By Phil Trotter, leader, Exercise is Medicine, Felipe Lobelo, associate professor of Global Health, Emory’s Rollins School of Public Health, and Ashley John Heather, co-founder, Off The Scale
The first white paper in this population health management series, Chronic Disease is Healthcare’s Rising Risk, reported on the health and financial burden associated with chronic disease, specifically the “rising-risk” and “high-risk” clinical population subgroups. For example, data indicates that the “rising-risk” population with one or more chronic diseases typically makes up between 20 percent and 30 percent of a stratified population and accounts for 32 percent of total healthcare expense. This group is growing due to the rising tide of chronic disease.
Patients diagnosed with chronic disease without intervention care can progress into the “high-risk” cohort that has an annual mean expenditure of $43,827 per years. Although the “high-risk” makes up only 5 percent of the population pool, they account for 49 percent of total healthcare spending. Therefore, in addition to patient wellbeing, there is a clear financial benefit to delaying or interrupting the clinical progression of chronic disease from “rising-risk” into “high-risk.”
Taking New Risk Requires A New Framework: Systematic Challenges
For health system leadership to transform healthcare from volume to value-based care, adoption of population health management (PHM) must be fast-tracked to prepare for value-based care payer contract acquisitions. These payer contracts have risk bearing payment models that focus squarely on population groups with one or more chronic diseases. These groups constitute the bulk of the rising-risk cohort with higher complication rates and rapidly increasing management costs.
The challenge for system leaders is scaling their efforts to take on more risk with value-based payer contracts. Organizations that are able to deliver population health programs on a large scale will be more likely to capture the value-based financial rewards from payers. Therefore, targeting the ‘rising-risk’ population segment must be a priority. This is particularly true of the ‘rising-risk’ cohort that is generally found to progress into high-acuity, therefore driving up care management costs.
Clinical providers are rarely organized to deliver lifestyle behavior change via group-based care. However, through collaboration and shared accountability between clinical care and a highly-trained community-based workforce, it is possible to create a standardized framework for behavior change. That subset of the rising-risk population cohort with comorbidities requires a behavioral intervention methodology reinforced by an intensive engagement strategy. In combination with adequate clinical care, these intervention approaches have the power to reverse or at least delay chronic disease progression before patients fall into the downward spiral of increased complications and cost.
Scaling up PHM resources for the ‘rising-risk’ cohort requires expertise delivering evidence-based lifestyle behavior change programs. Traditional clinical care struggles to deliver lifestyle change programs effectively because these programs are typically time-intensive and require skilled personnel and resources that are often not found ‘in-situ’ or standardized in most health systems. Delivery of these services becomes more effective and economical in community settings and group-based environments. As experienced in the Diabetes Prevention Program (DPP), the group delivery format has additional health behavior change benefits beyond economies of scale s.
Steady Progress Towards Clinical/Community Team Collaborations
A dramatic shift is under way for health system leaders that intend to provide their employees, contracted payer populations and communities with accessible, more efficient care targeting chronic conditions leading to better health outcomes and lower cost patient and provider satisfaction. The mistake that some health systems make is purely relying on existing capabilities that are unlikely to scale. System leaders are now recognizing that PHM programs should be organized based on their targeted chronic disease groups and driven by partnering with non-clinical intervention care resources in the community that can provide evidence-based interventions with adequate quality control.
Many system leaders are not yet wired to connect with non-clinical, community-based care. Clinical care outpatient workflows are well understood, but what about community-based care linked with clinical care workflows? Reducing chronic disease risk requires a framework of health behavioral strengthening tactics for change. Intervention care delivered with a framework that organizes formerly high-cost chronic care management more efficiently in community-based cost settings is worthy of consideration. For example, increasing patients’ physical activity levels has comparable effectiveness, and in some cases proven to be more effective when compared head-to-head with traditional pharmacological interventions for coronary heart disease, diabetes and stroke mortality outcomes. Furthermore, these physical activity interventions delivered via a robust clinical-community linkage have shown to be more cost effective. They are much more cost-effective when compared to traditional clinical care approaches that health systems would not hesitate to provide, such as intensive glucose or cholesterol control.
A Clinical/Community Care Collaboration
1.Change Referrals: define system populations and stratify into chronic disease risk groups for health behavioral change.
2.Change Readiness: refining individuals within the stratified cohorts for personal preferences, physical and motivational readiness.
3.Change Transition: enrolling and navigating cohorts to care interventionists who ensure the highest participation in their first intervention session.
4.Change Process: successful intervention care must contain:
- Methodologies for exercise, nutritional health, and behavior change;
- A balance of human and digital behavior change strategies over a duration to achieve self-care management;
- Progressive engagement intensity that establishes change momentum trajectory to maintain and sustain health behavior changes.
When properly executed, the design for each change element of the framework sets the stage for the next change element. The good news is that the framework integrates into the value-based care transformation already taking place for those health systems acquiring risk bearing payer contracts and implementing PHM programs.
The health behavior change framework concept contains six primary elements:
This is where the framework starts. Many population health programs stratify patients by the financial risk (claims data) they represent to the organization, grouping them based on their health needs (clinical data). To effectively scale their PHM programs for successful outcomes, health systems must also consider community data that include behavioral, social and environmental assessments for a more comprehensive health picture and guide to interventions. Stratifying chronic disease population groups using claim, clinical and community data provides population health management teams with the information needed to prioritize their focus.
Stratifying chronic disease population groups using claim, clinical and community data allows PHM teams to prioritize their focus. Further stratification into cohorts based on chronic disease priority targets, risk scores and continuum of care ranking placement serves to assemble the clinical and community intervention care programs needed to slow, stop or even reverse chronic disease progression. However, we need to identify which patients in these cohorts are actually ready for lifestyle behavior change.
Identifying the patients who are ready to participate in intervention care programs is a both a challenge and a big opportunity. Discovering who in the cohorts are ready to engage in behavior change requires a set of standardized readiness determinants. Refining the individuals in a cohort typically includes screening for motivational readiness, physical readiness and personal/logistical preferences (e.g. location, time, family support, and transportation)
Knowing who is not ready for change is critical to deprioritizing or delaying the referral of patients that will likely not stay engaged for the duration of an intervention program. The peer support nature of group sessions is disrupted by those who resist change through the course of the intervention. For those who are not ready, readiness counseling should be available to help patients reach a stage where change is being contemplated through theory-based interventions prioritizing behavior change cognitive processes.
Patient readiness data most often is collected by a member of the care coordination team who also has access to clinical records that provide medications and physician appointment adherence data, along with confirmed comorbidities and other associated risks and medically significant factors. Once it is determined that a patient meets the readiness standard for a behavior change intervention, then the referral process can transition the patient to community care.
Care coordinators, referral navigators, and community connectors can jointly or individually be given the responsibility to manage the patient enrollment in an intervention care cohort. Enrollment is the patient’s commitment to participate in the intervention care program as a significant component of their personal health care plan. Those that navigate and enroll referrals must carefully select locations offering the appropriately assembled intervention care program for patients that meet their personal preferences. Accessible care safe community places for intervention care programs are critical to methodological engagement and participation in group based sessions.
The hand off to the community care professionals that facilitate intervention care programs (interventionists) is a critical step in support of the patient’s transition to intervention participant. These program interventionists take over the responsibility for their cohort’s process of change. Patients must have a comparable level of trust in their interventionist as their clinical care professionals. This trust typically is gained during the onboarding process where the interventionist must consider all factors that encourage participation in program session one, the first health behavior change process milestone.
The change process must be assembled using evidence-based and practice-based intervention methodologies that play out over a duration (evidence indicates 12 to 16 weeks) to achieve a sufficient or higher level of self-care management. Self-care of a participant’s chronic conditions is the primary contribution expected from intervention participation. From the first face-to-face group session with their cohort and the interventionist, the journey begins to discover those unhealthy lifestyle routines that are contributing to a participant’s chronic conditions. Sedentary lifestyles, poor nutrition and sleep are typically the intervention focus for most cohorts, so programming should always include nutrition education and group exercise during sessions.
Once the unhealthy habits are discovered, the next step is to replace those habits with healthy routines. The interventionist leads the group with habit disruption and replacement strategies that are very dependent on digital engagement. Human engagement during the group sessions establishes the foundation for each week’s cohort goals and each participant care plan goals. Digital engagement provides the frequency and intensity to keep each participant on track for discovering unhealthy habits, replacing with healthy habits, and practicing those habits until engagement support is no longer required. Digital engagement also provides a management tool for interventionist to spot weaknesses during the change process for the cohort participants.
The power of progressive engagement during the intervention is the key for the cohort participants to change those unhealthy lifestyle elements that are the root causes of their chronic conditions. The change momentum created is likely to impact other dimensions such as high stress and low productivity, and promote change sustainability after the intervention. It is typically recommended that a maintenance program for at least 9 months supports the changes accomplished and triggers addition support when needed. During the intervention and maintenance programs, community outcome metrics measure core change datasets that validate methodology adherence, engagement frequency, and self-care management achievement.
The clinical and claims risk data categories are now joined by a community data category to help validate the effectiveness of population health management and chronic disease care programs. Quantitative and qualitative community data acquisition tools must be used to provide the source data to evaluate the health behavior change process to self-care management. The community data collected and the core outcome metrics analyzed are based on quality and performance standards set by the EIM GRCC (Exercise is Medicine® Global Research and Collaboration Center) at the Rollins School of Public Health, Emory University.
The effectiveness of chronic care programs is analyzed by using five (5) core datasets of community outcome metrics: referred, refined, on-boarded, engaged, and self-managed. The community data acquisition sources include: wearables, self-reporting, surveys, observation, and mobile apps. The aggregation of this actionable data for clinical and community care teams tracks program success and provides an analytical review, all in an effort to uncover best practices that support chronic disease self-care management. These are outcomes that lead to a return on investment from health system acquired value-based care payer contracts as revealed by correlating clinical and claims data.
Value-based payment models challenge the best administrators of direct payer contracts. For community care, performance payment models are just now being created and tested to see the impact on chronic disease care results. Reporting on health behavior change framework execution for performance, community network scalability for service area coverage, and chronic care programming for self-care management outcomes will be the focus of future reports.
With the successful execution of the first five change framework elements, payment and reporting configuration will be determined by health system leadership as value-based care payer contracts are acquired and patient-centered medical neighborhoods are expanded.
A health behavior change framework becomes essential as health systems continue moving toward community care that leverages the economies of scale in delivering care programs for chronic disease population groups. This six-element template creates the necessary framework for a collaborative community care operating structure. This is especially true for health systems seeking to deliver chronic care programs that empower participants to be better stewards of their own health.
This framework gives health system leadership along with ACO, PHM and medical neighborhood executives a path that makes their value-based care initiatives more efficient and effective.
About The Authors
Phil Trotter, B.S., leads the Exercise is Medicine® (EIM) on-the-ground team to integrate physical activity as a standard component of intervention, prevention and care management programs that support the implementation of Community Care Collaboratives and the necessary resources for community-based delivery of healthcare to payer, patient and underserved populations. Phil is a Community Care thought leader and Collaborative subject matter expert consulting with health system leadership and population health management executives and their teams.
Felipe Lobelo, MD Ph.D., is an associate professor of Global Health at Emory’s Rollins School of Public Health and directs the EIM Global Research and Collaboration Center (EIMGRCC). The EIMGRCC is the academic hub in charge of leading the evaluation of the EIM initiative, in collaboration with partnering health care systems, community organizations, and fitness and technology companies.
Ashley John Heather, B.A., co-founder of Off The Scale ® a turnkey, chronic disease intervention platform. http://offthescale.com