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The Danish Model for Improvement of Diabetes Care in General Practice: Impact of Automated Collection and Feedback of Patient Data
Background. Sentinel Data Capture is an IT program designed to collect data automatically from GPs' electronic health record system. Data include ICPC diagnoses, National Health Service disbursement codes, laboratory analysis, and prescribed drugs. Quality feedback reports are generated individ...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Hindawi Publishing Corporation
2012
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3409523/ https://www.ncbi.nlm.nih.gov/pubmed/22888424 http://dx.doi.org/10.1155/2012/208123 |
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author | Schroll, Henrik Christensen, René dePont Thomsen, Janus Laust Andersen, Morten Friborg, Søren Søndergaard, Jens |
author_facet | Schroll, Henrik Christensen, René dePont Thomsen, Janus Laust Andersen, Morten Friborg, Søren Søndergaard, Jens |
author_sort | Schroll, Henrik |
collection | PubMed |
description | Background. Sentinel Data Capture is an IT program designed to collect data automatically from GPs' electronic health record system. Data include ICPC diagnoses, National Health Service disbursement codes, laboratory analysis, and prescribed drugs. Quality feedback reports are generated individually for each practice on the basis of the accumulated data and are available online only for the specific practice. Objective. To describe the development of the quality of care concerning drug prescriptions for diabetes patients listed with GPs using the Data Capture module. Methods. In a cohort study, among 8320 registered patients with diabetes, we analyzed the change in the proportion of medication for uncontrolled cases of diabetes. Results. From 2009 to 2010, there was an absolute risk reduction of 1.35% (0.89–1.81: P < 0.001) in proportion of persons not in antidiabetic medication despite an HbA1c above 7.0. Similarly, there was a 4.51% (3.42–5.61: P < 0.001) absolute risk reduction in patients not in antihypertensive treatment despite systolic blood pressure above 130 mm Hg and 4.73% (3.56–5.90: P < 0.001) absolute risk reduction in patients with total cholesterol level above 4.5 mmol/L and not receiving lipid-lowering treatment. Conclusions. Structured collection of electronic data from general practice and feedback with reports on quality of care for diabetes patient seems to give a significant reduction in proportion of patients with no medical treatment over one year for participating GPs. Due to lack of a control group, we are, however, not able to say if the drop in the proportion of uncontrolled cases is a result of participation in collection of electronic data and feedback alone. |
format | Online Article Text |
id | pubmed-3409523 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2012 |
publisher | Hindawi Publishing Corporation |
record_format | MEDLINE/PubMed |
spelling | pubmed-34095232012-08-10 The Danish Model for Improvement of Diabetes Care in General Practice: Impact of Automated Collection and Feedback of Patient Data Schroll, Henrik Christensen, René dePont Thomsen, Janus Laust Andersen, Morten Friborg, Søren Søndergaard, Jens Int J Family Med Research Article Background. Sentinel Data Capture is an IT program designed to collect data automatically from GPs' electronic health record system. Data include ICPC diagnoses, National Health Service disbursement codes, laboratory analysis, and prescribed drugs. Quality feedback reports are generated individually for each practice on the basis of the accumulated data and are available online only for the specific practice. Objective. To describe the development of the quality of care concerning drug prescriptions for diabetes patients listed with GPs using the Data Capture module. Methods. In a cohort study, among 8320 registered patients with diabetes, we analyzed the change in the proportion of medication for uncontrolled cases of diabetes. Results. From 2009 to 2010, there was an absolute risk reduction of 1.35% (0.89–1.81: P < 0.001) in proportion of persons not in antidiabetic medication despite an HbA1c above 7.0. Similarly, there was a 4.51% (3.42–5.61: P < 0.001) absolute risk reduction in patients not in antihypertensive treatment despite systolic blood pressure above 130 mm Hg and 4.73% (3.56–5.90: P < 0.001) absolute risk reduction in patients with total cholesterol level above 4.5 mmol/L and not receiving lipid-lowering treatment. Conclusions. Structured collection of electronic data from general practice and feedback with reports on quality of care for diabetes patient seems to give a significant reduction in proportion of patients with no medical treatment over one year for participating GPs. Due to lack of a control group, we are, however, not able to say if the drop in the proportion of uncontrolled cases is a result of participation in collection of electronic data and feedback alone. Hindawi Publishing Corporation 2012 2012-07-24 /pmc/articles/PMC3409523/ /pubmed/22888424 http://dx.doi.org/10.1155/2012/208123 Text en Copyright © 2012 Henrik Schroll et al. https://creativecommons.org/licenses/by/3.0/ This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Article Schroll, Henrik Christensen, René dePont Thomsen, Janus Laust Andersen, Morten Friborg, Søren Søndergaard, Jens The Danish Model for Improvement of Diabetes Care in General Practice: Impact of Automated Collection and Feedback of Patient Data |
title | The Danish Model for Improvement of Diabetes Care in General Practice: Impact of Automated Collection and Feedback of Patient Data |
title_full | The Danish Model for Improvement of Diabetes Care in General Practice: Impact of Automated Collection and Feedback of Patient Data |
title_fullStr | The Danish Model for Improvement of Diabetes Care in General Practice: Impact of Automated Collection and Feedback of Patient Data |
title_full_unstemmed | The Danish Model for Improvement of Diabetes Care in General Practice: Impact of Automated Collection and Feedback of Patient Data |
title_short | The Danish Model for Improvement of Diabetes Care in General Practice: Impact of Automated Collection and Feedback of Patient Data |
title_sort | danish model for improvement of diabetes care in general practice: impact of automated collection and feedback of patient data |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3409523/ https://www.ncbi.nlm.nih.gov/pubmed/22888424 http://dx.doi.org/10.1155/2012/208123 |
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