Problems with primary care data quality: osteoporosis as an exemplar
Objective To report problems implementing a data quality programme in osteoporosis. Design Analysis of data extracted using Morbidity Information Query and Export Syntax (MIQUEST) from participating general practices’ systems and recommendations of practitioners who attended an action research works...
| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
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BCS, The Chartered Institute for IT
2004-11-01
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| Series: | Journal of Innovation in Health Informatics |
| Subjects: | |
| Online Access: | https://hijournal.bcs.org/index.php/jhi/article/view/120 |
| _version_ | 1819264257785593856 |
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| author | Simon DeLusignan Tom Valentin Tom Chan Nigel Hague Oliver Wood Jeremy VanVlymen Neil Dhoul |
| author_facet | Simon DeLusignan Tom Valentin Tom Chan Nigel Hague Oliver Wood Jeremy VanVlymen Neil Dhoul |
| author_sort | Simon DeLusignan |
| collection | DOAJ |
| description | Objective To report problems implementing a data quality programme in osteoporosis.
Design Analysis of data extracted using Morbidity Information Query and Export Syntax (MIQUEST) from participating general practices’ systems and recommendations of practitioners who attended an action research workshop.
Setting Computerised general practices using different Read code versions to record structured data.
Participants 78 practices predominantly from London and the south east, with representation from north east, north west and south west England.
Main outcome measures Patients at risk can be represented in many ways within structured data. Although fracture data exists, it is unclear which are fragility fractures. T-scores, the gold standard for measuring bone density, cannot be extracted using the UK’s standard data extraction tool, MIQUEST; instead manual searches had to be implemented. There is a hundredfold variation in data recording levels between practices. Therapy is more frequently recorded than diagnosis. A multidisciplinary forum of experienced practitioners proposed that a limited list of codes should be used.
Conclusions There is variability in inter-practice data quality. Some clinically important codes are lacking, and there are multiple ways that the same clinical concept can be represented. Different practice computer systems have different versions of Read code, making some data incompatible. Manual searching is still required to find data. Clinicians with an understanding of what data are clinically relevant need to have a stronger voice in the production of codes, and in the creation of recommended lists. |
| first_indexed | 2024-12-23T20:26:37Z |
| format | Article |
| id | doaj.art-a1d45bb7f8774dfba8579a420d054761 |
| institution | Directory Open Access Journal |
| issn | 2058-4555 2058-4563 |
| language | English |
| last_indexed | 2024-12-23T20:26:37Z |
| publishDate | 2004-11-01 |
| publisher | BCS, The Chartered Institute for IT |
| record_format | Article |
| series | Journal of Innovation in Health Informatics |
| spelling | doaj.art-a1d45bb7f8774dfba8579a420d0547612022-12-21T17:32:21ZengBCS, The Chartered Institute for ITJournal of Innovation in Health Informatics2058-45552058-45632004-11-0112314715610.14236/jhi.v12i3.12099Problems with primary care data quality: osteoporosis as an exemplarSimon DeLusignanTom ValentinTom ChanNigel HagueOliver WoodJeremy VanVlymenNeil DhoulObjective To report problems implementing a data quality programme in osteoporosis. Design Analysis of data extracted using Morbidity Information Query and Export Syntax (MIQUEST) from participating general practices’ systems and recommendations of practitioners who attended an action research workshop. Setting Computerised general practices using different Read code versions to record structured data. Participants 78 practices predominantly from London and the south east, with representation from north east, north west and south west England. Main outcome measures Patients at risk can be represented in many ways within structured data. Although fracture data exists, it is unclear which are fragility fractures. T-scores, the gold standard for measuring bone density, cannot be extracted using the UK’s standard data extraction tool, MIQUEST; instead manual searches had to be implemented. There is a hundredfold variation in data recording levels between practices. Therapy is more frequently recorded than diagnosis. A multidisciplinary forum of experienced practitioners proposed that a limited list of codes should be used. Conclusions There is variability in inter-practice data quality. Some clinically important codes are lacking, and there are multiple ways that the same clinical concept can be represented. Different practice computer systems have different versions of Read code, making some data incompatible. Manual searching is still required to find data. Clinicians with an understanding of what data are clinically relevant need to have a stronger voice in the production of codes, and in the creation of recommended lists.https://hijournal.bcs.org/index.php/jhi/article/view/120computerised medical recordgeneral practicemedical informaticsosteoporosisprimary carevocabularycontrolled – classification |
| spellingShingle | Simon DeLusignan Tom Valentin Tom Chan Nigel Hague Oliver Wood Jeremy VanVlymen Neil Dhoul Problems with primary care data quality: osteoporosis as an exemplar Journal of Innovation in Health Informatics computerised medical record general practice medical informatics osteoporosis primary care vocabulary controlled – classification |
| title | Problems with primary care data quality: osteoporosis as an exemplar |
| title_full | Problems with primary care data quality: osteoporosis as an exemplar |
| title_fullStr | Problems with primary care data quality: osteoporosis as an exemplar |
| title_full_unstemmed | Problems with primary care data quality: osteoporosis as an exemplar |
| title_short | Problems with primary care data quality: osteoporosis as an exemplar |
| title_sort | problems with primary care data quality osteoporosis as an exemplar |
| topic | computerised medical record general practice medical informatics osteoporosis primary care vocabulary controlled – classification |
| url | https://hijournal.bcs.org/index.php/jhi/article/view/120 |
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