The United States national health expenditure, already the fastest rising in the developed world, has only been driven higher by the COVID-19 pandemic. A massive 9.7% jump in growth in 2020 brought spending to $4.1 trillion that year. Studies also suggest that patients have delayed non-COVID related care, a trend also observed in patients with chronic conditions. Coupled with the fact that payers are also increasingly covering more vulnerable population segments with Medicaid expansion, it’s clear the focus and impetus on innovations in population health and care management will only increase.

 

For some time, payers have been investing in capabilities that enable them to own more of the care delivery directly. Originally seen as a way to manage costs while helping improve overall patient experience and outcomes, it’s become clear on this side of the pandemic that the investment strategy must also consider digital channels of care and home healthcare. Some of the big moves we’ve seen companies make toward this newly focused strategy include:

At the core of the payer evolution toward owning overall management for their members (and non-members) is population health management (PHM). We submit that PHM program core objectives will evolve from being a vehicle for managing per member per month (PMPM) or adherence metrics to being a key part of the overall value-positioning story for payers. In this article, we propose a three-part strategic framework for payers to structure their integrated care management initiatives. We’ll also lay out some of the high-level critical enablers for this strategy to work.

1. Value lever identification

 

As PHM programs move beyond utilization optimization, several aspects that contribute to overall member health require a detailed study. These include understanding:

  • Key social determinants of health (SDOH) factors (access to care, access to quality food, education, financial stability and local community context, among others)
  • Personal and behavioral factors influencing healthcare (biases, smoking, substance abuse, food habits, exercise habits, etc.)
  • Clinical history (chronic conditions, comorbidities, other diagnoses, prescription drugs prescribed, etc.)

Even with privacy guardrails in place, there are potentially thousands of data points that need to be integrated to make sense of the overall health care puzzle for individual members. Advanced segmentation and micro-segmentation capabilities may help narrow down member cohorts. Often value levers will be hidden in the cross-section of these segments. Furthermore, needs identification is becoming more apt at predicting high-utilization events (re-admissions, avoidable emergency department visits, etc.) and potential future diagnoses (diabetes, CKD progression, etc.).

 

The next big challenge will be the ability to scale AI investments—addressing any inherent biases in segmentation algorithms, optimizing for metrics beyond utilization, creating the ability to attribute predicted outcomes to tangible and actionable data points for individual members.

 

2. Personalized and holistic engagement

 

Traditionally, PHM programs have been referred to as “interventions.” We submit that as payers evolve to own overall healthcare for their members, the mindset needs to shift toward that of continuous engagement.

 

Community-based PHM programs are an effective tool for personalized interventions, especially if designed based on localized SDOH insights. Organizations have been investing in SDOH analytics capabilities either through direct data onboarding and integration or by establishing early relationships with SDOH-based platform providers and localized resource aggregators to inform community-based programs. However, digital engagement remains an underutilized lever for true ongoing personalized engagement. Digital channels are becoming increasingly important for healthcare delivery, as evidenced by the increase in telehealth adoption over the last few years.

 

Adoption trends in telehealth can be viewed as a proxy for members’ general willingness to engage through digital channels. It has been clear for a while that health plans also see the value in digital health, as seen by UnitedHealth Group’s acquisition of PatientsLikeMe and its subsidiary’s (Optum) bid to acquire Change Healthcare, Cigna’s plans to invest $450M in digital health startups and Centene’s bid to acquire Magellan Health. More broadly, private equity investment in health-tech companies during the first three quarters of 2021 rose to $4.5 billion over 47 deals, up from $1.75 billion over 38 deals in all of 2020, according to PitchBook. However, it can be argued more needs to be done to integrate digital-based innovation in the overall PHM roadmap.

 

Integrating digital-based innovation will require a holistic look at prior PHM programs to identify how the reach of those programs could have been expanded. Similarly, ongoing and future programs may have opportunities for more personalization and better integration and cohesion for care coordination across physical, behavioral and community providers. Furthermore, to engage members holistically, payers will also need to look at internal team reskilling or ways to augment existing skill sets with the right partnerships. The overall strategy design should better leverage existing care delivery assets owned or managed by the payers and could be informed better by data captured through these assets.

 

3. Optimization and impact measurement

 

The biggest challenge in PHM continues to be ROI quantification. At an individual intervention program level, there may be successful examples of reduction in PMPM metrics or improved adherence, but there’s a broader case to be made about PHM strategy being a key part of the overall payer value proposition story. It’s essential to build the right data pipes and visualization capabilities to track metrics that can then ladder up to form the value prop story. At a high level, there are three categories of metrics that may require scrutiny: outcomes tracking, member engagement and productivity.

 

The above metrics should inform and drive any strategic changes. Developing an effective feedback mechanism will be critical in doing this. This feedback mechanism could be implemented through market research or individual surveys designed so individual biases can be accounted for and through structured data collection outcomes and employee productivity to infer the unstated or implicit engagement impact.

In this article, we presented a member-centric PHM strategy that will help bring community-based, payer-driven care management and digital strategies together. We also outlined the case that these initiatives will require significant focus and investments. In conclusion, we want to highlight three foundational and priority capabilities health plans should look to invest in to bring the member-centric strategy to life. If developed with an enterprise lens, we also believe these capabilities can help other organizational functions.

 

Data strategy and infrastructure: While the integration of electronic health records, claims and SDOH has already been top of mind for most payers, we feel that bringing in and integrating data from digital channels to develop a member 360 view requires additional focus. This data strategy will require focusing on data acquisition, ingestion, cloud strategy and robust data infrastructure development and management. With investments being made in telehealth and other care delivery channels, there are opportunities to collect additional unstructured data.

 

Invest in scaling analytics and AI capabilities: One of the main areas of focus and AI-driven innovation has been in risk prediction and stratification. There’s an ever-growing list of predictions to be made to help define proactive and personalized interventions. With the increasing complexity and scale of analytics, payers should consider investing in setting up capabilities and processes for machine learning operations (MLops). It will become critical to separate experimentation from scaling to ensure that AI capabilities and insights are embedded firmly in how member populations are engaged. AI operations will also be critical for discovering, monitoring and managing biases and drifts that may appear in the predictions.

 

Insights-driven workflow management: Effective care model operations require a robust workflow management tool. Most health plans have invested in such capabilities to help with staff productivity and effective tracking of efforts. While the data from these systems has traditionally been analyzed to monitor effectiveness and productivity, we believe the next step is to augment such systems with data-driven insights. Payers should look to feed individual insights or potential next best actions for individual members under care management through the existing platforms. This could be the first step toward a broader orchestrated care management solution that may also include coordination across other digital health tools being deployed for care management. Augmenting existing care workflow tools with personalized insights will serve as a great proof of concept for this idea.

As national health spending is projected to grow to $6.2 trillion by 2028, the pressure on payers to maintain the bottom line will continue to increase. Coupled with the fact that end consumers expect more transparency and leadership from payers in managing their care, and the time is opportune for payers to invest in transforming their PHM strategy and investing in core capabilities to fuel innovation.