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The expansion of population health management, or PHM, is driven by two key factors. First, it is financially smart: Payment approaches established by the Affordable Care Act have encouraged payers and providers to shift towards population-based care, accountable care, and risk sharing—giving them a clear financial incentive to deliver on population-level health outcomes. Second, it makes for diligent care delivery: Visibility into patient populations helps payers and providers achieve better compliance, clinical outcomes, and delivery, benefiting everyone.

These dual incentives have reshaped risk management for the entire healthcare system, incentivizing providers to expand their focus on preventive care, provide chronic conditions management, and reduce unnecessary episodic care encounters and acute encounters. Both payers and providers have clear incentives for PHM to work, in terms of patient health but also in terms of claims volumes, wellness, and clinical outcomes.

To deliver this level of care, payers and providers need to get comfortable making data a critical part of their care strategy. Institutions already have this data available (and they gain more sources of it every day), but building the system required to use it is a challenge. PHM systems have several tasks:

  • Identification of patient populations in the organization’s footprint both in and out of the panel
  • Correlating populations to defined care needs
  • Measuring the care provided to these populations
  • Monitoring and measuring adherence and compliance to care plans
  • Creating and managing patient risk stratification and risk mitigation
  • Delivering the right care to the right patients at the right time

Thinking about this process as a data challenge, payers and providers have three fundamental requirements from a data system.

PHM Requirement 1: Data Aggregation and Transformation

Most care delivery is provided by separate, independent providers in different provider offices and locations. PHM tracking systems need to be accessible and interoperable with ambulatory, hospital, lab, diagnostic, emergency room, urgent care, surgical, ancillary, and provider departments and/or facilities. Each of these entities will have their own sets of data for the patient population they serve, both independently and/or in tandem as part of a care team. Therefore, no care delivery entity has the complete data sets for their patient panels.

Invariably, these various provider types will not just provide a high volume of different data sets but will also provide them in myriad of formats. To establish the data foundation needed for population health management, payers and providers will need to ingest data from multiple sources and organizations, including payers (claims), physician practices, hospitals, and more. Then, this multi-source, multi-organization data must undergo transformation into a uniform structure. Data sets must match terms and codes, mapping patient data, and provider identifiers. While data aggregation and transformation are a challenge, it is also a prerequisite for all the subsequent steps and processes flow in patient population health management.

PHM Requirement 2: Data Analysis

While payers and providers have mechanisms available to extract and visualize the data required to deliver effective population health management, too few of them are leveraging the available data to quickly identify and stratify risk. Many are missing a platform to store, analyze, and manage patient data aggregated from multiple sources other than the traditional buckets of claims and electronic health records.

Buckets typically missing—but critical to PHM—are demographic data by segmentation and cohort, past encounter data, social media, third-party claims, social determinants of health (SDOH), referral patterning, payer mix, geographic heat mapping, patient/provider engagement preferences, cancellation/no-show rates/reason codes, bump rates, and compliance/adherence rates. This is a considerable data lift—but bringing these data sets, together with traditional healthcare data, gives providers true 360-degree visibility, allowing for more effective management and care delivery, especially for high-risk patients.

Organizations that get this process right will better understand their past and present performance through reporting and gain insight into their future potential through predictive modeling. From here, they can act on the data insights, adjusting access, utilization management, compliance and adherence trends, and referral patterns and then adjust or enhance their care delivery and member engagement.

But before payers and providers can get these insights, there’s one complication: This information doesn’t live in the EHR or the health plan claims system. Payers and providers should use their CRMs for this need, taking advantage of their core functionalities and bolt-on capabilities that are more natural fits for relationship management, data aggregation, data visualization, and predictive modeling. Information captured in a healthcare CRM allows payers and providers to identify, manage, and mitigate risks more intuitively. Leaders will need to understand the challenges and preferences of patients that may make getting care a factor in their compliance with care plans, and they should consider these factors when assessing risk and formulating the strategy to mitigate the risk.

PHM Requirement 3: Managing and Measuring Care

By creating more personalized care delivery and better patient experience, payers and providers can achieve greater compliance with care plans, reduce care gaps, reduce risk, and drive better clinical outcomes. Patients expect care to be about more than treatments or procedures. It is about a strong relationship with their caregiver, receiving the support they need in difficult moments, and being known as a person rather than a number.

A lack of uniform clinical and operational preferences and protocols stymies this kind of care. Payers and providers will find it difficult to deliver PHM at scale without clear processes for review, dissemination, and coordination of actions, engagement, and follow up with patient populations and providers. Centralized and structured data provides insights to establish or refine and optimize these preferences and protocols and efficiently manage the desired outcomes and accountability.

A CRM and Data Analytics/Visualization Platform bring value here too. We have discussed how payers and providers can use their CRMs as a high-quality data repository, access, and analysis tool, but the same features that make a CRM effective for analysis also help make the data more actionable. Data Analytics/Visualization Platforms can serve comparable functionalities and pair well with CRM and EHR to trigger the appropriate engagement and encounter functionalities. Payers and providers can create predictive models to identify patients in the market and in active panels who are at risk for various health conditions in any tenure band, and then target and engage those patients based on those patients’ preferences, lifestyles, and needs. They can also manage patients’ care plans and preventative health needs, considering SDOH while looking at motivators for individual patients. And they can better understand trending volumes of care delivery so they can model demand, building the right supply/demand, utilization, and access models to deliver care to the right patient at the right time and place with the right provider.

Population Health Management Deployment and Other Considerations

Deploying and using these capabilities is more than a technical challenge—people, process, and technology all need to come together. Since no single platform or system can manage population health alone, payers and providers will require (at least) one system for data aggregation, risk stratification, and engagement, and different systems for care management. Numerous systems need to work together, but payers and providers who start with solid and stable data will have a solid foundation for the rest of the process. If this is not in place, payers and providers will struggle to get accurate enough numbers for true PHM, and analytics remain an impossibility.

There is an urgency to this work. As technology and consumerism reshape healthcare preferences and delivery, technological agility will help payers and providers stay competitive and maintain positive health outcomes. Patient population health management presents a chance to invest in data strategies and CRM capabilities that will work in the long-term.

Looking to the future, these investments in CRM and Data Analytics/Visualization Platforms have robust capabilities and optimize the effectiveness of the EHR and other clinical systems of record. These platforms also have impacts far beyond healthcare outcomes as well. Data Analytics/Visualization Platforms and CRMs can unlock the same data-driven strategies used in other industries to acquire, retain, maximize revenue intensity, mitigate risk, and enhance return on investment from their patient panels, clinically integrated network of providers (CIN), payer networks, and utilization levels of their clinical and operational staffs. New retail-centric entrants in the care delivery space can threaten traditional providers and payers, but CRM and Data Analytics/Visualization Platforms can help create a competitive hedge against churn.

In our work with numerous payers and providers, Spaulding Ridge has delivered data-powered solutions that improve outcomes for healthcare institutions and the patients they serve. We can help build a full-fledged PHM system, deliver enhancements to your CRM, get your data environment up and running, and more. If you have questions about how your healthcare institution can use data to improve outcomes, let’s talk.