The population of patient is typically defined by who has already been seen for care. These systems often use the patient registries in their EMRs to define the population of patient. Also, base their analysis on current diagnoses or self-identified demographics.
However, there is a better way of using GIS location technology and supporting data sources that may be especially useful for ACOs and other organizations concerned with managing population health.
A more accurate approach would be to first objectively define the geography within which the health system operates. Secondly, to define the subsequent population belonging to that overall service area. This is known as network coverage optimization. It offers a more robust way to define boundaries and identify populations.
As the geography-based care population is well defined, value-based strategies, such as disease cohort underwriting or at-risk contracting, become more realistic. Within a speedily changing healthcare market, it makes sense to leverage location analytics for more robust strategic assessments for healthcare systems.
A healthcare organization of all kinds should use GIS location technology to clearly define patient populations and determine sound strategies and decisions.
Determining Adequate Service Coverage
One simple approach to measure adequate service coverage across population density is to envision access times for various healthcare facilities.
To better measure the overall viability of this health system, a network coverage score can be calculated using zip code and population-based statistics. This score represents a system’s enrolled patients as compared to the total population. This type of scoring could also be used to compare health systems in various locations.
Optimized Service Area Boundaries result in an improved understanding for Population Health Management Strategy.
How Does ACOs Benefit from GIS Technology?
• ACOs derive a better understanding of their enrolled patients and eligible payer groups, using GIS-powered analytics to define their patient populations.
• A strategic population analysis coupled with the novel visualizations can yield better decisions in population health management, leading to enhancing quality and lowered cost, both imperative for ACOs to thrive.
• GIS location technology can be used to easily identify objective service area boundaries relevant to a specific healthcare system. This automated method of defining the service area also identifies the exact population for which health coverage is currently provided. The Population characteristics from several external source data are also leveraged.