Mapping and clinical data collide, and the result is a new way to incorporate location into the patient care experience.
Ed Hess, Health IT Outcomes
When Esri holds a conference, it’s little wonder that it’s going to focus on geography. That the conference was targeted at the healthcare space, however, made the focus of geography much more interesting. It’s not typically a talking point when hospitals discuss patient care, engagement, and wellness strategies. According to the GIS (geographic information system) mapping software provider, this is a mistake. At the three-day conference in Colorado Springs, healthcare providers offered ways in which GIS data has already impacted patient care and how its influence will grow in future decisions. There were some additional themes that emerged throughout the event.
- Can you really manage a patient population without considering – and using – GIS technology? For Esri, the answer is an obvious – “No.” But, even less-biased observers would have to concede that patient care and wellness are strongly influenced by patient geography. Clinical and geographic data is a powerful combination. And layering in social and environmental data increases the value to levels that are tough to explain.
- Clinicians need to understand the concept of “place” with regard to patient care. At the conference, place was referred to as another vital sign – on the same level as body temperature, blood pressure, and pulse. Researchers have already made this connection. Clinicians need to as well. Doctors already gather anecdotal geographic evidence as they treat patients. (“It seems like this is the third patient this week from the same neighborhood with similar symptoms.”) GIS technology allows clinicians to confirm or refute their hunches. When place is a vital sign, it opens up added dimensions to patient care.
- You’d love to be able to find a cause and effect behind the combination of clinical and GIS data. More than likely, however, you’ll have to settle for correlations. For example, you might find that readmission rates are higher for neighborhoods beyond a certain distance from a hospital. Or you discover that obesity rates are lower than expected for a specific neighborhood. You might not ever know why this is the case. Correlating this data, however, allows you to develop and test intervention strategies that impact care.
- Everyone knows the old chestnut, “A picture is worth a thousand words.” A lesser-known dictum is, “A map is worth a thousand questions.” (To be fair, I can’t imagine hearing that outside of a GIS conference.) It’s hard to look at a GIS map of a given area and not immediately ask questions. Why is there a hot spot here? Why is this neighborhood different from that one? Why do these patient groups respond differently? The point of GIS data and mapping technology isn’t necessarily to answer questions. It’s really about the ability to ask them.
- The concept of “One Health” is worth your time to understand. Visually, it’s a Venn diagram with three data sets – human health, environmental health, and animal health. The overlap of those three data sets is where One Health lives. Effective population health management and wellness programs have to consider all three of these data sets, as each one is influenced by the other. And, of course, geography underpins the health of each group – humans, animals, and then environment.
- The first step to leveraging clinical data relative to geography is to geocode your EHRs – essentially, getting patient addresses from their respective EHRs onto a map. Simple enough? Far from it. Some patients don’t want to give an accurate address. Others don’t have a permanent address. Some live with relatives. And, sometimes, addresses are simply entered inaccurately. Additionally, there is no standard for how EHR vendors capture address data. So that’s not especially helpful to the cause. Regardless of the reason, inaccurate patient address information dramatically impacts any effort related to geography. You need to have a plan in place to improve the accuracy of your front-end data collection and entry or ways to mitigate the problem as you’re looking at results.
