Implementation by simulation; strategies for ultrasound screening for hip dysplasia in the Netherlands

Background: Implementation of medical interventions may vary with organization and available capacity. The influence of this source of variability on the cost-effectiveness can be evaluated by computer simulation following a carefully designed experimental design. We used this approach as part of a national implementation study of ultrasonographic infant screening for developmental dysplasia of the hip (DDH). Methods: First, workflow and performance of the current screening program (physical examination) was analyzed. Then, experimental variables, i.e., relevant entities in the workflow of screening, were defined with varying levels to describe alternative implementation models. To determine the relevant levels literature and interviews among professional stakeholders are used. Finally, cost-effectiveness ratios (inclusive of sensitivity analyses) for the range of implementation scenarios were calculated. Results: The four experimental variables for implementation were: 1) location of the consultation, 2) integrated with regular consultation or not, 3) number of ultrasound machines and 4) discipline of the screener. With respective numbers of levels of 3,2,3,4 in total 72 possible scenarios were identified. In our model experimental variables related to the number of available ultrasound machines and the necessity of an extra consultation influenced the cost-effectiveness most. Conclusions: Better information comes available for choosing optimised implementation strategies where organizational and capacity variables are important using the combination of simulation models and an experimental design. Information to determine the levels of experimental variables can be extracted from the literature or directly from experts

A tutorial on discrete-event simulation for health policy design and decision making: Optimizing pediatric ultrasound screening for hip dysplasia as an illustration

Background It is increasingly recognized that healthcare is a complex system with limited resources and many interacting sources of both positive and negative feedback. Discrete-event simulation (DES) is a tool that readily accommodates questions of capacity planning, throughput management and interacting resources. As a result the use of DES in informing healthcare decision making is increasing. However, understanding when and how to build a DES model and use it for policy making is not yet a common knowledge.Methods The steps in building a DES model will be demonstrated using a real-world example, i.e., pediatric ultrasound screening for hip dysplasia. The main components of a DES model such as entities, resources and queues will be introduced and we will examine questions such as referral schedule, number of ultrasound machines and type of screeners and how these entities interact. Finally a review of the statistical techniques appropriate to DES will be provided.Conclusion Discrete-event simulation is a valuable tool in the policymakers armentarium. It can be used effectively to analyze and understand complex healthcare systems and policy problems such as population screening.Discrete-event simulation Infant screening Operations research Regional health planning