Is health IT a crystal ball? Nope; not yet. For all of its good, health IT still lacks in so many ways. Health IT may save the masses, but not necessarily the individual at this point. As it matures and grows, no doubt it will fill some voids, but as far as its current capabilities, the information collected in the form of electronic health records, for example, is still nothing more than a repository of information gathered from the past.
What we need are technologies that hint or predict health outcomes before they happen. I’m not talking about broad brush analysis, but individual predictions for each person with a record.
Who wouldn’t want their medical cases charted and entered into an EHR if it could help physicians determine which conditions were going to impact them down the road.
It’s not lost on me that on the current road map, if all healthcare data is aggregated, there’s a hope that a population’s data may provide insight into predicting what’s in store for the said population.
To cite IBM, “As digital records and information become the norm in healthcare, it enables the building of predictive analytic solutions. These predictive models, when interspersed with the day-to-day operations of healthcare providers and insurance companies, have the potential to lower cost and improve the overall health of the population. As predictive models become more pervasive, the need for a standard, which can be used by all the parties involved in the modeling process: from model building to operational deployment, is paramount.”
Even though current forms of data collection are merely meant to gather information to help establish standard approaches to most types of care in which the care system will use to treat the majority of patients (evidence-based care, essentially) as a way to reduce costs to the system (health insurance providers not excluded), there is little push for technologies that could actually help determine, at the individual level, what may affect us and how to treat it before it becomes chronic or life threatening.
Let’s be clear: I’m not talking about predicting the obvious. For example, in cases where years of overeating and lack of exercise are present, no one needs to predict what the outcome is likely to be. I’m referring to other types of conditions that are, for the most case, unavoidable: MS, cancer, Alhzeimer’s, and so on.
Whoever begins to develop these technologies is going to set the market and turn healthcare on its head. These people, or this person, will be considered genius and their effects on millions of lives great. It might be science fiction of me to think this will ever happen, but it gives me hope to think it could happen.
Until then, if such a day ever comes, we have to wait and hope for the best like a dear friend of mine who recently was diagnosed with brain cancer. Ironically, she has always been an advocate for healthful living, living an active lifestyle, working with a major organization dedicated to lobbying for and providing hope to those affected by cancer, and even championing healthcare technology as a means to improve patient health outcomes and our health as a society.
But given all of these efforts, despite the wise choices she’s made to live healthy and help others, there was little that could be done to predict that she too would be in this situation, where if predictive technologies existed she could have benefited.
Now, because there is not a predictive crystal ball, despite all the technological gains we’ve made, she, like everyone else, must react rather than act.
Sad to think that even after all the billions being spent in healthcare technology and with all of the apparent advances, as individuals, are we really better off?