Identifying Hotspots of Chronic Non-malignant Pain in Orlando, Florida

Abstract

Chronic pain (CP) is a biopsychosocial condition and is one of the most prevalent yet underestimated diagnoses in the world. A reported 50 million people in 2016 experienced CP in the United States, and this number continues to grow exponentially in subgroup variations, such as high-impact CP, which accounts for an additional 19.6 million individuals. A more specific category of CP, chronic non-malignant pain (CNMP), affects 20% of the world’s population. Collectively, CNMP has reduced quality of life, increased debilitating outcomes, and has cost the healthcare system billions of dollars every year. Though the prevalence of CP is well-established globally and nationally, the literature does not identify prevalence of more specific subsets, such as high-impact or non-malignant pain. Furthermore, there is a gap in the literature for CNMP in Orlando, Florida. Therefore, this scholarly project extrapolated existing national data of CP from the Center for Disease Control and Prevention (CDC) and, using a geographical information system (GIS), identified clusters of specific demographics related to CNMP in the Orlando community like sex, age, race, and a household income of less than 100% of the federal poverty line. Utilizing a geographic information system (GIS) we used K-means, empirical bayesian kriging (EBK), and the Getis Ord-Gi statistic to predict rates of clustering of CNMP populations within a 30-minute drive time of AdventHealth hospital main campus in Orlando, separated by census tracts. Hot spots concentrated on the northwest Apopka region due to the population having the highest risk factors for CNMP; being at or below 100% the federal poverty line and age greater than 44 years old. Such statistics can guide the development of health care strategies to appropriately address this debilitating disease and minimize health costs.

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Keywords

Chronic pain, chronic non-malignant pain, high-impact chronic pain

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