Hospital emergency treatment space layout optimization method and device, computer equipment and storage medium

Abstract

The invention discloses a hospital emergency treatment space layout optimization method and device, computer equipment and a storage medium, and the method comprises the steps: obtaining hospital emergency treatment department patient treatment data, extracting emergency treatment department plane information, carrying out the preprocessing of process mining of the patient treatment data, obtaining the treatment process feature information of a patient, and determining the optimization targets of the multi-target optimization model and the weight of each optimization target; collecting variable information required by the multi-objective optimization model according to the doctor seeing process feature information of the patient and the emergency department plane information; and inputting the variable information into a multi-objective optimization model for optimization, and outputting a layout optimization result to generate an optimization scheme. Based on the medical data of the large-scale comprehensive hospital, the flow mining method is utilized to objectively reflect the objective behavior rule of the patient from the medical treatment flow level, so that the finally generated scheme result is more objective, and the actual operation efficiency can be better improved.

Description

technical field [0001] The invention relates to a method, a device, a computer device and a storage medium for optimizing the spatial layout of a hospital emergency room, and belongs to the application fields of architectural design, information technology and computers. Background technique [0002] The existing algorithm model is combined with medical data to construct an optimization method for the plane layout of medical facilities. The optimization object is mainly the spatial layout of a department with relatively simple functions in the hospital, such as the layout of the wards in the inpatient department and the internal space layout of the operating room. A common way is to combine technologies such as shape grammar, cellular automata, and machine learning to help architects explore iterative optimization schemes for building plans with a single goal. [0003] The traditional hospital plane optimization technology based on operations research can generally be unders...

AI Technical Summary

Problems solved by technology

Therefore, traditional but objective optimization methods do not meet existing needs;

[0004] Machine learning algorithms are commonly used to generate simple residential floor plans, but they have certain limitations in the face of hospital building plans with complex functions and various layout methods;

[0005] The mathematical model of the quadratic assignment problem (The Quadratic Assignment Problem, QAP) has restrictions on the types of spatial functions. Although QAP can in principle be solved by exhaustively enumerating all possible activity assignment methods, and then choose a scheme that satisfies any given constraints, but In fact, the QAP model is not feasible for hospitals, because as the size of the problem increases (when the number of activities is greater than 15), the time to solve the QAP will increase exponentially, and it is difficult to avoid, so the QAP model is not suitable for Solving complex hospital building plan optimization problems

[0007] Other optimization methods of the same type are usually limited to interviews, questionnaires, manual path tracking, and video analysis for data collection on the patient visit process. Patient behavior is usually limited to subjective judgments of patient behavior, lacking objectivity

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