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With healthcare costs outpacing income growth and health insurance deductibles increasing by 212% over the past decade, many patients are left feeling that their health insurance doesn’t provide as much value as it did 10 years ago.
Value-based care has gained significant traction in the U.S. over the past few years, and for good reason. With healthcare costs outpacing income growth and health insurance deductibles increasing by 212% over the past decade, many patients are left feeling that their health insurance doesn’t provide as much value as it did 10 years ago.
Meanwhile, recent price transparency data has revealed that, on average, hospitals charge private payers more than twice the amount they charge Medicare and Medicaid. As a result, employers who offer employer-sponsored health insurance are increasingly demanding that payers take a more active role in reducing the cost of care. Developments like the Anthem-Parkview contract negotiations have sent a strong message to payers—look for ways to lower costs or lose your most profitable line of business.
Many payers are taking this message seriously and working with providers to implement risk sharing arrangements and value-based care models. Although these models can help cut costs and improve health outcomes, they also face a variety of challenges: “value-based care” measures (such as admission and readmission rates) that are not tied to health outcomes, a lack of data interoperability (Briefings in Bioinformatics 2021), and payers placing the responsibility of controlling costs onto providers. Providers are hesitant to enter such arrangements due to the higher financial risk, operationalization barriers, and additional cognitive strain associated with these arrangements (Health Payer Intelligence 2019).
These challenges raise an important question: how can payers reduce the cost of care and improve health outcomes for their members? Ultimately, payers will have to take a more active approach to value-based care by leveraging data to find targeted opportunities, collaborating with providers, and supporting investment in medical technology.
1. Identify Opportunities Using Data
Although most payers collect vast amounts of data about their members, few of them have unlocked the full potential of this data. Payers—especially those involved in integrated delivery networks (IDNs)—need to use this data to extract insights about their members, communicate these insights across functions, and identify opportunities to create meaningful interventions.
Many payers recognize the importance of data-driven insights and are already taking steps to improve their data analytics capabilities. In fact, a recent report found that 74% of health executives were planning to invest in predictive modeling this year.
But data analytics alone won’t lower healthcare costs and improve outcomes—especially when organizations keep their data siloed, don’t communicate their data well, or lack holistic data that includes social determinants of health and community factors. Payers must use their wealth of data (which, for IDNs, includes both claims and EHR) to find targeted opportunities and create population health initiatives. These initiatives should aim to stratify risk and target specific populations with actionable opportunities that reduce time to value.
We are frequently asked to help healthcare companies leverage their data to create predictive models and identify areas of opportunity. Over the course of nine weeks, we helped a large population health client develop a predictive model to identify members at high risk of falls. The client used our model to design population health interventions, preventing an estimated 75-100 falls per year and providing cost savings of $30M per year.
2. Collaborate and Build Trust with Providers
Payers also need to collaborate with providers to improve care quality and build trust. Currently, payers—especially those involved in risk-sharing arrangements—are exerting downward pressure on providers’ margins and providing little support for reducing the total cost of care. Between this lack of risk-sharing and the administrative burdens that insurance adds to provider workloads, providers may view payers as inhibiting their ability to provide high-quality care. Going forward, payers need to introduce more upside risk and provide incentives that align with provider goals.
Care pathways would particularly benefit from payer-physician collaboration. Payers could work alongside providers to identify at-risk populations and support referrals to participating providers. Specifically, payers could involve providers in identifying risk factors that might good indicators for predictive modeling. They could also co-create care pathways and reduce providers’ administrative burdens (e.g., prior authorization). These initiatives could help providers meet their targets, improve care quality for patients, and build trust between providers and payers.
3. Support Medtech Investments
Finally, payers should consider investing in medical technologies that can lower long-term costs and improve health outcomes outside of the existing claims and reimbursement structures. Many payers are already working alongside providers to implement advanced tools and technologies for large, high-cost member populations. For example, Cigna is working with Cricket Health, a comprehensive kidney care provider, to support chronic kidney disease (CKD) patients. Cricket Health uses a machine learning algorithm to identify members at high risk for CKD, then deploys care management solutions to reduce hospital admissions and disease progression rates. While these investments can improve care for large member populations, payers should also look to adopt tools that can improve care for smaller member segments with conditions that incur high medical costs for businesses—for example, neurological conditions.
Neurological conditions represent large areas of opportunity for payers. The single most common neurodegenerative condition is Alzheimer’s disease, which impacts 6 million patients across the U.S.—but over 50% of Alzheimer’s patients are either undiagnosed or unaware of their diagnosis. Implementing AI-enabled imaging technology at the beginning of the care pathway could help these patients get diagnosed and treated earlier, ultimately improving quality of life and slowing disease progression.
In other areas, AI-enabled imaging technology can improve providers’ workforce efficiency and imaging quality, thereby increasing healthcare utilization and value. Another high potential MedTech area is patient monitoring solutions, which can improve the patient experience by facilitating patient-provider connections. These solutions can also help drive member steerage. Finally, remote symptom management solutions allow for more touchpoints between patients and providers, improving provider visibility into their patients’ post-treatment profiles. The improved visibility can help slow disease progression and mitigate risks, such as unnecessary hospitalization or medication non-adherence.
Over the past decade, value-based care has become a popular buzzword among stakeholders across the healthcare system, but its benefits have yet to be realized. Fortunately, payers have several opportunities to help accelerate the transition to value-based care. These opportunities include using data to design targeted health initiatives, collaborating with providers, and supporting investment in medical technology. Ultimately, these interventions can help protect payer profit margins and streamline provider workloads while reducing costs of care and improving health outcomes for patients.
Emily Graham is a healthcare expert at PA Consulting. She is focused on helping health payers transform their operations to meet the demands of a rapidly changing industry.
Nadeem Fazal is a healthcare and life sciences innovation expert. He leverages his background in health policy and understanding of healthcare dynamics to bring innovative medicines and health solutions to market globally.
Erika Moen is a healthcare and life science expert at PA Consulting. She is focused on improving communication within healthcare systems and life science organizations to help business functions translate data into action.