Three experts from Health Catalyst, a provider of AI, analytics, and population health IT, present their forecasts, which can help CIOs and other health leaders plan for the year ahead.
To enhance corporate, data-driven decision-making, healthcare C-suites will move beyond transactional predictive models and use augmented intelligence.
A data strategy that combines new Internet of Things, patient-portal, and wearables data, as well as the governance and orchestration needed to integrate this data into patient care, will be necessary.
The problem will be identifying and obtaining the wealth of vital data currently available outside of conventional EHRs — mobile applications, smart health, wearables, and other devices.
Three executives from Health Catalyst, a health IT company focusing on AI, analytics, and population health, have made three health IT predictions for 2022.
The CEOs give in-depth explanations of their projections for health IT leaders at provider organizations in an interview with Healthcare IT News. Among the executives are:
- Health Catalyst’s chief analytics and data science officer, Jason Jones.
- T.J. Elbert, Health Catalyst’s senior vice president and general manager of data.
- Dr. Will Caldwell, Health Catalyst’s senior vice president and executive advisor.
Q. Healthcare C-suites will employ augmented intelligence to assist corporate, data-driven decision-making, according to one of your 2022 predictions. Why? And what will the result be?
JONES. Healthcare executives are faced with a growing number of crucial decisions to make, with less time to do so and a decreasing tolerance for mistakes.
Leaders have expressed a desire to be data-driven and have gained unparalleled access to information. For their clinicians, they’ve been looking for advanced algorithms built-in electronic health record systems.
Healthcare leaders, on the other hand, rarely see anything more than a simple table and chart while making their own decisions.
When these are used, there is a great danger of erroneous, inconsistent, and obfuscated interpretation.
The difference between a clinician’s and a leader’s bad decisions is how quickly, clearly, and widely the error is revealed.
But the flaws are there, and they’re becoming more obvious. More healthcare C-suites will rely on augmented intelligence to guide their judgments in the future.
Having augmented intelligence to lead a healthcare company is like having X-ray technology. Suddenly, everything you needed to see is apparent and understandable.
Consider the assassination of US President James Garfield in 1881.
Neither the greatest physicians nor Alexander Graham Bell could discover the bullet stuck in the president’s body in this pre-X-ray age.
As a result, Garfield endured weeks of useless dirty hand inspections before succumbing to sepsis.
The invention of the X-ray in 1895 would have easily rescued President Garfield.
It required World War I to make the technology widely available.
We anticipate this technology to be accessible now to save or alleviate the pain of our dogs as well as our presidents.
Now, as we approach 2022, healthcare professionals have an opportunity to make judgments in a similar way to how X-rays were used in the past.
Augmented intelligence has the potential to disclose previously hidden information.
It can now be demonstrated that no matter how proficient.
We are at visual pattern recognition, we make routine and inconsistent errors, and that there are techniques to reduce these errors.
To assist corporate, data-driven decision-making, we now can make insights more accurate, consistent, visible, and accessible.
Q. As you mentioned, telehealth necessitates a data strategy that combines the new Internet of Things, patient portal, and wearables data, as well as the governance and orchestration needed to integrate this data into patient care. Please provide more information.
ELBERT. For several years, the American healthcare paradigm has been shifting away from the hospital and toward a more outpatient-centric model.
COVID-19 has accelerated this trend since 2020, with increased usage of telehealth, remote patient monitoring, and other remote care access methods.
This rapidly expanding healthcare ecosystem means a lot more data and data sources, making it difficult for data and analytics skills in health systems to traverse and derive insights from these disparate sources.
Data governance and orchestration will become mission crucial in healthcare delivery by the year 2022.
Different forms and quality of data are produced by many sources, including patient portals, wearables, and others, necessitating health systems to apply standard definitions to make the data meaningful (governance).
Organizations require infrastructure to manage their data environments as more data sources raise the complexity of the data ecosystem (orchestration).
While corporations have moved to the cloud (from data warehouses to lakes) in response to more incoming data, new storage and curation demands are fueling the creation of the data “lake house” – a hybrid of new and conventional capabilities that can store, regulate, and orchestrate data.
The data mesh is one of the new capabilities, which consists of a loosely linked services architecture that enables businesses to integrate and share data at scale.
Organizations must curate and manage data as an asset and develop a reusable data product in 2022, which will necessitate a stronger focus on data operations.
Now is the time for healthcare leaders to assess their data operations skills and ask themselves three essential questions:
- What data-tech plan do we have in place to help us achieve this transition?
- How does our data mesh appear?
- What personnel and processes will we require?
Q. You’ve indicated that identifying and obtaining the multitude of crucial data currently outside legacy EHRs – mobile applications, smart health, wearables, and other tools – will be a key challenge for 2022 and a critical component of any successful population health management program. Why is this required, and how can healthcare providers deal with the problem?
CALDWELL. What will the state of population health be in 2022? A modern definition of this care model includes identifying and managing the clinical and financial risk drivers that affect a patient’s health, regardless of the payer model.
Physical environment, genetics and biology, medical care, social condition, and individual conduct are all factors.
To achieve the aims of this comprehensive population health management strategy, health systems must be prepared to use and integrate data outside of the EHR to gain a complete picture of their patient’s health and well-being.
While the healthcare sector has been talking about population health for more than a decade, the year 2022 presents a once-in-a-generation opportunity.
The current population health outlook is the result of a succession of revolutions in the way the United States’ healthcare system understands and operates, the most recent of which is the data revolution.
As the healthcare sector sees more data innovation (for example, outpatient, monitoring, and home health), private equity is pouring money into the business to fund innovation that isn’t backed by established companies.
Additional resources are being allocated to what modern population health management necessitates – more data from sources other than the EHR.
In addition, a shift in financial risk to providers – as well as regulatory reforms – is boosting data and service access and reducing information asymmetry.
As a result, population-based data becomes more important, as the standard EHR only holds 11% of the data that leaders need to understand their people.
Population health executives can use this extensive data to bend the cost curve in areas ripe for disruption, such as the junction of behavioral health and chronic disease.