income country settings. Primary care datasets, particularly from countries with a widely-accessible national healthcare system, are potentially valuable data sources warranting further investigation. |
| format | Article |
| id | doaj-art-97f6559bd2b04558ba1eb95790daa3aa |
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| issn | 1932-6203 |
| language | English |
| publishDate | 2017-01-01 |
| publisher | Public Library of Science (PLoS) |
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| series | PLoS ONE |
| spelling | doaj-art-97f6559bd2b04558ba1eb95790daa3aa2025-08-20T02:20:41ZengPublic Library of Science (PLoS)PLoS ONE1932-62032017-01-01122e017263910.1371/journal.pone.0172639Accuracy of routinely-collected healthcare data for identifying motor neurone disease cases: A systematic review.Sophie HorrocksTim WilkinsonChristian SchnierAmanda LyRebecca WoodfieldKristiina RannikmäeTerence J QuinnCathie L M Sudlow<h4>Background</h4>Motor neurone disease (MND) is a rare neurodegenerative condition, with poorly understood aetiology. Large, population-based, prospective cohorts will enable powerful studies of the determinants of MND, provided identification of disease cases is sufficiently accurate. Follow-up in many such studies relies on linkage to routinely-collected health datasets. We systematically evaluated the accuracy of such datasets in identifying MND cases.<h4>Methods</h4>We performed an electronic search of MEDLINE, EMBASE, Cochrane Library and Web of Science for studies published between 01/01/1990-16/11/2015 that compared MND cases identified in routinely-collected, coded datasets to a reference standard. We recorded study characteristics and two key measures of diagnostic accuracy-positive predictive value (PPV) and sensitivity. We conducted descriptive analyses and quality assessments of included studies.<h4>Results</h4>Thirteen eligible studies provided 13 estimates of PPV and five estimates of sensitivity. Twelve studies assessed hospital and/or death certificate-derived datasets; one evaluated a primary care dataset. All studies were from high income countries (UK, Europe, USA, Hong Kong). Study methods varied widely, but quality was generally good. PPV estimates ranged from 55-92% and sensitivities from 75-93%. The single (UK-based) study of primary care data reported a PPV of 85%.<h4>Conclusions</h4>Diagnostic accuracy of routinely-collected health datasets is likely to be sufficient for identifying cases of MND in large-scale prospective epidemiological studies in high income country settings. Primary care datasets, particularly from countries with a widely-accessible national healthcare system, are potentially valuable data sources warranting further investigation.https://doi.org/10.1371/journal.pone.0172639 |
| spellingShingle | Sophie Horrocks Tim Wilkinson Christian Schnier Amanda Ly Rebecca Woodfield Kristiina Rannikmäe Terence J Quinn Cathie L M Sudlow Accuracy of routinely-collected healthcare data for identifying motor neurone disease cases: A systematic review. PLoS ONE |
| title | Accuracy of routinely-collected healthcare data for identifying motor neurone disease cases: A systematic review. |
| title_full | Accuracy of routinely-collected healthcare data for identifying motor neurone disease cases: A systematic review. |
| title_fullStr | Accuracy of routinely-collected healthcare data for identifying motor neurone disease cases: A systematic review. |
| title_full_unstemmed | Accuracy of routinely-collected healthcare data for identifying motor neurone disease cases: A systematic review. |
| title_short | Accuracy of routinely-collected healthcare data for identifying motor neurone disease cases: A systematic review. |
| title_sort | accuracy of routinely collected healthcare data for identifying motor neurone disease cases a systematic review |
| url | https://doi.org/10.1371/journal.pone.0172639 |
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