M J D'Souza, D Wentzien, R Bautista, J Santana, M Skivers, S Stotts, F Fiedler
{"title":"数据密集型本科研究项目通知推进医疗保健分析。","authors":"M J D'Souza, D Wentzien, R Bautista, J Santana, M Skivers, S Stotts, F Fiedler","doi":"10.1109/SPMB.2018.8615591","DOIUrl":null,"url":null,"abstract":"<p><p>The overarching framework for incorporating informatics into the Wesley College (Wesley) undergraduate curriculum was to teach emerging information technologies that prepared undergraduates for complex high-demand work environments. Federal and State support helped implement Wesley's undergraduate Informatics Certificate and Minor programs. Both programs require project-based coursework in Applied Statistics, SAS Programming, and Geo-spatial Analysis (ArcGIS). In 2015, the <i>State of Obesity</i> listed the obesity ranges for all 50 US States to be between 21-36%. Yet, the Center for Disease Control and Prevention (CDC) mortality records show significantly lower obesity-related death-rates for states with very high obesity-rates. This study highlights the disparities in the reported obesity-related death-rates (specified by an ICD-10 E66 diagnosis code) and the obesity-rate percentages recorded for all 50 US States. Using CDC mortality-rate data, the available obesity-rate information, and ArcGIS, we created choropleth maps for all US States. Visual and statistical analysis shows considerable disparities in the obesity-related death-rate record-keeping amongst the 50 US States. For example, in 2015, Vermont with the sixth lowest obesity-rate had the highest reported obesity-related death-rate. In contrast, Alabama had the fifth highest adult obesity-rate in the nation, yet, it had a very low age-adjusted mortality-rate. Such disparities make comparative analysis difficult.</p>","PeriodicalId":91431,"journal":{"name":"... IEEE Signal Processing in Medicine and Biology Symposium (SPMB). IEEE Signal Processing in Medicine and Biology Symposium","volume":"2018 ","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1109/SPMB.2018.8615591","citationCount":"7","resultStr":"{\"title\":\"Data-intensive Undergraduate Research Project Informs to Advance Healthcare Analytics.\",\"authors\":\"M J D'Souza, D Wentzien, R Bautista, J Santana, M Skivers, S Stotts, F Fiedler\",\"doi\":\"10.1109/SPMB.2018.8615591\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>The overarching framework for incorporating informatics into the Wesley College (Wesley) undergraduate curriculum was to teach emerging information technologies that prepared undergraduates for complex high-demand work environments. Federal and State support helped implement Wesley's undergraduate Informatics Certificate and Minor programs. Both programs require project-based coursework in Applied Statistics, SAS Programming, and Geo-spatial Analysis (ArcGIS). In 2015, the <i>State of Obesity</i> listed the obesity ranges for all 50 US States to be between 21-36%. Yet, the Center for Disease Control and Prevention (CDC) mortality records show significantly lower obesity-related death-rates for states with very high obesity-rates. This study highlights the disparities in the reported obesity-related death-rates (specified by an ICD-10 E66 diagnosis code) and the obesity-rate percentages recorded for all 50 US States. Using CDC mortality-rate data, the available obesity-rate information, and ArcGIS, we created choropleth maps for all US States. Visual and statistical analysis shows considerable disparities in the obesity-related death-rate record-keeping amongst the 50 US States. For example, in 2015, Vermont with the sixth lowest obesity-rate had the highest reported obesity-related death-rate. In contrast, Alabama had the fifth highest adult obesity-rate in the nation, yet, it had a very low age-adjusted mortality-rate. Such disparities make comparative analysis difficult.</p>\",\"PeriodicalId\":91431,\"journal\":{\"name\":\"... IEEE Signal Processing in Medicine and Biology Symposium (SPMB). IEEE Signal Processing in Medicine and Biology Symposium\",\"volume\":\"2018 \",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://sci-hub-pdf.com/10.1109/SPMB.2018.8615591\",\"citationCount\":\"7\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"... IEEE Signal Processing in Medicine and Biology Symposium (SPMB). 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Data-intensive Undergraduate Research Project Informs to Advance Healthcare Analytics.
The overarching framework for incorporating informatics into the Wesley College (Wesley) undergraduate curriculum was to teach emerging information technologies that prepared undergraduates for complex high-demand work environments. Federal and State support helped implement Wesley's undergraduate Informatics Certificate and Minor programs. Both programs require project-based coursework in Applied Statistics, SAS Programming, and Geo-spatial Analysis (ArcGIS). In 2015, the State of Obesity listed the obesity ranges for all 50 US States to be between 21-36%. Yet, the Center for Disease Control and Prevention (CDC) mortality records show significantly lower obesity-related death-rates for states with very high obesity-rates. This study highlights the disparities in the reported obesity-related death-rates (specified by an ICD-10 E66 diagnosis code) and the obesity-rate percentages recorded for all 50 US States. Using CDC mortality-rate data, the available obesity-rate information, and ArcGIS, we created choropleth maps for all US States. Visual and statistical analysis shows considerable disparities in the obesity-related death-rate record-keeping amongst the 50 US States. For example, in 2015, Vermont with the sixth lowest obesity-rate had the highest reported obesity-related death-rate. In contrast, Alabama had the fifth highest adult obesity-rate in the nation, yet, it had a very low age-adjusted mortality-rate. Such disparities make comparative analysis difficult.