BACKGROUND AND PURPOSE: The current self-initiated approach by which hospitals acquire Primary Stroke Center (PSC) certification provides insufficient coverage for large areas of the United States. An alternative, directed, algorithmic approach to determine near optimal locations of PSCs would be justified if it significantly improves coverage. METHODS: Using geographic location-allocation modeling techniques, we developed a universal web-based calculator for selecting near optimal PSC locations designed to maximize the population coverage in any state. We analyzed the current PSC network population coverage in Iowa and compared it with the coverage that would exist if a maximal coverage model had instead been used to place those centers. We then estimated the expected gains in population coverage if additional PSCs follow the current self-initiated model and compared it against the more efficient coverage expected by use of a maximal coverage model to select additional locations. RESULTS: The existing 12 self-initiated PSCs in Iowa cover 37% of the population, assuming a time-distance radius of 30 minutes. The current population coverage would have been 47.5% if those 12 PSCs had been located using a maximal coverage model. With the current self-initiated approach, 54 additional PSCs on average will be needed to improve coverage to 75% of the population. Conversely, only 31 additional PSCs would be needed to achieve the same degree of population coverage if a maximal coverage model is used. CONCLUSIONS: Given the substantial gain in population access to adequate acute stroke care, it appears justified to direct the location of additional PSCs or recombinant tissue-type plasminogen activator-capable hospitals through a maximal coverage model algorithmic approach.
BACKGROUND AND PURPOSE: The current self-initiated approach by which hospitals acquire Primary Stroke Center (PSC) certification provides insufficient coverage for large areas of the United States. An alternative, directed, algorithmic approach to determine near optimal locations of PSCs would be justified if it significantly improves coverage. METHODS: Using geographic location-allocation modeling techniques, we developed a universal web-based calculator for selecting near optimal PSC locations designed to maximize the population coverage in any state. We analyzed the current PSC network population coverage in Iowa and compared it with the coverage that would exist if a maximal coverage model had instead been used to place those centers. We then estimated the expected gains in population coverage if additional PSCs follow the current self-initiated model and compared it against the more efficient coverage expected by use of a maximal coverage model to select additional locations. RESULTS: The existing 12 self-initiated PSCs in Iowa cover 37% of the population, assuming a time-distance radius of 30 minutes. The current population coverage would have been 47.5% if those 12 PSCs had been located using a maximal coverage model. With the current self-initiated approach, 54 additional PSCs on average will be needed to improve coverage to 75% of the population. Conversely, only 31 additional PSCs would be needed to achieve the same degree of population coverage if a maximal coverage model is used. CONCLUSIONS: Given the substantial gain in population access to adequate acute stroke care, it appears justified to direct the location of additional PSCs or recombinant tissue-type plasminogen activator-capable hospitals through a maximal coverage model algorithmic approach.
Authors: Michael T Mullen; Suzanne Judd; Virginia J Howard; Scott E Kasner; Charles C Branas; Karen C Albright; J David Rhodes; Dawn O Kleindorfer; Brendan G Carr Journal: Stroke Date: 2013-05-02 Impact factor: 7.914
Authors: James P Rhudy; Marie A Bakitas; Kristiina Hyrkäs; Rita A Jablonski-Jaudon; Erica R Pryor; Henry E Wang; Anne W Alexandrov Journal: Brain Behav Date: 2015-09-23 Impact factor: 2.708
Authors: Geoffrey Fairchild; Philip M Polgreen; Eric Foster; Gerard Rushton; Alberto M Segre Journal: Int J Health Geogr Date: 2013-12-09 Impact factor: 3.918
Authors: Ajay Aggarwal; Daniel Lewis; Malcolm Mason; Arnie Purushotham; Richard Sullivan; Jan van der Meulen Journal: Lancet Oncol Date: 2017-10-03 Impact factor: 41.316