Spurred by the 21^st Century Act and new mandates by the Centers for Medicare & Medicaid Services and Office of the National Coordinator for Health IT, the availability of unprecedented amounts of data offers a watershed moment for healthcare innovation at not a moment too late. Amid the public health crisis driven by COVID-19, the global health community is hard-pressed to find solutions that activate the type of interoperable data that recent legislation aims to solve. From determining how to deliver care remotely, providing greater visibility into variables dictating population health, advancing evidenced-based medicine, and improving tracking and contact tracing—we can no longer wait to implement headless, data-friendly, platform-based systems. 

Healthcare organizations cannot allow monolithic systems to be at the forefront of their consumer engagement strategy. Prescribed viewing of a patient’s data is not enough, and the continued data-blocking strategies that they rely on today will only isolate companies that are slow to adapt. New generations of patients expect to be more involved in their healthcare journey. We’re operating in an unrivaled time where consumers want to marry innovative solutions with their discrete data, understand their genomic implications, and have the ability to research, locate and ascertain the best and newest treatments to improve their health and extend their life expectancy.

To deliver on these expectations, patients require the rights to their discrete data elements, the ability to consent to innovators big and small—outside and inside of the healthcare ecosystem—that promise to create new ways of delivering care and healing. You can understand why retail firms and tech giants are spinning up their own products and applications to make self-care, diagnosis and medically based joint decision-making models more attainable and accessible. But without the patient’s express ability to access this information and the portability of that data, innovation will inevitably be stunted. With the digitalization of healthcare and patients seeking alternative treatment options instead of providers who are organized specifically around episodic and event-based care, it’s time for healthcare leaders to pause and evaluate their long-term strategies, investments in monolithic systems and care delivery models to focus on building solutions that encourage and incentivize the sharing of critical patient data.

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While the healthcare system has traditionally relied heavily on EHR data, the reality is: This data is not comprehensive of all the information required to effectively deliver effective population health management. Social determinants, individual behaviors, physical environments and economic factors all play a disproportionate role in community health compared to access and clinical care. Providers have faced data barriers perpetuating a vicious cycle that prohibit the ability to provide a comprehensive approach to understanding communities, identifying patients for targeted interventions and developing programs that deliver on the promise of precision medicine. Healthcare organizations are faced with a lack of internal and external data sources that capture health behaviors—such as tobacco, drug and alcohol use, as well as diet and exercise—clinical care, social and economic factors, and a patient’s physical environment. This lack of effective data capture is worsened by underdeveloped platforms required for data aggregation and transformation and the inability to holistically analyze all factors that contribute to community health.

The good news is that the healthcare system is on the precipice of a population health revolution—a future care delivery model anchored around the inherent necessity to understand all contributing factors to a patient’s healthcare journey. This new digital ecosystem is made possible largely through new interoperability standards, the increased prevalence of wearables, remote monitoring and telehealth, and the adoption of platform approaches to data management, transformation and analytics. To achieve efficiencies and benefit financially—and most important improve the outcomes of communities—providers must act now to break down the physical and digital barriers preventing them from the ideal state that population health management promises to deliver.

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Few patients want to be monitored remotely 24 hours a day and even fewer physicians wish to do that monitoring. Yet, research shows that remote monitoring enables better chronic and acute care for more patients due to greater convenience and fewer complications, lower burnout rates for physicians, higher revenues for providers, lower costs for clinical research and accountable care organizations. Today, remote patient monitoring informs and complements at-home therapeutic devices, adjustments to pharmaceutical prescriptions and dosing, as well as digital therapeutics. In addition, while the Affordable Care Act seems to be stalling out with 10% of the US population remaining uninsured, remote patient monitoring could be an access point for uninsured people to receive early interventional care before complications and delays in care result in even larger bills for them and the overall healthcare system. So, what’s really at the heart of remote monitoring’s current and anticipated long-term success?

Future-looking stakeholders must remember that successful implementations of remote monitoring treat ease-of-use and engagement as top priorities to drive patient and physician adoption and adherence. Beyond the hard work of developing and deploying state-of-the-art sensing technologies and required algorithms, device makers and their customers must consider the support needed to overcome the limited bandwidth and attention that remote care provides. 

For these solutions to be truly affordable and adoptable, a robust medical digital platform needs to encompass physician education, connectivity support, digital and tele-present patient engagement, and the ability to integrate with provider EHRs and billing systems. To add to the stakes, the level of engagement needs to be appropriate to the criticality of the disease state under care, as well as the resources and time physicians and patients want to devote to monitoring important outcomes. For example, a real-time ECG monitor may need to sample 50 times per second, 24 hours a day, but may not be something a patient or doctor needs to track daily, while a spot-check temperature for a fertility app is the sort of low-frequency data that a user may want interpreted privately, expertly and immediately. Achieving the right accuracy, resolution, latency, cadence and messaging are key considerations for the technologies, platforms and content engaging patients wherever they are.

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For payors and providers, it’s been slow going in the adoption of telehealth—that is, until stay-at-home orders and quarantine restrictions stemming from COVID-19 pressured them to make virtual care more accessible to patients.

To make this vision a reality, providers, insurers and government authorities need to start collaborating to drive toward greater adoption of high-quality, effective telemedicine. Despite recent policy efforts, virtual care is still largely constrained by limiting licensing and reimbursement roadblocks, but COVID-19 has likely course corrected requirements for providers and payors. With increased patient demand and reliance on telehealth, it’s time to build and scale virtual capabilities that extend care beyond the four walls of the exam room, while continuing to strengthen the relationship between the patient and physician.

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It’s no secret that humans often solve problems most effectively by having a conversation. In recent years, a wide range of smart speakers have entered the market, enabling users to engage with devices through simple, yet helpful, interactions throughout various aspects of their lives. Products that use voice as the primary mode of communication are increasing in popularity, as new research estimates that over 75 million US adults own smart speakers and 150 million use voice assistants on smartphones.

In healthcare, voice has emerged as a promising frontier to create a more “human” experience, enabling patients and providers to access information seamlessly without having to navigate a complicated interface. The most common voice assistance uses in healthcare today include asking questions about symptoms or medical information and finding a hospital, clinic or treatment option. Thinking beyond these examples, voice-enabled solutions pose a wide range of benefits to patients and providers alike. Imagine the opportunities voice can create for patients who are elderly, disabled, have chronic conditions or live in rural areas. 

For providers, having the ability to leverage advanced voice assistants equipped with natural language processing to automatically generate encounter notes can save time and tedious documentation while maintaining patient privacy and allowing physicians to review and edit the information before accepting it into clinical records.

Forward-thinking healthcare organizations should view voice-enabled products and services as a new and growing channel for reaching consumers to deliver differentiated, human experiences. Voice presents a tremendous opportunity for healthcare organizations to remove friction for healthcare providers, engage with patients and deploy solutions to help facilitate burdensome aspects of care delivery, such as clinical documentation, which can help reduce physician’s administrative burden, and increase patient volume and billable revenue.

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Life-saving surgical robotics and state-of-the-art imaging or genetic sequencing equipment in hospitals to home-use blood glucose meters and heart-monitoring radar—whether they are therapeutic or diagnostic, used in a clinical setting or at home, or impact clinical biomarkers or important patient outcomes, medical devices provide data that serve as inspiration for a physician’s insight and evidence of the patient experience. Imagine if we could collect therapy-response data through the devices of the 300 million people around the globe who suffer from rare diseases. If this functionality were available on a worldwide machine learning-enabled platform, it could be the key to shortening the typical six- to eight-year odyssey before patients even receive a reliable diagnosis. We can’t afford to let medical device connectivity be meaningless.

IoT was born in 2008, back when the number of things outnumbered the number of people on the internet. In 2020, we all have some idea of how truly useless some of those things can be. Just like the villagers in Aesop’s fable about the boy who cried wolf, we can expect patients and caregivers to become fatigued if medical IoT data promises, but does not deliver relevance to their lived truth. And we’re talking about a global village.

In an ecosystem where care is delivered anywhere, when stakeholders like pharmaceutical, medical device makers, payors and basic research organizations have access to high-fidelity data that is privacy- and consent-compliant and associated with outcomes, machine learning can help discover improved hypotheses, products and care protocols.

Successfully connected medical devices represent the “last mile” connection to patients and providers. When they are designed for ease of adoption and integrated with smart, validated analytics platforms, data from these devices can be leveraged to provide guidance and education to patients, training and assistance to physicians, insights for R&D and manufacturing, and models for improved care, billing and payment protocols for ACOs.

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In the rush to deploy EHR systems, there was almost an exclusive focus on the functional needs the systems would provide—robust reimbursement and billing capabilities—but what was overlooked was an understanding of people. This led, sadly, to EHRs becoming a top reason for physician burnout as they increased time doctors spend on bureaucratic tasks. Patients who hoped EHRs would mean enhanced access to data instead have faced a proliferation of platforms that vary among providers, each with its own security requirements and means of engagement. Looking at the future of EHRs, there are three essential “people” needs.

1. We need systems that can improve the provider experience—systems that augment providers’ capabilities rather than seeking to replace them; systems that create more predictable revenue streams by, for example, optimizing a physician’s calendar; systems that operate silently in the background, capturing and processing the contents of the patient engagement as opposed to compelling providers to be data entry clerks; systems that have their providers’ backs by helping to reduce human errors; and systems that triage the overwhelming granular data available to them and focus instead on data that matters. Future EHRs, from the providers’ view, must involve systems that ultimately enable them to spend more of their time caring for patients. 

2. The second need is, of course, on the patient side. Patients need systems that track their medical history in ways that they can understand and that enable data-sharing no matter what institution providers are affiliated with. A successful EHR for patients can help ensure accurate diagnosis and treatment, provide quality care efficiently and lower their share of costs.

3. Finally, future EHR systems need to take a much more expansive view of stakeholders. Clinically, this means moving beyond physicians and nurses to include pharmacists, physician assistants, social workers and researchers, to name a few. Operationally, future EHRs should address the needs of billing and finance coordinators, schedulers, claims adjudicators and payors. Many patients have families and caregivers—whose roles are very different from patients themselves. In short: Next-gen EHRs must be designed for all the essential people.

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