AI-based data collection and analysis will likely be the foundation on which future value-based care programs are built.
The healthcare industry, and payers in particular, are faced with myriad challenges today. Soaring care costs, accessibility issues, and dropping profits have forced payers to reassess their operational strategies. Healthcare spending across the US is poised to hit nearly 20% of national GDP by 2030, putting increasing strain on an already beleaguered system.
Savvy insurance leaders have already made customer-centricity, digitally-driven care systems, and new payment models a serious priority. Key focus areas are optimizing healthcare payouts, building connected ecosystems that can readily integrate changes in the compliance landscape, and lobbying for government action to create more value for every stakeholder.
As an industry, healthcare insurance is putting its weight behind more customer-focused initiatives, new digital tools, and digitally powered pricing models. It’s also well worth noting that value-based care (VBC) is on the rise. In fact, reports show that VBC has seen a 50% increase over the past 5 years, with 73% of payers opining that VBC is likely to be the future of payer-provider engagement models.
To ease the shift to VBC, insurance leaders would do well to better understand the key drivers of the contemporary plan member experience.
See also: Unlocking Insights in Healthcare: AI and Topic Modeling for Better Patient Care
The Value-Based Care Revolution
Risk sharing between payers and providers is an integral part of the new insurance models, with payers offering higher payouts for better patient outcomes and penalties for inconsistent healthcare delivery. This is particularly evident in Medicare programs, with CMS creating new guidelines to promote accountable care with a view toward risk adjustment and improved preventive care. Within the payer-provider ecosystem, AI-based data collection and analysis will likely be the foundation on which future VBC programs are built, given the technology’s ability to eliminate organizational inefficiencies, boost diagnostic capabilities, and create a transparent system of data sharing between all stakeholders.
Connected Systems and Richer Data Orchestration
Merging silos is just as much a technological imperative as an organizational one. This is especially critical for payers, where data bottlenecks and poor stakeholder communication can delay diagnoses and drive up the costs of care. AI, especially generative AI, can help enormously by automating data extraction, organization, and analysis. Modern AI platforms allow insurers to gather information from patient devices, track historical medical data, and capture insights on system and process optimization relatively effortlessly. In turn, this helps them create customized insurance plans and offers for each customer while improving workforce productivity across claims administration, customer support, and underwriting. According to Ernst & Young, 70% of major insurers have allocated at least $5 million from their IT budgets toward generative AI.
The New Patient Experience Paradigm
With the bar for great consumer experiences constantly being raised across different industries, insurance providers can no longer afford to deliver lackluster services. Leading healthcare insurers have already recognized the need for transformation and are leveraging a number of technologies in tandem to make healthcare more accessible and convenient for digital natives. These include wearable technology to track consumer lifestyles and incentivize healthy living with lower premiums, rapid and intuitive claims resolution driven by intelligent document scanning and app-based member portals, and video-based consultations to lighten the load on both patients and provider infrastructure.
The Never-Ending Battle for Compliance
Value-based care presents significant compliance challenges for insurers and payers. The shift from fee-for-service to outcomes-based reimbursement increases the risk of violations related to anti-kickback laws, fraud and abuse, and data privacy regulations.
AI platforms can help mitigate these risks by leveraging AI to automate data processing, reducing the risk of human error, creating fewer opportunities for fraudulent claims to fall through the cracks, and enabling more robust security and data access management protocols.
See also: Study: AI Outperforms Humans in Writing Medical Summaries
The Stumbling Blocks to Adopting VBC
For payers, building out a value-based care (VBC) ecosystem comes with its own set of pitfalls. Part of the challenge lies in creating an up-to-date technology ecosystem that supports all stakeholders, but that isn’t all there is to it.
- Acquiring and analyzing comprehensive patient data is crucial for measuring outcomes and identifying areas for improvement. However, data silos, legacy provider systems, and the variety of data formats created by proprietary healthcare tech can pose significant hurdles.
- Shifting from fee-for-service to VBC involves assuming greater financial risk. Payers must develop strategies to manage this risk while ensuring adequate reimbursement. Successfully implementing VBC requires strong partnerships with providers to help align incentives and address concerns related to financial risk and performance measurement.
- Transitioning to a VBC mindset requires a cultural shift within payer organizations, emphasizing quality, outcomes, and collaboration over volume-based reimbursement.
- Investing in advanced analytics, data management, and technology platforms is essential for supporting VBC initiatives, but it can be daunting for payers who are already juggling increased IT costs and plummeting profit margins.
See also: AI’s Potential in Enhancing Chronic Disease Management for Improved Patient Outcomes
The C-Suite’s Role in Navigating the Evolving Healthcare Landscape
To address the changing healthcare payer paradigm, insurance executives have their work cut out for them. Most, however, will find a multi-directional approach useful in building a robust ecosystem and elevating organizational resilience.
Democratized Tech Deployment and Access to Insights
A well-defined vision statement and an outcome-oriented plan of action are half the challenges when it comes to managing costs and mitigating risks associated with new initiatives. Implementing VBC-based business models is no different. But to do that, leaders must first build a powerful foundational understanding of both emerging and extant data tools, and their applications at every point within the larger ecosystem and across the enterprise itself. In turn, that will help them enable access to insights for everyone, from primary care physicians and patients to field executives, claims auditors, and business executives.
Integrate SDOH Parameters
The US government is likely to place increased emphasis on social determinants of health (SDOH) within healthcare legislation and policy. In fact, the CMS has long been an active proponent of integrating SDOH into healthcare planning. In the near future, this will have a significant impact on how healthcare services are packaged and delivered. And in response, payer executives would do well to build links with community organizations to generate SDOH insights at a local level. This can assist in integrating SDOH parameters within VBC contracts and developing targeted care coordination programs that transcend economic and social barriers while improving preventative healthcare outcomes. Of course, once again, doing this at scale will require significant expertise and investment in the right data tools and networks to access SDOH insights in real time.
A Focus on Strategic Partnerships
If insurance leaders want to build the knowledge base and network needed to access complete and adaptable solutions while scaling up operations, they will have to craft strong relationships with technology partners, healthcare providers, and other stakeholders. A robust basis for collaboration, especially in the context of technology solutions, makes it easier to quickly respond to business challenges and expand market reach without skipping a beat.
Often, building the right partnerships and crafting an effective roadmap can mean the difference between a frustrating member experience or an exceptional one, between seamless stakeholder networking or fragmented systems of data sharing, and between staying ahead of disruption or failing at digital transformation.
