Can Better Analysis Improve Healthcare?

For decades, our understanding of the relationship between healthcare spending, pricing, and health outcomes has been limited to the crude level of epidemiological studies.  Most of those results suggested that offering better healthcare didn’t improve outcomes, a depressing conclusion.  However, everyone seems to be talking about how we’re now in the era of “big data.”  Interest in deeper analysis of healthcare data, and more sophisticated responses to the results of that analysis, seems to be spiking.  Here are a few examples of budding healthcare innovation that have received attention in just in the last few weeks:

  • U.S. tries open-source model for health data systems
    • The government and a variety of big companies are working to quickly develop a standard for sharing healthcare information among different providers.  The early version basically appears to be encrypted email.  It sounds ridiculously simple, but maybe getting a basic standard in place and seeing what healthcare users need to help them do their jobs is a better approach than spending years in standard-setting only to realize the specification doesn’t really meet people’s needs.

  • A new challenge looks for a smarter algorithm to improve healthcare
    • The Heritage Provider Network, a big primary care network in Southern California, is offering a Netflix-style prize of $3 million to whoever can best predict which patients will end up in the hospital based on anonymous medical data.  The idea is that statistical analysis might catch risk trends that physicians miss, allowing riskier patients to receive better care and thus mitigating the chance of costly hospitalization.
  • Can we lower medical costs by giving the neediest patients better care?
    • In New Jersey, Boston, and Atlantic City, a few doctors are taking a much more intensive approach to the sickest patients, trying to minimize extremely expensive chronic hospitalizations.  Even more interestingly, the article mentions companies like Verisk that are attempting to use data analysis to minimize healthcare costs in much more sophisticated ways than usual.
  • Massive Health uses big data, mobile phones to fight chronic disease
    • Details are a bit slim, but Massive Health recently got a couple of million in funding from top-tier venture investors like Andreessen Horowitz to help patients manage their chronic diseases with the help of mobile phone data.  The idea is that real-time feedback on their behavior will encourage them to change it, the same way real-time mileage information changes driving patterns.

Of course, these initiatives are all different.  And there are very legitimate reasons to be skeptical of whether they can all be successful, or more importantly whether initial, localized success can be extended to the overall healthcare landscape.

But these initiatives already seem more likely to have an impact than efforts like Google Health and Microsoft Health Vault, both of which seem like platforms looking for a problem to solve.  Most patients simply aren’t that interested in the abstract idea of online health records.  To make inroads with health data, companies need to either focus on helping healthcare providers or create consumer applications that focus on self-improvement rather than healthcare per se.   The paradox, as always, is that the patients who need to be the most vigilant about health issues are usually the hardest to motivate.  That challenge won’t simply wash away in a wave of new technology.  Innovation in medical business models and practices will also be necessary, and progress will probably be slow.

From a technology perspective, we can only hope that the insoluble problems of healthcare decision-making become more tractable over time.  Speech recognition, computer vision, and the tricorder all once seemed like pie in the sky but are now either a reality or just around the corner.  Now that healthcare information is finally becoming digital, perhaps similar advances will finally be possible with the treatment of chronic disease.


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