Is Health IT Being Rushed, Leading To Patient Errors?
Bolstered by the stimulus, there’s no doubt that there’s a significant push for doctors and hospitals to adopt digital medical records.
I’ve written before how we’re essentially throwing money at Windows 95 technology, but now, as an article from BusinessWeek points out, there’s a real danger in moving too fast.
Somewhat under-publicized were the incompatibilities with older systems in the Geisinger Health System, which after spending $35 million on software, noticed a spike medication errors that required another $2 million to fix.
Or what happened at the University of Pennsylvania, which found medication errors stemming from software designed to prevent mistakes.
Worse, there is no national database tracking the errors that are caused from electronic medical records. Because most of the programs are not open-source, confidentiality agreements meant to protect proprietary technology also serve to hide mistakes.
Ideally, these issues need to be resolved before throwing more money into bad technology. But, because of the intuitive notion that technology automatically improves health care, no one seems to be advocating a more cautious route which may, in actuality, better serve patients.
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Better Health Editor’s Note: Please read this post for more in-depth coverage of how difficult it is to transfer health records electronically.
Kevin, you rock! Thank you SO MUCH for telling people to read my original post! 99% of what's been written about the story has been second- or third-hand. And the hell of it is, dagnabbit, I actually put a fair amount of work into detailing and thinking about the story, so it would be WORTH reading.
This stuff can be solved, but it takes WORK. Fortunately the issues are well known in the non-medical IT world; one of the more accurate early write-ups about my post was on the Information Quality Trainwrecks, where they write about all sort of disasters (large and small) that happen when data is used cluelessly.
I do data work in my day job. The first place to start is always “What are you going to DO with the data, once it's in the system?” If you don't start there, there's no way to assess the suitability of whatever methods you choose. And given the vastness of the medical “vocabulary” (90,000+ SNOMED-CT codes, not to mention CPT and everything else), failure to define these so-called “use cases” will surely cause us to simultaneously go crazy AND get nowhere.
Kevin, you rock! Thank you SO MUCH for telling people to read my original post! 99% of what's been written about the story has been second- or third-hand. And the hell of it is, dagnabbit, I actually put a fair amount of work into detailing and thinking about the story, so it would be WORTH reading.
This stuff can be solved, but it takes WORK. Fortunately the issues are well known in the non-medical IT world; one of the more accurate early write-ups about my post was on the Information Quality Trainwrecks, where they write about all sort of disasters (large and small) that happen when data is used cluelessly.
I do data work in my day job. The first place to start is always “What are you going to DO with the data, once it's in the system?” If you don't start there, there's no way to assess the suitability of whatever methods you choose. And given the vastness of the medical “vocabulary” (90,000+ SNOMED-CT codes, not to mention CPT and everything else), failure to define these so-called “use cases” will surely cause us to simultaneously go crazy AND get nowhere.