Most of the time, Health IT spawns artificial concepts – born as a result of relentless media hype, each reaches a precocious peak of publicity and then quickly fades away. Buzzwords like RHIO, NHIN, PHR, Chronic Disease Management, etc. were all touted as game changing at one point or other in the past. Now it’s more about patient engagement, HIE, Analytics, Care Collaboration. One stands out in my mind though – Population Health Management (PHM). I think that even though it may be riding the hype cycle like all others, it has signs of legitimacy.
Think of it this way. For decades, we have endured and participated in a healthcare system that is geared towards encounter-based medicine. Patient comes in with complaint X, gets treated and billed for complaint X. Now with changing payment models though, it is important for the payers and providers to broaden their perspective. They need to keep track of patient (member) over a period of time, and keep them out of hospitals/ERs. As a result they need a “Longitudinal Health Record” that spans across encounters. This is what HIEs promise to provide and interoperability standards promise to enable.
From a Health IT vendor perspective, PHM means tools that help user do two things:
This is done by analyzing a population in a given care context. Like HbA1c tests for diabetics. PHM construct is based on the premise of looking beyond those who need immediate care (i.e. are having an encounter) and provide insights on the entire cohort under care.
This is where the analytics graduates into what it should be – Actionable Analytics. The ideal PHM tool will not only help find at-risk individuals, but also make it easy to do something about it. So if the PCP user has found the 50 at-risk diabetics in his/her 1000 patient panel, they now need to send reminder letters or queue them up for some kind of outreach. This workflow integration is what really legitimizes the emerging niche of PHM. Just analytics on it’s own doesn’t cut it.
But the devil is in the details, of course. One can argue why EHRs, the perennial stolid incumbents of health IT world, don’t have this as native capability. The answer is clear if you’ve ever used an EHR. They were (and are) built as transactional systems that focus on the current visit billing and documentation. Doing a parallel meta-analysis of how this patient fits into a population profile and what they need outside the context of this visit is a humungous leap for almost all EHRs. And that is why a new crop of startups have started to focus on this niche.
AmplifyHealth says all the right things on it’s website. They point out the need for finding patients that are going off-track. Like most startups, it avoids putting a live demo video on the site (so frustrating) so I’m going off of what the webpages claim as capabilities. The three areas they speak of:
- Patient Management: Seems like this provides ability to create custom lists, akin to registries. That is a valid value-add, aligned with actionable analytics as described above. But the website description veers off into “engage new patients, influence productive behavior, establish relationship” which is confusing. All those belong to the foundational practice management and EHR system.
- Measuring Outcomes: This would be the ‘meta-analysis’ that doesn’t come native with EHRs. Tracking outcomes based on measures is just starting to get engrained into the EHR DNA, thanks to the bullying by Meaningful Use regulation. But even that is a very regimented approach to this meta-analysis, and may not suffice for an ideal user. Hence the value-add opportunity.
- Client-Sales Support: Very interesting. This seems to be an administrative dashboard for provider groups, self-insured employer groups to analyze of potential savings for a population. So it goes beyond just the clinical aspect of Population Health Management. I can see that as a separate sell to administrative, non-clinical users.
Buoyed by the hype that usually accompanies anything new Health IT, PHM is ready to bask in media limelight. But this may be one of the rare occurrences where there is actual substance underlying the claim to fame. Of course, only time will tell. One thing is for sure – you will see this term splattered across a lot of vendor booths in HIMSS 2014.
Scientific and medical research has seen explosive growth in the past few decades. Since 1996, the United States National Library of Medicine (NLM) has maintained PubMed, a free portal providing access to references and abstracts on life sciences and biomedical topics. PubMed now has over 21 million citations going back to 1966, and continues to add a staggering amount (about 500,000 new records) each year. The chart below was adapted from a recently published journal article about PubMed.
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.
Patient Monitoring is one of the mature, established markets in healthcare industry. A promising trend in that is the emerging ‘Remote Patient Monitoring’ (RPM) paradigm. (If you don’t know much about RPM, this 2009 report from Frost.com is one of most insightful ones out there. It requires paid subscription though).
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?).
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.
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.
TrialX.org is an fantastic example of how the web enables linking specific demand with relevant supply. The services matches users (patients, affected individuals) to ongoing clinical trials using their submitted personal health information.
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.