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:


How to Get the Most Out of Population Health Analytics

Post by Sumeet Shrivastava

VP Engineering for Population Analytics, Caradigm

It seems like there is a constant buzz these days around healthcare analytics and their role in population health. It makes sense because in order to effectively manage a population of patients, healthcare organizations need to gain a variety of different insights. For example, they need to understand the clinical and financial risk of their population, define cohorts and prioritize patients to be enrolled in care management, evaluate how they are performing against quality measures, view patterns in utilization for financial improvement, etc. Analytics provide these insights.   

However, in order to get the most value from analytics, it’s important to understand how analytics are integrated with other population health strategies. Analytics shouldn’t be viewed as an independent activity because population health is a connected series of activities impacting the entire organization and requires a broad set of capabilities including data aggregation, analytics, care coordination and patient engagement and outreach.  It is also important to consider end user needs such as making it easy to access, visualize and take action. Let’s explore a few of the key success factors needed for population health analytics in more detail.

  • Quantity and quality of data: These elements are essential to light up any pop health analytics scenario. Across many organizations, I have seen implementations get delayed due to “bad data”, i.e. data that is not ingested in the format that is required to produce quality analytics, and later requires additional work to cleanse the data to be usable. A data aggregation solution should be designed to handle bad data and provide tooling to make it easier and faster to consume data from different and often non-uniform sources. While the data from different systems will be inherently non-uniform, data ingestion tooling and software should considerably shorten the process. Quantity i.e. completeness of data is also important because incomplete data dilutes the value of the insights presented. Incomplete data can skew or inflate insights, which then can make it challenging to formulate actionable strategies based on the information. 
  • Easy and real-time access: Once data has been aggregated and cleansed, it needs to be easily accessible, timely and in a format that can be used by both applications and by non-technical analysts. If it takes days or weeks to access analytics, then that time lag can render the data out- of-date.  Creating consistent and reusable data models along with self-service tools better ensures that queries are simple, maintainable and timely. 
  • Actionable insight: For analytics to make the greatest impact, they need to be actionable and integrated into clinician workflows. For example, gaps in care can be surfaced in an EMR so that a physician can close them while still in the presence of a patient. Also, if an analyst sees quality measures below where they should be, the analyst should be able to drill down to the provider and patient level so that additional action can be taken (e.g. enroll patient in a campaign or the analyst creates a task to prompt a clinician to take action). Analytics should also be surfaced within care management workflows as part of a longitudinal patient record so that all members of a care team have a more complete picture of patients, which can then be incorporated into the plan of care.
  • Flexible visualization engine: A picture is worth a thousand words. Users need to able to visualize the data in various formats – whether it is graphs, plots, trend lines, etc. An analytics engine should support different forms of visualizations that give users flexibility to derive value. 
  • Advanced analytics: To evolve beyond retrospective reporting and receive greater value from analytics, organizations need to leverage predictive and prescriptive analytics. Predictive analytics are essential for prioritizing resources as they forecast clinical risk, identify cost savings opportunities, likelihood of readmission, and can even identify which patients are likely to comply with a plan of care. Based on these predictions, prescriptive analytics can go one step further by suggesting interventions and identifying what actions should be taken to improve care for the patient.

Caradigm has taken a holistic approach to population health analytics since our inception.  We designed our enterprise data warehouse, analytics applications and workflow applications to work together, which makes each individual application more effective. Our analytics offering is unique because it can leverage virtually all of an organization’s data from disparate systems in real-time, apply best-of-breed algorithms to that data to derive insights, then surface that information directly within clinician workflows to drive action. If you’d like to discuss pop health analytics more, then please send us a note here. I look forward to continuing the discussion on analytics in an ongoing series of posts that will be coming from the Caradigm team. 


Rethinking the Business of Healthcare

Post by Brad Miller

Vice-President of Clinical Solutions, Caradigm

“What businesses are we in?” ask Michael Porter and Thomas Lee of the healthcare industry in their New England Journal of Medicine Perspective article entitled “Why Strategy Matters Now[.”[1]  As the entire healthcare spectrum transitions from a fee-for-service (FFS) paradigm to a more risk-based system, Porter and Lee contend that healthcare has entered a new era of strategic thinking and must employ new business approaches. I wholeheartedly agree that we need to start focusing on value in healthcare versus maximizing revenue.  

This new era in healthcare is marked for its focus on population health and patient-centric care to drive high value outcomes.  Porter and Lee believe that healthcare organizations should adopt new care concepts like the Integrated Practice Unit (IPU). Their IPU concept is based around specific diseases and comorbidities – like diabetes or asthma – rather than the traditional model of being department or provider-specialty centric.  This means that provider systems can truly focus on delivering disease and condition specific care across a population to achieve high value care. This concept would bring high quality practice and refinement to some of our sickest and highest utilizers, while also driving preventive care for those who have not converted to a full disease state. 

As the healthcare economy evolves in this risk-based direction, the IPU model (or a similar concept – patient-centric care across specific populations) will help break from the FFS “one size fits all” era.  It allows providers to focus not only on what they do well, but to provide a care environment for continual learning, discovery and refinement of care models and methodologies for their specific populations. There is also the possibility that IPUs can reduce large amounts of medical waste by standardizing best practices and reducing unnecessary or redundant tests and procedures. 

Simultaneously, there is a manifestation resulting from the physician and nurse education models that aligns with this disruption in the traditional healthcare business model. Predominantly, in the late 1980s and 1990s many medical schools switched to systemic-based curricula vs organ and departmental approaches.  I know this was the case at Weill Cornell, where I went, and at many of the other medical schools where my colleagues went with whom I have discussed their curricula.  From a learning standpoint, our generation of physicians were taught to view the body more as a system, rather than isolated organs. This generation of physicians are now in leadership roles at healthcare entities, ready to bring a more holistic perspective to the practice of medicine and healthcare.

It reminds me of the Apple Computer strategy of focusing on the educational market in the 80s and 90s – seeds planted a decade or two ago that helped create Apple brand loyalty and the foundation for making computing so central to our lives today. 

We are in an era of transformation as evidenced by the Affordable Care Act (ACA), the removal of Sustainable Growth Rate (SGR) for Medicare, Centers for Medicare and Medicaid Services (CMS’) rapid focus on risk-based payment models, and private businesses directly contracting for care with health systems in growing numbers (private ACOs, bundled payments, etc.). While we might not know exactly where the future will move healthcare, many signs point to it being risk-based and an era of rapid evolution and adaptation. In my experience with ONC’s Beacon Program and various providers under the CMS Innovation program, creating a clinical care environment that can easily adapt on top of a solid data and IT infrastructure is critical to supporting providers in this new and changing world.  Deep intelligence into a provider’s patient population, financial and clinical risk among other information and technical requirements will become central in this healthcare evolution.  I’ll tackle that technical aspect in my next blog post. In the meantime, check out Porter and Lee’s piece on the rapidly shifting sands of healthcare business strategy.

[1] Porter, Michael E and Lee, Thomas H. “Why Strategy Matters Now” New England Journal of Medicine. April 30, 2015.Publsihed from

How Population Health Enriches the Patient Record

Post by Sameer Bade, MD

Vice President of Clinical Solutions, Caradigm

As providers seek new capabilities to help them in their journey to population health, one of the first items they usually target is analytics. Analytics are undoubtedly an important piece of a population health strategy, however, this is just one of a number of important capabilities providers must obtain. In my experience collaborating with providers, a sometimes overlooked capability is creating and sharing a comprehensive, enriched longitudinal patient record. With the shift from physician-focused, episodic-care to team-based care involving multiple clinicians and care givers, it has become essential to have a real-time, 360 degree view of the patient that is shared among the entire team. With that enriched view, a care team can more effectively and efficiently deliver coordinated and proactive patient-centered care that drives improved outcomes. Let’s explore this issue in greater detail.

The reality is that clinical information from a single electronic health record (EHR) provides only a small portion of the information needed for population health management. If there are multiple EHR’s in a clinically integrated network, clinical data for patients may be siloed in disparate EHRs. Also absent from patient records are numerous other key pieces of information such as:

  • Claims data (e.g. services obtained, medications, etc)
  • Care plans
  • Lab results
  • Patient outreach information
  • Patient submitted / supplied information (biometrics, logs/journals, preferences, etc.)
  • Predictive analytics such as a readmissions risk score, clinical risk, forecasted cost, etc.
  • Analytics that measure medication compliance
  • 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)

Enriching the patient record with this information enables a depth of patient understanding required to support the transformation to value-based care. Here are a few examples of how the enriched patient record can have an impact.

Scenario 1

With pharmacy benefits claims data automatically augmenting the patient record, a care manager can quickly see which prescriptions have been filled without having to log into multiple systems. They can complete a medication review faster and more accurately and can share this with the care team. It is well known that improper or inadequate medication management can  play a major factor in readmissions and complications (shown to cause as much as 20 percent of hospital readmissions[1]). However, having just EHR based medications (list or prescriptions) and pharmacy benefit / fill data is not enough. Being able to capture what the patient is actually taking can provide enhanced insight.  After medication review, a care manager can determine that a pharmacist needs to be added to the care team to help manage dosing regimens and timing of medications. The care manager can then assign a task to the appropriate care team member working at top of license to make arrangements with the pharmacist and add a note to the patient record that is shared with all other care team members. 

While completing medication review, a care manager may also discover life events that are barriers to medication compliance such as an inability to pay for medications, not having transportation to pick them up, or patterns such as sharing/splitting doses with a spouse. The care manager can then assign a task to an appropriate care team member to make transportation services arrangements for the patient or enroll them in an financial assistance program, and add another note to the patient record that is shared with all other care team members. 

Scenario 2

The same high-risk patient described above goes to see a primary care physician who is part of a clinically integrated network. When the physician looks up the patient’s record in their own EHR, the enriched longitudinal information and actions taken in Scenario 1 are carried forward to the point of care. In this scenario, the physician or nurse can have a deeper and more informed conversation with the patient about medication compliance. Furthermore, easy access to a  comprehensive, validated medication review as part of the enriched longitudinal record, can help speed up the medication reconciliation process in the clinic. With full context on the patient that also includes all care programs they are enrolled in, lab results, visits history, readmissions risk score and relevant patient documents such as a care plan, the provider is better equipped to evaluate and direct additional care. Simultaneously, the provider can also see gaps in care and quality measures (e.g. need for a depression screening) that can be closed while the patient is still in the clinic. From a patient perspective, the provider’s enhanced understanding of issues and plan of care can improve the overall experience. The physician can even see what motivates the patient (perhaps the care manager noted that the patient has a goal to be able to attend their grand daughter’s college graduation) and encourage continued participation.

In the big picture, successful population health management requires addressing a population of patients as individuals. An enriched longitudinal patient record as described here can help providers gain a better understanding of their patients and enable the care team to be more effective, efficient, coordinated and patient-centered.

To learn more about how your organization can obtain and share a longitudinal patient record across a care team, send us a note here to schedule a discussion. 

[1] Guitierrez, David. “Drug Side Effects Blamed for 20 Percent of Hospital Readmissions.” Posted from 1.4.10.



HIMSS15 Day 3 Recap

Post by Azam Husain

Senior Product Manager, Caradigm

After three jam packed days of activity inside and outside our booth, HIMSS15 came to a close. Our final panel presentation of the week focused on the important topic of healthcare data privacy and security. Marianne Kolbasuk McGee, Executive Editor of Information Security Media Group (ISMG) moderated and shared information from ISMG’s annual information security study. Also on the panel were Steve Shihadeh, Senior Vice President of North America Sales Caradigm, Mac McMillan, Chief Executive Officer CynergisTek, and Shane Whitlatch, Executive Vice President FairWarning. The survey results that Marianne shared were really interesting because they showed that despite the high profile breaches that have occurred over the past couple of years, there’s still plenty of room for healthcare organizations to give information security greater focus. Some of the statistics shared were:

  • Only about half of organizations indicated that preventing and detecting breaches is a top priority in 2015.
  • Just 31 percent of healthcare organizations have “high” or “somewhat high” confidence in the security controls of their business associates and subcontractors.
  • Nearly 80 percent of organizations rely on usernames and passwords as the dominant method of authentication used for on-site and remote access to clinical data with use of more advanced forms of authentication still rare.
  • 51 percent of organizations reported having no breaches of any size in 2014 compared to 37 percent in 2013.

The panelists advised that healthcare organizations need to guard against complacency in order to stay ahead of security risks. Everyone should be doing more because of the continuous presence of insider threats and increasing hacking threats that are targeting healthcare heavily because of the value of the data and intellectual property. The panel also stressed the importance of tools to help control identity and access management and ongoing workforce training that needs to be put into greater context for how employees do their jobs.

Another very cool event that took place today was that patient rights advocate and renowned artist, Regina Holliday was in the Caradigm booth painting a mural on population health to raise awareness for the Society for Participatory Medicine. The mural is inspired by the idea that healthcare needs powerful and disruptive change and was completed in a single day. To learn more about Regina’s patient advocacy, I recommend reading her blog and following her on Twitter.


Regina HIMSS