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BACKGROUND: The purpose of this work is to assess the current utilization patterns of telehealth for oncology care and identify opportunities for increased utilization for underserved regions. In order to accurately and efficiently obtain this information a national data extraction and analysis was required to better understand the current needs. Approximately 33% of veterans are considered to live in rural America. A significant proportion of cancer patients must travel long distances to access cutting-edge VA cancer care. Some VAMCs provide academic subspecialized oncology care including next generation sequencing (NGS), genetic counseling, opportunities to enroll in clinical trials, and world-renowned clinical expert consultation. These services are not conveniently accessible for veterans therefore requiring a program which supports access to all.
METHODS: Baseline assessment measurements were identified to understand resource supply, demand, and telehealth utilization needs. Data were extracted from VA’s CDW and VSSCs Service Analysis Services cubes. 15 data measures from 8 data sources were pulled for 141 VAMCs spanning in time period from FY18 to March FY20.
Cluster Analysis, k-means clustering method, were used to classify VAMCs into distinct groups to identify facilities with the highest needs for oncology telehealth services. The evolutionary solving method was used to find the minimum sum of squared estimate of errors (SSE) allowing a more diversified approach in cluster assignment. Three cluster analysis were performed which include a combination of three variables specific to oncology staffing, telehealth usage, patient rurality, and community care consults (CCC).
RESULTS: Results show that 30 (21%) VAMCs are categorized as high need for TeleOncology. These facilities have low staff support, high CCC, and low telehealth usage. Of these, 11 (37%) VAMCs have high percent of rural patients. Eleven (8%) of all VAMCs are categorized as having high staff support, low CCC, and high telehealth usage; good hub site candidates for the National TeleOncology Program.
CONCLUSION: VA is expanding the National TeleOncology Program to offer oncology services to underserved VAMCs and Veterans across the United States. Results of this analysis are being applied to determine where to prioritize telehealth services for oncology care and which sites may serve as hubs.
BACKGROUND: The purpose of this work is to assess the current utilization patterns of telehealth for oncology care and identify opportunities for increased utilization for underserved regions. In order to accurately and efficiently obtain this information a national data extraction and analysis was required to better understand the current needs. Approximately 33% of veterans are considered to live in rural America. A significant proportion of cancer patients must travel long distances to access cutting-edge VA cancer care. Some VAMCs provide academic subspecialized oncology care including next generation sequencing (NGS), genetic counseling, opportunities to enroll in clinical trials, and world-renowned clinical expert consultation. These services are not conveniently accessible for veterans therefore requiring a program which supports access to all.
METHODS: Baseline assessment measurements were identified to understand resource supply, demand, and telehealth utilization needs. Data were extracted from VA’s CDW and VSSCs Service Analysis Services cubes. 15 data measures from 8 data sources were pulled for 141 VAMCs spanning in time period from FY18 to March FY20.
Cluster Analysis, k-means clustering method, were used to classify VAMCs into distinct groups to identify facilities with the highest needs for oncology telehealth services. The evolutionary solving method was used to find the minimum sum of squared estimate of errors (SSE) allowing a more diversified approach in cluster assignment. Three cluster analysis were performed which include a combination of three variables specific to oncology staffing, telehealth usage, patient rurality, and community care consults (CCC).
RESULTS: Results show that 30 (21%) VAMCs are categorized as high need for TeleOncology. These facilities have low staff support, high CCC, and low telehealth usage. Of these, 11 (37%) VAMCs have high percent of rural patients. Eleven (8%) of all VAMCs are categorized as having high staff support, low CCC, and high telehealth usage; good hub site candidates for the National TeleOncology Program.
CONCLUSION: VA is expanding the National TeleOncology Program to offer oncology services to underserved VAMCs and Veterans across the United States. Results of this analysis are being applied to determine where to prioritize telehealth services for oncology care and which sites may serve as hubs.
BACKGROUND: The purpose of this work is to assess the current utilization patterns of telehealth for oncology care and identify opportunities for increased utilization for underserved regions. In order to accurately and efficiently obtain this information a national data extraction and analysis was required to better understand the current needs. Approximately 33% of veterans are considered to live in rural America. A significant proportion of cancer patients must travel long distances to access cutting-edge VA cancer care. Some VAMCs provide academic subspecialized oncology care including next generation sequencing (NGS), genetic counseling, opportunities to enroll in clinical trials, and world-renowned clinical expert consultation. These services are not conveniently accessible for veterans therefore requiring a program which supports access to all.
METHODS: Baseline assessment measurements were identified to understand resource supply, demand, and telehealth utilization needs. Data were extracted from VA’s CDW and VSSCs Service Analysis Services cubes. 15 data measures from 8 data sources were pulled for 141 VAMCs spanning in time period from FY18 to March FY20.
Cluster Analysis, k-means clustering method, were used to classify VAMCs into distinct groups to identify facilities with the highest needs for oncology telehealth services. The evolutionary solving method was used to find the minimum sum of squared estimate of errors (SSE) allowing a more diversified approach in cluster assignment. Three cluster analysis were performed which include a combination of three variables specific to oncology staffing, telehealth usage, patient rurality, and community care consults (CCC).
RESULTS: Results show that 30 (21%) VAMCs are categorized as high need for TeleOncology. These facilities have low staff support, high CCC, and low telehealth usage. Of these, 11 (37%) VAMCs have high percent of rural patients. Eleven (8%) of all VAMCs are categorized as having high staff support, low CCC, and high telehealth usage; good hub site candidates for the National TeleOncology Program.
CONCLUSION: VA is expanding the National TeleOncology Program to offer oncology services to underserved VAMCs and Veterans across the United States. Results of this analysis are being applied to determine where to prioritize telehealth services for oncology care and which sites may serve as hubs.