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152: A MEASURE FOR ESTIMATING THE MAGNITUDE OF UNNECESSARY OVERTREATMENT, OVER TESTING AND OVER PREVENTING
There is not any summary measure in EBM for showing the magnitude of unnecessary medical interventions including overtreatment, over testing and over preventing. Based on the finding of a valid and reliable double blinded randomized controlled clinical trial (RCT) with a good external validity, two...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BMJ Publishing Group
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5759446/ http://dx.doi.org/10.1136/bmjopen-2016-015415.152 |
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author | Pezeshki, Mohammad Zakaria Pezeshki, Sina |
author_facet | Pezeshki, Mohammad Zakaria Pezeshki, Sina |
author_sort | Pezeshki, Mohammad Zakaria |
collection | PubMed |
description | There is not any summary measure in EBM for showing the magnitude of unnecessary medical interventions including overtreatment, over testing and over preventing. Based on the finding of a valid and reliable double blinded randomized controlled clinical trial (RCT) with a good external validity, two groups of patients may receive unnecessary overtreatment: the first group consists of patients who will not respond to medication or surgery. The second group consists of patients who respond to the placebo or sham surgery. Here we define an index to cover these two groups: Unnecessary Overtreatment Index (UOI). Based on the finding of RCTs, the UOI is defined as summation of two proportions: the proportion of patients who do not respond to medication/surgery and the proportion of patients who are improved by the placebo or sham surgery intervention as well. For example if the RCT shows that 30/100 of patients who received medication/surgery have improved and for the placebo intervention group only 20/100 patients have also improved, then the UOI is summation of (1–30/100) and 20/100. It means if a physician prescribes the medication/surgery to 100 patients then 90 of these patients will be treated unnecessarily. Seventy out of 90 are patients who will not be improved and 20 out of 90 are patients who would be improved even if they received placebo intervention. The 95% Confidence Interval can be calculated for UOI. An interesting point is the relation of UOI with Absolute Risk Reduction (ARR). Considering the definition of UOI and ARR, we will show that UOI is equal to “1- ARR. As in the example, ARR is 10/100 (30/100–20/100). Then, it can be stated that UOI=1–10%=90%. If the RCT is a diagnostic trial examining a diagnostic test, then we can define Unnecessary Overtesting Index and if the RCT examines a preventive intervention, we can define Unnecessary Over preventing Index. The utility of UOI in clinical practice will be discussed with demonstrating a few examples. |
format | Online Article Text |
id | pubmed-5759446 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | BMJ Publishing Group |
record_format | MEDLINE/PubMed |
spelling | pubmed-57594462018-02-12 152: A MEASURE FOR ESTIMATING THE MAGNITUDE OF UNNECESSARY OVERTREATMENT, OVER TESTING AND OVER PREVENTING Pezeshki, Mohammad Zakaria Pezeshki, Sina BMJ Open Abstracts from the 5th International Society for Evidence-Based Healthcare Congress, Kish Island, Ira There is not any summary measure in EBM for showing the magnitude of unnecessary medical interventions including overtreatment, over testing and over preventing. Based on the finding of a valid and reliable double blinded randomized controlled clinical trial (RCT) with a good external validity, two groups of patients may receive unnecessary overtreatment: the first group consists of patients who will not respond to medication or surgery. The second group consists of patients who respond to the placebo or sham surgery. Here we define an index to cover these two groups: Unnecessary Overtreatment Index (UOI). Based on the finding of RCTs, the UOI is defined as summation of two proportions: the proportion of patients who do not respond to medication/surgery and the proportion of patients who are improved by the placebo or sham surgery intervention as well. For example if the RCT shows that 30/100 of patients who received medication/surgery have improved and for the placebo intervention group only 20/100 patients have also improved, then the UOI is summation of (1–30/100) and 20/100. It means if a physician prescribes the medication/surgery to 100 patients then 90 of these patients will be treated unnecessarily. Seventy out of 90 are patients who will not be improved and 20 out of 90 are patients who would be improved even if they received placebo intervention. The 95% Confidence Interval can be calculated for UOI. An interesting point is the relation of UOI with Absolute Risk Reduction (ARR). Considering the definition of UOI and ARR, we will show that UOI is equal to “1- ARR. As in the example, ARR is 10/100 (30/100–20/100). Then, it can be stated that UOI=1–10%=90%. If the RCT is a diagnostic trial examining a diagnostic test, then we can define Unnecessary Overtesting Index and if the RCT examines a preventive intervention, we can define Unnecessary Over preventing Index. The utility of UOI in clinical practice will be discussed with demonstrating a few examples. BMJ Publishing Group 2017-02-08 /pmc/articles/PMC5759446/ http://dx.doi.org/10.1136/bmjopen-2016-015415.152 Text en Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/ This is an Open Access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/ |
spellingShingle | Abstracts from the 5th International Society for Evidence-Based Healthcare Congress, Kish Island, Ira Pezeshki, Mohammad Zakaria Pezeshki, Sina 152: A MEASURE FOR ESTIMATING THE MAGNITUDE OF UNNECESSARY OVERTREATMENT, OVER TESTING AND OVER PREVENTING |
title | 152: A MEASURE FOR ESTIMATING THE MAGNITUDE OF UNNECESSARY OVERTREATMENT, OVER TESTING AND OVER PREVENTING |
title_full | 152: A MEASURE FOR ESTIMATING THE MAGNITUDE OF UNNECESSARY OVERTREATMENT, OVER TESTING AND OVER PREVENTING |
title_fullStr | 152: A MEASURE FOR ESTIMATING THE MAGNITUDE OF UNNECESSARY OVERTREATMENT, OVER TESTING AND OVER PREVENTING |
title_full_unstemmed | 152: A MEASURE FOR ESTIMATING THE MAGNITUDE OF UNNECESSARY OVERTREATMENT, OVER TESTING AND OVER PREVENTING |
title_short | 152: A MEASURE FOR ESTIMATING THE MAGNITUDE OF UNNECESSARY OVERTREATMENT, OVER TESTING AND OVER PREVENTING |
title_sort | 152: a measure for estimating the magnitude of unnecessary overtreatment, over testing and over preventing |
topic | Abstracts from the 5th International Society for Evidence-Based Healthcare Congress, Kish Island, Ira |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5759446/ http://dx.doi.org/10.1136/bmjopen-2016-015415.152 |
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