We will release our newest report, 2019 Healthcare Provider Analytics Market Trends Report, in the next few days. This report reviews the current market for provider analytics and evaluates offerings from 23 different vendors.
Key Takeaways
In recent years, providers invested in analytics technology to support the transition from fee-for-service (FFS) to value-based care (VBC). Vendor offerings that support the variety of pay-for-performance (P4P), pay-for-reporting (P4R), and risk-sharing programs with payers have helped them better understand the interaction of costs, quality, and utilization in the populations they serve. But the applications for analytics are broader than just VBC. Provider healthcare organizations (HCOs) are seeking to leverage these technologies more broadly to support a range of clinical, financial, and operational performance improvement goals and programs.
Provider-oriented analytics availability mirrors EHR penetration. Providers in acute and ambulatory settings have many choices for analytics across multiple use cases. Providers in post-acute settings and others with low EHR penetration have relatively fewer choices. While vendors have devised a number of ways to extend their offerings to underserved settings, not all providers take full advantage of such capabilities.
EHR vendors are often, but not always, providers’ first choice for analytics. Most EHR vendors sell analytics offerings almost exclusively to their existing EHR customers. Independent vendors – not owned by an EHR vendor or a payer – are a strong alternative to EHR companies for value-based care use cases. Claims analytics companies have deep experience with claims data sources or rely heavily on claims-related data to fuel analytics and reporting. Applications from many of these vendors emphasize cost and utilization control and feature deeply descriptive insights into risks, costs, quality, and utilization. Providers have historically been reluctant to adopt these offerings, but that is changing.
This report characterizes current analytics solutions as either “mainstream” or “advanced.” Most HCOs have experience with mainstream analytics – often cloud-hosted and reliant on relational databases that store historical data from the EHR, claims, and other sources. The resulting applications characterize and summarize performance along multiple dimensions. While this technology approach is well-established, mainstream analytics still faces challenges. Chief among these are data quality and variability. Diligence is required on the part of vendors and HCOs to ensure this data is accurate, high-quality, and up-to-date.
Data complexity challenges are only increasing because new data sources are on the horizon. The All of Us program (formerly known as the Precision Medicine Initiative) promises to unleash a torrent of novel and voluminous data types. In addition, the vast trove of unstructured data in EHRs will soon contribute to a better understanding of patient cohorts and risks. Social determinants of health (SDoH), data from smart health monitoring and fitness devices, and a variety of patient-reported and publicly-available data sets are also beginning to be used in provider analytics.
Mainstream analytics has yet to supply a variety of predictive and prescriptive insights; for that, HCOs are looking at advanced analytics.
Advanced analytics consists of interrelated technologies, the most common of which are artificial intelligence (AI)/machine learning (ML), natural language processing (NLP) and extraction, and big data technologies. These technologies and techniques are not widely deployed in healthcare, but are used to varying degrees by most of the vendors profiled in this report. The expectation is that as these technologies mature, advanced analytics will offer more and better predictive and prescriptive capabilities. Many vendors now offer optional services to help providers take better advantage of advanced analytics technologies. Increased organizational familiarity with AI technologies and algorithms should naturally increase user trust as the technologies mature and become more widespread.
Many provider organizations, with experience gained from their VBC efforts, want more benefits from analytics. Whether it is from their legacy point and departmental reporting solutions, mainstream, or advanced analytics, provider organizations see analytics and reporting as a reliable way to pursue performance improvement goals across their enterprises.
Matt Guldin · 2 years ago
Liz Gavriel · 4 years ago
John Moore · 2 months ago
Brian Edwards · 3 months ago
Brian Murphy · 2 weeks ago
Walgreens ‘Front Door to Care’ Strategy is Building Horizontally
Key Takeaways:
Last Tuesday, Microsoft and Walgreens announced a strategic partnership aimed at “transforming healthcare delivery,” including a commitment to a “multiyear research and development investment.” The partnership intends to create new care delivery models, retail innovations, next-generation health networks, integrated digital-physical experiences, and care management solutions.” Additionally, Walgreens will pilot 12 store-in-store “digital health corners” featuring “select health care-related hardware and devices” in 2019.
Through the partnership, Walgreens hopes to improve access to virtual care and other healthcare services, make better use of data with analytics in community settings, and to create personalized healthcare “experiences.” The goal is to improve patient health outcomes, lower overall healthcare costs, and better integrate IT between participants in the healthcare ecosystem. They plan to accomplish this via:
This consumer-focused platform sounds like it will be part of a larger ecosystem aimed at connecting consumers, providers, pharma manufacturers and payers supported by Microsoft’s cloud, AI and IoT technologies. Additionally, Walgreens will transition the majority of the company’s IT infrastructure to Microsoft Azure.
This and other partnerships (see Figure 1) are part of a larger strategy for Walgreens to be the new ‘front door to care’–bringing healthcare to where patients and customers want to receive it. Walgreens can make it easier for patients to access care since 75% of the United States population is within 10 minutes of a Walgreens.
The question now is whether Walgreens can scale its various partnerships quickly enough to contribute to satisfy investors or to attract payers and employers looking to drive cost savings.
Each partnership is different in terms of complexity and will scale at its own pace (see Figure 1). Some will begin to show more immediate results and some will require multiple years to be successful. Here are some of the key observations and unanswered question about the most recent announcement.
At the J.P. Morgan Health conference, management stated it has all of the healthcare services that Walgreens needs at this point through the various partnerships it formed over the past 18 months. The question is how quickly Walgreens can execute on them. Walgreens management stated the partnership with Humana has gone well, but it is still very early days, and the company can’t make projections about the scope of the rollout beyond the initial 2 locations in the Kansas City area. However, the positive results of the LabCorp partnership mean that it will expand to 600 stores over the next few years.
Figure 1. Walgreens Health and Retail Partnerships
While customers may already see benefits from these partnerships, whether investors will have the patience to allow these partnerships to mature is an open question. Management has been under pressure to explain how these various partnerships will contribute to the companies’ financial performance.
Walgreens announced a new digital consumer platform, Find Care Now, last July to help consumers connect to an array of services offered by its provider partners, Walgreens-owned health services, and third-party providers including telehealth services (MDLive and DermatologistOnCall) and on-demand doctor house calls (Heal), where available.
Find Care Now will be hosted on Microsoft Azure with plans to enhance it with chronic disease management and more patient engagement apps. Whether the apps developed with Verily will be included is unclear. Walgreens plans to develop a separate B2B platform with Microsoft with services for payers and device manufacturers.
The overwhelming majority of Walgreens’ 370+ retail health clinics use Epic’s EHR. Announced in Nov. 2015, the rollout was fully completed in March 2017. Walgreens announced 14 new partnerships with healthcare systems, such as Advocate Health Care in Chicago and Swedish Medical Center in Seattle, in which the health system operates clinics inside Walgreens retail stores. These health systems hire the providers, oversee patient care, and bring in their own EHRs. The question is how, and more important if, Verily and Microsoft might work together with Epic to find synergies from the solutions each is creating with Walgreens.
Walgreens has a different strategy to its ‘front door to care’ model compared to Aetna-CVS and Walmart which relies upon a multiple ‘horizontal partnerships.’ The question now is whether Walgreens can scale its various partnerships, especially with Humana, quickly enough to contribute to satisfy investors looking for better financial performance or to attract payers and employers looking to drive cost savings.
Health Catalyst: Good Vision but Short of Grand
Health Catalyst (HC) is arguably the strongest, best-of-breed vendor for clinical data analytics in the market today. And as a best-of-breed vendor, it has been able to stay one step ahead of its leading competitors, Epic and Cerner – though as former Intel CEO Andy Grove once pointed out, “only the paranoid survive”, certainly holds true for Health Catalyst as Epic and to a lesser extent Cerner, are heavily investing in their analytics solutions.
Brian Edwards and I had the pleasure to attend the recent HC Analytics Summit, providing us an opportunity to get a pulse on HC, their clients, and their strategy going forward.
The Health Analytics Summit (HAS) brought together about 1500 attendees. It was a geeky crowd of data scientists, analytics team leaders and a smattering of executives. Sessions were by and large well attended though the level of discussions in the few I sat in on was modest. Client testimonials were plentiful, most clearly showing significant savings. However, one has to question what were the sunk costs on a given project when claimed savings were a paltry ~$65k.
Health Catalyst has grown quickly with over 700 employees currently. A couple of secrets to HC’s continuing success are:
Unlike most vendor organizations that put their customers first, Health Catalyst goes to great lengths to ensure their employees are engaged – they are the number one priority. Their belief: an engaged employee is a happy employee. A happy employee will strive harder to make customers equally happy. I’m surprised more companies do not follow a similar strategy.
While all vendors want their customers to be successful, Health Catalyst takes it one step further by guaranteeing to clients a CFO-verifiable 2:1 return on investment (ROI). In speaking to one client, she mentioned how some in her organization have pushed back on the costs of Health Catalyst. I asked her are they seeing that expected 2:1 ROI? She gave an emphatic Yes! – which she went on to confirm hushes critics.
A key message from CEO Dan Burton to attendees is their desire to remain an independent company that is mission-focused – “to unleash data as a catalyst of dramatic healthcare improvements.” To date, that message has resonated well across their growing provider installed base. But I wonder: Is it enough if the company plans to do an IPO?
The provider market is just getting started in understanding how to effectively use data and its insights to affect care delivery – no doubt there is still plenty of runway here. However, there are enormous opportunities outside the confines of this market. While I never wish to see HC lose sight of its mission, its long-term success, including a future IPO, will require a far grander vision that goes beyond the provider market to serve all stakeholders in the healthcare industry.
Unlocking Healthcare’s Big Data with NLP-powered Ambient and Augmented Intelligence
It wouldn’t be a radical statement to say NLP bridges the human-computer divide more than many technologies. ROI has been elusive, leaving prospective adopters reluctant to embrace it despite the numerous opportunities for NLP-driven solutions. NLP technologies have reached an inflection point with the emergence of advanced deep machine learning methods that are on-par with humans for an ever-increasing list of core natural language skills, such as speech recognition and responding to questions. In our newest report, Natural Language Processing: Enabling the Potential of a Digital Healthcare Era, we profile 12 vendors, all with a track record in text mining and speech recognition, including 3M, Artificial Intelligence in Medicine (Inspirata), Clinithink, Digital Reasoning Systems, Health Catalyst, Health Fidelity, IBM Watson Health, Linguamatics, M*Modal, Nuance, Optum and SyTrue. Each has a reputation for delivering solutions that serve a particular set of use cases or customer groups, distinctions we capture using heat maps for each company.
NLP is particularly well suited to address two huge problems in healthcare – easing the clinical documentation burden for clinicians and unlocking insights from unstructured data in EHRs. Documentation consumes an ever-increasing portion of clinician’s time. Recent research has shown physicians spend as much as half of their work day (6 hours of a 12 hour shift) in the EMR. Another recent study showed clinicians spend two hours on clinical documentation for each hour spent face-to-face with patients. Unsurprisingly it is often cited as a key factor contributing to physician burnout. Ambient Intelligence refers to passive digital environments that are sensitive to the presence of people, aware context-aware, and adaptive to the needs/routines of each end user. The familiar virtual personal assistants (VPAs), such as Amazon’s Alexa and Google’s Assistant, are familiar examples.
Speech recognition technology is approaching 99-percent accuracy, a milestone that some argue means that voice will become the primary way we interface with technology. I am skeptical of this prediction, at least when it comes to the broader utility of voice-based interfaces for consumers. The visual display, with its links and rich media, is an indispensable element of the modern digital experience.
Smart speakers, the input device for speech recognition, are the hottest technology trend of the moment, with an adoption curve that exceeds even the smartphone (see graphic below from Activate). We expect the smart speaker to rapidly become a fixture in both the home and office setting, following a similar path to maturity as the smartphone, offering applications for consumers and enterprises.
Interest and adoption in healthcare is already apparent. In September Nuance announced a smart speaker virtual assistant that uses conversational cloud-based AI (Microsoft Azure) to engage physicians during clinical documentation. In late November a post on the Google Research Blog described internal research and a pilot at Stanford investigating the potential to use a similar smart speaker interface and Automatic Speech Recognition (ASR) technology to create a virtual scribe.
Startups are taking on this problem too. Saykara, led by former executives at Nuance and Amazon, is developing a virtual assistant similar to Google’s. The company claims to have far more advanced speech recognition technology than its heavyweight competitors. Other are developing ambient scribes to passively document patient encounters, including Suki.ai , Robin Healthcare, and Notable Health.
EHR vendors are also making investments in ambient intelligence. Epic has partnered with Nuance and M*Modal to embed their ambient scribe technology directly into clinical workflows. Allscripts and athenahealth have partnered with startup NoteSwift. eClinicalWorks has launched a virtual assistant called Eva. Eva operates is initially intended to respond to queries for things like recent lab data or past clinical note content.
Barriers remain on the road to ubiquitous adoption of NLP technology by healthcare enterprises. NLP provides HCOs a low-risk opportunity to experiment with advanced machine learning and deep learning technologies, but its not the type of technology that can be implemented optimally by just any analyst in the IT department, but instead requires specialized expertise that is in short supply. While free text and mouse clicks will dominate the clinical documentation landscape in the near-term, healthcare enterprises will soon expect their users to talk their applications.
Predictions in Healthcare: Unpacking the Complications
Interest in predictive analytics in healthcare is on the rise. How long will someone be in the hospital? What are their chances of being readmitted? Which treatment will work the best?
On the surface, these seem like straightforward questions, but it turns out that prediction is not a simple topic. Questions about what data and effort goes into the prediction, how accurate it is, who gets to see it, and how actionable it is can all make a huge difference in its value.
As we start to develop our major Market Trends Report for Analytics, scheduled for release in early 2019, I thought I would unpack these questions a bit.
To start, it makes sense that the more data and the better data you can include in making a prediction, the more accurate it will be. However, you don’t always know what factors will matter the most, or at all.
If you over-collect data to ensure you factor in most everything, you unnecessarily raise the cost, time, and complexity, as data warehouses are not inexpensive and interoperability is still a struggle. If you under-collect, you might miss something important, and clinicians will continue to complain about the burden of documentation.
The recent focus on social determinants of health is promising, but it requires much more data collection and management, along with more sophisticated analytic models. Here, we welcome the contributions of AI and Machine Learning (ML) to help determine which variables to focus on.
Prediction is not a simple topic. Questions about what data and effort goes into the prediction, how accurate it is, who gets to see it, and how actionable it is can all make a huge difference in its value.
Accuracy has all kinds of complications. You’ve likely come across the difference between precision and recall.
With precision, you measure how right you were that something was going to happen when it did, in relation to how often you thought it was but didn’t. With recall, you measure how often you thought something was going to happen, and you were right, but you missed some that did happen. In the first situation, false alarms could be costly, leading to additional tests and much worry. In the second situation, missing an important prediction (such as a cancer diagnosis) could also be costly.
Fortune tellers make many predictions and eventually get some stuff right, but most of us don’t take them seriously; Chicken Little got into trouble when he cried out too many times. Conversely, someone who makes too many conservative predictions might have a lot of credibility but also miss too many opportunities.
Consider who wants to know or gets to see the predictions. Most clinicians, healthcare workers, and leadership teams want do the best they can, but negative predictions about their approaches or performance may not be met with welcome arms. Exposing their problems can lead to potential unwanted oversight by others, reduced funding, etc.
In other words, expect pushback about the quality of the data, the accuracy of the prediction, the motivations of the prediction team, and who is really responsible for the bad trends. Think about how predictions are supported and presented. Also consider the flip side: Positive predictions, if not accurate, may lull an organization into a false sense of security.
This leads to one of the most important questions: How actionable is the prediction, and what can be done about it? (This also brings prescriptive analytics into the discussion.) If the answer is “not much,” there may still be value in knowing it – but you have to brace for impact, as it could also lead to helplessness and negativity; consider the effect of telling a patient they have an incurable disease.
Better in most circumstances to focus on those predictions where positive action can be taken. Some actions might be obvious: You’re running out of medication x, so you’d better reorder now. Others might be more complex: What will be the effect of changing our portfolio mix?
Complexity of action can arise when dealing with interdependent systems, multiple parties, and lots of variables. (Welcome to healthcare!) Like the old game Whack-a-Mole, addressing one trend may lead to unanticipated or unwanted changes in others. Image how well you could play if you knew what was going on under the table. To properly act on predictions, you have to employ systems thinking.
As our data sources grow, our ability to analyze them using AI and ML advances. Given regulatory and market pressure to provide higher-quality care while reducing care costs, healthcare’s need to manage to value also continues to increase.
In the coming years, we’ll see a lot more use of predictive analytics in healthcare, and a lot more tools and vendors to support it. As we analyze these predictive tools, we will focus on how healthcare will employ them to deal with the complexities of data selection, model accuracy, user perception, and actionability.
What’s All the Fuss – Some Thoughts on Recent News
At times it can be challenging to draft commentary on all that is happening across this industry sector. Rather than write short posts for each, I have created an amalgamation of commentary to some of the more newsworthy announcements.
Wow, whoever knew that data could be such a valuable resource? Roche’s total spend to acquire Flatiron Health, a company focusing on the oncology space, was an eye-popping $2.1B. At first, I just could not fathom why anyone would spend that much for a relatively young company, that despite receiving a lot of VC funding early on, had little to show other than acquiring a modest oncology EHR.
Digging deeper however I learned that Flatiron was taking all that oncology data being collected in their EHR at physician offices across the country and cleansing and normalizing the data for clinical research purposes. Clean, normalized data is hard to come by in this industry and near impossible in oncology. Upon reflection, it now appears that Roche made an incredibly savvy move, one that will reap a handsome, long-term return on investment for the company.
This acquisition by Veritas is a tough one to understand. Over one billion dollars cash for assets that are dated and fading from the market? Granted, there is that installed base, there is that maintenance revenue to leverage and if you strip out virtually all SG&A costs you can make some money here, but is it really worth the trouble?
Veritas’s acquisition of Thomson-Reuters healthcare business that became Truven and later sold to IBM for roughly 2x what they paid shows that Veritas may know what they are doing. Maybe combining these GE assets with Verscend (formerly Verisk Health), also under Veritas, creates a 1+1=3 scenario but right now, just don’t see it.
Attended my first American College of Healthcare Executives (ACHE) Congress two weeks ago. This is a very collegial event – warm and welcoming. Everyone is there to learn from one another through various educational sessions and seminars. It is also an event where I was a bit floored and probably under-dressed as virtually everyone was in suits and ties.
I attended several sessions, mostly on IT and innovation, to get a feel for how these senior-level executives think about these issues. Came away with a feeling that most really do not see what is coming. Along with all of those suits, one walks away with the impression that there is a certain level of calcification across this audience. Sadly, many will likely become the detritus of the digital train that will run right over them.
Have been taken aback by all the fuss being made about Apple’s recent announcements regarding its Health Record app. From the Twitterverse, to a wide range of trade mags, to blog posts, folks are making this app seem like the second coming – that this signals Apple’s ability to disrupt the industry.
Hold on folks.
While I certainly applaud Apple’s efforts and for that minority of the population using an Apple iOS device, this may be just what they are looking for, I can’t help but feel a deja vu moment.
Were not Google Health and MSFT’s Healthvault going to do the same thing – revolutionize healthcare, put patient’s health records into their control. We all know where that ended – in the dustbin of history.
I’ll stay cautiously optimistic, but will reserve excitement until that day when Android devices also have the same capability with both clinicians and citizens warmly embracing and using this functionality for their care and the care of loved ones.
Podcast: The Convergence of Providers and Payers
Chilmark’s founder and president John Moore recently took some time to speak with the producer of the Relentless Health Value podcast, Stacey Richter, to discuss current strategies of one of the biggest trends in healthcare right now, provider-payer convergence.
The discussion begins by outlining how convergence is unique compared to the many other changes and initiatives sweeping through American healthcare. Most organizations enter into these partnerships as an answer to high administrative costs, the wave of recent consolidations, and unsuccessful provider-sponsored health plans. Most importantly, a successful convergence partnership requires a deep understanding and commitment to the local market served and trust between the organizations. John also outlines some of the challenges to creating successful partnerships and suggestions to overcome or avoid them entirely. For widespread convergence success, health care organizations (payers and providers) will need to systematize both the business processes and IT infrastructure to support data sharing and actionability.
Listen here and be sure to scroll to the end of this post to see some of the content discussed:
00:00 Convergence and the delivery of health care.
02:20 “How do we deliver greater value?”
03:00 Why establishing health plans within a provider organization is often not the best idea.
04:30 How you can get around needing prior authorization and subsequently cut costs.
05:50 The motivation for a payer and provider to form a partnership.
08:00 Why consolidation doesn’t necessarily drive down costs.
08:50 Payer-provider population health management.
09:20 Understanding where the patient might be going outside of the network to get their health care.
10:00 What does it take to be good at collaboration?
10:30 “What is the opportunity here?”
10:40 “Is there a level of trust between the payer and provider?”
18:00 Advice for payers looking to partner with providers.
18:50 Look for someone wanting to deliver high-value care.
19:30 “Trust, then verify.”
23:00 New and interesting innovations coming out of current convergences.
24:00 Things still being worked out in the market today.
25:25 The innovator’s dilemma.
26:30 “How do you scale quickly?”
27:20 “Is that scalable?”
30:20 The path forward for most markets in the United States.
Throughout the program, John and Stacey touch on several Chilmark publications, available here:
Tackling Prior Auth: New Solutions to Address Provider-Payer Friction
John emphasizes how prior authorization requirements are driving up admistrative costs for both providers and payers. Even outside of a full convergence partnership, both parties can begin to work together to reduce these costs and share the benefits.
2017 Healthcare Analytics Market Trends Report
As a population health management becomes more essential to healthcare, robust solutions are incresingly important for sharing and analyzing data from several sources, including payers, for sustainable value-based reimbursements.
Free February (and March)! Assessing the Market for Condition Management Solutions
Stacey mentions how difficult, yet important successful behavioral change can be for improving overall health. This report covers both factors driving adoption plus profiles for leading solutions for a variety of conditions and users.
Bold Move: CVS’ Acqusition of Aetna – 5 Takeaways for Delivery Chain and Health IT
John talks a little about his predictions for the future of the CVS-Aetna healthcare offerings in the podcast, including how MinuteClinics might become the first point of care. Read more in our blog about MinuteClinics, the implications for Epic Systems’ EHR, and challenges both companies face as they ambitiously attempt to transform how Americans seek healthcare.
PHM Market Trends Report Coming Before HIMSS
Key TakeawayThe Chilmark Research 2018 Population Health Management Market Trends Report, long in development, will be released immediately before HIMSS in March. This report profiles 25 vendors and describes the technology landscape for enabling a population health management (PHM) strategy.
Why a PHM Market Trends Report Now?
We hesitated to release a report on this emerging market for several years. Until recently, most available solutions were not able to fully address the range of provider requirements for PHM. The earliest solutions focused on the needs of Healthcare Organizations (HCOs) caring for Medicare Shared Savings Program (MSSP) patient panels. Over time, vendors added functionality to support bundles and private payer requirements requiring a good understanding of quality, costs, and utilization.
Another reason we held off with this report had to do with provider readiness. Healthcare delivery organizations needed time to incorporate these capabilities into their processes and workflows. The earliest HCO adopters of PHM relied on a variety of manual processes to conduct their PHM programs. Most HCOs lacked extensive experience with one or more of the constituent functional domains of PHM to fully utilize and benefit from the technology.
By early 2018 vendors had amassed significant experience building, managing, and supporting PHM enabling technology for providers and payers. Virtually all HCOs realize that PHM will be an increasingly important part of their operations and influence a significant percentage of their future revenue streams.
Virtually all HCOs realize that PHM will be an increasingly important part of their operations and influence a significant percentage of their future revenue streams.
Uncertainty About Value-Based Healthcare Makes Providers Pause
PHM’s close association with value-based care and payments cements its reputation as both a key strategy and technology enabler for transforming the U.S. healthcare system to achieve the goals of the Triple Aim. The PHM market’s growth closely mirrors the growth in value-based reimbursement (VBR). The pace of transformation to the payment system has not been smooth, and the Centers for Medicare and Medicaid Services (CMS) has sent mixed signals about its future in 2017. The business mandate for providers to embrace PHM slowed in the last 12-18 months. Provider concerns about revenue or market share losses have dampened enthusiasm for changing the fee-for-service (FFS) status quo. But the overall trend is moving in one direction: Away from FFS.
While uncertainty about the fate of value-based payments restrained provider’s embrace of PHM, the number of accountable care organizations (ACO), clinically integrated networks (CIN), and other risk-bearing programs continues to grow. Providers of all sizes have come to terms with the inevitable move to value-based contracting. ACOs will serve 10.5 million Medicare patients this year, a 17% increase over 2017. Delivering care to this expanding panel of patients requires providers, and in particular primary care providers, to organize themselves to make their PHM efforts successful. A variety of community based organizations, such as regional or state-level health information exchange organizations and to some extent payers, are also beginning to see the need to build and run PHM programs for, or in concert with, their provider partners.
Evolving Perception of PHM and the Four Technology Domains
PHM means different things to different people in 2018. Vendors built on products for pay-for-performance (P4P) programs to support CMS’ original set of ACO programs. Vendors, as a result of both organic development and acquisitions, now offer more PHM related functionality then they did a few years ago. While it is too early to say that PHM requires an established and fixed set of capabilities, the general outlines of the technology to enable a PHM strategy are broadly understood to fall into four technology domains:
Most of the vendors in this report have special expertise with one or a few of these domains.
As recently as a few years ago, analytics products provided the key enabling function for most PHM programs. While this functionality has an indispensable role in PHM programs, its core functionality – cost and utilization analytics and clinical quality monitoring – is arguably the most mature aspect of existing PHM solutions. Attention has shifted somewhat to care management. The value proposition for care management stems from a perception that these workflows are the “tip of the spear” for PHM generally. Care management products are often the central tool for organizing and running PHM programs on a day-to-day basis. Payer-oriented solutions with case, utilization, and/or disease management legacy have transferable skills for clinically oriented PHM. These vendors are beginning to make inroads into provider markets. Care management capabilities are less mature than analytics but are undergoing the most rapid pace of change by vendors.
The least mature aspect of PHM from a functional standpoint is patient engagement. In most of the solutions described in this report, the care management product supports some level of interaction between patients and a care team, mostly relying on a patient portal or app. Telephonic interaction with patients still seems to be the dominant method for most providers.
Data aggregation and data source management are core competencies for PHM. They form the foundation for all of the other domains of PHM. Managing diverse data sources is complex in all PHM sub-markets and for every organization developing PHM programs. Transactions, messages, documents, and files flow in from different organizations. These sources need to be reconciled, deduped, monitored for quality, and have all of their various records matched to patients, providers, organizations, health plans, and contracts. Organizations express this data using a multitude of formats and vocabularies. Vendors must constantly monitor these transfers and streams for quality, timeliness, and completeness. Every vendor in this report has skills in this regard but they differ in the scale at which they can operate. The number of organizations and sources from which they can ingest and process data is shaping up to be an important differentiator for providers. This set of capabilities is marked by fairly mature technologies and techniques but they are being deployed against a rapidly expanding universe of health-related information.
EHR Vendors Do Not Own the PHM Market
No vendor today has anything like a “PHM Platform.” The largest EHR vendors aspire to develop such an offering and have the resources to pull it off. Hospitals and health system turn to these vendors for all of their PHM needs, but it is not unusual for them to assemble their own solution from a variety of vendors supplemented with internally developed capabilities.
But these offerings come with price tags with little appeal outside of the large HCOs. Independent physician practices, most with limited budgets and no significant IT development staffs, are more interested in turnkey capabilities from a single vendor. Often this means their EHR vendor, but just as often it means an independent vendor with a full range of PHM capabilities. While EHR vendors are fielding increasingly full-featured solutions, they have not cornered the market.
Bottom Line
Not all providers and payers have fully embraced value-based care and payments but the need for, and interest in, enabling solutions for PHM continues to grow. Armed with this report, providers can distinguish between the capabilities and services needed to help them meet their complex information and workflow needs for multi-disciplinary, multi-organizational teams striving to optimize the health of populations. This report will help providers sort through the different vendors and solutions in this confusing market.
