David M. Eddy, MD, PhD is a legend when it comes to Evidence-Based Medicine. He coined the term in 1980s, actually. Being exceptionally skilled in mathematics, it was perhaps natural for him to apply it to medicine. The result is Archimedes Model- a mathematical simulation of the human physiology and how it interacts with healthcare interventions.

A more loaded one-line description of Archimedes (taken from his original paper in 2002): “It’s an object-oriented, continuous-time, full simulation model for addressing a wide range of clinical, procedural, administrative, and financial decisions in health care at a high level of biological, clinical, and administrative detail.” Phew. I’ll confess that I don’t know what exactly is under the hood. But I know enough about the informatics field to believe that this approach is viable and very exciting.

This YouTube video explains how the model can be used to run virtual clinical trials. Kasier has already backed the findings of Archimedes to change their diabetes care delivery.  I think there are fantastic, unlimited opportunities for applying such a fundamental model to medicine- personalized health predictions, public health, health policy, cost-effectiveness and what not.  As a startup, they are doing fine. With an impressive list of partners/clients, and a $15.6M RJWF grant (2007), they have a good runway and momentum. They have all the right ingredients to be a change agent for next-generation Healthcare IT.

Healthcare applications of Twitter keep surfacing everyday. Qwitter (not to be confused with another application by the same name that tracks people who stop following you on twitter) is a smoking-cessation tool built by the Florida Department of Health under a 2008 campaign called ‘Tobacco Free Florida’. It works like this- you tweet the number of cigarettes you smoked to @iquit <number> and Qwitter collects that into a progress ‘graph’. If your tweet is not a number, it adds it to your ‘journal’. So it becomes an ongoing dashboard of sort- with which you can monitor your progress and share it with others (that follow you) to get their supporting tweets back. People may scoff at this idea for being too niche or too small.. but I say “why not?”  Its putting social media to good use for smokers. Every little bit helps.

Google.org’s flutrend is an attempt to model flu activity across US based on the search terms that Google.com users enter around flu symptoms, treatment etc. The underlying premise is that there is a relationship between how many people search for flu-related topics and how many people have flu symptoms. Think of it as a virtual public health surveillance proxy. If you are not convinced that this is a brilliant idea, take a look at how their analysis relates to CDC reporting.

In case you didn’t know, Google.org is the philanthropic arm of Google, and it was formed with the commitment of 1% of Google.com’s profits to address some of world’s most urgent problems (read the famous 2004 IPO letter by Larry and Sergey where they mention it). The site humbly admits that the Flutrends system is experimental. Nevertheless, it’s impressive that in some instances Flutrends was actually predicting flu before CDC.

Of course, not all people who search for flu have flu necessarily, but the power of this analysis comes from the coverage and promptness, not the granular accuracy. The basic idea of harnessing the collective thought (a.k.a. search needs) of the population to predict/monitor health events is fantastic. And this is just the beginning, IMHO. When a population is connected real-time and discussing what they think/want/need, abstracting that information can yield powerful insights- not just for prediction and monitoring, but for most aspects of healthcare (diagnosis, prognosis, news, followup etc).

The concept is applicable to domains outside of healthcare too. Take twitter for example. Twitter is another platform with mass adoption where people are having real-time conversations about what they are thinking/doing. Just look at what intelligent twitter mashups did for getting real-time snow report of the Feb’09 storm in UK or the Dec’08 Ice Storm in New Hampshire. There are health related examples too- the feb’09 salmonella-in-peanut-butter recall could be tracked promptly on a Twitter feed (btw, this slideshare presentation by PF Anderson at the University of Michigan explains ‘Twitter for Health’ in detail. Thanks to Christine Gorman for the link).