Re:Medical communication is bad–how can we fix it?
by breck on Friday February 04, 2022 @03:09PM
(#30212314)
This is neat. The author makes a list of problems with online medical information, defines what makes good medical information, and then coded a prototype to improve the accessibility of one class of medical information—the meta-analysis. The author's prototype imports 17 randomized, controlled trials on whether zinc lozenges reduce cold duration.
The prototype is interactive and you can add/remove trials to build your own informal meta-analysis. For example, I can easily generate screenshots that claim `According to 11 selected studies, there's an insignificant chance that zinc lozenges reduce cold durations by 1%.` or the exact opposite `According to 12 selected studies, there's a significant chance that zinc lozenges reduce cold durations by 21%.`. This provides the reader with better insight into the uncertainty of an issue, and also highlights the vulnerability of meta-analyses to manipulation. This tool, and some of the links provided by the author, highlight how higher level meta-analysis tools may build on the benefits offered by the original static meta-analysis.
The prototype also includes a "Funnel Plot", a clever chart type common in meta-analyses that I hadn't noticed much before.
One minor suggestion would be to include a 4th critical attribute of what constitutes "good" medical information: precision (aka personalization). A bit of demographic information can often make all the difference in a treatment. What has a 1,000% effect on one person might have predictably 0% affect on another, and so those decision trees should probably always be included. I suspect the author is aware of this and just cut it for scope.
The prototype is interactive and you can add/remove trials to build your own informal meta-analysis. For example, I can easily generate screenshots that claim `According to 11 selected studies, there's an insignificant chance that zinc lozenges reduce cold durations by 1%.` or the exact opposite `According to 12 selected studies, there's a significant chance that zinc lozenges reduce cold durations by 21%.`. This provides the reader with better insight into the uncertainty of an issue, and also highlights the vulnerability of meta-analyses to manipulation. This tool, and some of the links provided by the author, highlight how higher level meta-analysis tools may build on the benefits offered by the original static meta-analysis.
The prototype also includes a "Funnel Plot", a clever chart type common in meta-analyses that I hadn't noticed much before.
One minor suggestion would be to include a 4th critical attribute of what constitutes "good" medical information: precision (aka personalization). A bit of demographic information can often make all the difference in a treatment. What has a 1,000% effect on one person might have predictably 0% affect on another, and so those decision trees should probably always be included. I suspect the author is aware of this and just cut it for scope.