From espinello@rpmconsulting.com Tue May 4 09:20:41 1999 Received: from mxu3.u.washington.edu (mxu3.u.washington.edu [140.142.33.7]) by lists.u.washington.edu (8.9.3+UW99.02/8.9.3+UW99.01) with ESMTP id JAA10316 for ; Tue, 4 May 1999 09:20:40 -0700 Received: from wren.prod.itd.earthlink.net (wren.prod.itd.earthlink.net [207.217.120.64]) by mxu3.u.washington.edu (8.9.3+UW99.02/8.9.3+UW99.01) with ESMTP id JAA26189 for ; Tue, 4 May 1999 09:20:40 -0700 Received: from rr2 (pool043-max20.mpop2-ca-us.dialup.earthlink.net [207.217.243.243]) by wren.prod.itd.earthlink.net (8.8.7/8.8.5) with SMTP id JAA16495 for ; Tue, 4 May 1999 09:20:38 -0700 (PDT) Message-ID: <008101be964c$274ea920$6bf3d9cf@rr2> From: "Elio Spinello" To: Subject: Re: Hospitals catchment area Date: Tue, 4 May 1999 09:35:36 -0700 MIME-Version: 1.0 Content-Type: text/plain; charset="iso-8859-1" Content-Transfer-Encoding: 7bit X-Priority: 3 X-MSMail-Priority: Normal X-Mailer: Microsoft Outlook Express 4.72.3110.5 X-MimeOLE: Produced By Microsoft MimeOLE V4.72.3110.3 The process which I have used in the past for creating catchment areas has been based on penetration rates by region. Using either a grid or some other relatively small unit of geography (like U.S. block groups), the percent of a hospital's discharges (compared to all discharges for the same diagnosis) is calculated for each region surrounding the hospital. Then by establishing a cutoff penetration rate you can identify which grid cells or regions will be part of the catchment area. ++++====++++====++++====++++====++++====++++====++++====++++====++++====++++ Elio Spinello, MPH Department of Health Sciences California State University, Northridge 18111 Nordhoff St. Northridge, CA 91330-8285 Voice: 818-831-7607 Fax: 831-9078 elio.spinello@csun.edu Home Page: http://www.csun.edu/~hchsc018 ====++++====++++====++++====++++====++++====++++====++++====++++====++++==== -----Original Message----- From: Alberto Zucchi To: waphgis@u.washington.edu Date: Tuesday, May 04, 1999 3:37 AM Subject: Hospitals catchment area >Dear Listers, I'd like to receive some suggestion on the following problem. >I have a data-set containing all paediatric admissions (say, 200,000) in >all the hospitals in a region (say, 30). >I have two tables. The first contains hospitals' localization (with related >coordinates). The second contains each admissions these hospitals did in >one year, with each patient's city of residence (say approx. 200,000 >patients for 2,000 cities/villages). I'd like to create a "catchment area" >for each hospital, in relation to their patients' residence. I thought to >build a "distance matrix" in kilometres, and the calculate the mean or >median distance for each city/hospital, and finally superimpose a "buffer" >(or maybe drawing a simple circle...to simplify reality). Does anyone have >some suggestion/trick on the way to perform this? > >Thank you in advance. > >Alberto Zucchi, MD >Epidemiology Office >ASL Bergamo > > .