To say that digital health is having an impact on the way healthcare is being delivered is an understatement. The real question is: what is being understated? Is it the impact on mindshare? Is it the impact on investment? Is it the impact on the “front lines” of care delivery? Or is it the impact of innovation on care delivery?
Since we opened with a politically inspired subject line, it’s only appropriate to start with fundamental policies that have affected digital health and care delivery, long before “digital health” was a coined term. The Health Insurance Portability and Accountability Act (HIPAA) and the Health Information Technology for Economic and Clinical Health (HITECH) Act laid the foundation for care delivery and digital health adoption many years ago.
HIPAA is over 20 years old and HITECH just hit 10. Even now, the term “meaningful use” stipulated by these policies is a struggle – and neither of these policies (and many others) provide a framework that pragmatically prescribes how care delivery can and should be impacted by digital health and innovation. In fact, many would argue that they have been quite the opposite. They would say that “Digital Hell” is a separate topic, that we will tackle in the near future, starting with the damning state-of-the-union on EHRs.
For this discussion, we want to focus on “Digital Heaven” – making digital technologies work in harmony with the advancement of care delivery. Allow us to introduce a candidate called the learning health system.
What is a Learning Health System?
The learning health system (LHS) construct was defined by the Institute of Medicine as a framework where “science, informatics, incentives, and culture are aligned for continuous improvement and innovation, with best practices seamlessly embedded in the delivery process and new knowledge captured as an integral by-product of the delivery experience.” Below is a simple illustration to break it down :
For Lean Startup enthusiasts especially, the resemblance to “Build, Measure, Learn” is completely aligned with modern software innovation. For Quadruple Aim advocates, it intrinsically supports patient experience, clinician well-being, care outcomes, and care innovation.
How Does Digital Health Enable an LHS?
Today, in the US, over 90% of healthcare institutions have adopted certified EHRs. That is a very positive outcome of HIPAA and HITECH and has created the data backbone that is essential for a learning health system to learn.
An LHS is enabled by:
Robust data stores: Starting with EHRs, but also extending to provider directories, claims repositories, genetic data repositories, clinical trial repositories and other data captured by a growing variety of tools and devices.
Capture and monitoring devices and apps: Novel solutions are continuously becoming available to capture information both actively (requested of the patient and caregivers) and passively (automatically detected by sensors).
Connectivity and network management: In addition to the plethora of apps and devices, connecting patients to clinical and non-clinical staff is finally coming of age. While adoption among hospitals is still low, it is on everyone’s “shopping list. In fact, an executive survey from Becker Hospital Review shows that Interoperability, patient-provider connectivity, and patient engagement are among the top 3 priorities for Healthcare CIOs in 2019.
Engagement platforms and channels: This is still a huge weakness in healthcare service organizations. LHS growth and scale only works if patients are engaged, and according to a Deloitte report the variance in patient satisfaction levels today is pronounced.
Artificial Intelligence (AI) and Machine Learning (ML): ML, deep neural networks and natural language are examples of processes that are used to mine data at volumes that humans alone couldn’t possibly handle. These processes are used to identify correlations between data otherwise undetectable and to emerge real-time insights based on empirical data. Examples of AI assistance include front line interventions, pathway decision support, workflow automation, drug discovery, patient safety surveillance, image interpretation, and clinical research as a care option (CRAACO).
Clinical workflow enhancement: A learning health system would not be an LHS without changes in care plans, guidelines, and workflows. While EHRs provide a data backbone, enhancement of workflow is often a complicated and time-consuming process. This has created an opportunity to use EHR-compatible platforms that focus on an iterative and integrated approach instead.
What will it take to deploy an ecosystem approach?
Now that we’ve painted a picture of Digital Heaven, where technology works in harmony with the Quadruple Aim. We need to be realistic about how a learning health system future can come to pass. It will take the following:
Policies that support innovation: HIPAA and HITECH are no longer the big influencers, though HIPAA needs a serious revisit. Policies going forward (both government and enterprise) must favor a future where privacy and portability co-exist.
Collaboration with scientific leaders and pioneers: Not all science is developed in health systems. Solutions should be co-developed with transparent methods that create multi-party business value and complementarity.
Collaboration with agile startups: It is no accident that the tech giants of today were the startups of yesteryear. It is therefore imperative to be able to find the signal through the noise and use a “portfolio” approach to working with startups. Hospitals are already inundated with point solutions that need more disciplined governance.
Patient-centric care delivery development: While it is easy to forget that the purpose is to personalize care for an individual, it is both possible and imperative to use human-centered methods in every part of the learning process. A great example of this is the Stanford’s Human wide Pilot.
Culture of learning and critical thinking: Adjustments to shifting technology, market, and ecosystem learnings are the point of a learning health system. Leaders must experiment and adapt in short time frames. To scale, decisions must be based on both negative and positive learnings with a culture that thinks big, starts small, and shares knowledge.
According to a publication by Norman Sartorius MD, over the past two decades, the prevalence of comorbid mental and physical diseases have increased dramatically, reaching epidemic proportions in many countries. More than ever, clinicians need to address care delivery more holistically. The use of digital “point solutions” focused on a single condition or ailment are not moving the outcome needle at a systemic level.
The vision for a LHS may not have been rooted in policy, technology or collaboration. Implementing an LHS that builds on clean data, integrated analysis and commonly validated treatment guidelines is not trivial. Nor will it bear fruit overnight. However, it does provide a compelling vision for how clinical fundamentals can be matched with a digital ecosystem to deliver transformational change at the system and “front line” levels.
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