Using intelligence to help people live healthier and longer is also my passion. I approached this by first working on whole-genome analysis technologies since 2000. But, soon I realized that the dream of individualized medicine wouldn’t be possible if there is no large amount of clinical data and patient data available electronically. In fact, there is a more fundamental problem, as you pointed out, that is our whole health care system is lacking data that can be shared and analyzed in large scale.

So, I have started to work on healthcare search engine for consumers in the past several years. In particular, apply semantic technologies and NLP to integrate structured and unstructured data and make them easily searchable by consumers. I hope by bringing large amount of health care data online, we will then be able to create intelligent systems to deliver healthier choices to everyone.

Until EHRs support computable data that covers subjective clinical data with objective metrics, we will never “bend the cost curve”. Clinical decision making is a highly connected graph with complex joint probabilities are simply unknown. Even large studies fail to provide much insight into these complex joint distributions due to data fragmentation.

I look forward to innovations at Keas. 2 years ago I worked for a company called Enfold (funded briefly by MDV) to create a similar application. Technology was not the problem. Financial support for the initiative from prospective customers was the failure point even they all “saw the value”. Hopefully Mr. Bosworth’s name recognition will create some sustained traction.

Thanks for the thought-provoking piece. Here’s what it, um, provoked from me:

The “Safeway” amendment currently included in the latest health reform draft potentially does just what you suggest in your reply to JP – allow payers to offer reduced premiums based upon good behaviors (smoking cessation, weight reduction, etc.). Given that motivation, people (or their employers or insurers) my look to tools like Keas to empower individuals to achieve their health goals. We’ll see what comes out of the other end of the sausage-making process.

While I agree with the eventual result you suggest, I wonder if the timing is right. Ten years seems like too short a time to effect a sea-change of the magnitude you present. ARRA Meaningful Use incentives for EHR adoption (and the ARRA enhancements to the language of HIPAA that gives patients the right to request an _electronic_ copy of their records and have them sent to a designated repository) will certainly move us down this path in a significant way. But there are still significant impediments to moving us to true evidence-based medicine that leverages information exchange, data mining and machine learning.

- Even given (a big, hairy given, mind you) sufficient data that is accessible, aggregated, longitudinal, and attributable to specific individuals (whether “identified” or not), finding the “evidence” takes time because most changes in medicine happen over time. We’ve learned an immense amount about heart disease and related illnesses through the Framingham Study data, but it’s taken decades of data collection to follow the progression of disease and reach a measurable clinical endpoint. Personal Health Records will help get us there because only the individual person is the common link between a lifetime of health-related actions, encounters and outcomes. That may seem obvious, but most data sources are provider, payer or disease-state centric, and don’t cover a lifespan. So the data will accumulate, but it will take time for the data stores to collect sufficient baseline conditions (genomics, environmental, etc.), interventions, and outcomes to show the evidence.

- Once the evidence is clear, you still need to change perceptions around the veracity of “wild” data compared with the gold standard of double-blind, placebo-controlled, prospective, randomized clinical studies that control for everything except the thing you’re trying to prove or disprove. Acceptance is growing, but not necessarily in a balanced way. Take the Vioxx example. Individual studies are equivocal regarding the effect of Vioxx and other Cox-2 Inhibitors on heart disease. But the meta-analysis of all of those studies suggests an association. Kaiser digs into their 9 million patient lives worth of data, shows the association, and shares the data with the FDA. FDA goes public and Vioxx is pulled off the market (Celebrex and Bextra too). Score one for data mining. But what if, instead of showing an increased mortality rate, Kaiser’s data had shown a beneficial effect on heart disease. Do you think the FDA would have given Merck a new indication for Vioxx based on this evidence? Not a chance. They would have said: go spend $20 million and five years to prove it in trials, then come back with the “real” evidence.

- Once you’ve got the evidence and have convinced everyone that it is valid and useful, then you have to change behavior – specifically, clinician behavior. Docs are not known for their rapid adoption of new approaches that are supported by evidence (unless, it seems, they are detailed by preternaturally attractive sales reps and offered samples – but that’s another discussion).

What I do believe is that this will ultimately be easier to achieve with consumers/patients/people than it will be with healthcare providers and regulators. That’s great and we’ll see some marked improvements in these capabilities through precisely what you’ve described. But there are an awful lot of conditions and interventions that can only be managed through the healthcare system (you know, where that frighteningly huge percentage of our GDP gets spent?). Changing that will take some serious time.

Nice WSJ video interview, btw. Great to see Keas finally taking wing…

Of course this was presented against the backdrop of data that indicates a patient visiting a physician has basically 50/50 odds of being accurately diagnosed and prescribed the most effective course of treatment. (As you can imagine this ignited a lively debate.)

The reality – the potential of the human mind to process all known symptoms, conditions, etc., and align them with emerging research, innovations in protocols is quite simply – impossible. This is what IT does so well. Where is the physicians talent best utilized – the very front end of processing “raw” data from their patient, or the backend of receiving refined data and then applying their insights and experiences to the proposed diagnosis and treatment plan?

If we extend this one level – we have in excess of 300,000,000 people in the U.S. and a much smaller population of physicians to provide care for every condition from the acute, to the chronic to the preventive. The ratio doesn’t work. Intelligent systems have the capacity to provide guidance and insight to consumers and direct them to the appropriate level of care. In some cases – self directed – with trended monitoring, in others clinical care. The foundation is the tracking of accurate, personal and automatically updated health information. Once this information is stored – IT and associated applications can work their data mining magic and create a new generation of health consumers and providers.

An overnight cure for healthcare for 100% of the population – absolutely not. The foundation for comprehensive long term “reform” – quite possibly.

I suspect that in the next 5 years, we will see electronic patient records established. The question will be; will they be accessible to enable learning. A new model of sharing de-identified data will be required or we may be in a world of information islands. The privacy rules and sensitivity of data will be the biggest challenge and may slow the process.

The alternative is the facebook of health where people self divulge health records. This is also happening in many ways. It will be a very different data base and create a very different set of values and issues. Enough group think and we will create a new disease, or treatments – a bit like rising sea levels and the yo yo craze or we will uncover observational disease data that reveal insights beyond any basic science, especially in areas where science has few answers today, like MS and autoimmune diseases.

Most likely, both will occur. How exciting. Need help?

Martin

For example, if a cholesterol drug works for 80% of the people, but not for me, due to some unique genetics, I’m likely to be lost in the noise. Data mining relies to some extent on generalizability — e.g., most people type “britney spears” correctly — , but presumably this is exactly the opposite of where medical/pharmaceutical research is heading.

Although problematic, it seems expert systems and the like still have some role to play.

Maybe what you are saying is that a) without more data, we can’t even tell whether that is the case and b) even ‘personalized’ treatments will still help a large enough group that data mining can detect it.

Keep up the great work!

In my work, I have dealt with a significant number of small private healthcare practices (clinics and physicians offices), who simply don’t perceive a ROI to them esp given what appears to be a very expensive investment. I’m sure I’m not telling you something you don’t know about here, and that your vision provides for a way such primary and specialty care providers can participate in EHR.

But what may turn out to be the primary driver for EHR adoption are the patients themselves, IF they learn the benefits firsthand in a meaningful way. SO…providing patients with the means of “taking” their health records with them everywhere they go and showing them when they need to any healthcare provider may do the trick. How to do this? A viral way of accomplishing that may be providing patients a way to log into and display their EHRs via a smart phone web browser, or from their doctors’ web browser. And perhaps you get patients to start doing this because (1) it’s free, (2) it’s relevant info, (3) it’s easy, (4) it evokes excitement, humor, passion, or some other appropriate emotion (ie marketing 101), and (5) it ultimatley benefits them personally. As more people become exposed to the idea of online health info on the patient side, the more pressure to implement naturally occurs on the provider side via politics/regulation, technologies/solutions, and clear ROI factors.

BTW, on point (4) above, something healthcare-related that is an analog to what you find at http://www.propel.com is one such tool that evokes passion; Propel is a retail distributor of biofuels, and they help their customers “feel good” about the carbon reduction they’re accomplishing by tracking their biodiesel purchases and calculating how much less CO2 they produced and equivalent number of trees for consumption. Perhaps someone can think of a way to dynamically track one or more benefits of shared EHRs that can be displayed to users as a feedback metric on how great this all is.