Technology Infrastructure Needed to Support Value-based Care

By Lynn Carroll, Chief Operations Officer and Rahul Sharma, Chief Executive Officer, HSBlox
Twitter: @blox_hs

The U.S. healthcare system’s transition away from fee-for-service toward value-based care represents the most significant change in how healthcare is delivered and paid for in generations. According to a recent study by McKinsey, the percentage of the insured population in value-based contracts is expected to grow by 10% per year from 2022 to 2025.

Ideally, an emphasis on value-based care, as well as the principles that drive the concept, will lead to higher-quality care delivered more efficiently, and cost-effectively. By incentivizing providers to focus on their patients’ health outcomes under value-based arrangements – as opposed to the volume of procedures they perform under fee-for-service – these new payment models offer the promise of helping the healthcare industry achieve the elusive quintuple aim: improving population health, reducing the overall cost of care, enhancing the patient experience, boosting provider satisfaction, and advancing health equity.

Without a doubt, the evolution toward value-based care holds the potential to improve nearly all Americans’ overall experience with the healthcare system, but one often-overlooked part of this transition is the need for the digital health infrastructure necessary to support the operations of sometimes-complicated value-based contracting arrangements.

Specifically, among the critical building blocks for administrating value-based programs is the need to support complex many-to-many hierarchies between entities in the network. These relationships become important not only for stakeholder onboarding and data capture, but also to administer the funding pools, payments, and risk-sharing between the entities.

Legacy delivery approaches and payment structures, which have remained largely unchanged for decades, have reinforced the problem and produced a system with erratic quality and unsustainable costs.

Infrastructure challenges of administering value-based programs
Successful administration of value-based programs requires infrastructure that enables the many-to- many relationships between stakeholders in the value-based network and their counterparts. These entities may include health insurance carriers, risk-bearing entities such as accountable care organizations, clinically integrated networks, carve-out programs for chronic disease management, primary care, care management programming, social service networks, and community-based organizations. Additionally, the administration of funding pools, including downstream distribution of funds and data exchange to participating partners, is one of the most critical functions of successful value-based execution.

One major challenge of administrating value-based care networks is the need to onboard and manage a complex multi stakeholder care network while accommodating the event-driven and episodic requirements of payment models no longer claim-centric. Another key challenge of value-based administration is the timeliness of data reporting and the ability to understand contract performance prospectively, as opposed to after the fact.

By providing ecosystem participants with a solid onboarding model and the right supporting capabilities, organizations can successfully administer value-based programs that incorporate whole health. These emerging care and payment models demand real or near real-time status and data exchange, a more prospective approach to reimbursement, and precision approaches to care team data sharing. Engaging and integrating the patient across the continuum of care will empower patients to be effective stewards of their own health.

Employing AI to improve the value of care
Traditional electronic health records systems were built to solve the challenges with transactional data related to claims submission, adjudication processing, clinical data processing, pharmacy data processing, and billing. The same is true for many of the legacy solutions used today in the healthcare industry. The data captured in these systems is never really digitized and is captured and stored in an unstructured form as charts, notes, images, audio, and video files.

Now, however, advances in computing power, coupled with advanced algorithm models in the field of artificial intelligence (AI) techniques, provide deep retrospective and prospective insights to improve the value of care. Key AI techniques in use today to glean information from the treasure trove of healthcare big data fall into the areas of machine learning, natural language processing, robotics, cognitive systems, deep learning, and computer vision. Together, these AI-based tools enable processing of very large data sets, help with precise and comprehensive forecast of risks, and deliver recommended actions that improve outcomes for consumers.

Additionally, to deliver value-based healthcare, a unified view of the patient via a longitudinal health record is an absolute must. A patient-centric longitudinal health record allows for easy data sharing in a permissioned manner – plus it allows physicians to make better decisions since a 360-degree view of the patient is available. By employing the AI techniques above, value-based networks can capture and gather data to develop detailed records of patients’ medical histories that are searchable.

Creating ‘networks of networks’
A value-based care network is generally comprised of the providers, facilities, suppliers, and caregiver organizations a health insurer or risk-bearer has contracted with to deliver healthcare services to patients. Arrangements such as these create very complex many-to-many relationships when an entity in a network is engaged in several networks with different contractual engagements with other entities.

These “networks of networks” are possible only with an infrastructure that supports both the complex hierarchies between the entities involved in value-based care and the data infrastructure driven through technology. Interoperability between these networks as well as legacy systems is possible only with a proper data-as-a-service (DaaS) layer that is built on top of this data infrastructure.

The support for networks of networks also creates the opportunity for a real-time exchange beneficial for the care team entities involved, as well as patients. A majority of organizations already have a technical infrastructure in place – but one that does not have the robust support for the hierarchies, nor the data foundation layer of ontologies previously discussed. As a result, the challenge becomes how to supplement existing infrastructure while still gaining the advantage of new infrastructure that facilitates a faster move to value-based care.

Such an incremental approach is feasible without having a rip and replace strategy. It requires a platform infrastructure to integrate the data layers seamlessly, then extend that data layer either as a DaaS or as a PaaS (Platform as a Service) so that partner firms or clients can use existing applications served up via microservices or extend/create microservices and business applications for their own needs.

To support the transformation to value-based care, healthcare organizations need a foundational platform that is data-digitization-driven and fulfills the following four objectives:

  • Connecting existing private cloud infrastructure to ensure compliance with regulatory and organizational guidelines
  • Leveraging existing infrastructure investments
  • Consolidating and transforming existing data sets while combining them with external data sets
  • Supporting applications critical to patient care and safety

Though it has been underway for about a decade, the U.S. healthcare system’s transition to value-based care has largely been characterized by fits and starts – as evidenced by a recent study revealing that the majority of physicians and specialists employed in group practices owned by health systems are still paid based on volume. Many of the reasons behind this slow transition are rooted in the technological challenges of administering value-based networks: specifically, barriers associated with supporting complex many-to-many hierarchies between entities in these networks. However, by having the right technological infrastructure, value-based networks can overcome these challenges to realize the quintuple aim.