Artificial Intelligence | News | Insights | AiThority
[bsfp-cryptocurrency style=”widget-18″ align=”marquee” columns=”6″ coins=”selected” coins-count=”6″ coins-selected=”BTC,ETH,XRP,LTC,EOS,ADA,XLM,NEO,LTC,EOS,XEM,DASH,USDT,BNB,QTUM,XVG,ONT,ZEC,STEEM” currency=”USD” title=”Cryptocurrency Widget” show_title=”0″ icon=”” scheme=”light” bs-show-desktop=”1″ bs-show-tablet=”1″ bs-show-phone=”1″ custom-css-class=”” custom-id=”” css=”.vc_custom_1523079266073{margin-bottom: 0px !important;padding-top: 0px !important;padding-bottom: 0px !important;}”]

Creating a Network Infrastructure to Support Administration of Value-Based Care

Value-based care (VBC) reimbursement models are designed to reward better patient outcomes while reducing the costs of healthcare. The American Medical Association (AMA) identifies several components necessary to make a VBC ecosystem successful. These include a clear, shared, patient-centric vision, the leadership and professionalism of healthcare workers, and broad access to care for anyone who needs it. 

But there are two other essential elements without which VBC cannot succeed. One is the accessibility of unified patient Longitudinal Healthcare Records (LHRs) on a permissioned basis with required entities. The other is a robust infrastructure that supports both the complex many-to-many hierarchies of the healthcare ecosystem and complex healthcare data capture, digitization, and sharing. 

Recommended: Biggest AI-based Telehealth Updates for 2022

A VBC network consists of multiple stakeholders that may include providers such as hospitals and physician groups, payers, risk-bearing entities such as accountable care organizations (ACOs), clinically integrated networks, carve-out programs for chronic disease management, care management programming, social service networks, and community-based organizations (CBOs). 

For a VBC reimbursement model to work, it must facilitate easy onboarding of stakeholders and data capture. Critically, it also must include mechanisms by which stakeholders are rewarded financially for their roles. Thus, the administration of funding pools, including downstream distribution of funds and data exchange to participating partners, is one of the most vital functions of successful value-based execution. 

Traditional approaches and legacy systems, however, do not support the hierarchical relationship structures needed for onboarding stakeholders in value-based contracts, creating a formidable challenge for providers and payers. Likewise, traditional approaches and legacy systems do not enable scalability for the orchestration of cascading payment models, under which payer-provider collaborations incorporate risk-bearing entities and downstream providers, reducing the ability to accelerate the adoption of varied alternative payment models.

This hierarchical approach to partner onboarding, scaling of contract operationalization, and permissioned data sharing is necessary for aligning the medical, social, behavioral, and environmental components of successful value-based program administration and high-performance networks that allow providers to treat the whole person and deliver on healthy patient outcomes.  

Connecting networks of Value-based care

The execution of whole-person care plans must occur across networks where both medical and non-medical resources are tightly coordinated within an infrastructure that aligns performance for healthy patient outcomes and financial risk management. A patient-centric whole-health approach incorporates social and community services to ensure healthy post-acute outcomes and chronic disease management.

Healthcare organizations that provide ecosystem participants with a solid onboarding model and the right supporting capabilities can effectively 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. And by engaging and integrating the patient across the continuum of care, patients are empowered to be stewards of their own health. 

Related Posts
1 of 11,850

Such a transition must entail a shift from transactional data processing to outcomes-driven care. Advances in computing power, coupled with advanced algorithm models in the field of artificial intelligence (AI) techniques, enable deep insights both retrospectively and prospectively 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 (NLP), robotics, cognitive systems, deep learning, and computer vision. 

Top NLP Blog: Are Voicebots and Chatbots the Key to Modern Customer Service?

Digitization, as well as co-relation of data to create a Patient LHR, are essential to moving from transactional processing to the outcomes-based mindset underlying personalized VBC. This requires the creation of a data infrastructure based on ontology mapping and proper digitization of semi-structured and unstructured data sets that span clinical, demographic, claims, benefits, financial, social determinants of health (SDoH), connected device, clinical trials data and more.

Such an infrastructure is needed to support the move to VBC. To deliver value-based healthcare, a unified view of the patient is imperative. A patient-centric LHR 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. 

Every entity involved in providing care to the patient eventually will become a part of the networks that provide VBC. Yet this transition will not happen overnight since most of the platforms and solutions used in the industry today do not support complex hierarchical needs, complex payment models or data infrastructure requirements. Interoperability between these networks as well as legacy systems is possible only with a proper DaaS (Data as a Service) layer built on top of the data infrastructure.

Supporting hierarchical needs

While most organizations already have investments in infrastructure, these typically lack sufficient support for both the hierarchies and the data foundation layer of ontologies. So how can healthcare organizations supplement existing investment while still gaining the advantage of such robust data/microservices/hierarchy support infrastructure that facilitates a faster move to expand VBC?

Fortunately, such an incremental approach is possible without having a rip and replace strategy. It requires a platform infrastructure to integrate the data layers seamlessly, then extends 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. 

Supporting the hierarchical needs between the different entities involved in VBC, coupled with the data and microservices infrastructure mentioned above, will accelerate the move toward the adoption and scaling of Value-based care.

[To share your insights with us, please write to sghosh@martechseries.com]

Comments are closed.