Applying Geospatial Analysis to Population Health

Posted on June 28, 2016 I Written By

John Lynn is the Founder of the blog network which currently consists of 10 blogs containing over 8000 articles with John having written over 4000 of the articles himself. These EMR and Healthcare IT related articles have been viewed over 16 million times. John also manages Healthcare IT Central and Healthcare IT Today, the leading career Health IT job board and blog. John is co-founder of and John is highly involved in social media, and in addition to his blogs can also be found on Twitter: @techguy and @ehrandhit and LinkedIn.

This post is sponsored by Samsung Business. All thoughts and opinions are my own.

Megan Williams wrote a very interesting piece called “Geospatial Analysis: The Next Era of Population Health” in which she highlighted Kaiser’s efforts to use geospatial analysis as part of their population health efforts. Here’s her description of their project:

This means using data to inform policy adjustments and create intervention programs that lead to meaningful change. One of the best examples of this lies with healthcare giant Kaiser Permanente. In April, they launched a database that gave researchers the ability to examine patient DNA and bump it against behavioral and environmental health factors. The goal of the project is to pull information from half a million patients and use it to build one of the most “diverse repositories of environmental, genetic and health data in the world,” which could then be used to inform research around conditions including diabetes and cancer and their relationships to issues including localized violence, pollution, access to quality food and other factors.

This type of effort from Kaiser is quite incredible and I believe will truly be part of the way we shift the cost curve on healthcare costs. One challenge to this effort is that Kaiser has a very different business model than the rest of the healthcare system. They’re in a unique position where their business benefits from these types of population health efforts. Plus, Kaiser is very geographically oriented.

While Kaiser’s business model is currently very different, one could argue that the rest of healthcare is moving towards the Kaiser model. The shift to value based care and accountable care organizations is going to require the same geospatial analysis that Kaiser is building out today. Plus, hospital consolidation is providing real geographic dominance that wasn’t previously available. Will these shifting reimbursement models motivate all of the healthcare systems to care about the 99% of time patients spend outside of our care? I think they will and large healthcare organizations won’t have any choice in the matter.

There are a number of publicly and privately available data stores that are going to help in the geospatial analysis of a population’s health, but I don’t believe that’s going to be enough. In order to discover the real golden insights into a population, we’re going to have to look at the crossroads of data stores (behavioral, environmental, genomic, etc) combined together with personal health data. Some of that personal health data will come from things like EHR software, but I believe that the most powerful geospatial personal health data is going to come from an individual’s cell phone.

This isn’t a hard vision to see. Most of us now carry around a cell phone that knows a lot more about our health than we realize. Plus, it has a GPS where all of those actions can be plotted geospatially. Combine this personally collected health data with these large data stores and we’re likely to get a dramatically different understanding of your health.

While this is an exciting area of healthcare, I think we’d be wise to take a lesson from “big data” in healthcare. Far too many health systems spent millions of dollars building up these massive data warehouses of enterprise health data. Once they were built, they had no idea how to get value from them. Since then, we’ve seen a shift to “skinny data” as one vendor called it. Minimum viable data sets with specific action items tied to that data.

We should likely do the same with geospatial data and population health and focus on the minimum set of data that will provide actual results. We should start with the skinny data that delivers an improvement in health. Over time, those skinny data sets will combine into a population health platform that truly leverages big data in healthcare.

Where do you see geospatial data being used in healthcare? Where would you like to see it being used? What are the untapped opportunities that are waiting for us?

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