Can data extraction from general practitioners’ electronic records be used to predict clinical outcomes for patients with type 2 diabetes?
<p><strong>Background</strong> The review of clinical data extraction from electronic records is increasingly being used as a tool to assist general practitioners (GPs) manage their patients in Australia. Type 2 diabetes (T2DM) is a chronic condition cared for primarily in the gene...
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| Format: | Article |
| Language: | English |
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BCS, The Chartered Institute for IT
2013-11-01
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| Series: | Journal of Innovation in Health Informatics |
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| Online Access: | http://hijournal.bcs.org/index.php/jhi/article/view/30 |
| _version_ | 1818126515455393792 |
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| author | Michael Staff |
| author_facet | Michael Staff |
| author_sort | Michael Staff |
| collection | DOAJ |
| description | <p><strong>Background</strong> The review of clinical data extraction from electronic records is increasingly being used as a tool to assist general practitioners (GPs) manage their patients in Australia. Type 2 diabetes (T2DM) is a chronic condition cared for primarily in the general practice setting that lends itself to the application of tools in this area.</p><p><strong>Objective</strong> To assess the feasibility of extracting data from a general practice medical record software package to predict clinically significant outcomes for patients with T2DM.</p><p><strong>Methods</strong> A pilot study was conducted involving two large practices where routinely collected clinical data were extracted and inputted into the United Kingdom Prospective Diabetes Study Outcomes Model to predict life expectancy. An initial assessment of the completeness of data available was performed and then for those patients aged between 45 and 64 years with adequate data life expectancies estimated.</p><p><strong>Results</strong> A total of 1019 patients were identified as current patients with T2DM. There were sufficient data available on 40% of patients from one practice and 49% from the other to provide inputs into the UKPDS Outcomes Model. Predicted life expectancy was similar across the practices with women having longer life expectancies than men. Improved compliance with current management guidelines for glycaemic, lipid and blood pressure control was demonstrated to increase life expectancy between 1.0 and 2.4 years dependent on gender and age group.</p><p><strong>Conclusion</strong> This pilot demonstrated that clinical data extraction from electronic records is feasible although there are several limitations chiefly caused by the incompleteness of data for patients with T2DM.</p> |
| first_indexed | 2024-12-11T07:02:41Z |
| format | Article |
| id | doaj.art-7152518b942b48debbb1660f72577938 |
| institution | Directory Open Access Journal |
| issn | 2058-4555 2058-4563 |
| language | English |
| last_indexed | 2024-12-11T07:02:41Z |
| publishDate | 2013-11-01 |
| publisher | BCS, The Chartered Institute for IT |
| record_format | Article |
| series | Journal of Innovation in Health Informatics |
| spelling | doaj.art-7152518b942b48debbb1660f725779382022-12-22T01:16:35ZengBCS, The Chartered Institute for ITJournal of Innovation in Health Informatics2058-45552058-45632013-11-012029510210.14236/jhi.v20i2.3021Can data extraction from general practitioners’ electronic records be used to predict clinical outcomes for patients with type 2 diabetes?Michael Staff0Public Health Physician, Northern Sydney and Central Coast Local Health Districts, NSW Health and Clinical Senior Lecturer, School of Public Health, University of Sydney, Australia<p><strong>Background</strong> The review of clinical data extraction from electronic records is increasingly being used as a tool to assist general practitioners (GPs) manage their patients in Australia. Type 2 diabetes (T2DM) is a chronic condition cared for primarily in the general practice setting that lends itself to the application of tools in this area.</p><p><strong>Objective</strong> To assess the feasibility of extracting data from a general practice medical record software package to predict clinically significant outcomes for patients with T2DM.</p><p><strong>Methods</strong> A pilot study was conducted involving two large practices where routinely collected clinical data were extracted and inputted into the United Kingdom Prospective Diabetes Study Outcomes Model to predict life expectancy. An initial assessment of the completeness of data available was performed and then for those patients aged between 45 and 64 years with adequate data life expectancies estimated.</p><p><strong>Results</strong> A total of 1019 patients were identified as current patients with T2DM. There were sufficient data available on 40% of patients from one practice and 49% from the other to provide inputs into the UKPDS Outcomes Model. Predicted life expectancy was similar across the practices with women having longer life expectancies than men. Improved compliance with current management guidelines for glycaemic, lipid and blood pressure control was demonstrated to increase life expectancy between 1.0 and 2.4 years dependent on gender and age group.</p><p><strong>Conclusion</strong> This pilot demonstrated that clinical data extraction from electronic records is feasible although there are several limitations chiefly caused by the incompleteness of data for patients with T2DM.</p>http://hijournal.bcs.org/index.php/jhi/article/view/30clinical informaticsdiabeteslife expectancyprimary care |
| spellingShingle | Michael Staff Can data extraction from general practitioners’ electronic records be used to predict clinical outcomes for patients with type 2 diabetes? Journal of Innovation in Health Informatics clinical informatics diabetes life expectancy primary care |
| title | Can data extraction from general practitioners’ electronic records be used to predict clinical outcomes for patients with type 2 diabetes? |
| title_full | Can data extraction from general practitioners’ electronic records be used to predict clinical outcomes for patients with type 2 diabetes? |
| title_fullStr | Can data extraction from general practitioners’ electronic records be used to predict clinical outcomes for patients with type 2 diabetes? |
| title_full_unstemmed | Can data extraction from general practitioners’ electronic records be used to predict clinical outcomes for patients with type 2 diabetes? |
| title_short | Can data extraction from general practitioners’ electronic records be used to predict clinical outcomes for patients with type 2 diabetes? |
| title_sort | can data extraction from general practitioners electronic records be used to predict clinical outcomes for patients with type 2 diabetes |
| topic | clinical informatics diabetes life expectancy primary care |
| url | http://hijournal.bcs.org/index.php/jhi/article/view/30 |
| work_keys_str_mv | AT michaelstaff candataextractionfromgeneralpractitionerselectronicrecordsbeusedtopredictclinicaloutcomesforpatientswithtype2diabetes |