A pathologist uses the EMR to find out just a little more about the patient whose cerebro-spinal fluid she has under her microscope — and changes her diagnosis:
This patient had a diagnosis of plasma cell myeloma with recent acute mental status changes. So the lone plasma cell or two I was seeing, among the lymphs and monos, could indicate leptomeningeal spread of the patient’s disease process. I reversed the tech diagnosis to atypical and added a lengthy comment – unfortunately there weren’t enough cells to attempt flow cytometry to assess for clonality of the plasma cells to cinch the diagnosis. But with the information in the EMR I was able to get a more holistic picture on a couple of cells and provide better care for the patient. I cringe to wonder if I might have blown them off as lymphs without my crutch.
The much-hoped-for improvement in quality due to the adoption of EMRs has been elusive to date, so anecdotal experiences like this will be important evidence to consider in judging the impact of the EMR on healthcare outcomes.
If you’ve been watching Jeopardy! over the past couple days, you probably know that IBM’s highly-advanced artificial intelligence software, Watson, has been competing against Jeopardy!’s most successful contestants (and as of Tuesday night, took a commanding lead over the humans, despite having some trouble with United States geography).
Besides the amazing ability to power through “Daily Doubles” and answer random trivia in the form of a question, IBM researchers believe that Watson could revolutionize the healthcare industry. From diagnostics to informatics, Watson could quickly search through medical records, clinical documents, and research information for precise answers that would benefit both doctors and patients.
Check out the video below to see physicians explain how Watson’s technology could transform medicine.
Also watch the TED.com webcast of Dr. David Ferrucci (Principal Investigator of the DeepQA/Watson project at IBM), Dr. Herbert Chase (Professor of Clinical Medicine at Columbia University School of Physicians and Surgeons), and others discussing the Jeopardy! challenge and the impact the technology behind Watson could have on society.
A new sensor developed at Stony Brook University may become a clinically useful tool for detecting disease biomarkers in breath. The nanoprobe-based technology is currently able to detect acetone, but should be modifiable to spot other compounds.
From the study abstract:
This paper describes a sensor nanotechnology suitable for non-invasive monitoring of a signaling gas, such as acetone, in exhaled breath. This is a nanomedicine tool comprised of a selective acetone nanoprobe working on the principle of ferroelectric poling sensing, and a microelectronics circuit for comparing the actual sensor signal to a predetermined threshold value, displaying the result using LED signals. This on/off type non-invasive diagnostics platform technology is based on nanotechnology, gives a fast response, it is simple to operate and inexpensive to manufacture, and may truly revolutionize personalized medicine.
Yanko, the design blog we highlight occasionally, shows us a device design by Antonia Haaf meant to automatically detect melanoma, called Black Skin Cancer.
Details are vague, as they usually are with concept designs, but the device is meant to be placed over a suspected legion and “[analyze] 2D and 3D characteristics from melanocytic lesions with just one shot. Using a secret algorithm, the device recognizes critical lesions such as the nodular melanome.”
While pretty, commenter Widepers on the site points out: “Frankly, a magnifying glass and the skin doctor’s email might do the trick just as well.”
In a Thought Police kind of way, a new computer program can detect depression through your online writing.
Researchers at Ben-Gurion University of the Negev, in Beer-Sheva, Israel, have developed a program that detects depression in text without obvious terms like “depression” or “suicide.” In a sample of 200 positively-identified texts out of 300,000 which were screened by the program, there was a 78 percent agreement between the program and a panel of psychologists. Read more »
*This blog post was originally published at Medgadget*
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Yanko, the design blog we highlight occasionally, shows us a device design by Antonia Haaf meant to automatically detect melanoma, called Black Skin Cancer.
