{"id":1874,"date":"2014-09-04T06:19:25","date_gmt":"2014-09-04T10:19:25","guid":{"rendered":"http:\/\/mat.tepper.cmu.edu\/blog\/?p=1874"},"modified":"2014-09-04T06:19:25","modified_gmt":"2014-09-04T10:19:25","slug":"using-analytics-for-emergency-response","status":"publish","type":"post","link":"https:\/\/mat.tepper.cmu.edu\/blog\/index.php\/2014\/09\/04\/using-analytics-for-emergency-response\/","title":{"rendered":"Using Analytics for Emergency Response"},"content":{"rendered":"

I just attended a great talk by Laura McLay<\/a> at the German OR Society meeting in Aachen<\/a>. \u00a0In her semi-plenary, Laura talked about all the work she has done in Emergency Medical Response. \u00a0Planning the location and operation of ambulances, fire trucks, emergency medical technicians, and so on is a difficult problem, and Laura has made very good progress in putting operations research to use in making systems work better. \u00a0She has been recognized for this work not only in our field (through things like outstanding paper awards and an NSF CAREER award) but also by those directly involved in emergency response planning, as evidenced by an award from the National Association of Counties.<\/p>\n

Laura covered a lot of ground in her talk (she has a dozen papers or more in the area), but I found one result in particular very striking. \u00a0Many ambulance systems have a goal of responding to 80% of their calls in 9 minutes (or some such numbers). \u00a0One of the key drivers of those values is the survivability from heart attacks: \u00a0even minutes matter in such cases.\"response\"<\/a> \u00a0The graph attached (not from Laura, available in lots of places on the internet) shows a sharp dropoff as the minutes tick away.<\/p>\n

But why 9 minutes? \u00a0It is clear from the data that if the goal is to provide response within 9 minutes, there is an awful lot of 8 minute 30 second response times. \u00a0Systems respond to what is measured. \u00a0Wouldn’t it be better, then to require 5 minute response times? \u00a0Clearly more people would be saved since more people would be reached within the critical first minutes. \u00a0This looks like a clear win for evidence-based medicine and the use of analytics in decision making.<\/p>\n

But Laura and her coauthors have a deeper insight than that. \u00a0In the area they are looking at, which is a mix of suburban and rural areas, with a 9 minute response time, the optimal placement of ambulances is a mixture of suburban and rural locations. \u00a0With a 5 minute response time, it does no good to place an ambulance in a rural location: they can’t get to enough people in time. \u00a0All the ambulances would be placed in the higher-density suburban location. \u00a0If a call comes in from a rural location, eventually an ambulance would wend its way to the rural location, but after 20 or 30 minutes, many cases become moot.<\/p>\n

To figure out the optimal response time, you need to figure out both survivability and the number of cases the system can reach. \u00a0For the area Laura and her team looked at, the optimal response time turned out to be 8 to 9 minutes.<\/p>\n

Of course, this analysis is not relevant if the number of ambulances is increased with the decreased response time requirement. \u00a0But the enthusiasm for spending more on emergency response is not terrifically high, so it is more likely that the time will be changed without a corresponding increase in budget. \u00a0And that can have the effect of making the entire system worse (though things are better for the few the ambulance can reach in time).<\/p>\n

This was a great example of the conflict between individual outcome and social outcomes in emergency response. \u00a0And a good example of how careful you need to be when using analytics in health care.<\/p>\n

I highly recommend reading her\u00a0Interfaces<\/i> article “Hanover County Improves its Response to Emergency Medical 911 Patients”<\/a>\u00a0(no free version). \u00a0I even more highly recommend her blog Punk Rock Operations Research<\/a> and her twitter stream at @lauramclay<\/a>.<\/p>\n","protected":false},"excerpt":{"rendered":"

I just attended a great talk by Laura McLay at the German OR Society meeting in Aachen. \u00a0In her semi-plenary, Laura talked about all the work she has done in Emergency Medical Response. \u00a0Planning the location and operation of ambulances, fire trucks, emergency medical technicians, and so on is a difficult problem, and Laura has … Continue reading “Using Analytics for Emergency Response”<\/span><\/a><\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[13,35],"tags":[],"class_list":["post-1874","post","type-post","status-publish","format-standard","hentry","category-conferences","category-medicine"],"jetpack_featured_media_url":"","_links":{"self":[{"href":"https:\/\/mat.tepper.cmu.edu\/blog\/index.php\/wp-json\/wp\/v2\/posts\/1874","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/mat.tepper.cmu.edu\/blog\/index.php\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/mat.tepper.cmu.edu\/blog\/index.php\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/mat.tepper.cmu.edu\/blog\/index.php\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/mat.tepper.cmu.edu\/blog\/index.php\/wp-json\/wp\/v2\/comments?post=1874"}],"version-history":[{"count":0,"href":"https:\/\/mat.tepper.cmu.edu\/blog\/index.php\/wp-json\/wp\/v2\/posts\/1874\/revisions"}],"wp:attachment":[{"href":"https:\/\/mat.tepper.cmu.edu\/blog\/index.php\/wp-json\/wp\/v2\/media?parent=1874"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/mat.tepper.cmu.edu\/blog\/index.php\/wp-json\/wp\/v2\/categories?post=1874"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/mat.tepper.cmu.edu\/blog\/index.php\/wp-json\/wp\/v2\/tags?post=1874"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}