Today, clinical professionals have tools (like Ovid, ScienceDirect, UpToDate, Trip) that help answer complex questions and are connected to validated knowledge bases derived off of sources like PubMed. But how does a patient, with no access or expertise in the domain find and leverage this information? Medify tries to solve that.

The value proposition of Medify is not easy to describe. In fact, the ‘What is Medify‘ description on the site was banal enough to be dismissed, just like most other online social health startup marketing. They do a better (albeit prolix) job on the ‘How it works‘ page. Medify will appeal to the well-informed patients who are not afraid to sift through piles of academic articles burdened with medical jargon to understand and manage their own disease. Medify gives them a dashboard of existing literature – with it they can monitor things like which treatments are gaining traction in the provider community, which institutions are on the forefront of relevant research, etc. Affiliated web 2.0 functionality like faceted search, social sharing, tracking, annotating are bundled in to make it more personal.

Under the hood, it is smartly leveraging what public knowledge bases are already out there. The citation and abstract are free from PubMed. Interstitial phrases and terms in the content are further linked to sources like Wikipedia and MeSH. Brief outcomes or summaries are synthetically constructed from the article text.

Medify is not alone. There are other sites that try to help patients navigate the vast sea of research literature. PubMed’s parent NLM runs MedLinePlus,  UpToDate has a patient-oriented version, and niche startups like MyDailyApple, PatientsLikeMe are also tackling this to some extent.

In 2001 Brian Haynes, MD, PhD wrote an article describing the landscape of such ‘pre-appraised’ resources through a hierarchical structure that had four layers (called “4S” Model):

• Original ‘Studies’ (what PubMed provides) at the base
• ‘Syntheses’ (systematic reviews sources like The Chochrane Library) of evidence just above that
• ‘Synopses’ (like EBM, EBN Online) of studies and syntheses next up, and
• the most evolved evidence-based information ‘Decision Support Systems’ at the top.

He later expanded the model to 2 more layers (read about the “6S” paper here), but the basic argument remained same – Information seekers should begin looking at the highest level resource available for the problem that prompted their search. That is a good framework to understand why services like Medify are needed.

The skeptics would argue that offerings like Medify will do little more than empower hypochondriacs. But I believe that well-served health information only makes outcomes better. The lag time between published research being implemented in real-world medical practice can be in the order of decades. As consumers, we are entrusted to make choices about other important topics like money, and the market provides personal finance tools/services to help. Same can apply to healthcare, without diminishing the role of experts.

The underlying concept is nothing new in medical device industry, with it’s origins perhaps in holter monitoring fifty years ago. But true at-home remote monitoring began gaining traction in early 1990s; and today some major names are in the race: Honeywell Hommed, Philips, Health Hero, Cardiocom, Corventis. All of these companies have had an actual device as a part of the overall offering-  some piece of electronic hardware that enables capture and transmission of given physiological parameter(s). LifeStream, Motiva, HealthBuddy, Commander, PIIX are the respective names of the hardware from companies mentioned before. Even the recent consumer-oriented solutions like GlowCaps, Zeo, Fitbit etc. have a proprietary piece of electronics central to them.

And that, is what makes Welldoc is interesting. They have a disease management solutions that are entirely mobile and web-based. No proprietary hardware. It’s an interesting approach that points to an underlying need as well as an overall weakness of such models.

The unmet need here is for solutions that help engage patients at home and provide round-the-clock assistance in chronic disease management (e.g. what insulin dose to take, when to see your physician, etc.). That doesn’t require a device hooked to patient necessarily- it can be accomplished by manual data entry, easy-to-use software and intelligent algorithms. The value proposition is across many soft (as in, hard to quantify ROI on) aspects: enabling patient self-management, promoting health education, improving compliance, effecting positive behavior change etc. Of course, all these lead to some hard benefits that can be quantified (like improved Hb A1C values over time), but the cause-effect relationship can never be established beyond doubt.

The weakness in this approach is that all this depends on manual data entry by the patient or caregiver. It assumes that the affected individual is capable and disciplined enough to interact with the software consistently and reliably. Offering mobile applications is one way to start making that assumption partially valid. As a constant companion with computing power and internet connection, mobile phone makes it easier to use such software. But not enough to cover what I call the ‘last mile‘ of remote patient monitoring- from the patient’s body to an electronic data capture device. No matter how sophisticated the software is, it’s no good if there is not enough data to run its logic on. And our fundamental human behavior tends to revert back to lazy, undisciplined ways sooner or later. So yes, there is a role for pure disease management software but its a stretch to assume that it’ll suffice on its own.

WellDoc was founded by endocrinologist Suzanne Sysko Clough, MD in 2005. Their first solution, focused on Diabetes managment, was piloted in Baltimore in early 2006. Digging through their news it seems they have been fortunate enough to find substantial angel and grant funding, starting with $5M in 2007 and totaling nearly $17M to date. Recent years have also brought some big milestones for WellDoc: deal with Jitterbug (April 2009), FDA clearance (August 2010), deal with AT&T (October 2010), and integration with AllScripts EHR (December 2010). WellDoc website is skimpy on the actual details of their product, but there is a high-level demo. They seem to be expanding beyond diabetes into cardiovascular, wellness, medication adherence and clinical trials data management areas. That is a smart move. Also smart is their attempt at a business model. As their CEO explains in this article, they are aiming to get paid by large employers, plans and payers for making chronic disease management programs more effective.

The whole RPM industry has been praying for national direct reimbursement for decades now. Its been a tough journey so far- positive studies keep trickling out, and every year seems to be the one that will finally see payers admitting the cost-savings from RPM and starting reimbursement. WellDoc has also invested heavily in clinical trials to convince the industry. It’ll be worthwhile to see how successful a purely software-based company would be at making a living in the RPM market.

February 2011 Update: WellDoc announced that they have acquired Oncology Care Home Health, LLC, a education and consulting company helping home health providers implement specialized oncology home care programs. Probably the idea is to use that specialized knowledge to augment the logic behind their oncology offering (maybe get that FDA certified?).

At the heart of the model are a set of ordinary and differential equations that represent the physiological pathways relevant to diseases and their complications. The ‘variables’ in this model include signs, symptoms, patient behaviors (including adherence), provider behaviors, provider performance, encounters (e.g.  ER visits, office visits, admissions), protocols, guidelines, tests, treatments, etc. Basically, it tries to incorporate all aspects of diseases and healthcare system that are needed to analyze downstream clinical outcomes, utilization and costs.

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.

Jan 2011 Update: The FDA and Archimedes entered into a research agreement to understand the benefits of weight loss compared to the long-term risks of cardiovascular outcomes in patients treated with weight loss drugs.

What a great startup idea. Service demand can be tapped easily since users are searching the web for highly specific keywords (almost all include the keyword “trials”, so bit of SEO and keyword advertising would direct the traffic effectively). Other sources are the rapidly growing PHR platforms like Google Health and Microsoft Healthvault- both encourage developers to write apps that provide such value-added services based on user’s health information. Supply is readily available on ClinicalTrials.gov, a government-sponsored online public registry of clinical trials in US.

TrialX.org is completely free for users (patients). They let investigators create free accounts to post their trial information directly, but charge a fee for providing access to the interested potential trial enrollee. It’s hard for trial investigators to find eligible patients who are motivated to stick around for the complete trial. TrialX solves both the problems for them.

Imagine the possibilities if this service gets integrated into CIS vendor products. A patient coming in for advanced  breast cancer treatment can be flagged right at admission and be given the option to enroll in an experimental drug trial right then, if they so choose. If nothing else, it’ll give the medical research community a much more real-time opportunity to advance the science.

September 2010 Update: Just read about another startup in the same space- MyTrus. They have little information on their website, so not much to discuss at this time.

Wiki’s are a good way to organize collective wisdom in any field, so the concept is valid. Problem with wiki’s are that 90% of content is written (and policed) by 10% of the users. When your potential audience is not a big number (only 100K or so residents enrolled in US every year) and nature of material necessitates careful oversight, all that translates into a very slow progress for content. Their homepage was last edited in Dec 07 and last blogpost was in April 08. The site draws a decent number of unique visitors though..in range of 5,000. Hope they gain momentum in future.

SimulConsult has an interesting logic behind it. Roughly speaking, its knowledge is derived from a ‘computational wiki’ that is restricted to physician users only. So its database is not only open for viewing, but users can submit modifications to the database. The system performs bayesian pattern matching and also considers temporal information like the age of onset and disappearance of each finding for each disease under consideration.

According to Dr.Segal, there are about 33,000 data points (disease findings) in the system and the future expansion plans are to include more of metabolism and genetic diseases. Interestingly, the wiki approach for knowledge gathering in healthcare is becoming more common (AskDrWiki, WikiDoc, wikiMD to note a few- more on them later).

Feb 20, 2009 Update: Got an email today announcing that those who contribute information to SimulConsult database will now get paid for their contributions. As they are adding sponsored links in the software, I guess it makes sense to share the wealth. More info here.

I took it for a test drive with a moderately complex question (‘what is the indication for platelet transfusion in an 80 year old female with dengue fever?’) and got relevant results in terms of review articles and clinical trial outcomes. Pretty cool.

The logic behind Curbside.MD is semantic indexing using a controlled medical terminology (they call it “semantic fingerprinting“) with a bit natural language processing. They provide a bunch of tools (search box, news, spellchecker etc.) for partners and a browser search toolbar for users. The technology is also available as an API service from an alternate website called Fingerprint.MD.

Praxeon is the company that started Curbside.MD and MyDailyApple in 2006. Both websites are currently free for users, but the company admits to a future ad-based business model.