We will plant a tree for each of the first 5,000 downloads.
When it comes to clinical decision support software, there's the wish list and there's the real list. The wish list is the collection of IT tools that clinicians would like to have but that remains out of reach for any number of reasons, including that the technology isn't mature enough to use in everyday practice. Over on the real list are things you have to deliver today--if not yesterday--to meet the expectations of patients and doctors as medical practice moves into a new digital age.
A number of technologies look poised to make the leap from wish list to reality--software and hardware systems that could only have been dreamed of a short while ago. Natural language processing is one example. The promise is for NLP algorithms to analyze ordinary sentences and extract critical medical terms to derive possible causes of a patient's symptoms and recommend treatment options. With advances like IBM's Watson supercomputer, IT departments are exploring natural language processing, edging health IT one step closer to artificial intelligence, which would allow computers to help clinicians through the complex process of differential diagnosis.
Similarly, impressive new software tools may help providers personalize patient care. The big point of change is the data supply: There's now a vast and growing collection of digital patient data in electronic health record systems to tap in search of individualized clinical guidelines. The pressure to use that data horde to help clinicians make better decisions is growing.
As health IT leaders plan for 2012, they'll have to decide which clinical decision support tools are ready for prime time and which will have to wait. The three areas we explore below--personalized medicine, clinical analytics, and natural language processing--aren't entirely new, but the advances being made in each field show how quickly the technology is advancing. And it should challenge IT managers to ask: Is it time to move it up their list?
We're profiled by Amazon, by Netflix, and by iTunes, each predicting what we might most like based on our historical data. Personalized profiling also is the future for medicine, says C. William Hanson III, MD, chief medical information officer at the University of Pennsylvania Health System. Healthcare organizations are starting to analyze disease patterns in the general population and among their own patients to provide a more individualized look at who's at risk for various complications, and decide if these predictive tools are accurate enough to let providers take proactive measures to avoid such problems.
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