Expansion of off-site percutaneous coronary intervention centres significantly reduces ambulance driving time to primary PCI in the Netherlands.

INTRODUCTION: In patients with ST-elevation myocardial infarction (STEMI), percutaneous coronary intervention (PCI)-mediated reperfusion is preferred over pharmacoinvasive reperfusion with fibrinolysis if transfer to a PCI centre can be ensured in ≤120 min. We evaluated the ambulance driving time to primary PCI centres in the Netherlands and assessed to what extent ambulance driving times were impacted by the expansion of off-site PCI centres. METHODS AND RESULTS: We calculated the driving routes from every Dutch postal code to the nearest PCI centre with (on-site) or without (off-site) surgical back-up. We used data from ambulance records to estimate the ambulance driving time on each route. There were 16 on-site and 14 off-site PCI centres. The median (interquartile range) time to on-site PCI centres was 18.8 min (12.2-26.3) compared with 14.9 min (8.9-20.9) to any PCI centre (p < 0.001). In postal code areas that were impacted by the initiation of off-site PCI, the median driving time decreased from 25.4 (18.2-33.1) to 14.7 min (8.9-20.9) (p < 0.001). Ambulance driving times of >120 min were only seen in non-mainland areas. CONCLUSION: Based on a computational model, timely ambulance transfer to a PCI centre within 120 min is available to almost all STEMI patients in the Netherlands. Expansion of off-site PCI has significantly reduced the driving time to PCI centres.

Demographic projections of future pharmaceutical consumption in the Netherlands.

Over the next few decades, many Western European countries will undergo a large demographic transformation introduced by the retirement of the "baby boomers" and the possibility of striking increases in longevity. The aim of this study was to estimate the effect of a growing and ageing Dutch population on the future consumption of pharmaceuticals, so as to be able to anticipate the potential future emissions of these pharmaceuticals and their residues to surface waters. A total of 354 prescribed pharmaceuticals from 40 therapeutic groups was selected for study. These constitute 1.251 metric tonnes (98%) of the total Dutch consumption of prescribed pharmaceuticals in 2007. Calculations based on a fixed consumption rate (2007) predict that demographic developments can be expected to push consumption up to 1.504 metric tonnes in 2020 (+17%) and 1.851 metric tonnes by 2050 (+37%). Therapeutic groups showing the largest increase are related to illnesses associated with old age. The only groups showing a decrease are the antivirals and drugs for addiction treatments as well as ethinylestradiol, an active compound in contraceptives.

A waiting list model for residential care for the mentally disabled in The Netherlands.

We present a model of the waiting list for residential care for the mentally disabled in the Netherlands. The model is a linear stock-flow model and distributes the mentally disabled over different living situations. It includes institutional and semi-institutional care explicitly and ambulatory and other types of care implicitly. Four scenarios are simulated, exploring possible future developments. Scenarios differ in the mortality rate of mentally disabled, the supply and use of ambulatory care and the possible effect of uncertainty in the data. Results show that unless continuous efforts are made to decrease the inflow in the waiting list and to supply extra care as well as extra alternative care. the waiting list for residential care will continue to grow.

Patient flows and optimal health-care resource allocation at the macro-level: a dynamic linear programming approach.

In this paper we present a deterministic allocation model in which a patient's health-state changes due to health-care interventions. This change in a patient's health-state has a direct effect on the patient's expected future need for health-care. Hence, current allocation decisions determine to some extent the set of possible allocation decisions in the future. In order to take this into account we have formulated a dynamic linear programming version of a patient-flow system. This enables us to describe the effects of using different objective functions on the optimum level and composition of the provision of health services within given resource constraints. The linear programming approach enables the quantification of the health effects and therefore the desirability of the (re-)allocation of health-care resources. We provide some simulation results in order to illustrate the working of the model.