[Integrated care concepts and multidisciplinary process chains in a radiological context]

Modern patient-centered and cost-efficient care concepts in hospitals require the mapping of multidisciplinary process chains into clinical pathways. Clinical decision support systems and operations research methods use algorithms to classify patients into homogeneous groups and to model a complete clinical pathway for scheduling individual procedures. An improvement of the economic situation of the care facility can be achieved through improved resource utilization, reduced patient waiting times and a shortening of the length of stay. The interdisciplinary use of centrally stored interoperable information and comprehensive care management via information technology (IT) services lay the foundation for the dissolution of traditional IT system architectures in medicine and the development of flexibly integrable modern system platforms. New IT approaches such as the semantically standardized definition of procedures and resource properties, the use of clinical decision support systems and the use of service-oriented system architectures form the basis for the deep integration of radiology services into comprehensive interdisciplinary care concepts.

Closure simulation for reduction of emergency patient diversion: a discrete agent-based simulation approach to minimizing ambulance diversion

Background

The city of Munich uses web-based information system IVENA to promote exchange of information regarding hospital offerings and closures between the integrated dispatch center and hospitals to support coordination of the emergency medical services. Hospital crowding resulting in closures and thus prolonged transportation time poses a major problem. An innovative discrete agent model simulates the effects of novel policies to reduce closure times and avoid crowding.

Methods

For this analysis, between 2013 and 2017, IVENA data consisting of injury/disease, condition, age, estimated arrival time and assigned hospital or hospital-closure statistics as well as underlying reasons were examined. Two simulation experiments with three policy variations are performed to gain insights on the influence of diversion policies onto the outcome variables.

Results

A total of 530,000+ patients were assigned via the IVENA system and 200,000+ closures were requested during this time period. Some hospital units request a closure on more than 50% of days. The majority of hospital closures are not triggered by the absolute number of patient arrivals, but by a sudden increase within a short time period. Four of the simulations yielded a specific potential for shortening of overall closure time in comparison to the current status quo.

Conclusion

Effective solutions against crowding require common policies to limit closure status periods based on quantitative thresholds. A new policy in combination with a quantitative arrival sensor system may reduce closing hours and optimize patient flow.