Andrew K Smith1, Nawar M Shara2, Alexander Zeymo3, Katherine Harris1, Randy Estes3, Lynt B Johnson4, Waddah B Al-Refaie5. 1. Department of Surgery, Georgetown University Hospital, Washington, DC; MedStar-Georgetown Surgical Outcomes Research Center, Georgetown University Hospital, Washington, DC; Department of Biostatistics and Bioinformatics, MedStar Health Research Institute, Hyattsville, MD. 2. MedStar-Georgetown Surgical Outcomes Research Center, Georgetown University Hospital, Washington, DC; Department of Biostatistics and Bioinformatics, MedStar Health Research Institute, Hyattsville, MD; The Georgetown-Howard University Center for Clinical and Translational Science, Washington, DC. 3. Department of Biostatistics and Bioinformatics, MedStar Health Research Institute, Hyattsville, MD. 4. Department of Surgery, Georgetown University Hospital, Washington, DC; MedStar-Georgetown Surgical Outcomes Research Center, Georgetown University Hospital, Washington, DC; Department of Biostatistics and Bioinformatics, MedStar Health Research Institute, Hyattsville, MD; Lombardi Comprehensive Cancer Center, Georgetown University Hospital, Washington, DC. 5. Department of Surgery, Georgetown University Hospital, Washington, DC; MedStar-Georgetown Surgical Outcomes Research Center, Georgetown University Hospital, Washington, DC; Department of Biostatistics and Bioinformatics, MedStar Health Research Institute, Hyattsville, MD; Lombardi Comprehensive Cancer Center, Georgetown University Hospital, Washington, DC. Electronic address: Waddah.B.Al-Refaie@gunet.georgetown.edu.
Abstract
BACKGROUND: Regionalization of complex surgeries has increased patient travel distances possibly leaving a substantial burden on those at risk for poorer surgical outcomes. To date, little is known about travel patterns of cancer surgery patients in regionalized settings. To inform this issue, we sought to assess travel patterns of those undergoing a major cancer surgery within a regionalized system. MATERIALS AND METHODS: We identified 4733 patients who underwent lung, esophageal, gastric, liver, pancreatic, and colorectal resections from 2002-2014 within a multihospital system in the Mid-Atlantic region of the United States. Patient age, race and/or ethnicity, and insurance status were extracted from electronic health records. We used Geographical Information System capabilities in R software to estimate travel distance and map patient addresses based on cancer surgery type and these characteristics. We used visual inspection, analysis of variance, and interaction analyses to assess the distribution of travel distances between patient populations. RESULTS: A total of 48.2% of patients were non-white, 49.9% were aged >65 y, and 54.9% had private insurance. Increased travel distance was associated with decreasing age and those undergoing pancreatic and esophageal resections. Also, black patients tend to travel shorter distances than other racial and/or ethnic groups. CONCLUSIONS: These maps offer a preliminary understanding into variations of geospatial travel patterns among patients receiving major cancer surgery in a Mid-Atlantic regionalized setting. Future research should focus on the impact of regionalization on timely delivery of surgical care and other quality metrics.
BACKGROUND: Regionalization of complex surgeries has increased patient travel distances possibly leaving a substantial burden on those at risk for poorer surgical outcomes. To date, little is known about travel patterns of cancer surgery patients in regionalized settings. To inform this issue, we sought to assess travel patterns of those undergoing a major cancer surgery within a regionalized system. MATERIALS AND METHODS: We identified 4733 patients who underwent lung, esophageal, gastric, liver, pancreatic, and colorectal resections from 2002-2014 within a multihospital system in the Mid-Atlantic region of the United States. Patient age, race and/or ethnicity, and insurance status were extracted from electronic health records. We used Geographical Information System capabilities in R software to estimate travel distance and map patient addresses based on cancer surgery type and these characteristics. We used visual inspection, analysis of variance, and interaction analyses to assess the distribution of travel distances between patient populations. RESULTS: A total of 48.2% of patients were non-white, 49.9% were aged >65 y, and 54.9% had private insurance. Increased travel distance was associated with decreasing age and those undergoing pancreatic and esophageal resections. Also, black patients tend to travel shorter distances than other racial and/or ethnic groups. CONCLUSIONS: These maps offer a preliminary understanding into variations of geospatial travel patterns among patients receiving major cancer surgery in a Mid-Atlantic regionalized setting. Future research should focus on the impact of regionalization on timely delivery of surgical care and other quality metrics.
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