Payers Refocus Efforts on ROI for Member Engagement

cvrWhat a difference a year has made to the payer market. In late 2012 Chilmark Research published the first version of our Payer Benchmark report — detailing how leading payers were beginning to adopt emerging consumer technologies. We found a market where significant experimentation was occurring, but little if any broad, member wide deployments and a market still trying to understand social media.

This week we are releasing the next iteration of this report – Benchmark Report 2013: Payer Adoption of Emerging Consumer Tech – Payers Continue their Pursuit of the Digital Consumer. Based on the research I conducted for this report, I find it simply amazing to see how this market has shifted over the course of a single year.

For one thing, the traditional health insurance business model continues to erode, as the Affordable Care Act (ACA) has capped medical loss ratios (MLRs) and has completely stripped payers of their ability to underwrite based on health risk.

Meanwhile, payer-provider realignment is ongoing. Hospitals are partnering directly with employers or launching health plans that might compete with payers in the employer market. Likewise, some payers are acquiring providers to more closely align financial interests with healthcare services delivered.  All this bodes well for rising interest in payer-provider-aligned population health management and patient engagement technologies.

In addition, the ACA/Obamacare has come to be seen as inevitable, and Health Insurance Exchanges (HIX) are forcing payers to seek out new places in the minds of consumers and within the broader healthcare ecosystem –  with an increasing focus on engaging and retaining consumers.

Outside of healthcare, the consumer tech space continues to defy our expectations.  It is easy to see how in the past year that emerging, low-cost activity tracking technologies have spread far beyond early adopters.

These and other macro forces are pushing payers toward the digital consumer in ever more multi-faceted ways.  For example, payers have drastically pulled back from their flurry of experimentation in 2012, and are now focusing their efforts into fewer, more precise areas where they foresee strong potential for ROI.

One change from 2012 is the pull-back in creating mobile app versions of member service portals, as have health & wellness app launches. (This makes sense: in general, very few payer-launched or payer-owned mobile apps have gained any kind of significant traction, with iTriage as a notable outlier, and they already had good traction prior to acquisition by Aetna).


While payers may have pulled back from rapid experimentation along certain lines, this does not mean that they have given up on the digital consumer. To the contrary, we continue to see growing investment in payer-owned consumer platforms, biometric tracking initiatives, the next generation of social media, and more… all detailed in the report.

This report profiles an expanded set of payers as compared to the first edition, across commercial, Blues, and provider-aligned categories. These innovative payers are exploring the wild west of digital consumer engagement and learning as they go. The report describes their experimentation in detail, what initiatives are working and why, and where promising new territory might lie. Any organization that is looking to build-out a strategy that leverages consumer tech for member/patient engagement will find this report invaluable.

We hope our subscribers enjoy the read…as much as we enjoyed the research.


The Two Faces of Population Health Management

As we head into the New Year, we at Chilmark Research have been thinking a lot about how we will approach Population Health Management (PHM) in 2014, and beyond.

PHM is actually a pretty unfortunate term for the data-driven business processes and associated tech stack that HCOs must adopt as they head towards value-based reimbursement. But, the term is here to stay and therefore we must embrace it (besides, does anyone have a better term that does not include “Big Data” or “Accountable Care”?)

In August, we released our first market trends report addressing one aspect of enabling PHM: 2013 Clinical Analytics for Population Health Management Report. We are now working on the next iteration of this seminal research report, and as the market evolves, we must continually ask ourselves: “What does Population Health Management mean today?”

In public health circles, the concept of PHM is simple: increase a set of quality KPIs across a population that includes both low and high-risk groups.

In the real world, PHM is what is happening as providers move from FFS to value-based payment models — effectively forcing them to adopt HIT to (1) improve and report on ever proliferating quality metrics, and (2) move from a “cost plus” business model to one of cost containment.

Currently, we see PHM divided into two main categories that were previously, by and large, the responsibility of payers and vertically integrated HCOs: Care Management, and Performance Management. Below is a tech stack figure that I am using to visualize these two categories:

Care Management involves managing patients –both during and between visits– according to standardized protocols. The hope is that by identifying sources of patient health risk and through clinician intervention, costly utilization can be prevented and/or quality measures attained. Analytics and associated content are required to build out the necessary quality measures, care gaps, predictive models, etc. Workflow tools are needed so that clinical and care management teams can take timely action.

Care Management solutions on the market today are incredibly heterogeneous, ranging from basic disease registry dashboards to full-fledged care coordination workflows that can span an exceedingly wide range of care venues.

Performance Management is the domain of the Chief Medical Officer (CMO), CMIO, CFO and department leaders. This category of tools is informed by analytics and is meant to identify opportunities for care delivery process improvement across the HCO’s network. The emphasis is on turning the HCO into an efficient and cost effective organization (improving the health of a population might be a side effect).

For example, consider how important it is to identify which orthopedic surgeons are responsible for the highest variation in length-of-stay (LOS) and cost:

Yes, there is overlap between these two categories. For example, a physician leader might want a dashboard to view aggregate quality measures for different cohort populations, as well as have the ability to slice and dice and drill down to specific patient outliers. In addition, utilization and cost metrics are increasingly being used within care management tools as a way to identify high-risk patients.

One thing we at Chilmark Research continue to debate is how the definition of PHM might keep expanding. It is easy to define certain boundaries. We do see PHM as care delivery and care management centric – it is not about optimizing all HCO operations. Therefore, Chilmark will not wade not wading into RCM or supply chain/staffing territory when it conducts research on PHM.

Other boundaries, however, are not as easy to define. For example, what about  data mining tools that monitor inpatient vital signs in real time to predict sepsis? What about treatment pathways and the data-driven AI tools of the future that are meant to replace doctors? These should all have tremendous impact on patient health, right? Not to mention how activity-based costing systems (ABC) will eventually integrate with PHM systems (e.g., Intermountain’s relationship with Cerner).

The bottom line in my research that I will keep coming back to is the concept of driving care delivery efficiencies under value-based reimbursement, and the current separation between performance management and care management. Having said that, I look forward to 2014 where we will see if the term PHM will stand the test of time, or go the way of ACO-enablement.

Lastly, I invite our readers to chime in or contact me directly with their thoughts on PHM. Do you agree with how we have scoped out our PHM research? Is there anything that is currently a prioritization  at your organization that I have overlooked? I look forward to hearing from you.




Time to Move Beyond HIE

CNMOur ongoing coverage of the HIE industry leads us to the question of what clinicians do after getting connected to an HIE?

To this end, we are conducting a 10-minute web survey on clinician’s experiences using HIEs for care coordination. We want to understand how clinicians are using HIEs today in their daly activities. If you are a credentialed clinician with any experience using an HIE of any kind, we invite you to take the survey by clicking on this link.

In appreciation for completing the survey, we will provide a $50.00 Amazon gift certificate for the first 50 completed surveys we receive from verifiable clinicians (i.e. a working email address at the end of the survey). We are particularly looking for clinicians working in large group practices or in post-acute care but any care venue is appropriate. Just remember, you must be a credentialed clinician, have a good sense of how your HCO is or should be using an HIE, complete the entire survey and provide us with an email address to qualify (and also so we know where to send that Amazon GC). Don’t worry, we promise to never to disclose your name or the name of your organization and your contact details to anyone, for any reason.

Why are we doing this?
Simple. The days of thinking about HIE as basic plumbing are over. Enabling HIE remains complex and expensive due to the lack of interoperability across the heterogeneous EHR landscape found in most communities. At a recent conference, David Kibbe of DirectTrust gave a presentation with the following data points.

In one Arizona County there are…

Specific Data Points

  • ~6400 physicians
  • ~70 EHR vendor products
  • 58 of these vendors have fewer than 100 physician customers each
  • 104 Walgreens locations
  • 64 CVS locations
  • 8 HIEs
  • 1 Immunization Registry

Unspecific Data Points

  • Some number of reference labs
  • Some number of imaging centers
  • Some number of long term care providers and facilities
  • Some number of home care provider organizations with some number of nurses, home health aides, assorted other clinicians and social workers
  • One state ELR system and disease surveillance system

While we certainly recognize why many still speak of HIE in the context of just stitching together communities of practice and their disparate EHRs; to truly move forward, healthcare leaders need to stop thinking that they are enabling HIE. Thinking within the construct of HIE is a natural, self-limiting proposition that does not focus on value realization.

Follow the Money – Network Management Critical
As the industry makes the massive transition from fee-for-service to value-based reimbursement models, the long-term success (or ultimate failure) of a healthcare organization will be highly dependent on their ability to effectively manage their clinician network, both owned and affiliated. And when we say manage, we are not talking about heavy-handed management, but more about ensuring that all in-network clinicians are aligned along the same goals and objectives to maximize reimbursement. Network of clinicians need to work together to accomplish such goals as:

  • Successful care transitions that minimize readmits
  • Managing care gaps
  • Define, distribute and track clinical pathways
  • Keeping those at risk of chronic disease from contracting the disease
  • Effectively manage patients with chronic disease(s)
  • Practice score-carding to identify outliers and take corrective action
  • Assign attribution based on contract terms and clinician involvement

Virtually all ambulatory practices do not have the resources to address the above and their EHRs certainly won’t get them there either. Only the parent HCO has the resources and expertise to enable this advance functionality and it is their job to insure such is distributed to their network and owned and affiliated physicians.

Our hypothesis is that large HCOs are searching for ways to influence clinical processes and workflow outside their walls and will leverage their HIE infrastructure to do so. At the same time, community-based clinicians need better access to better information so they know what is expected of them when treating shared risk patients. In the next year, we will be looking at the ways that HCOs are building alignment within their networks of physicians – owned or affiliated – to establish common care goals and objectives that also maximize contract opportunities for everyone.

This survey is the first step in our research on the necessary transition from HIE to Clinician Network Management (CNM). Time to roil the industry and think beyond the limited confines of HIE to the value that can be delivered within a clinician network.


Data-Driven Patient Outreach: Financially Efficient or Morally Compromised?

I recently spoke with a clinical analytics vendor about one of their provider customer’s bizarre decisions – to no longer encourage a subset of their diabetic population to take the HbA1C test. The reason? These diabetics were covered under a new P4P payment contract, which no longer rewarded such testing.

I am not naïve to the fact that, since the beginning of the practice of medicine, patients have been treated according to different care standards…with payment to blame more often than not.

Now our payment models are evolving and population health management (PHM) has become a word du jour. In addition, the payer-provider line is blurring, and data is flowing more freely than ever between the two former adversaries. From a PHM-centric standpoint, new incentives now present themselves to treat similar patients differently based on these newly acquired datasets.

Different Payment, Different Data, Different Outreach

Take for example, massive healthcare systems such as Intermountain and Geisinger. These HCOs own their own health plans, but unlike Kaiser Permanente, also accept outside insurance. Patients can therefore be covered be under FFS, P4P contracts, risk-based contracts, as well as the HCO-specific payer plan. In addition, these HCOs have developed their own advanced care models that should, in theory, override the influences of payment on care. However, things soon get tricky with regards to PHM outreach:

  • If Debbie the Diabetic is covered under FFS, she will get zero outreach or, if she is lucky, outreach based on her sophisticated HCO’s advanced care models — with the HCO acting against its own short term financial interests.
  • If Debbie is covered under an all-upside P4P contract, she will get reminders in order for the HCO to tick off certain boxes in her payer’s P4P contract (process or outcomes-based), for example, to encourage her to come in for HbA1C testing, foot exams, etc. Perhaps there will be minimal effort invested in helping her control her blood glucose better.
  • If Debbie is covered under an at-risk contract that incentivizes global cost reduction (MSSP ACO, ACO with potential downside, capitation), someone will be trying to figure out how to get her cost utilization down. Her claims data will be run through a risk assessment model, and her costs will be projected. If Debbie is sufficiently out of control and really racking up the costs, she will be assigned a high touch case manager.

Note: the important enabler within these different outreach models is different datasets and the analytics software that runs on top. P4P Registries run on top of billing or EHR data. Risk-based analytics runs on top of adjudicated claims data. Within each analytics system, care gaps and associated outreach are tailored toward entirely different payment models.

Giving up on “Hopeless” patients (because the data says so)

There are many more usecases ahead in which data can be leveraged to perform unequal PHM-outreach. Take, for example, the ability of a risk-bearing HCO to predict which patients will actually comply with outreach, and which can be assigned to the “Hopeless” bucket.

Every medical professional can recount various patient horror stories. The mentally ill woman who visits the ED every weekend even though there is nothing wrong with her physically. The morbidly obese diabetic who has just lost a foot but continues to eat himself into oblivion. Despite the repeated pleas of multiple case managers, these patients are unable or unwilling to modify their respective trajectories.

If there is absolutely nothing the HCO can do to change certain patients’ behavior (within a given budget), should the HCO cut its losses, ignore the Hopeless, and focus resources on other patients?

Shiny new predictive models could be used to this end. Think of the growing number of variables with predictive power beyond ICD, CPT, and charges: BMI, race, zipcode, past outreach responses, self-generated fitness data. Let’s enter morally shady territory and include variables sold by data scrapers: real estate transactions, courthouse documents, credit worthiness of facebook friends, etc.

Running Debbie the Diabetic through this predictive model, we might learn that there is a 1% chance that she will respond to automated outreach, and a 15% change that she will respond to high touch outreach. It may be financially efficient to focus care management resources on other patients, but what would Debbie’s doctor say about this?

The medical establishment isn’t exactly in love with unfamiliar predictive models that use sensitive data sources to tell them which patients will respond to outreach. Clinicians usually already know who these patients are within their panels — and believe in a more equal approach to outreach.

As providers continue to disrupt themselves via value-based reimbursement, PHM-outreach inequalities will be just one of the many contentious problem areas going forward…and the desires of risk managers and clinicians will continue to collide. In my conversations with vendors and end-users for the Clinical Analytics Market Report research, I for one was surprised at how nonchalant my interviewees were in discussing this morally ambiguous territory — and I have yet to hear the patient’s voice.




Can Mirth Revive NextGen?

Last week, NextGen’s parent company, QSI, acquired open-source tools vendor Mirth for $59M. While a relatively small acquisition, it nonetheless will have an impact on the broader HIE market. Mirth’s toolset has an array of HIE components, notably its well-regarded Mirth Connect integration engine, the cornerstone of its commercial and open-source success to date.

The acquisition confirmed two critical points we made in our 2013 HIE Market Trends Report:

1) EHR vendors need new and better ways to support clinical interoperability in an increasingly heterogeneous EHR world and
2) that consolidation in the HIE market will continue unabated.

Mirth, was never a full-bodied HIE vendor, but has been a steady presence in the market as a component supplier to HIEs and HIE vendors, notably Harris and Covisint among others. Its open-source tools get potential customers in the door who can then convert to a commercial license. In a call with Mirth executives, post acquisition, they stated that today, there are nearly 650 commercial licensees of Mirth Connect – for clinical interoperability projects.

Mirth’s integration engine, Mirth Connect, is not as widely deployed in production environments as most of its competitors (i.e., Orion Health, Corepoint, InterSystems or Infor). However,, Mirth Connect has found its way into a variety of prototyping and testing environments for HL7 messaging and EHR integrations. For many developers and healthcare systems, its no-cost, initial cost has been irresistible to desperate HL7 developers around the industry with Mirth claiming some 25,000 active open source licenses out of the 100,000 plus downloads of Mirth Connect.

While Mirth Connect is the cornerstone of Mirth’s product suite, the company does offer other tools that are commonly found in HIE deployments including a data warehouse and master patient index (MPI).

Like other open source vendors, Mirth has grown by selling wrap-around services to healthcare organizations (HCOs) that use its solutions for more extensive and complex deployments. Accordingly, Mirth pops up on our radar screen in discussions with public and enterprise HIEs. Mirth has also been very active in the efforts of the EHR Vendor Affinity Group for the Beacon Community, convened by ONC. But despite its well-received tools and commitment to better clinical interoperability, Mirth has always been somewhat hamstrung by its organizational reach, resources and delivery capabilities.

With this acquisition, NextGen will now use Mirth products for the 90,000 physician users of its community EHR offerings. In speaking with a senior executive at NextGen, she informed us that NextGen plans to preserve Mirth’s independence, retaining the Mirth brand, staff, offices and existing partner relationships and software licensing terms.

We see this acquisition of Mirth as a relatively low cost way for NextGen to accomplish two goals:

1) Do what it could not accomplish internally; develop a cross-enterprise interoperability platform for its current and future customers.
2) Reinvigorate the company and its market luster.

Main Street Realities and Wall Street Expectations
Quality Systems is under pressure to change for two sets of reasons: the dynamics of the community EHR market and the requirements of Wall Street.

These are unsettled times in the community EHR market as physicians gain more day-to-day experience with EHRs, leading inexorably to heightened expectations for EHRs. While the giants of the community EHR market boast like Roman emperors about their offerings, single-digit market shares and rumors of mass EHR replacements have vendors looking over their shoulders. NextGen, like all community EHR vendors, has customer retention concerns and must take product actions so its customers can participate in new models of care at both the patient and population level.

The acquisition of Mirth is also a tacit admission that NextGen’s EHR Connect has not been entirely equal to the complex task of providing cross-enterprise EHR interoperability for its customers. NextGen EHR Connect, like similar offerings from most EHR vendors, does not readily support interoperability in a heterogeneous EHR environment.

While the company is making all the right noises about how Mirth can help provide more interoperable data to support new payment models and population health management, it is unclear why NextGen took this specific product action: buying – rather than partnering with – a company to achieve this goal. After all, plenty of HIE vendors, EHR vendors and HIT integrators thrive using partnerships to get any or all of the tools that Mirth sells.

The explanation probably lies in Quality Systems, Inc.’s (QSI) relationship to Wall Street. The company is now “dead money” in Wall Street lingo. It certainly has fared less well than some its competitors (see chart for an unflattering 1-year comparison with Cerner, athenahealth and even down on its luck Allscripts). A hedge fund owner forced QSI to take on three new board members this summer and reevaluate the company’s “strategy”.

This acquisition could be more related to how the company is perceived by Wall Street than Main Street HIT customers and partners. Buying Mirth was relatively cheap – $59 million reportedly – and, in the Wall Street worldview, a way to burnish NextGen, with its roster of captive physician customers, thereby making it a more attractive target to the usual roster of larger, acquisitive HIT and private equity companies.

Licensing Caution for Mirth Customers and Partners
For existing Mirth customers, product licensing could become problematic over the long term. While NextGen is committed to preserving Mirth’s existing open-source and commercial licenses, the pressure to deliver better revenue results is on at NextGen and the company will eventually turn its attention to increasing the revenue yield of solutions built with Mirth tools that are now spread across many HCOs.

For Mirth’s open-source customers, the transition to some kind of NextGen master license from Mirth’s Mozilla-derived license could introduce unwelcome changes in the form of decreased deployment flexibility or increased direct or indirect costs. These customers could experience higher than expected costs and contractual complexity as they expand their deployments to support new needs or more users. All Mirth customers risk being stranded on existing software as NextGen evolves the software and licensing terms of future versions of Mirth tools to suit its needs. NextGen’s commitment to or interest in preserving the licensing rights or upward compatibility of existing customers is a question mark over the long term. If QSI itself is acquired, that uncertainty multiplies.

For Mirth partners, the foregoing concerns could be more significant. We know that HIE vendors Harris and Covisint have relationships with Mirth under which they use a variety of Mirth tools. We can only hope that these and other partners contemplated that Mirth could be acquired – and its new parent could in turn be acquired – when negotiating the terms of their partnership agreements and licenses. If not, they and their HCO customers could be surprised as Mirth’s licensing terms change to meet the business needs of its new owners.

Granted, all Mirth customers have the current source code should NextGen indeed change terms and conditions in unacceptable ways, this may put some of these companies in the position of directly supporting the code base going forward.

Consolidation Continues and EHR Vendors Interoperate

The bottom line is that this acquisition is more evidence of consolidation in the market for clinical interoperability and for the technology stack found within HIE solutions suites. NextGen is not the only EHR company to acquire HIE technology with Allscripts having acquired dbMotion earlier this year and Siemens acquired MobileMD nearly two years ago. It is also evidence of EHR vendors’ need for better interoperability technology and the inadequacy of existing EHR vendor solutions for connecting care communities in the new world of payment reform.

If history is any guide though, HIE-related acquisitions by EHR vendors do not bode well for this acquisition of Mirth. Over the last several years several HIE vendors have been acquired by EHR vendors. In all cases, these acquisitions have led to the former independent HIE vendor to be but a shadow of its former self.



Clinical Data Has Arrived. Now What?

Last year it became clear that the term ACO-enablement was going out of fad, and a new buzzword — population health management (PHM) — was surfacing. After interviews with several industry stakeholders, it soon became clear to us at Chilmark Research that there were high levels of interest in:

  1. Just how new sources of clinical data (EHR, HIE, user-generated), were going to be ingested into analytics systems, and:
  2. How providers were going to adopt analytics for PHM as they began to take on patient health risk in value-based reimbursement contracts.

As we continued interviewing vendors and talking to people in the field, our first Analytics research endeavor, Clinical Analytics for Population Health Management (CAPH) Market Trends Report, (expected publication: week of Aug 19th – stay tuned) began to take shape. As an analyst I was both excited to dive right in, and at the same time daunted by the level of technical, clinical, and business-model complexity that would be involved.

A large, thorny, elephant was in the room that no one seemed to want to talk about — were providers the right parties to take on patient health risk? Would they fail like payers before them? Regardless, providers were starting to march down the risk continuum, and I was going to follow them.

As we began talking to more vendors, it soon became clear that an incredible number of them were pivoting, purporting to serve the CAPH market. Some were positioning offerings along the ACO lines, others were talking about Big Data, and others preferred a Population Health Management marketing message. In the end we selected 14 vendors to profile across several different categories:

Top Level Classification Vendors
Clinical Best of Breed: Infrastructure-Centric Caradigm, Explorys, Health Catalyst, InterSystems
Clinical Best of Breed: App-Centric Humedica, Wellcentive
Claims-Based Best-of-Breed App & Pivoting The Advisory Board Company, Aetna/ActiveHealth Management, Truven
HIT Vendor with Secondary Analytics Solution athenahealth, CareEvolution, Cerner, MedVentive
Generic Horizontal Analytics/Services IBM

The process of interviewing these vendors and their end-users was initially tedious, as vendors often had radically different architectural approaches and stances on the market. A common language had not (and has not) developed for talking about CAPH, and I soon learned to speak claims-centric and clinical-centric dialects.

Over the coming month I will be writing a series of posts on some of the more interesting findings from the report. Please feel free to leave comments below or get in touch with me directly if you are interested in clinical analytics/population health management — I will enjoy any and all feedback and as I continue to follow the CAPH space closely over the coming year.