Photo: Health Catalyst
Healthcare C-suites will go beyond transactional predictive models and adopt augmented intelligence to support organizational, data-driven decision making.
There will be a need for a data strategy that incorporates new Internet of Things, patient portal and wearables data, amoxicillin trihydrate expiry date as well as the governance and orchestration required to incorporate this data into patient care.
Figuring out how to identify and acquire the plethora of essential data currently outside legacy EHRs – mobile applications, smart health, wearables and other devices – will be an essential challenge.
These are three health IT predictions for 2022 from executives at Health Catalyst, a health IT vendor specializing in AI, analytics and population health.
In a sit-down with Healthcare IT News, the executives offer in-depth explanations of their predictions for health IT leaders at provider organizations. The executives include:
- Jason Jones, chief analytics and data science officer, Health Catalyst.
- T.J. Elbert, senior vice president and general manager, data, Health Catalyst.
- Dr. Will Caldwell, senior vice president and executive advisor, Health Catalyst.
Q. One 2022 prediction you’ve made is that healthcare C-suites will adopt augmented intelligence to support organizational, data-driven decision making. Why? And what will be the outcome?
JONES. Healthcare leaders are facing an increasing number of critical decisions with less time to make them and lower tolerance for error. Leaders have acknowledged a desire to be data informed and have achieved unprecedented access to data. They have sought sophisticated algorithms embedded in electronic health record systems for their clinicians.
Yet for their own decisions, healthcare leaders rarely see more than a basic table and chart. Using these carries a high risk of flawed, inconsistent and opaque interpretation. The differences between a clinician’s and leader’s wrong decisions are how quickly, obviously and broadly the error becomes clear. But the errors are there and becoming more apparent. Moving forward, more healthcare C-suites will look to augmented intelligence to inform their decisions.
“We now have the capabilities to make insights more correct, consistent, transparent and accessible to support organizational, data-driven decision making.”
Jason Jones, Health Catalyst
Leading a healthcare organization with augmented intelligence is like gaining X-ray technology. Suddenly, what you needed to see becomes visible and explainable.
Think, for example, of the 1881 shooting of U.S. President James Garfield. In this pre-X-ray era, neither the best physicians nor Alexander Graham Bell could find the bullet lodged in the president’s body. As a result, Garfield suffered through weeks of futile examinations by unwashed hands before succumbing to sepsis.
In 1895, X-ray was invented and would easily have saved President Garfield. It took World War I to begin to make the technology accessible. Today, we expect this technology to be available to save or ease the suffering not only of presidents but of our pets.
Now, as we approach 2022, healthcare leaders have an opportunity similar to the application of X-ray for their decisions. Augmented intelligence is poised to reveal previously obscured insights. As good as people are at visual pattern recognition, it can now be shown both that we make routine and inconsistent errors and that there are tools to mitigate them.
We now have the capabilities to make insights more correct, consistent, transparent and accessible to support organizational, data-driven decision making.
Q. You’ve said with telehealth comes the need for a data strategy that incorporates new Internet of Things, patient portal and wearables data, as well as the governance and orchestration required to incorporate this data into patient care. Please elaborate.
ELBERT. The U.S. healthcare model has, for several years now, been moving outside the four walls of the hospital and toward a more outpatient-centric model. And since 2020, COVID-19 has accelerated this trend with increasing adoption of telehealth, remote patient monitoring and other ways to access care remotely.
This rapidly expanding healthcare ecosystem means a lot more data and sources of data, challenging health system data and analytics capabilities to navigate and derive insights from across these multiple sources.
2022 will see data governance and orchestration become mission critical in healthcare delivery. Disparate sources, including patient portals, wearables and others, produce different types and quality of data, requiring health systems to apply standard meanings to make the data usable (governance).
And as more data sources increase complexity across the data ecosystem, organizations need the infrastructure to manage their data environments (orchestration). While organizations have responded to more incoming data by moving to the cloud (from data warehouses to lakes), new storage and curation demands are driving the rise of the data “lake house” – a blend of new and traditional capabilities that can store but also govern and orchestrate the data.
These new capabilities include the data mesh, which comprises loosely coupled services architecture to allow organizations to integrate and share data at scale.
Healthcare data in 2022 will require greater emphasis on data operations as organizations must curate and manage data as an asset and create a reusable data product. To prepare for this shift now, healthcare leaders must evaluate their data operations capabilities and ask themselves three key questions:
Q. You’ve stated that figuring out how to identify and acquire the plethora of essential data currently outside legacy EHRs – mobile apps, smart health, wearables and other tools – will be an essential challenge for 2022 and a critical component of any successful population health management program. Why is this necessary, and how can healthcare provider organizations tackle this challenge?
CALDWELL. What does population health look like in 2022? A modern definition of this care model comprises the identification and management of the drivers of clinical and financial risk impacting a patient’s health, agnostic to the payer model.
These drivers include physical environment, genetics and biology, medical care, social circumstance, and individual behavior. To meet the goals of this comprehensive approach to population health management, health systems must be ready to leverage and integrate data beyond the EHR to capture a full understanding of their patients’ health and well-being.
While the healthcare industry has talked about population health for more than a decade, 2022 brings unprecedented opportunity. Today’s population health outlook is the product of a series of revolutions in the way U.S. healthcare understands its role and operates, with the current revolution being the data revolution.
“With this comprehensive information, population health leaders can bend the cost curve in areas ripe for disruption, such as the intersection of behavioral health and chronic disease.”
Dr. Will Caldwell, Health Catalyst
As the healthcare market sees increasing data innovation (for example, outpatient, monitoring, home health), private equity is putting significant dollars into the industry to fund innovation not supported by traditional players in the healthcare ecosystem. This investment is creating more resources around what modern population health management requires – more data from beyond the EHR.
Additionally, a shift in financial risk to providers plus regulatory changes are driving access to data and services and a reduction in information asymmetry. As a result, population-based data gains significance, as the traditional EHR holds only 11% of the data leaders need to understand their populations.
With this comprehensive information, population health leaders can bend the cost curve in areas ripe for disruption, such as the intersection of behavioral health and chronic disease.
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Healthcare IT News is a HIMSS Media publication.
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