By John Porawksi | June 3, 2022
Delivering on the promise of value-based care (VBC) requires providers and payers to have a deep understanding of the health and well-being of the patients they serve, both individually and population-wide.
VBC, which promotes proactive vs reactive care, depends on diverse data, including social determinants of health (SDoH), claims, clinical, and behavioral health data. A comprehensive view of data supports accurate risk predictions, better total cost of care understanding, and, ultimately, improved care quality and clinical outcomes.
In addition, VBC models promote lowering health care costs through early intervention for patients/members at risk for chronic disease, transforming processes for greater efficiency and optimizing utilization of care resources. This requires providers and payers to identify high-need, high-cost patients, who comprise only 5% of the population yet account for nearly half of annual health care costs in the United States, most of which is preventable.
Data analysis that allows providers and payers to create cohorts of people with common attributes enables health care organizations to prioritize action based on urgency, severity, or cost of the challenges faced by patient/member groups. Population data analysis helps providers and payers quickly determine which patients/members should be targeted for outreach and intervention.
In truth, population definition is essential to the care of most health conditions. Often, providers will delegate care of a patient segment based on diagnosis or will require additional screening based on an identified concern. A majority of VBC contracts include funding for accountable care organizations to coordinate care of these defined groups.
Plus, to ensure patients/members have timely screenings, providers and payers can use data to identify those who have missed their annual wellness visits and then reach out to them to schedule appointments or any other necessary interventions.
Proactive Engagement Is Critical
Chronic disease in the United States is growing in prevalence and cost, spurred by aging baby boomers and the increased incidence of disease in children and young adults. The cost of inpatient care and prescription drugs is an obvious issue, but lost education and job opportunities mean additional costs.
“When including indirect costs associated with lost economic productivity, the total cost of chronic disease in the United States reaches $3.7 trillion each year, approximately 19.6% of the country’s gross domestic product,” writes Tara O’Neill Hayes, former director of human welfare policy, American Action Forum.
Providers and payers can pull data from claims, electronic health records (EHRs), and SDoH that affect health—food insecurity, racial bias, and smoking, for instance—to segment patients/members who may have significant medical conditions. By continually updating the health data of people in these cohorts and routinely applying advanced analytics, providers and payers can implement interventions that mitigate medical risks and avoid unnecessary, costly care utilization.
Use cases may include:
- patients with diabetes who have not had a qualifying encounter with a physician in the past 18 months;
- patients with body mass index scores above 40 who have not been coded for morbid obesity; and
- members at high risk for emergency department (ED) utilization.
Also, segmentation helps trigger reassessment of select patient or member groups for better, more accurate risk-adjusted factor (RAF) scoring—a critical consideration because VBC contracts are benchmarked off risk scores.
The accuracy and speed of advanced analytics in extracting and aggregating patients/members who share specific traits allow providers and payers to meet their needs and achieve the objectives of VBC.
From Understanding to Action
In assessing how patients/members are affected by SDoH such as transportation problems, low income, unemployment, housing insecurity, food deserts, racial and ethnic bias, and other social and cultural factors, providers and payers identify actions that can have a positive impact on care and outcomes for individuals. These actions may include arranging rides to medical appointments or making referrals to social service agencies for job training or subsidized housing.
With the right advanced analytics solution, providers and payers can navigate and segment populations based on all the data available. Not only will this allow them to improve health outcomes, but it also increases their ability to meet VBC-related financial and clinical goals, while improving efficiency across the organization.
Actionable insights can be used to inform appropriate care decisions and correct RAF scores to favorably affect Medicare payments. In the case of avoidable ED utilization, providers and payors can enroll high-risk populations into care management plans. For people with high LDL levels who live in food deserts, a nutritional foods program may help them lower their LDL scores.
Navigating populations can also be useful in identifying patients/members with behavioral health problems such as psychosis and postpartum depression. People struggling with behavioral health conditions tend to utilize EDs—by far the most expensive form of health care—at a far higher rate than average. Referring these patients/members to behavioral health treatment options can help reduce expensive visits to the ED.
Health outcomes for individual patients and members collectively determine whether providers and payers are meeting the requirements spelled out in VBC contracts. Advanced analytics can determine how much money providers and payers save by closing care gaps and how much more revenue they can capture by meeting performance targets and coding individuals properly for accurate RAF scores.
Population navigation can play a significant role in improving health outcomes for patients/members, as well as revenue outcomes for providers and payers under alternative payment models that reward quality care and cost reductions.
Using advanced analytics, payers and providers can navigate their overall populations, define their own cohorts, and build segmented groups. This will enable them to optimize VBC performance against specific cost and quality measures, including clinical quality and safety, effectiveness of care, care coordination, cost optimization, network management, and patient experience.