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Assessing the validity of using administrative data to identify patients with epilepsy
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| Zeitschriftentitel: | Epilepsia |
|---|---|
| Personen und Körperschaften: | , , , , , , , |
| In: | Epilepsia, 55, 2014, 2, S. 335-343 |
| Format: | E-Article |
| Sprache: | Englisch |
| veröffentlicht: |
Wiley
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| Schlagwörter: |
| author_facet |
Tu, Karen Wang, Myra Jaakkimainen, R. Liisa Butt, Debra Ivers, Noah M. Young, Jacqueline Green, Diane Jetté, Nathalie Tu, Karen Wang, Myra Jaakkimainen, R. Liisa Butt, Debra Ivers, Noah M. Young, Jacqueline Green, Diane Jetté, Nathalie |
|---|---|
| author |
Tu, Karen Wang, Myra Jaakkimainen, R. Liisa Butt, Debra Ivers, Noah M. Young, Jacqueline Green, Diane Jetté, Nathalie |
| spellingShingle |
Tu, Karen Wang, Myra Jaakkimainen, R. Liisa Butt, Debra Ivers, Noah M. Young, Jacqueline Green, Diane Jetté, Nathalie Epilepsia Assessing the validity of using administrative data to identify patients with epilepsy Neurology (clinical) Neurology |
| author_sort |
tu, karen |
| spelling |
Tu, Karen Wang, Myra Jaakkimainen, R. Liisa Butt, Debra Ivers, Noah M. Young, Jacqueline Green, Diane Jetté, Nathalie 0013-9580 1528-1167 Wiley Neurology (clinical) Neurology http://dx.doi.org/10.1111/epi.12506 <jats:title>Summary</jats:title><jats:sec><jats:title>Objective</jats:title><jats:p>Previous validation studies assessing the use of administrative data to identify patients with epilepsy have used targeted sampling or have used a reference standard of patients in the neurologist, hospital, or emergency room setting. Therefore, the validity of using administrative data to identify patients with epilepsy in the general population has not been previously assessed. The purpose of this study was to determine the validity of using administrative data to identify patients with epilepsy in the general population.</jats:p></jats:sec><jats:sec><jats:title>Methods</jats:title><jats:p>A retrospective chart abstraction study was performed using primary care physician records from 83 physicians distributed throughout <jats:styled-content style="fixed-case">O</jats:styled-content>ntario and contributing data to the <jats:styled-content style="fixed-case">E</jats:styled-content>lectronic <jats:styled-content style="fixed-case">M</jats:styled-content>edical <jats:styled-content style="fixed-case">R</jats:styled-content>ecord <jats:styled-content style="fixed-case">A</jats:styled-content>dministrative data <jats:styled-content style="fixed-case">L</jats:styled-content>inked <jats:styled-content style="fixed-case">D</jats:styled-content>atabase (<jats:styled-content style="fixed-case">EMRALD</jats:styled-content>) A random sample of 7,500 adult patients, from a possible 73,014 eligible, was manually chart abstracted to identify patients who had ever had epilepsy. These patients were used as a reference standard to test a variety of administrative data algorithms.</jats:p></jats:sec><jats:sec><jats:title>Results</jats:title><jats:p>An algorithm of three physician billing codes (separated by at least 30 days) in 2 years or one hospitalization had a sensitivity of 73.7% (95% confidence interval [<jats:styled-content style="fixed-case">CI</jats:styled-content>] 64.8–82.5%), specificity of 99.8% (95% <jats:styled-content style="fixed-case">CI</jats:styled-content> 99.6–99.9%), positive predictive value (<jats:styled-content style="fixed-case">PPV</jats:styled-content>) of 79.5% (95% <jats:styled-content style="fixed-case">CI</jats:styled-content> 71.1–88.0%), and negative predictive value (<jats:styled-content style="fixed-case">NPV</jats:styled-content>) of 99.7% (95% <jats:styled-content style="fixed-case">CI</jats:styled-content> 99.5–99.8%) for identifying patients who had ever had epilepsy.</jats:p></jats:sec><jats:sec><jats:title>Significance</jats:title><jats:p>The results of our study showed that administrative data can reasonably accurately identify patients who have ever had epilepsy, allowing for a “lifetime” population prevalence determination of epilepsy in <jats:styled-content style="fixed-case">O</jats:styled-content>ntario and the rest of <jats:styled-content style="fixed-case">C</jats:styled-content>anada with similar administrative databases. This will facilitate future studies on population level patterns and outcomes of care for patients living with epilepsy.</jats:p></jats:sec> Assessing the validity of using administrative data to identify patients with epilepsy Epilepsia |
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Wiley, 2014 |
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Wiley, 2014 |
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2014 |
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Wiley |
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Epilepsia |
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49 |
| title |
Assessing the validity of using administrative data to identify patients with epilepsy |
| title_unstemmed |
Assessing the validity of using administrative data to identify patients with epilepsy |
| title_full |
Assessing the validity of using administrative data to identify patients with epilepsy |
| title_fullStr |
Assessing the validity of using administrative data to identify patients with epilepsy |
| title_full_unstemmed |
Assessing the validity of using administrative data to identify patients with epilepsy |
| title_short |
Assessing the validity of using administrative data to identify patients with epilepsy |
| title_sort |
assessing the validity of using administrative data to identify patients with epilepsy |
| topic |
Neurology (clinical) Neurology |
| url |
http://dx.doi.org/10.1111/epi.12506 |
| publishDate |
2014 |
| physical |
335-343 |
| description |
<jats:title>Summary</jats:title><jats:sec><jats:title>Objective</jats:title><jats:p>Previous validation studies assessing the use of administrative data to identify patients with epilepsy have used targeted sampling or have used a reference standard of patients in the neurologist, hospital, or emergency room setting. Therefore, the validity of using administrative data to identify patients with epilepsy in the general population has not been previously assessed. The purpose of this study was to determine the validity of using administrative data to identify patients with epilepsy in the general population.</jats:p></jats:sec><jats:sec><jats:title>Methods</jats:title><jats:p>A retrospective chart abstraction study was performed using primary care physician records from 83 physicians distributed throughout <jats:styled-content style="fixed-case">O</jats:styled-content>ntario and contributing data to the <jats:styled-content style="fixed-case">E</jats:styled-content>lectronic <jats:styled-content style="fixed-case">M</jats:styled-content>edical <jats:styled-content style="fixed-case">R</jats:styled-content>ecord <jats:styled-content style="fixed-case">A</jats:styled-content>dministrative data <jats:styled-content style="fixed-case">L</jats:styled-content>inked <jats:styled-content style="fixed-case">D</jats:styled-content>atabase (<jats:styled-content style="fixed-case">EMRALD</jats:styled-content>) A random sample of 7,500 adult patients, from a possible 73,014 eligible, was manually chart abstracted to identify patients who had ever had epilepsy. These patients were used as a reference standard to test a variety of administrative data algorithms.</jats:p></jats:sec><jats:sec><jats:title>Results</jats:title><jats:p>An algorithm of three physician billing codes (separated by at least 30 days) in 2 years or one hospitalization had a sensitivity of 73.7% (95% confidence interval [<jats:styled-content style="fixed-case">CI</jats:styled-content>] 64.8–82.5%), specificity of 99.8% (95% <jats:styled-content style="fixed-case">CI</jats:styled-content> 99.6–99.9%), positive predictive value (<jats:styled-content style="fixed-case">PPV</jats:styled-content>) of 79.5% (95% <jats:styled-content style="fixed-case">CI</jats:styled-content> 71.1–88.0%), and negative predictive value (<jats:styled-content style="fixed-case">NPV</jats:styled-content>) of 99.7% (95% <jats:styled-content style="fixed-case">CI</jats:styled-content> 99.5–99.8%) for identifying patients who had ever had epilepsy.</jats:p></jats:sec><jats:sec><jats:title>Significance</jats:title><jats:p>The results of our study showed that administrative data can reasonably accurately identify patients who have ever had epilepsy, allowing for a “lifetime” population prevalence determination of epilepsy in <jats:styled-content style="fixed-case">O</jats:styled-content>ntario and the rest of <jats:styled-content style="fixed-case">C</jats:styled-content>anada with similar administrative databases. This will facilitate future studies on population level patterns and outcomes of care for patients living with epilepsy.</jats:p></jats:sec> |
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| author | Tu, Karen, Wang, Myra, Jaakkimainen, R. Liisa, Butt, Debra, Ivers, Noah M., Young, Jacqueline, Green, Diane, Jetté, Nathalie |
| author_facet | Tu, Karen, Wang, Myra, Jaakkimainen, R. Liisa, Butt, Debra, Ivers, Noah M., Young, Jacqueline, Green, Diane, Jetté, Nathalie, Tu, Karen, Wang, Myra, Jaakkimainen, R. Liisa, Butt, Debra, Ivers, Noah M., Young, Jacqueline, Green, Diane, Jetté, Nathalie |
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| description | <jats:title>Summary</jats:title><jats:sec><jats:title>Objective</jats:title><jats:p>Previous validation studies assessing the use of administrative data to identify patients with epilepsy have used targeted sampling or have used a reference standard of patients in the neurologist, hospital, or emergency room setting. Therefore, the validity of using administrative data to identify patients with epilepsy in the general population has not been previously assessed. The purpose of this study was to determine the validity of using administrative data to identify patients with epilepsy in the general population.</jats:p></jats:sec><jats:sec><jats:title>Methods</jats:title><jats:p>A retrospective chart abstraction study was performed using primary care physician records from 83 physicians distributed throughout <jats:styled-content style="fixed-case">O</jats:styled-content>ntario and contributing data to the <jats:styled-content style="fixed-case">E</jats:styled-content>lectronic <jats:styled-content style="fixed-case">M</jats:styled-content>edical <jats:styled-content style="fixed-case">R</jats:styled-content>ecord <jats:styled-content style="fixed-case">A</jats:styled-content>dministrative data <jats:styled-content style="fixed-case">L</jats:styled-content>inked <jats:styled-content style="fixed-case">D</jats:styled-content>atabase (<jats:styled-content style="fixed-case">EMRALD</jats:styled-content>) A random sample of 7,500 adult patients, from a possible 73,014 eligible, was manually chart abstracted to identify patients who had ever had epilepsy. These patients were used as a reference standard to test a variety of administrative data algorithms.</jats:p></jats:sec><jats:sec><jats:title>Results</jats:title><jats:p>An algorithm of three physician billing codes (separated by at least 30 days) in 2 years or one hospitalization had a sensitivity of 73.7% (95% confidence interval [<jats:styled-content style="fixed-case">CI</jats:styled-content>] 64.8–82.5%), specificity of 99.8% (95% <jats:styled-content style="fixed-case">CI</jats:styled-content> 99.6–99.9%), positive predictive value (<jats:styled-content style="fixed-case">PPV</jats:styled-content>) of 79.5% (95% <jats:styled-content style="fixed-case">CI</jats:styled-content> 71.1–88.0%), and negative predictive value (<jats:styled-content style="fixed-case">NPV</jats:styled-content>) of 99.7% (95% <jats:styled-content style="fixed-case">CI</jats:styled-content> 99.5–99.8%) for identifying patients who had ever had epilepsy.</jats:p></jats:sec><jats:sec><jats:title>Significance</jats:title><jats:p>The results of our study showed that administrative data can reasonably accurately identify patients who have ever had epilepsy, allowing for a “lifetime” population prevalence determination of epilepsy in <jats:styled-content style="fixed-case">O</jats:styled-content>ntario and the rest of <jats:styled-content style="fixed-case">C</jats:styled-content>anada with similar administrative databases. This will facilitate future studies on population level patterns and outcomes of care for patients living with epilepsy.</jats:p></jats:sec> |
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| spelling | Tu, Karen Wang, Myra Jaakkimainen, R. Liisa Butt, Debra Ivers, Noah M. Young, Jacqueline Green, Diane Jetté, Nathalie 0013-9580 1528-1167 Wiley Neurology (clinical) Neurology http://dx.doi.org/10.1111/epi.12506 <jats:title>Summary</jats:title><jats:sec><jats:title>Objective</jats:title><jats:p>Previous validation studies assessing the use of administrative data to identify patients with epilepsy have used targeted sampling or have used a reference standard of patients in the neurologist, hospital, or emergency room setting. Therefore, the validity of using administrative data to identify patients with epilepsy in the general population has not been previously assessed. The purpose of this study was to determine the validity of using administrative data to identify patients with epilepsy in the general population.</jats:p></jats:sec><jats:sec><jats:title>Methods</jats:title><jats:p>A retrospective chart abstraction study was performed using primary care physician records from 83 physicians distributed throughout <jats:styled-content style="fixed-case">O</jats:styled-content>ntario and contributing data to the <jats:styled-content style="fixed-case">E</jats:styled-content>lectronic <jats:styled-content style="fixed-case">M</jats:styled-content>edical <jats:styled-content style="fixed-case">R</jats:styled-content>ecord <jats:styled-content style="fixed-case">A</jats:styled-content>dministrative data <jats:styled-content style="fixed-case">L</jats:styled-content>inked <jats:styled-content style="fixed-case">D</jats:styled-content>atabase (<jats:styled-content style="fixed-case">EMRALD</jats:styled-content>) A random sample of 7,500 adult patients, from a possible 73,014 eligible, was manually chart abstracted to identify patients who had ever had epilepsy. These patients were used as a reference standard to test a variety of administrative data algorithms.</jats:p></jats:sec><jats:sec><jats:title>Results</jats:title><jats:p>An algorithm of three physician billing codes (separated by at least 30 days) in 2 years or one hospitalization had a sensitivity of 73.7% (95% confidence interval [<jats:styled-content style="fixed-case">CI</jats:styled-content>] 64.8–82.5%), specificity of 99.8% (95% <jats:styled-content style="fixed-case">CI</jats:styled-content> 99.6–99.9%), positive predictive value (<jats:styled-content style="fixed-case">PPV</jats:styled-content>) of 79.5% (95% <jats:styled-content style="fixed-case">CI</jats:styled-content> 71.1–88.0%), and negative predictive value (<jats:styled-content style="fixed-case">NPV</jats:styled-content>) of 99.7% (95% <jats:styled-content style="fixed-case">CI</jats:styled-content> 99.5–99.8%) for identifying patients who had ever had epilepsy.</jats:p></jats:sec><jats:sec><jats:title>Significance</jats:title><jats:p>The results of our study showed that administrative data can reasonably accurately identify patients who have ever had epilepsy, allowing for a “lifetime” population prevalence determination of epilepsy in <jats:styled-content style="fixed-case">O</jats:styled-content>ntario and the rest of <jats:styled-content style="fixed-case">C</jats:styled-content>anada with similar administrative databases. This will facilitate future studies on population level patterns and outcomes of care for patients living with epilepsy.</jats:p></jats:sec> Assessing the validity of using administrative data to identify patients with epilepsy Epilepsia |
| spellingShingle | Tu, Karen, Wang, Myra, Jaakkimainen, R. Liisa, Butt, Debra, Ivers, Noah M., Young, Jacqueline, Green, Diane, Jetté, Nathalie, Epilepsia, Assessing the validity of using administrative data to identify patients with epilepsy, Neurology (clinical), Neurology |
| title | Assessing the validity of using administrative data to identify patients with epilepsy |
| title_full | Assessing the validity of using administrative data to identify patients with epilepsy |
| title_fullStr | Assessing the validity of using administrative data to identify patients with epilepsy |
| title_full_unstemmed | Assessing the validity of using administrative data to identify patients with epilepsy |
| title_short | Assessing the validity of using administrative data to identify patients with epilepsy |
| title_sort | assessing the validity of using administrative data to identify patients with epilepsy |
| title_unstemmed | Assessing the validity of using administrative data to identify patients with epilepsy |
| topic | Neurology (clinical), Neurology |
| url | http://dx.doi.org/10.1111/epi.12506 |