Dr. Charles Macias is the Chief Clinical Systems Integration Office for Texas Children’s Hospital in Houston and a leading proponent of population health analytics. In his practice as an emergency room physician, Macias has seen first-hand the impact of population health and the potential it has to streamline workflows and improve outcomes. We recently sat down with him to discuss his views on population health analytics and where it is headed in the future.
Intel: What is your definition of population health analytics?
Macias: Population health analytics really refers to how an organization, or government, is addressing the healthcare issues of a population at large. While many people think of population health as an entire region, state or country, there’s variable definitions for how we could parse out one’s segment of a population. In my particular setting, for example, we service the pediatric population up to age 21. Our definition of population health is really about what’s happening to children.
Intel: In another blog you told the story of a young asthma patient. How does that experience years ago compare to today in terms of analytics?
Macias: From a population health perspective, in 2004, when that story took place, population health really wasn’t about population health; it was about treating single patients. That was a paper-based world. We had to depend on published research to understand something about the populations, and when you depend only on the published evidence, you’re assuming that somewhere out in this periphery of research you’re going to be able to translate it down to a population that looks like your own. So, if that direct connection doesn’t exist, if your population is very different, you’re at odds with what you’re really going to know about how to treat your population. Today, the story is very different. Today, we have electronic medical records. Today, we have an electronic data warehouse. We can store data and information about our populations. What used to take me six months to find out now can take about 24 hours thanks to updates in our enterprise data warehouse. I have the answer at my fingertips.
Intel: Today in your practice, how do analytics impact your workflow?
Macias: Analytics today has a completely different impact than it did on clinicians five years ago, 10 years ago, and certainly 20 years ago. Number one, it’s given us the understanding that the 800,000 medical articles that are out there that are essentially non-digestible bits of information. They can systematically be filtered into some kind of clinical standards that can be placed into the analytics and matched against the analytics to say this population parallels what this evidence is telling us and, therefore, this clinical standard should really interdigitate with that work and we should understand how that population fits in with that clinical standard. So, now we have the ability to use best practice alerts, health maintenance reminders, and create long term plans of care embedded directly within the medical record.
Intel: What’s your vision for the future of analytics?
Macias: My vision for analytics is in the world of decision support. It’s really about making clinicians’ workflow much smarter and quicker, and much easier. We already know that when we start a day, we have so many patients to see. In my setting I know I’m going to be overwhelmed with a number of patients in the emergency department. If there are ways to translate the work that’s ongoing, the workflow within the EMR to the kind of decision support that’s going to make prediction rules and strategies much easier, that’s going identify the patients at risk for bad outcomes and link them to the right strategies that will help obviate a need for much more escalated care in the future. That’s a win/win. As we begin to place resources against the value that’s given, I see a lot better alignment with where our healthcare infrastructure supports those strategies.
Intel: How do you work with Health Catalyst to get the information you need?
Macias: The role that Health Catalyst has had in our data governance has been critical to evolving to where we are as an organization. We have learned from how we look at populations of care and how we look at our approaches to merging the science of care with operational care process teams. Predictive analytics comes from how we house data in our enterprise data warehouse. It really goes beyond the EMR’s capability of doing bedside analytics; it’s about the bigger picture of integrating all of those critical domains to effectively improve outcomes. It would not have been possible without our partnership with Health Catalyst.