{"id":545342,"date":"2024-10-04T14:35:45","date_gmt":"2024-10-04T14:35:45","guid":{"rendered":"https:\/\/uat.esri.com\/en-us\/industries\/blog\/?post_type=blog&p=545342"},"modified":"2024-10-04T14:52:53","modified_gmt":"2024-10-04T14:52:53","slug":"trends-in-health-gis-mapping-healthcare-accessibility","status":"publish","type":"blog","link":"https:\/\/www.esri.com\/en-us\/industries\/blog\/articles\/trends-in-health-gis-mapping-healthcare-accessibility","title":{"rendered":"Trends in Health GIS: Mapping Healthcare Accessibility"},"content":{"rendered":"

How GIS Identifies and Fills Gaps in Healthcare Networks<\/strong><\/h2>\n\n

Welcome to the second of four blogs in my Trends in Health GIS series.<\/strong> If you missed the first blog<\/a>, the focus was on applying GIS to the ongoing opioid crisis. Today, we focus on the critical challenge of ensuring equitable access to quality healthcare services. Whether in urban or rural areas, disparities in healthcare accessibility continue to impact patient outcomes, with geography often serving as a barrier to timely care. It makes sense that if geography is part of the problem, then GIS should be part of the solution.

The Foundation: Why Healthcare Accessibility Matters<\/b><\/p><\/p>\n\n

Access to healthcare is not just a convenience\u2014it is a known determinant of health. Studies have shown that individuals with better access to healthcare experience lower rates of preventable diseases and improved overall health outcomes. Conversely, lack of access leads to delayed treatment, increased hospitalizations, and higher mortality rates. As healthcare services consolidate and move increasingly into virtual formats like telehealth, understanding how to maintain and expand accessibility has never been more vital. Here are some of the trends in healthcare accessibility as I see them:<\/p>\n\n

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GIS provides a powerful platform to address these challenges by offering spatial insights into where healthcare services are located, who can reach them, and what barriers prevent people from accessing the care they need.<\/p>\n\n

The Basics of Calculating Access to Care<\/strong><\/h2>\n\n

Let\u2019s start with what is probably the most foundational component of this field, calculating an individual\u2019s access to a healthcare provider. Not so long ago, the calculation of access was quite coarse, using Euclidean (straight-line) distances to estimate levels of accessibility. Worse yet, the distances weren\u2019t even calculated from a person\u2019s residence, they were most often calculated using a person\u2019s ZIP Code centroid. Without employing an accurate road network that accounts for traffic and geographic barriers, like mountains or bodies of water, it\u2019s impossible to advance beyond travel distance to the more important metric of travel time. Furthermore, the legacy method compounds errors in the access calculations and therefore can completely mask access disparities \u2013 the very thing the calculations were meant to overcome.<\/p>\n\n

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A health plan member\u2019s address is represented as the centroid of their ZIP Code. From there, a straight line is drawn to the provider location. In this case, the travel distance is 2.5 miles.<\/figcaption><\/figure>\n\n
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The health plan member actually lives closer to the edge of their ZIP Code. Therefore, their travel is 25% farther than the calculation representing their individual access to care.<\/figcaption><\/figure>\n\n
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With an accurate road network and geographic context, we can clearly see how previous methods of convenience significantly distort the truth. In this case, the health plan member travels 6.2 miles to get to care, 148% longer than their calculated access. And because they must cross a busy bridge, the travel time along the road network is 20 minutes.<\/figcaption><\/figure>\n\n