tag:blogger.com,1999:blog-3916610575947257275.post6122625957342390134..comments2012-03-25T22:25:53.596-07:00Comments on CATCH-IT Blog: Health Informatics Journal Club: CATCH-IT DRAFT: Individualized electronic decision support and reminders to improve diabetes care in the community: COMPETE II randomized trial.Gunther Eysenbach MD MPHhttp://www.blogger.com/profile/03418681005679727986noreply@blogger.comBlogger6125tag:blogger.com,1999:blog-3916610575947257275.post-66401329029140096052009-11-02T18:23:44.273-08:002009-11-02T18:23:44.273-08:00Thanks for the review James. I agree with you on ...Thanks for the review James. I agree with you on your points in the discussion. While multi-nodal nature of the intervention makes it difficult to assess, I wonder how the research design could have been improved. Given the costs of electronic tools, not sure if the researchers could compare the electronic tool versus the control group with the paper tool.Claudiahttps://www.blogger.com/profile/17838814260478407987noreply@blogger.comtag:blogger.com,1999:blog-3916610575947257275.post-60228091028492897552009-10-31T09:26:50.098-07:002009-10-31T09:26:50.098-07:00Hi James,
The issue of multiple comparison may a...Hi James, <br /><br />The issue of multiple comparison may also be worth mentioning. In Table 4: Result of clinical outcomes, various numbers of clinical outcomes were compared simultaneously between intervention and control groups without accounting for the multiple comparisons issue. Meaning that as the number of comparisons increases, it becomes more likely that the groups being compared will appear to differ in terms of at least one attribute and show at least one or two statistically significant p values. When we compare several outcomes of the same population, the type one error will be more than 0.05 and proper adjustment would be needed. Bonferroni correction is a method that addresses this issue, which is looking at a smaller p value. The formula would be, 0.05(p value) / n (number of comparisons) which will results in an overall type one error at 0.05 level.Marjan Moeinedinhttps://www.blogger.com/profile/07709732766372054509noreply@blogger.comtag:blogger.com,1999:blog-3916610575947257275.post-89975108123519918302009-10-30T21:30:36.066-07:002009-10-30T21:30:36.066-07:00Good review James.
Not sure if you are posing any...Good review James.<br /><br />Not sure if you are posing any questions for the authors, just in case you decide to, here is one-“How did they account for the usability of the web-based tracker since a greater proportion of patients were not regular internet users?” I think it is important to bring this up because although patient adherence and access to high quality diabetes care improved, many primary care providers faced technical difficulties with the electronic decision support tool which had an impact on the perceived usefulness of the intervention.ShamsaJiwanihttps://www.blogger.com/profile/12199963244805850772noreply@blogger.comtag:blogger.com,1999:blog-3916610575947257275.post-45709750072363081422009-10-27T08:12:13.247-07:002009-10-27T08:12:13.247-07:00It is flexible - you can go beyond it. Same questi...It is flexible - you can go beyond it. Same question was asked by Plumaletta - I should probably announce it in class...Gunther Eysenbach MD MPHhttps://www.blogger.com/profile/03418681005679727986noreply@blogger.comtag:blogger.com,1999:blog-3916610575947257275.post-240737759111362182009-10-27T07:43:07.859-07:002009-10-27T07:43:07.859-07:00Thanks Gunther, I will address these points in the...Thanks Gunther, I will address these points in the final paper. Just a quick question though. Your comments alone (from my draft page) were about 700 words. The word count for the paper is 1000. I think it will be difficult to write a final paper that is 1000 words yet addresses all of the points made in class. Is this word count set in stone or flexible?James Mullenhttps://www.blogger.com/profile/00305176966301991699noreply@blogger.comtag:blogger.com,1999:blog-3916610575947257275.post-68728846688046293872009-10-27T06:56:53.947-07:002009-10-27T06:56:53.947-07:00Thanks for this. The final report needs to improve...Thanks for this. The final report needs to improve significantly - you need to sharpen your arguments and add some additional points raised during discussion.<br /><br />Just a few points:<br /><br />1. My <a href="http://ehealth-catchit.blogspot.com/2009/10/individualized-electronic-decision.html" rel="nofollow">points 3, 5, 7 from the initial discussion</a> did not make it into the CATCH-IT report. Why not? Do you disagree with them? <br />2. "randomization at the patient level could have caused contamination due to possible interactions amongst patient of the same physician." - I do not see this as a very plausible scenario - could you explain this further what exactly you mean by this? You are basically arguing that patients in the waiting room discussing the application would lead to process and outcome improvements? Much more plausible is the concern that the intervention "spills over" into the control group by physicians "learning" from intervention patients. This leads to a process improvement in the control group, making it more difficult to show a true difference. This is called a "bias towards null". The remedy is a cluster randomized trial, as discussed in class.<br />3. your argument to provide utilization data is framed in a confusing way, as you argue that the low Internet use in the patient group is the issue (it is not, because the intervention was also delivered on paper, and also targeted physicians). Still, it would be essential to report usage data because system developers need to know what parts of the intervention worked/was used. <br />4. "counterintuitive" needs to be explained - why exactly are these figures "counterintuitive"? (I am not saying they aren't, but you need to sharpen your arguments)Gunther Eysenbach MD MPHhttps://www.blogger.com/profile/03418681005679727986noreply@blogger.com