Go Big or Go Home: The Importance of Scale in Population Health

Post by Scott McLeod

Director of Product Marketing, Caradigm

In a recent article, “Why Dartmouth Ditched the Pioneer ACO Program”, Rene Letourneau for HealthLeaders Media described Dartmouth-Hitchcock Health System’s exit from the Pioneer ACO program. While the article notes Dartmouth’s defection was “unsurprisingly” prompted by financial concerns related to the CMS targets, it also revealed an often-overlooked factor in success or failure of accountable care initiatives—the size of the population served.

Robert A. Greene, MD, executive vice president and chief population health management officer for Dartmouth-Hitchcock, touched on this concern. “We would have to go it alone if we stayed in the program, which means our population would have been smaller, said Greene, “If we stayed in for 2015, we would have expected to owe another $3 million to $4 million.” Estimates place the size of Dartmouth-Hitchcock’s at-risk population at 23,500 lives in 2013.

As healthcare delivery organizations seek sustainability under risk contracts, they should look to the experienced health plans and insurance companies. Health payers range in size from local plans with ten thousand covered lives to national carriers covering millions. Many of those at the lower end of this scale struggle financially, and as a result, also with attaining the clinical outcomes desired for their members.

While smaller size can create a number of challenges, I will call out two—the cost of variability and critical mass for programs.

Utilization and costs of healthcare services vary from year to year. In a larger population, the overall variation is less noticeable because there is typically enough patients with lower utilization to balance those that incur higher costs. In a smaller population, a relatively small set of patients can have a negative impact on the average utilization and per capita spend. This is why insurers are concerned about adverse selection, resulting in a larger-than-desired proportion of higher-risk individuals among its members.

Population health initiatives need a certain number of patients to be sustainable. For example, focusing on preventive care targeted at high-risk diabetics requires a sufficient number of members that qualify and enroll in a program for it to be successful at the population level. Smaller payers often do not have the necessary membership. Adding to this, on the other side of the equation, is the fact that lower revenues makes it difficult to allocate resources for these programs.

In my experience working with payer organizations, the minimum size for long-term sustainability is 80,000 – 100,000 covered lives. It will be some time before a significant portion of ACOs and other at-risk organizations achieve that size. Until then, in addition to some success stories, I expect we will see more developments like those occurring at Dartmouth-Hitchcock.


Technology to Understand the “Pop” in Population Health

Post by Brad Miller

Vice-President of Clinical Solutions, Caradigm

My last post detailed the “Pop” in Population Health. As an industry, we think about patients when we think about the “population” in Pop Health, and indeed patients are at the core of Pop Health. Providers, however, are facing a new set of populations – the collective group of sub-populations they care for. Put another way, the evolution of Pop Health and risk-based care has generated a complex business landscape for healthcare providers. Providers will need to lean increasingly on technology and data to enable the clinical and business cases around healthcare.

Let’s consider an example of a provider managing a group of sub-populations. A provider could be participating in a Clinically Integrated Network (CIN) that runs a Medicare Shared Savings Program  (MSSP) ACO and also has an Medicare Advantage (MA) plan. They could also be participating in two bundled payment programs, have Accountable Care Network (ACN) relationships with three employers, and their state could be remaking their Medicaid program. On top of everything is their traditional Fee-For-Service population. That adds up to at least nine sub-populations amongst the provider’s complete population – that’s their “population of populations.” That group is dynamic and evolving – as needs and times change, so too will these populations and how they are measured and cared for.

Caradigm Technology Driving the Pop Health Revolution

At Caradigm, we live for this type of healthcare complexity. We designed our data foundation, the Caradigm Intelligence Platform (CIP), from the ground up to be both transactional and analytical, which not only allows for powerful analysis, but drives real-time intelligence to applications so that the intelligence mined in the data can be put to use. Most platforms are either one or the other – transactional to power applications (e.g. EMRs are built on transactional databases) or analytical (many “big data” solutions to date are analytical platforms). Each and every piece of relevant data from the provider system – from clinical records, labs to claims can be ingested into CIP. This means all of a provider’s data can be located in one place and can be used together to generate highly functional intelligence for patient care. From baseline risk-adjustment to contracted clinical quality and outcomes, today’s providers and CINs require real-time intelligence to manage such diverse populations.

At a population level, Caradigm looks to the analytical applications in its product suite to drive real insight into a provider’s populations and to manage to contracted quality and financial arrangements. The Caradigm Risk Management application is built upon a partnership with MEDai, a LexisNexus company, to drive industry-leading prospective risk profiles of populations and individual patients. Most risk applications only look retrospectively or only in a clinical vein, however our risk management application distinguishes itself on the broad set of big data available in CIP and the 25 year history MEDai has in predictive analytics. Further, Risk Management looks at six key predictive indexes on a patient-by-patient basis. This means that a provider can not only understand clinical and financial risk on a patient basis, but also the patient’s specific “Motivation” and “Mover” risks. The Motivation Index details a patient’s likeliness to respond to any intervention. The Mover Index corresponds to a patient’s likelihood of becoming more ill during the next 365 days. This means that a provider can more accurately assign care management and follow-up assistance to patients in an efficient manner that up until now could not be provided. Providers would have to use more blunt force and address a population of the top 10% of A1cs or 10% highest cost patients without any insight as to whether the patient would or could respond to any intervention. This leads to much more precise care and financial outlay in a risk-based system. Targeted insight means highly actionable and effective pop health care.

The Caradigm Quality Improvement application, built directly on top of CIP, highlights the current quality measure status for a provider across each population and contract. For example, the QI application tracks ACO33 measures, allowing for the identification of up to date gaps in care on a patient-by-patient basis that via CIP can be surfaced directly at the point-of-care to drive quality improvement in the appropriate setting. Caradigm’s Utilization Management Analytics application takes a look at some of the costliest medications, procedures and providers to help pinpoint areas of high spending.

Together, these applications help our customers manage not only their total population, but their sub-populations as well. Each risk-based contract – whether MSSP, ACN, bundled payment or direct-employer purchasing – brings a population with its own unique clinical and financial risk factors and gaps in care. Caradigm not only drives success in these early days of Pop Health, but because of CIP and the nature of the suite of applications, will enable health systems to rapidly expand their risk-based contracting and arrangements to drive true value-based population health.

The Rise in Electronic Prescription of Controlled Substances (EPCS)

Post by Mike Willingham

Vice President of Quality Assurance and Regulatory Affairs, Caradigm

Healthcare organizations are facing a serious societal problem that has become more pronounced in the last 15 years – the widespread abuse of prescription drugs. Controlled substances now account for approximately 10% to 11% of all prescriptions in the United States.[1] Deaths from prescription painkillers have quadrupled since 1999, killing more than 16,000 people in the United States in 2013.[2] Nearly two million Americans, aged 12 or older, either abused or were dependent on opioids in 2013.[3] More than 12 million people reported using prescription painkillers non-medically in 2010 (i.e. without a prescription or for the feeling they cause).[4] The misuse and abuse of prescription painkillers was responsible for more than 475,000 emergency department visits in 2009, a number that nearly doubled in just five years.[5] High profile news stories involving prescription drug abuse (e.g. Brett Favre, Heath Ledger) have also seemingly become more common.

In response to the rapid increase in both the prescribing and abuse of controlled substances in recent years, the Drug Enforcement Agency (DEA) has set a number of regulatory requirements for healthcare practitioners and organizations that want to prescribe those controlled substances by electronic means. In order to be able to prescribe controlled substances electronically, the DEA requires a secure, auditable chain of trust for the entire process. In addition, several states are mandating the use of EPCS, including Ohio, Florida and New York (with its I-STOP law).

Overall, it’s hard to argue that EPCS is anything but a positive for the healthcare industry. E-prescribing is a tool that increases efficiency and reduces risk of fraud and errors. A study has estimated that e-prescribing resulted in a decrease in the likelihood of prescription errors by 48%.[6]

So far though, healthcare providers have been slow to adopt EPCS thus far because most states have not had a mandate for it yet, and there are no penalties for non-compliance. However, it is inevitable that more mandates are coming, and I believe that EPCS will inevitably become the de facto standard of prescribing controlled substances. While overall adoption is currently low, it is growing fast as an average of 287 clinicians are adding this capability every month.[7]

Caradigm offers a comprehensive EPCS solution that is a seamless extension of our industry leading Identity and Access Management portfolio. We are actively working with our customer base to help them address EPCS, and are looking forward to partnering with more organizations to help them do their part in tackling this important societal issue. In a follow-up blog post, I will dive deeper into the technical solutions required for EPCS. For additional information, please visit our EPCS page.

[1] Meghan Hufstader Gabriel, PhD; Yi Yang, MD, PhD; Varun Vaidya, PhD; and Tricia Lee Wilkins, PharmD, PhD, Adoption of Electronic Prescribing for Controlled Substances Among Providers and Pharmacies. The American Journal of Managed Care. 11.17.14. http://www.ajmc.com/journals/issue/2014/2014-11-vol20-sp/adoption-of-electronic-prescribing-for-controlled-substances-among-providers-and-pharmacies
[2] Centers for Disease Control and Prevention. National Vital Statistics System mortality data. (2015) Available from URL: http://www.cdc.gov/nchs/deaths.htm.
[3] Substance Abuse and Mental Health Services Administration, Results from the 2012 National Survey on Drug Use and Health: Summary of National Findings, NSDUH Series
[4] http://www.cdc.gov/VitalSigns/PainkillerOverdoses/index.html
[5] https://www.atrainceu.com/course-module/2270162-118_oregon-pain-module-11
[6] Radley DC, Wasserman MR, Olsho LE, Shoemaker SJ, Spranca MD, Bradshaw B. Reduction in medication errors in hospitals due to adoption of computerized provider order entry systems. J Am Med Inform Assoc. 2013; 20(3):470-476.
[7] Meghan Hufstader Gabriel, PhD; Yi Yang, MD, PhD; Varun Vaidya, PhD; and Tricia Lee Wilkins, PharmD, PhD, Adoption of Electronic Prescribing for Controlled Substances Among Providers and Pharmacies. The American Journal of Managed Care. 11.17.14. http://www.ajmc.com/journals/issue/2014/2014-11-vol20-sp/adoption-of-electronic-prescribing-for-controlled-substances-among-providers-and-pharmacies

Four Steps To Make Population Health Analytics Actionable

Post by Neal Singh

Chief Technology Officer, Caradigm

Last week, I had the pleasure of moderating an analytics roundtable at the Caradigm Customer Summit (CCS), which took place on the Seattle waterfront. CCS was a fantastic event where provider organizations from around the country came to learn and share best practices as they lead the way with population health. You can read more about CCS in these posts – Day 1 recap and Day 2 recap. As this week is National Health IT Week, it’s an ideal time to share some of the discussion points from the roundtable to help raise awareness on the impact of data and analytics in transforming healthcare.

There were four key recommendations that came up during the discussion:

1. Build a Data Foundation

A population health analytics strategy starts with a data foundation. We heard in the roundtable that population health forces organizations to bring together a variety of data types including clinical, claims data from multiple payers (CMS and commercial payers), internal billing data, lab, pharmacy, etc. Aggregating clinical data continues to be a challenge as large health systems often are using dozens of EMRs and or are part of a clinically integrated network (CIN) that will likely always utilize many EMRs. Attendees said that while all EMR vendors publicly claim neutrality, it continues to be a challenge to get all the data that they need. Using a vendor neutral solution to aggregate data from disparate systems is one way to help overcome interoperability issues.

2. Increase Use of Predictive Analytics

The group also talked about how they are taking steps to evolve analytics efforts beyond retrospective reporting to predictive analytics that can have greater impact of patient outcomes. Most providers are still in the early stages as they have been focused on being able to report on and attain required quality metrics. Some are now starting to leverage predictive analytics in order to proactively impact patient care. For example, one attendee explained that they are giving care managers a patient readmission risk score along with the reasons for the score, which helps them take action with high-risk patients before they are discharged.

3. Surface Analytics in Workflows to Make Them Actionable

One of the most important considerations in a population health analytics strategy is to embed analytics in clinician workflows at the point-of-care. We heard repeatedly at CCS that clinicians are already faced with too much information, and that it’s not effective to present them with yet another report. What clinicians want is additional information presented in their existing workflow and tool that can help support clinical decisions. A great example of this that we heard about was surfacing a predictive Sepsis risk score for clinicians to see at the point-of-care. The Sepsis algorithm calculates a risk score based on real-time data (vital signs, lab results, medications and dates/times) and then stratifies patients as “At Risk”, “High Risk” and “Very High Risk”. Clinicians see the risk score including aggregated clinical data in their customary EMR and then examine at-risk patients to determine if they meet the criteria for severe sepsis treatment according to established protocols.

4. Establish Data Governance

Lastly, the group discussed how important it is to have a data governance structure with executive support representing all modalities of data such as quality measures, HCAHPS scores, fall risk, readmissions, hospital acquired conditions, etc. It’s critical to get different parts of the organization on the same page because there are inevitably many initiatives in motion at the same time. One attendee shared that they have built a dashboard for each modality, which helps align the different stakeholders.

CCS was an engaging event for industry leaders who are all striving to get to the same goal of population health. If you’d like to have a discussion about how to augment your population health analytics strategies or see the list of best practices we developed in conjunction with the analytics roundtable, then drop us a note here.

Leaning in on Population Health (Part 2): Caradigm Customer Summit 2015

Post by Christine Boyle

Chief Marketing Officer and Senior Vice President, Caradigm

On Day 1 of the Caradigm Customer Summit (CCS), we heard multiple provider organizations talk about how they are leaning in on population health, and are seeking to build the best practices and health IT to successfully scale their programs. On Day 2, we continued to explore the strategies and tools that can help organizations succeed with new value-based reimbursement models. Here are the highlights from another great day of learning at CCS.

Neal Singh Chief Technology Officer, Caradigm and Kendra Lindly VP, Global Product Management, Population Health and Analytics, Caradigm

Neal and Kendra provided insights into the overall vision of Caradigm’s product strategy as well as the collaborative development approach they take with customers. They also highlighted new applications and features that are in the roadmap across Caradigm’s four pillars of integrated solutions (Data Control, Healthcare Analytics, Care Coordination and Management, and Patient Engagement & Wellness).

Nicholas Greif, Project Manager Virtua and Jill Manz, System Integrator Virtua

Nicholas and Jill talked about how Virtua, a leading provider in South Jersey, is using Caradigm’s information security and population health tools to help improve patient care within their VirtuaCare ACO. They explained how over time, Virtua has continued to mature its population health IT infrastructure, and will be delivering actionable predictive analytics such as Sepsis risk scores to clinicians in their native EMR so they can take proactive action.

Federal and State Driven Programs Panel

Vicki Harter, VP of Care Transformation moderated a panel made up of John Supra from Greenville Health System, Scott Anderson from MyCareCoach and Todd Ellis from KPMG. They discussed how to succeed with the variety of Federal and State Funded programs that are available to providers today. The panelists agreed that although providers don’t have to have all the answers right now, they do need to start thinking about who they’re going to align and partner with, and how they’re going to get their hands on the right data and share it.

Michael Robinson SVP, Global Services, Caradigm and Mike Macedo Director, Application Services, Caradigm

The closing presentation was from Michael Robinson and Mike Macedo who talked about how to drive user adoption of new population health technologies. It’s an important consideration for providers when seeking new health IT because acquiring technology is only part of the journey. It takes deep collaboration between a technology partner and a provider to train and engage employees who are learning about new organizational strategies, workflows and IT systems. While it does take much effort to train users and drive adoption, Mike and Mike explained that the payoff is when employees become fully engaged in the process. They talked about the collective excitement that they’ve seen in recent customer deployments that energizes the entire organization. With that level of employee engagement, a provider is well positioned to succeed with their population health initiatives.

Day 2 also included more outstanding peer-to-peer discussion during roundtables on patient engagement, physician engagement and IT security organizational engagement. As mentioned in the Day 1 post, we’ll share best practices from those sessions in a upcoming blog series.

In addition to learning and sharing about population health, CCS is also about having fun and building relationships in the industry. It’s not always sunny in Seattle, but it always seems to be sunny during CCS. Our attendees were treated to a couple of beautiful days of weather on the Seattle waterfront, and were able to relax and get to know each other at evening events.

It was an amazing two days at CCS 2015. Caradigm is extremely proud to be collaborating with so many of the top provider organizations in the country and around the world. We look forward to helping our customers with their key initiatives as they continue to lean in on population health.

Wheel Cropped

The Seattle Great Wheel lit up in Caradigm mulberry.

Leaning in on Population Health (Part 1): Caradigm Customer Summit 2015

Post by Christine Boyle

Chief Marketing Officer and Senior Vice President, Caradigm

We were absolutely delighted to kick-off the 4th annual Caradigm Customer Summit (CCS) at the Bell Harbor Conference Center on the beautiful Seattle Waterfront. As healthcare continues its transformation to value-based care, gatherings like CCS are great opportunities for provider organizations to engage with peers who are on similar journeys to population health. In truth, population health is still so new that everyone is learning together. With over one hundred senior healthcare executives from leading organizations in attendance, CCS is a unique event focused exclusively on population health.

My main take away from the first day was that provider organizations are now further along in their journey to population health and are “leaning in”. The dialogue has matured from “should we do it” to “how do we optimize what we are doing”. The business decisions have been made, technology has been evaluated, and now it’s time to operationalize and scale efficiently. Here are some of the highlights from the day.

Michael Simpson Caradigm CEO Opening Welcome

“Every organization across the U.S. and the globe has to figure out how we make this journey to pop health work. We have a common goal.”

In Michael’s opening welcome, he shared a number of statistics that show that the growth in population health is real and that momentum is building. While technology barriers to population health and threats to information security also continue to be real, Michael talked about how Caradigm customers are progressing, and as a whole are leveraging Caradigm solutions to tap into data from over 150 different systems in over a billion patient encounters.


Angelo Sinopoli, MD VP, Clinical Integration & Chief Medical Officer, Greenville Health System

“The discussion used to be with the HR representative. Now the cost of healthcare has gotten so high, the discussion is with the CEO.”

Dr. Sinopoli explained that Greenville Health System views population health as the key strategy that will help them better serve patients while also helping them be a leading provider in the state of South Carolina. He also talked about why they formed their state-wide clinically integrated network, the MyHealth First Network and how they will drive care management best practices through the Care Coordination Institute, which leverages Caradigm’s full suite of solutions including Caradigm Care Management.


Marian Lowe, SVP of Payer and Employer Strategies USPI and Ashley Wise, VP of Strategic Systems USPI

“Population health for us is about how do we create a meaningful network of providers that improves patient care.”

Marion and Ashley detailed USPI’s journey to population health. As one of the largest network of surgical centers in the country, USPI realized that as their national network of partners started moving towards clinical integration and value-based care, USPI had to build the capabilities to support those activities. USPI then formed a clinically integrated network and an accountable care organization and are using Caradigm’s solutions to support those efforts with data aggregation and analytics.


Matt Stevens Advisory Board – Population Health and the Retail Revolution

“Providers are trying to provide the right care in the right location – achieve meaningful geographic reach and clinical scope.”

Matt Stevens from the Advisory Board shared industry insights about how the retail revolution in healthcare aligns with the movement towards population health. He explained that providers must win at two points of sale: 1) they must secure enrolled lives and 2) win share of volumes. In order to do so, they must form the right strategic network and gain the health IT infrastructure that can lower costs, manage populations, increase access and improve the patient experience.


Regina Holliday, Patient Advocate

“We are all patients in the end. This is where I take my stand.”

Renown patient advocate, Regina Holliday capped off Day 1 with a moving presentation about the patient information challenges her family faced while trying to receive care for a sick family member. As provider organizations seek to transform care models and improve the patient experience as part of population health efforts, Regina asked providers to take a patient-centered approach and include patients in the care team in order to best serve their populations.

Also on the agenda were several roundtable sessions where attendees engaged in peer-to-peer discussions on topics such as analytics, care and chronic condition management as well as health data privacy and security. In future blog posts, we will share some of the best practices that came out of those sessions. Thanks to our phenomenal guest speakers and customer attendees, it was an inspiring day of learning on the first day of the Caradigm Customer Summit. Check back tomorrow for a recap of Day 2!

The “Population” in Population Health

Post by Brad Miller

Vice-President of Clinical Solutions, Caradigm

In my last post I wrote about the 3 P’s of Population Health – Population, Patient, and Practice. Pop Health has become a ubiquitous concept not only in healthcare IT (see HIMSS 2015), but in healthcare at large. That said, there is no one way to define Pop Health – it can mean many things to many people. I am hoping the 3 P’s will help start a new way of thinking about the definition and execution of Pop Health. In this post I will talk about the ‘Pop’ in Pop Health – the Population.

Traditionally, providers have had three distinct populations – Commercial, Medicare and Medicaid. Sure, there were a couple of exceptions, but by and large those three were the types of populations that comprised a provider’s total population. That status quo has changed dramatically as Pop Health has begun to take hold and more “sub-populations” have been created to meet the distinct financial, quality and health challenges faced by purchasers, payers, providers and patients. Here are a few examples:

Medicare Populations:

  • Traditional: This is the fee-for-service sub-population of Medicare, and is an approach and population that CMS is planning to fade out over the next couple of years.
  • Medicare Advantage: MA plans are essentially outsourced traditional Medicare patients – a commercial insurance company takes responsibility for managing a Medicare population. Well executed MA plans with a pop health strategy can lead to significant quality and financial opportunities for providers and payers.
  • Medicare Shared Savings Program (MSSP) and Pioneer ACOs: In this sub-population, a provider agrees to drive savings and quality across a Medicare population. The provider must not only create savings relative to a baseline, but they must maintain quality standards (ACO33s) as well if they wish to partake in those savings in part or in full.


  • Medicaid programs vary greatly from state to state. Currently, most states are in the midst of Medicaid reform – the ACA has greatly expanded Medicaid eligibility and many states are either consolidating Medicaid programs or restructuring them all together to meet this demand for access and quality. This can greatly increase population variability for a health system.


  • Traditional: Here we have the traditional fee-for-service patient where volume of patient services typically drives system revenue.
  • Direct Purchasing: Where purchasers of healthcare, typically companies or local/state governments purchase care directly with a health system and with a contracted quality standard required to maintain good standing.
  • Accountable Care Networks (ACNs) or Clinically Integrated Networks (CINs): Health systems teaming up to enable large, direct healthcare purchasing contracts. These organizations share financial risk and resources like IT systems or drive purchasing agreements.
  • Bundled Payments: This has typically been a subset of direct purchasing, except a purchaser has arranged for a fixed-fee for a procedure – typically high-cost procedures like knee or hip replacements. This places the provider at risk and incentivizes them to drive better outcomes through quality.

A Population of Populations

While these sub populations are likely to be quite familiar to a number of readers, noting them together highlights the sheer number and complexity of the Populations that are a part of Pop Health. Indeed, providers now have a “Population of Populations.” Why did I run through the list of sub-populations above? While most of the sub-populations are self-evident on their own, I find it useful to literally see the number and diversity of a provider’s care models and contracts. In this time of increasing model and population diversity and complexity, providers are also taking on more risk. Providers are changing multiple, complex and difficult variables in their business and operational models to serve these populations. Most healthcare workflows and technology were established in a time of transactional fee-for-service, not dynamic and highly interactive pop health. Each sub-population has its own needs, financial drivers and quality measures, and new technology will enable providers to scale to meet the demands of those requirements. Real-time data and analytics, feeding a scalable technology platform and applications will enable providers to manage this Population of Populations. I’ll get deeper into “the how” when I take a closer look at the technology requirements needed to manage these populations in my next post. For now, the “Pop” in Pop Health has truly become a “Population of Populations.”

The 3 P’s of Population Health

Post by Brad Miller

Vice-President of Clinical Solutions, Caradigm

When most people think of the term “Population Health”, visions of ACOs dance in their heads. ACOs are a provider group that pulls together patients and contracts at a fixed rate per patient over a given timeframe while either maintaining or increasing quality of care, with savings typically accruing to all parties. An academic definition of pop health is: “the health outcomes of a group of individuals, including the distribution of such outcomes within the group.” While that definition may be accurate, I find it a bit nebulous, and would like to suggest the 3 Ps of pop health to simplify the definition and conversation: the Population, the Patient and the Practice. The 3 P’s provides a specific framework under which to have practical conversations around population health.

The Population

The population is the collective patient cohort that a provider has contracted with a paying entity to provide healthcare for a fixed price. In the case of CMS’s Medicare Shared Savings Program, providers receive payments based upon traditional CMS fee for service schedules, but are then incentivized to provide higher quality care through ACO33 measures, and have their populations risk-adjusted using the CMS-HCC methodology. Providers must now determine efficient and effective ways to deploy their limited care resources in order to impact clinical outcomes and overall population savings. In the case of private ACOs or health systems directly contracting with self-insured employers, the population is defined by that contract. To make this more complex, a provider’s overall population health approach may be comprised of many contracts – each with its own specific population and contract behind the care. This population complexity adds an additional element of chaos in an already chaotic system.

The Patient

The paradox of population health is that in order to “move the needle” on a population, a provider must focus on the specific needs and use cases of each and every patient who is part of the population. While I will dive into the specifics and caveats of how to define an individual’s care in later posts, for now I want to establish that “the patient” is a critical component of any ACO. Each patient of a defined population has their own health issues and specific personal needs. For example, one member of a population may be a relatively healthy 68 year old woman in good shape, but has moderately high cholesterol. Her personal issues and barriers to care will be completely different than a 74 year old, wheelchair-bound diabetic with heart failure. The critical component to improving the value of healthcare and drive quality measures for a population is understanding how we can make the individual patient respond to care and meet their own needs. Delivering personalized care for each patient is critical for the long-term success of any population health model.

The Practice

Here lays what I find to be the most important of the 3 Ps of pop health – practice. Yes, it’s all about the people – both on a macro (the population) and micro (the patient) side of things, but population health itself is a practice, much like medicine, and yet we do not treat it as such. Best practices and models are unique to the provider, the patient base and payers involved. What has worked at one provider may not work at another. More direct, what has worked for a rural, integrated care network will not work at an academic medical center, will not work at a large urban public hospital system. While the basics may be similar the practice and execution of the basic models will be very different However, I would argue that the learning, best practices and business models from these efforts can serve as a starting foundation for a population health effort.

At the surface, this seems to be self-evident, but I have seen providers establish fairly rigid care and financial models and too often not create a governance or technical infrastructure to embrace the practice of population health. From my time working with ONC’s Beacon Communities and CMS’s Innovation program, most of the reasons programs were not successful can be traced back to overly ambitious and complex beginnings that were rigid in approach. Successful programs were more modest in size, focused on specific measures and outcomes, and allowed for the learning and iteration on successes and small failures. From those more modest beginnings the successful programs expanded their capabilities as they learned how to assess risk, create effective population cohorts and to deploy personnel to meet the individualistic challenges faced by their populations. Most of the successful organizations were able to iterate and iterate often, which allowed providers to hone the practice of managing large, diverse populations. All of these challenges are unique to each population health effort – and may actually be different on a contract-by-contract basis for each provider. The bottom line is that population health is a practice – one that can take years to make robust and to perfect.

I will tackle each one of these 3 Ps in upcoming posts. For now, the 3 Ps act as a basic framework for conversations around the path to pop health success.

Engaging High Risk Patients through Care Management (Part 2)

Post by Vicki Harter

Vice President, Product Management-Care Coordination

In part one of this post on engaging high-risk patients through care management, I discussed how different patient segments require different levels of care management relationships and tools. For the highest risk patients, a patient engagement strategy is centered on high intensity care management. Next, let’s look at how technology can help care management have a greater impact on outcomes for the highest risk segment.

Coordinating Care Across a Multi-Disciplinary Team

The care for a high risk patient can involve a large team including multiple specialists, pharmacists, care managers, office assistants, community health organizations and family members or friends. Coordinating activities among a diverse team requires shared access to a longitudinal patient record that gives a comprehensive “360 degree view” of the patient. The 360 degree view includes information such as:

  • Claims data (e.g. services obtained, medications, etc)
  • Dynamic care plans
  • Lab results
  • Medications
  • Patient outreach information
  • Patient supplied information (biometrics, logs/journals, preferences, etc.)
  • Predictive analytics such as a readmissions risk score, clinical risk, forecasted cost, etc.
  • Barriers to care
  • Gaps in care/quality measures that need to be closed
  • Important non-clinical information (e.g. patient motivation, family support team members, life events such as a recently deceased spouse, and other social factors)

With this enriched view of the patient, care team members across the continuum can work more efficiently together closing gaps in knowledge and communication while operating at the top of their license. This can result in reduced redundancy in assessments, surveys and tests. Today, enterprise population health technology can bring together and make available all of this information in a shared workspace even if the information is stored in disparate IT systems.

Incorporating a patient-centered approach

A deeper understanding of patients helps drive a patient-centered approach, which is critical for patient engagement. For example, if a patient is motivated to achieve a certain goal such as travel to her daughter’s wedding, then every member of the care team can reinforce her motivation and encourage the patient and engage them in the plan of care. If every care team member has access to all patient information, then patients won’t have to repeat the same information to different care team members and patients begin to sense coordination among providers. If there is a family member, friend or community organization that plays a key role in the patient receiving care, then that critical piece of info will be incorporated into the assigning of tasks. The end result is a personalized plan of care. If patients see that the entire team “knows” them, it improves the overall patient experience, builds trust and can improve engagement.

Optimizing time with patients

Care managers are often challenged by a high volume of daily manual tasks. For example, in order to assess a patient and complete a care plan, care managers must track down and synthesize information from multiple systems and offline sources. With a full case load, efficiency is a challenge that ultimately impacts the amount of time care managers can spend focused on patients. Technology can help care managers spend more time with patients by automating time-consuming tasks. For example:

  • Care plans, task lists and interventions can be automatically generated and updated from assessment responses
  • Complete medication histories can display order history and fill history to enable faster review and support compliance review
  • Patient workloads or specific tasks can be reassigned to other care managers or support staff, assuring “top of license” activity
  • High risk patients can be tracked across the continuum through event-based alerts (e.g. admissions, discharges or blue tooth device alerts).

To summarize the main takeaway from both posts, patient engagement and care management strategies are closely linked and should be tailored by segment. As part of population health initiatives where the focus is often on high-risk patients, patient engagement strategies should be on a one-to-one basis, and linked to relationship building through high-intensity care management. New population health technology has emerged to help coordinate care for the highest risk patients. As more providers make the shift to value-based care and seek efficiencies to help them scale programs, I believe that technology will play a central role in helping the highest risk patients. If you’d like to discuss your care management strategies in more detail then send us a note here.

Engaging High Risk Patients through Care Management (Part 1)

Post by Vicki Harter

Vice President, Product Management-Care Coordination

One of the most challenging issues in healthcare today involves “patient engagement”. It is defined by the Center for Advancing Health as “Actions individuals must take to obtain the greatest benefit from the health care services available to them”. The importance of patient engagement is undeniable. Patients active in the participation of their own care have a greater likelihood of achieving successful outcomes. How providers should approach patient engagement for different patient segments is still an evolving science. Patient engagement requires different levels of care management relationships and tools for different segments. In this two-part blog post, I am going to focus on the highest risk segment, and will address lower risk segments at another time.

Population health management is a large undertaking, requiring a variety of approaches to assure broad impact. The figure below shows an example of patient segmentation along with the types of care management relationships and tools appropriate for each segment. At the top of the pyramid is the highest 5 percent in terms of risk. In the middle are the 30 percent of patients with rising risk. The base of the pyramid is the 65 percent identified as having low risk. Let’s examine the segments more closely to see how patient engagement and care management strategies can vary between the segments.

CM Pyramid


High Risk

The top 5 percent of patients require high-intensity, 1 to 1 care management involving a multi-disciplinary team. Patients may have comorbidities that require more complex coordination across the continuum of care. Due to the high clinical risk for this group of patients, a care manager needs to play a lead role within the care team, guiding patients to take the actions needed to obtain the greatest benefit from the health care services available to them. Therefore, a patient engagement strategy for high-risk patients is really centered on high-intensity care management providing direction to the appropriate level of care and education about symptom monitoring and action plans.

Rising Risk

In general, the rising risk segment requires moderate intensity care management services, referred to as condition management in the diagram. These patients can pose an escalation risk if unmanaged, so the emphasis is on providing a consistent set of evidence-based care or education about self-management of a newly diagnosed condition. Patient engagement for medium risk patients is often a combination of consistent patient outreach and communication along with tools to encourage self-management. Within this group, there can be a subset of patients identified as “movers”, patients whose level of clinical risk is predicted to increase over the next 12 months. Higher intensity care management can be appropriate for “movers” in order to proactively address their conditions before they become more acute.

Low Risk

The low risk segment is the largest group, nearly two-thirds of the population. The focus for this segment is on preventive health and wellness to provide age and gender appropriate recommendations for care. Wellness tools including patient education and coaching may center around lifestyle choices and illness prevention based on health risk assessment data. Due to the size of this segment, low-risk patients must take on more of the responsibility for self-care. They are the ideal segment to benefit from patient engagement and outreach tools such as an interactive portal and patient reminders.

In the second part of this post that will be published next week, I will go deeper into technology designed to achieve effective high-intensity care management.