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 Greet 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.

Moving Healthcare Analytics from Measurement into Management

Post by Corinne Stroum (Pascale)

Sr. Program Manager for Healthcare Analytics, Caradigm

Current hot topics in healthcare analytics include user-centric dashboards and self-service reporting. These provide users with information they need, but don’t necessarily provide them with the means to extract key insights or take action on their results. I consider this to be traditional measurement, but propose that healthcare analytics must evolve into a rich management tool alongside these new features. Let’s explore the key steps to achieving this management goal.


Quantify Your Performance

Whenever a computer or device is in use in healthcare delivery, there is an opportunity to capture data. This is a natural starting point for either a measurement or management tool: both types of tools must empower users to build reports or identify key performance indicators (KPIs) from an authoritative source of data.

Know your Population

An authoritative data source is a great start, but a patient doesn’t leave a footprint in just a single system. Information about a patient spans many systems and the mash-up of this data from these sources is vital to producing meaningful and actionable analytics.

Incomplete data can lead to user distrust – “I see in system X that my patient has had this immunization; why doesn’t my report reflect that?” A complete view of the patient’s data, from all systems, enables deeper and more accurate insights.

Find the Signal in the Noise

An evolution from measurement to management relies on a user’s ability to explore the data on their own terms rather than with prepackaged KPIs. There are natural hierarchies within healthcare data that can aid users in this exploration. For example, a provider group is composed of individual practitioners, an inpatient facility has its departments, a grouping of diagnoses will narrow down into individual health issues and services, etc.

Exposing these natural hierarchies in a management tool helps users to uncover areas that warrant attention. For example, are particular classes of drugs having unexpected outcomes? Can a user spot a spike or drop in performance metrics for a single provider in a given facility? A user should be able to dig into data hierarchies and determine the factors affecting a particular metric.

Take Action

Recent advances in analytics allow users to look at metrics in real time, providing an opportunity to intervene and change the course of performance trends. Therefore, an analytics management tool should enable users to do something with their data, such as:

  • Identify quality compliance gaps and let users contact the provider to facilitate a necessary appointment or enroll patients into a campaign, which results in the patient being contacted by a care manager or receive a mailer reminding them of an important healthcare issue they should address
  • Show the user a utilization hotspot and enable him to export data from this report to assign and share amongst their colleagues
  • Provide opportunities to move insights into different applications, such as flagging patients who have not received a post-discharge outreach to ensure that a provider is performing appropriate due diligence (and tracking it in the appropriate application).

Measure Outcomes of your Actions

If an analytics application empowers a user take action, it certainly needs to measure the impacts of the interventions. It might report on the following:

  • On average, how long did it take between the user’s action and the desired result?
  • Are some users more successful at generating positive results?
  • If a user is given many actions as part of an intervention, which is most effective at achieving the desired result quickly?

In summary, healthcare analytics applications are no longer just for quantifying performance from a single source. They’re beginning to help users find meaningful signals in large amounts of data, enabling users to take action, and measuring outcomes of these interventions. These improvements are the key to evolving analytics applications from measurement to management. If you’re interested in discussing how Caradigm can help evolve your reporting and measurement efforts then send us a note here.

Super Clinically Integrated Networks Will Lead the Way to Population Health

Post by Steve Shihadeh

Senior VP, Sales & Customer Operations, Caradigm

One of the most interesting recent trends that I’ve seen is that large integrated delivery networks (IDNs) are expanding their reach by forming more diverse and sophisticated clinically integrated networks (CINs). CINs have been around for a while in a much simpler form, typically coordinating activities between employed and non-employed physicians. Today, CINs are more diverse and can include networks of large independent health systems and or physician groups. This type of “Super CIN” provides a vehicle for independent providers to collaborate to achieve shared goals such as population health management for a specific employer contract or to deliver regional care. The MyHealthFirst Network that includes our customer, Greenville Health System is a prime example of a Super CIN.

How prevalent are CINs as a whole? The Advisory Board estimates that there are 500 CINS in the US today.[1] According to a recent research study that Caradigm conducted, 60 percent of respondents indicated that they are forming or active in a clinically integrated network that includes physicians or hospitals not part of their current system. Five years ago, this almost never happened and even basic collaboration between competitors was uncommon. From the conversations I have had with providers, I believe that the trend towards Super CINs is only going to accelerate as it has become essential to succeed in the new value-based healthcare environment. Let’s explore the drivers of this trend further.

Increased need for ambulatory care

As providers take on financial risk for patient populations, ambulatory care becomes more important in order to deliver lower cost, preventive care, and reduce the need for acute care. The challenge for hospital organizations is that they typically aren’t structured to deliver ambulatory care everywhere a large population needs access. Under the fee-for-service model, the focus was inside the walls of the hospital. Population health management now requires providers to expand their reach across the entire continuum of care, which includes primary care physicians, specialists, skilled nursing facilities, community based organizations, etc. Few organizations will be able to do it completely on their own, which is why Super CINs are an attractive option.

Scaling to manage larger populations

According to the study we just completed, 52 percent of respondents have contracted to manage at least 25,000 lives. 61 percent indicated that they are planning to take on more risk over the next 12 months with 36 percent planning to add at least another 25,000 covered lives. As providers take on more risk, they must also scale their ability to drive quality and lower costs for these larger populations. Compared to opening new facilities or growth through mergers, forming Super CINs gives providers a faster path to scalability while maintaining ownership independence.

Alignment with multiple initiatives

There are many different “flavors” of risk that providers can choose to engage in such as Bundled Payments, Medicare Shared Savings Program ACOs, Commercial ACOs, DSRIP programs, direct contracts with employers, etc. Providers often engage in multiple programs to diversify their risk while they develop new care workflows and best practices. The beauty of Super CINs is that they can support a variety of different risk-based programs. Working together, these providers can more effectively compete for payer and employer contracts because they demonstrate higher quality and greater efficiency in care delivery. Super CINs are a foundational strategy whether a provider is looking to form a broader network of hospitals to meet the needs of a large employer, partner with other organizations as part of a state Medicaid initiative such as DSRIP, or strengthen the primary care an organization can provide for a regional population.

The growth of Super CINs also creates a need for new health IT tools. Information has to be gathered and shared among a broader network of providers that may be using disparate information systems. Analytics have to be applied to that information and then shared throughout the network at the point-of-care where it can have an impact. Workflows have to be streamlined so that providers can efficiently provide care for an increasingly larger population. These are new challenges that electronic medical record systems (EMRs) were not built to meet. Ultimately, Super CINs need IT solutions specifically designed for population health management that can complement their existing infrastructure and help them evolve to value-based care. If you’d like to see the full results of the study referenced above you can send us a note or download this whitepaper to learn more about how to take the next step with Super CINs and population health.

[1]Greene, Jay. “Ascension Health, CHE Trinity form integrated network in Michigan.” Modern Healthcare. May 7, 2014. Published on:

The Cultural Shift to Population Health

Post by Brian Drozdowicz

Senior Vice President of Population Health, Caradigm

The cultural shift needed for organizations to transition to value-based care is a key consideration in the journey to population health management. A provider must have strong internal alignment across the organization in order to succeed. Three questions that providers need to come to a consensus around are: 1) Do we need to change? 2) Do we want to change? 3) How do we change?

Do we need to change?

The statistics say we do need to change. Too much healthcare is ineffective or redundant as “an estimated 20 to 30 percent of [annual U.S. healthcare] spending – up to $800 billion a year – goes to care that is wasteful, redundant, or inefficient.”[1] I believe that the industry also intuitively recognizes a need to evolve its fee-for-service (FFS) model. If the goal of healthcare is to drive better patient outcomes, it’s in the best interests of patients to become healthier so they need less acute healthcare services. FFS does not incentivize organizations to reduce utilization today. Another key driver for change is that it’s becoming mandatory in order to compete for business. For example, to win contracts from government, commercial and employer payers, providers have to prove they can deliver higher quality care at a lower cost.

Do we want to change?

Even if an organization recognizes the benefits and drivers for change, there can be other cultural impediments to making the shift. For example, some organizations are risk and change adverse, and prefer to take a wait and see approach. Making the shift to value-based care can certainly be intimidating from a financial point of view as there is no guaranteed return on investment for value-based initiatives. Only about 25 percent of Medicare Shared Savings Program (MSSP) ACOs have been able to generate shared savings to date[2]. Providers may also naturally wonder how they will succeed in the long run if they see their patients significantly less than they do now.

Despite these obstacles, more providers are coming to the conclusion that they do want to change because they see value-based care as the future that they need to prepare for now. Organizations pursue population health management when leadership views it as a key initiative that will help the organization achieve its highest priority goals such as improving quality, improving access or differentiating itself in the market. Developing this business case for population health is a critical part of building momentum for an organizational shift.

How do we change?

After a provider has developed their business case for population health, they can then implement specific strategies and address specific challenges in care delivery. In terms of which programs to roll out, I recommend that providers start small and then diversify the types of contracts they engage in. This allows providers to experiment with different risk-based contracts, learn from initial efforts and iterate before expanding. Starting with an employee population is a popular way to begin due to the manageable population size and easy ability to communicate with members.

As providers look to build their capabilities and best practices, they need to be able to answer questions such as how do we bring our data together? Which patients should we focus on first? How do we coordinate care across the continuum when patients are seeing a variety of clinicians? How do we best interact with patients when they aren’t in front of us? It’s not uncommon for providers to get by with manual spreadsheets and basic health IT tools when the size of the population is small, however the desire to scale programs successfully requires a higher class of health IT infrastructure.

Technology as an enabler of culture change

Organizations need transparency and consistency in order to help drive cultural change, which is where health IT can help. I have seen customers successfully move to partially reimbursing physicians on quality measures leveraging technology to provide transparency to those physicians. Without that trust in the accuracy and timeliness of the data, physicians would not allow compensation to be tied to quality measures. This transparency also extends to the patient level so that physicians know exactly where to focus improvement efforts.

Technology can also play a major role in ensuring consistency of care by integrating a provider’s best practices and evidence-based guidelines into workflows such as care management workflows. For example, an application can prompt a care manager to ask the right questions during an assessment, suggest the right interventions based on the responses, and then automatically update the plan of care and assign tasks to the care manager. Therefore, adopting change in care management workflows becomes easier because the workflows are automated.

These are just two examples of the ways technology can help with the cultural change to value-based care. Although the amount of change can be daunting, I have seen population health energize and bring together cross-functional groups within organizations that had not historically collaborated much. As population health is ultimately about delivering better quality care in a more efficient manner, it is a worthy goal that I am excited to help providers achieve.


[1] America’s Health Insurance Plans (AHIP). “Rising Health Care Costs.” Published from

[2] Kocot, S., Mostashari, F., White, R. (2014, February 7) Year One Results from Medicare Shared Savings Program: What it Means Going Forward. Retrieved from: