Investigating the detection of adverse drug events in a UK general practice electronic health-care database
Data-mining techniques have frequently been developed for Spontaneous reporting databases. These techniques aim to find adverse drug events accurately and efficiently. Spontaneous reporting databases are prone to missing information,under reporting and incorrect entries. This often results in a de...
| Main Authors: | , , , , , |
|---|---|
| Format: | Conference or Workshop Item |
| Published: |
2011
|
| Online Access: | https://eprints.nottingham.ac.uk/2025/ |
| _version_ | 1848790707399032832 |
|---|---|
| author | Reps, Jenna Feyereisl, Jan Garibaldi, Jonathan M. Aickelin, Uwe Gibson, Jack E. Hubbard, Richard B. |
| author_facet | Reps, Jenna Feyereisl, Jan Garibaldi, Jonathan M. Aickelin, Uwe Gibson, Jack E. Hubbard, Richard B. |
| author_sort | Reps, Jenna |
| building | Nottingham Research Data Repository |
| collection | Online Access |
| description | Data-mining techniques have frequently been developed
for Spontaneous reporting databases. These techniques
aim to find adverse drug events accurately and efficiently. Spontaneous reporting databases are prone to missing information,under reporting and incorrect entries. This often results in a detection lag or prevents the detection of some adverse drug events. These limitations do not occur in electronic healthcare databases. In this paper, existing methods developed for spontaneous reporting databases are implemented on both a
spontaneous reporting database and a general practice electronic health-care database and compared. The results suggests that the application of existing methods to the general practice database may help find signals that have gone undetected when using the spontaneous reporting system database. In addition the general practice database provides far more supplementary information, that if incorporated in analysis could provide a wealth of information for identifying adverse events more
accurately. |
| first_indexed | 2025-11-14T18:16:53Z |
| format | Conference or Workshop Item |
| id | nottingham-2025 |
| institution | University of Nottingham Malaysia Campus |
| institution_category | Local University |
| last_indexed | 2025-11-14T18:16:53Z |
| publishDate | 2011 |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | nottingham-20252020-05-04T20:24:30Z https://eprints.nottingham.ac.uk/2025/ Investigating the detection of adverse drug events in a UK general practice electronic health-care database Reps, Jenna Feyereisl, Jan Garibaldi, Jonathan M. Aickelin, Uwe Gibson, Jack E. Hubbard, Richard B. Data-mining techniques have frequently been developed for Spontaneous reporting databases. These techniques aim to find adverse drug events accurately and efficiently. Spontaneous reporting databases are prone to missing information,under reporting and incorrect entries. This often results in a detection lag or prevents the detection of some adverse drug events. These limitations do not occur in electronic healthcare databases. In this paper, existing methods developed for spontaneous reporting databases are implemented on both a spontaneous reporting database and a general practice electronic health-care database and compared. The results suggests that the application of existing methods to the general practice database may help find signals that have gone undetected when using the spontaneous reporting system database. In addition the general practice database provides far more supplementary information, that if incorporated in analysis could provide a wealth of information for identifying adverse events more accurately. 2011 Conference or Workshop Item PeerReviewed Reps, Jenna, Feyereisl, Jan, Garibaldi, Jonathan M., Aickelin, Uwe, Gibson, Jack E. and Hubbard, Richard B. (2011) Investigating the detection of adverse drug events in a UK general practice electronic health-care database. In: UKCI 2011, 11th Annual Workshop on Computational Intelligence, 7-9 Sept 2011, Manchester, England. http://ukci.cs.manchester.ac.uk/files/Proceedings.pdf |
| spellingShingle | Reps, Jenna Feyereisl, Jan Garibaldi, Jonathan M. Aickelin, Uwe Gibson, Jack E. Hubbard, Richard B. Investigating the detection of adverse drug events in a UK general practice electronic health-care database |
| title | Investigating the detection of adverse drug events in a UK general practice electronic health-care database |
| title_full | Investigating the detection of adverse drug events in a UK general practice electronic health-care database |
| title_fullStr | Investigating the detection of adverse drug events in a UK general practice electronic health-care database |
| title_full_unstemmed | Investigating the detection of adverse drug events in a UK general practice electronic health-care database |
| title_short | Investigating the detection of adverse drug events in a UK general practice electronic health-care database |
| title_sort | investigating the detection of adverse drug events in a uk general practice electronic health-care database |
| url | https://eprints.nottingham.ac.uk/2025/ https://eprints.nottingham.ac.uk/2025/ |