How do different densities in a network affect the optimal location of service centers?

The p-median problem is often used to locate p service centers by minimizing their distances to a geographically distributed demand (n). The optimal locations are sensitive to geographical context such as road network and demand points especially when they are asymmetrically distributed in the plane. Most studies focus on evaluating performances of the p-median model when p and n vary. To our knowledge this is not a very well-studied problem when the road network is alternated especially when it is applied in a real world context. The aim in this study is to analyze how the optimal location solutions vary, using the p-median model, when the density in the road network is alternated. The investigation is conducted by the means of a case study in a region in Sweden with an asymmetrically distributed population (15,000 weighted demand points), Dalecarlia. To locate 5 to 50 service centers we use the national transport administrations official road network (NVDB). The road network consists of 1.5 million nodes. To find the optimal location we start with 500 candidate nodes in the network and increase the number of candidate nodes in steps up to 67,000. To find the optimal solution we use a simulated annealing algorithm with adaptive tuning of the temperature. The results show that there is a limited improvement in the optimal solutions when nodes in the road network increase and p is low. When p is high the improvements are larger. The results also show that choice of the best network depends on p. The larger p the larger density of the network is needed. 

Factors facilitating a national quality registry to aid clinical quality improvement : findings of a national survey

Objectives: While national quality registries (NQRs) are suggested to provide opportunities for systematic follow-up and learning opportunities, and thus clinical improvements, features in registries and contexts triggering such processes are not fully known. This study focuses on one of the world's largest stroke registries, the Swedish NQR Riksstroke, investigating what aspects of the registry and healthcare organisations facilitate or hinder the use of registry data in clinical quality improvement. Methods: Following particular qualitative studies, we performed a quantitative survey in an exploratory sequential design. The survey, including 50 items on context, processes and the registry, was sent to managers, physicians and nurses engaged in Riksstroke in all 72 Swedish stroke units. Altogether, 242 individuals were presented with the survey; 163 responded, representing all but two units. Data were analysed descriptively and through multiple linear regression. Results: A majority (88%) considered Riksstroke data to facilitate detection of stroke care improvement needs and acknowledged that their data motivated quality improvements (78%). The use of Riksstroke for quality improvement initiatives was associated (R2=0.76) with ‘Colleagues’ call for local results’ (p=<0.001), ‘Management Request of Registry data’ (p=<0.001), and it was said to be ‘Simple to explain the results to colleagues’ (p=0.02). Using stepwise regression, ‘Colleagues’ call for local results’ was identified as the most influential factor. Yet, while 73% reported that managers request registry data, only 39% reported that their colleagues call for the unit's Riksstroke results. Conclusions: While an NQR like Riksstroke demonstrates improvement needs and motivates stakeholders to make progress, local stroke care staff and managers need to engage to keep the momentum going in terms of applying registry data when planning, performing and evaluating quality initiatives.