The real time health system: adapting healthcare to the new normal
Right now, in the midst of a pandemic, our healthcare system is struggling with uncertainty – some might even say chaos – as it tries to stem the tide of infections that are sweeping across the nation. The COVID-19 pandemic demonstrates, vividly, that our healthcare system is unsuited to delivering systemic services to preempt, intervene and mitigate health crises affecting the general population.
It’s a problem as old as organized medicine, and we have yet to effectively harness the collective resources of healthcare to optimize human and physical assets, eliminate the frictions, and introduce the efficiencies that remove gaps in care and uneven outcomes. The solution set is going to require a departure, maybe a divorce, from traditional care delivery, and a pivot towards a data driven, real time health system.
U.S. healthcare has reached an inflection point – accelerated by COVID-19, in which the industry’s’ brick-and-mortar, encounter based business model is being extended and magnified by technology-inspired care innovation.
Pandemic aside, that transformation is largely a consumer driven phenomenon: Consumers have grown accustomed to the convenience of real-time access to people, process, information and transactions from any location and any connected device, and healthcare is no exception. In growing numbers, consumers expect greater engagement in decisions about their health, and connectivity to their care team beyond the encounter.
For both payers and providers, the challenge is to define and deliver this higher order of clinical value to the new healthcare consumer– conveniently, and beyond the boundaries of the traditional provider -patient relationship. A further wrinkle is the introduction of value-based care – allowing the consumer a greater voice, and greater choice, in the services and the sources of their care.
The common thread running through all these consumer expectations is clinical information – data that is captured and aggregated from any stakeholder, including the patient, normalized regardless of structure, analyzed, translated into actionable information, and delivered into a shared record.
In practical terms, the heart of healthcare consumerism is the patient experience – the range of interactions between the patient and their touchpoints of care – their health plan, inpatient and outpatient, office and virtual encounters, home based, portals and social media. And it’s not just about fluid access or a retail level of convenience – it’s about immediate, fully informed clinical decision making. The clinical capability that addresses this right here, right now patient dynamic is the Real Time Health System.
RTHS describes healthcare systems in which stakeholders share, adopt, and apply medical knowledge in real time. The RTHS value prop: if we can collect data, analyze it, and get it to providers quickly, we can improve care, accelerate workflows, streamline business processes, and better balance resources with demand.
The RTHS is characterized by curated, comprehensive clinical data – sourced and shared between all of healthcare’s stakeholders and delivered in real time to the patient record and the decision makers who can deliver informed care as a result.
But beyond data sharing, RTHS impacts the speed and clinical expediency of data, and through applications like AI and population health, allows healthcare’s decision makers to deliver precision medical care.
The key ingredient of the RTHS is data interoperability – defined by HIMSS as “the ability of health information systems to work together within and across organizational boundaries in order to advance the effective delivery of healthcare for individuals and communities.”
Interoperability involves the bilateral sharing of clinical information, including medical records, laboratory results, clinical summaries, medication lists, and much more. It achieves this level of data access and transparency by establishing a common data lexicon that enables the interpretation, and delivery of relevant clinical information regardless of format, platform, or vendor.
The grand vision of healthcare interoperability is to remove the structural, technical, and cultural divisions that prevent transparent clinical data exchange among every stakeholder in the care continuum.
Foremost among interoperability solutions is Fast Healthcare Interoperability Resources, or FHIR, a set of HL7 sponsored standards that facilitate the exchange of health information through connected, independent systems. FHIR provides consistent data formats, elements, and an application programming interface to connect health information across different health systems, payers, practices, pharmacies, and consumers.
Ultimately, FHIR creates a common language where any clinical system can connect and share data. A few examples of FHIR in practice include the DaVinci project, a private sector initiative working to help payers and health care providers positively impact clinical quality, cost and care management outcomes by facilitating the adoption of FHIR data standards.
The CARIN Alliance is a multi-sector collaborative that promotes the ability of consumers and their authorized caregivers to gain digital access to their health information via open APIs (APIs provide the means for disparate applications and systems to communicate with each other). In the public sector, CMS has created Blue Button, a system that enables Medicare beneficiaries to view online and download their own personal health records.
Additionally, there are collaborative interoperability alliances like SHIEC (HIEs), DirectTrust (HISPs), the Sequoia Project (nationwide interoperable health information exchange), and the Discover Alliance (multi sector).
These initiatives share the common goal of delivering a dashboard style, consolidated patient record on any connected device, from any qualified source, and will provide a trove of research and best practice information to members of the care team, including providers, payers, pharmacy, and consumers.
If interoperability is the vehicle that enables the RTHS, then clinical data tools – tools that capture, analyze, and transmit data from all points of the healthcare compass – are the fuel. These tools include:
- Population health envisions the health outcomes of a group of individuals, including the distribution of outcomes within the group. Groups can be defined by geography, but also by other demographics such as employees, ethnicity, disabled persons, prisoners, or any social structure. Employing RTHS resources, Population health tools aggregate broad patient data from multiple health venues, and action is directed at the health of an entire population, or sub-population, rather than individuals. In the era of value-based care, that means taking clinical and even financial responsibility for managing the overall health of a defined population and being accountable for the health outcomes of that population.
- Virtual health encompasses a catalog of digital and telecommunication technologies used to deliver on demand health care, including telemedicine, remote patient management, virtual visits and virtual assistants, and self-care. It includes tools such as wearables and home-based monitors, virtual reality and portals that collectively enable continuous monitoring, recording, and sharing of clinical data. As a component of the RTHS, Virtual health captures and makes usable clinical data between (or in lieu of) visits, and by removing the physical barriers to care, shifts the focus of care from reaction to prevention and wellness.
- Patient-generated health data describes data that is recorded and shared by patients, their family members, or caregivers in the management of health conditions. Patient-reported outcomes measures can help patients and providers monitor the results of an encounter or treatment. For Providers, PGHD is a useful tool in monitoring overall health and well-being, and early detection of potential health conditions.
- Artificial intelligence and analytics describes algorithms and software that enable the extraction of actionable insights from sets of patient data sourced from patient claims, pharmaceutical and research and development data, clinical data collected from electronic health records, and patient generated data. Taken a step further, AI and predictive analytics uncover previously unseen data patterns that can be used to improve clinical decisions and treatment protocols. Through tools like AI and predictive analytics, the RTHS can anticipate and intervene in health issues at their onset – or even before they occur.
Clinical data, captured from any source, distilled, evaluated, analyzed, translated into actionable information, and delivered in real time within the patient record, is the bonding agent of patient engagement and the RTHS.
But the value of RTHS stretches beyond the use of digital tools to compile and share data. It combines digital and telecommunication technologies to create a continuous connection between patients, physicians, and other caregivers. And by combining technologies, health care stakeholders can more effectively coordinate patient care and optimize the patient experience.
RTHS is emblematic of sweeping changes that are redefining the terms and tools of healthcare. As value-based care takes hold, clinical decisions based on episodes of care will be replaced by the continuous capture and sharing of patient data.
Isolated snapshots of patient health will be replaced by a holistic, 360-degree, real time view of the patient, and the role of the patient will be elevated from bystander to fully engaged member of the care team. And with health crises apparent (like opioid abuse) or immediate (like COVID-19), the RTHS isn’t just aspirational, it’s critical.
Rick Krohn, principal at HealthSense, is an expert in connected health. He is the author of more than 100 articles and three HIMSS books detailing healthcare innovation.
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