that’s low-salt and low-cholesterol and help you access healthy food. Indeed, that means that Sitipati and her colleagues are not only identifying individuals with chronic illness, such as hypertension, diabetes, or congestive heart failure; they are also connecting those individuals to micro-level community disease prevalence, and are working to help those individuals overcome structural barriers that can be uncovered through population-level and micro-community-level data analysis. Overall, Sitipati says, the technology is

available now to do everything that needs to be done in terms of population health- level data analytics (though she adds that there remains a “hassle factor” with some applications); the key challenges, once an organization reaches her organization’s level, become process-related. “Tech-quity is a hard one; how do you achieve technol- ogy access and literacy for all? And linguis- tic access—are we actually there? There are things we need to do on a health system side to make it work, and at the patient level. I think of my own mom who’s in her late 70s but has poor vision and mobility and has difficulty simply connecting her iPad to her TV—or my Spanish-speaking patient who has diabetes and may not have Wi-Fi at home, what does that mean to offer digital health? These are the things we need to talk about.”

Still, it’s clear that nothing is stopping

the leaders of pioneering patient care organizations around the country from moving ahead on countless fronts now. What’s clear is that the technology is adequate to do advanced data analytics for population health management, care management, clinical transformation, and operational optimization. Now, industry leaders agree, the challenges are strategic and operational. As Carl Dolezal, a principal at The Chartis Group, the Chicago-based consult- ing firm, puts it, “I think different organi- zations are pursuing different journeys. I work with many organizations on this. Those that are truly data-driven and really get value out of their analytics investment,

and formed a partnership around analytics. Strategic plan, clinical improvement, rapid response to COVID. You’ve got analytics sitting with you, and are engaging early in the process. Some organizations are still in a more transactional mode. Meaning, they sit at a table, ask analytics to help them with specific things.” That said, Dolezal adds that “We’re in a transition period, where organizations are moving from a transactional model to a more consultative model, where analyt- ics is at the table working to help solve the problems. They’re an active part of the solution.”

Let a thousand flowers bloom The very heterogeneity of the analytics initiatives taking place in patient care organizations across the country speaks to the energy and commitment being demonstrated by leaders in the field right now. Among the countless efforts evolving forward:

At the 40-hospital, $23 billion UPMC health system in Pittsburgh, chief health-

moving forward, Marroquin says, “The clinicians are beginning to understand why there are differences in outcomes among some of the patients. Why are some patients doing very well in managing their hemoglobin a1c, as compared to others, for whom their hemoglobin a1c is more dif- ficult to control? Is it because of social issues? Access to care? Other fac- tors? A little bit of everything? We’re using a lot of tools that can allow our clinicians to

Michael Kelleher, M.D.

visualize the data, so that they can start to understand some of the nuances, to bet- ter understand the population—from their baselines all the way to their outcomes. And from that, one can generate hypoth- eses: what are the predictors of not having your hemoglobin a1c in control? or who are the chronic kidney disease patients who suddenly require urgent dialysis without

“The clinicians are beginning to understand why there are differences in outcomes among some of the patients. We’re using a lot of tools that can allow our clinicians to visualize the data, so that they can start to understand some of the nuances.” —Oscar Marroquin, M.D.

care data and analytics officer Oscar Marroquin, M.D. reports that he and his colleagues are involved in a comprehen- sive effort to analyze the populations of patients the system is caring for, who have either diabetes or chronic kidney disease. Dr. Marroquin and his team are helping cli- nician leaders to work to understand how many patients of each type are being seen in a given year, how often, how comorbid they are, their ages, what medications they’re on, and in what settings (i.e., in-per- son versus telehealth). As the initiative is

“We’re now dealing with much more information, and it has to be defined and formatted, to create that insight. I think that

interoperability, right out, is still a challenge.” —Carl Dolezal


warning? And when we identify that there are some populations that behave that way, they’re asking how we can intervene more proactively” to improve those patients’ outcomes.

At the Palo Alto, Calif.-based Nines Radiology, a 12-radiologist practice that is also affiliated with Nines Inc., a radiology information solutions company, president Michael Kelleher, M.D. and his fellow radi- ologists are applying artificial intelligence (AI) to a range of challenges in radiology practice, beginning with optimizing how radiological studies are developed and resolved. “What we’re doing,” Dr. Kelleher says, “is that we’re using AI-based algorithms to detect when studies have incomplete information that the radiologist won’t be able to read, and then that’s being directed to the reading-room assistants to prepare the study to be read. And that’s had a really huge impact on our ability to be efficient.” With around 15-20 percent

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