{"id":153,"date":"2017-01-16T04:28:14","date_gmt":"2017-01-16T04:28:14","guid":{"rendered":"https:\/\/blogs.scu.edu\/dataviz\/?p=153"},"modified":"2017-01-16T04:28:14","modified_gmt":"2017-01-16T04:28:14","slug":"public-healthcare-data-visualization","status":"publish","type":"post","link":"https:\/\/blogs.scu.edu\/dataviz\/2017\/01\/16\/public-healthcare-data-visualization\/","title":{"rendered":"Public Healthcare Data Visualization"},"content":{"rendered":"<p>Nowadays data plays an important role in public healthcare management. To better understand what stories large volumes of data tell, we need accurate and clear data visualizations to uncover the actionable insights. \u00a0Below is\u00a0an example of data visualization\u00a0created by Ken Patton and Dr. Heather King, which analyzes health outcomes by prevalence across a number of demographic factors including geography, gender, age, and activity levels.<br \/>\n<img loading=\"lazy\" decoding=\"async\" class=\"alignnone  wp-image-165\" src=\"https:\/\/blogs.scu.edu\/dataviz\/files\/2017\/01\/Diabetes-300x255.jpg\" alt=\"Diabetes\" width=\"724\" height=\"615\" srcset=\"https:\/\/blogs.scu.edu\/dataviz\/files\/2017\/01\/Diabetes-300x255.jpg 300w, https:\/\/blogs.scu.edu\/dataviz\/files\/2017\/01\/Diabetes.jpg 781w\" sizes=\"auto, (max-width: 724px) 100vw, 724px\" \/><\/p>\n<p>The cells displayed in different colors and percentages immediately convey the messages that African-Americans and people with annual income between 10-15k have higher prevalence of diabetes. The distribution map indicated that diabetes are more prevalent in Pennsylvania and Southern States. The appropriate use of colors enhanced the story telling. It is accepted that colors have meanings. The warm colors\u00a0(i.e. red, orange)\u00a0usually describe danger or worse situations while the\u00a0cool colors\u00a0(i.e. light blue)\u00a0usually indicate safe or less worse situations.\u00a0\u00a0So it&#8217;s a good design of data visualization as it&#8217;s easy to catch the points and very intuitive.<\/p>\n<p>source: http:\/\/www.tableau.com\/stories\/workbook\/tackle-government-data-public-health<\/p>\n<p>reference: http:\/\/www.healthcareitnews.com\/news\/best-practices-healthcare-data-visualization<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Nowadays data plays an important role in public healthcare management. To better understand what stories large volumes of data tell, we need accurate and clear data visualizations to uncover the actionable insights. \u00a0Below is\u00a0an example of data visualization\u00a0created by Ken Patton and Dr. Heather King, which analyzes health outcomes by prevalence across a number of &hellip; <a href=\"https:\/\/blogs.scu.edu\/dataviz\/2017\/01\/16\/public-healthcare-data-visualization\/\" class=\"more-link\">Continue reading <span class=\"screen-reader-text\">Public Healthcare Data Visualization<\/span><\/a><\/p>\n","protected":false},"author":1880,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"qubely_global_settings":"","qubely_interactions":"","kk_blocks_editor_width":"","_kiokenblocks_attr":"","_kiokenblocks_dimensions":"","footnotes":""},"categories":[1],"tags":[],"class_list":["post-153","post","type-post","status-publish","format-standard","hentry","category-uncategorized"],"gutentor_comment":0,"qubely_featured_image_url":null,"qubely_author":{"display_name":"xhuang","author_link":"https:\/\/blogs.scu.edu\/dataviz\/author\/xhuang\/"},"qubely_comment":0,"qubely_category":"<a href=\"https:\/\/blogs.scu.edu\/dataviz\/category\/uncategorized\/\" rel=\"category tag\">Uncategorized<\/a>","qubely_excerpt":"Nowadays data plays an important role in public healthcare management. To better understand what stories large volumes of data tell, we need accurate and clear data visualizations to uncover the actionable insights. \u00a0Below is\u00a0an example of data visualization\u00a0created by Ken Patton and Dr. Heather King, which analyzes health outcomes by prevalence across a number of&hellip;","post_mailing_queue_ids":[],"_links":{"self":[{"href":"https:\/\/blogs.scu.edu\/dataviz\/wp-json\/wp\/v2\/posts\/153","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/blogs.scu.edu\/dataviz\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/blogs.scu.edu\/dataviz\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/blogs.scu.edu\/dataviz\/wp-json\/wp\/v2\/users\/1880"}],"replies":[{"embeddable":true,"href":"https:\/\/blogs.scu.edu\/dataviz\/wp-json\/wp\/v2\/comments?post=153"}],"version-history":[{"count":6,"href":"https:\/\/blogs.scu.edu\/dataviz\/wp-json\/wp\/v2\/posts\/153\/revisions"}],"predecessor-version":[{"id":178,"href":"https:\/\/blogs.scu.edu\/dataviz\/wp-json\/wp\/v2\/posts\/153\/revisions\/178"}],"wp:attachment":[{"href":"https:\/\/blogs.scu.edu\/dataviz\/wp-json\/wp\/v2\/media?parent=153"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/blogs.scu.edu\/dataviz\/wp-json\/wp\/v2\/categories?post=153"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/blogs.scu.edu\/dataviz\/wp-json\/wp\/v2\/tags?post=153"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}