Case04A-Defining Service Areas of Acute Hospitals in Baton Rouge

Chapter 4 Delineating Functional Regions and Application in Health Geography

Case study 4A illustrates how to use the proximal area method and the Huff model to estimate the service areas of acute hospitals in Baton Rouge. Case study 4B implements the Dartmouth method that pioneered the delineation of hos?pital service areas (HSAs) by a simple plurality rule, and the network community detection approach to define HSAs with maximal patient flows within HSAs and minimal flows between HSAs. It relies on data of observed hospitalization service volumes between residents and hospitals in Florida.

Case Study 4A: Defining Service Areas of Acute Hospitals in Baton Rouge, Louisiana

This case study definnes the service areas of five acute hospitals in Baton Rouge based on travel time through the road network derived from Chapter 2. In the Huff model, we use the number of beds to define the capacity of each hospital S and assume the traditional power function for the distance decay effect with β = 3.0.

Data sets needed for the project are the same as in Case Study 2 under the data folder BatonRouge . Several data sets generated from Case Study 2 are also used.

The data used includes:

(1) a projected census block group layer BR _ Bkg.zip used in Chapter 2 and its centroids layer BRPt.zip generated in Step 8 of Section 2.1.2,

(2) a hospitals layer Hosp.zip generated in Step 8 of Section 2.1.2,

(3) a major road network dataset BR_MainRd.zip , and

(4) an OD drive time matrix fille OD _ Drive _ Time.csv generated by step 12 in Section 2.1 (its ? eld Duration representing drive time in minutes and Distance for drive distance in meters).

Computational Methods and GIS Applications in Social Science - KNIME Lab Manual

Lingbo Liu, Fahui Wang

External resources

• Github for Workbook Issue Report
• Github for Geospatial Analytics