Medical facility service bearing capacity evaluation method
A technology of carrying capacity and facilities, applied in the field of big data, can solve the problems that the research results cannot provide timely and effective guidance
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Embodiment 1
[0055] The present invention provides a method for calculating GDCL of medical facility service carrying capacity from the perspective of residents' choice behavior, comprising the following steps: S1: Obtain POI data of medical facilities and residential areas and regional health statistical yearbook; S2: Calculate residential area i according to the gravitational model formula Potential A to medical facility j ij ;S3: If A i = 0 (ie ∑ j A ij =0), then the residential point i chooses the nearest medical facility k; if A i ≠0, then incorporate this potential into the multinomial Logit (MNL) model, and calculate the probability P that residents at residential point i choose facility j ij ; S4: Randomly give the probability distribution of each resident's medical facility selection, if P ik If it falls within the interval of the probability distribution, the residents at the residential point i choose to choose the medical facility k; S5: Repeat the above steps, and all the ...
Embodiment 2
[0058] In this embodiment, on the basis of Embodiment 1, step S2 includes the following sub-steps: Calculate the potential A from the settlement i to the medical facility j according to the gravity model formula ij .
[0059] When this embodiment is implemented, it is necessary to reasonably set the service capacity M of medical facilities j , The grade scale S of the medical facilities ij and the resistance factors of residents' travel and other parameters. Among them, the service capacity of medical facilities can be comprehensively reflected by different indicators such as the number of beds, the number of health technicians, and the number of consultations. Different grades of medical facilities should have different grade scale coefficients, and at the same time, the attenuation effect of grade scale attractiveness should be produced with the increase of travel distance. The travel friction coefficient β reflects the sensitivity of residents to the travel distance, u...
Embodiment 3
[0061] In this embodiment, on the basis of Embodiment 1, step S4 includes the following sub-steps: S41: Calculate the calculated P based on the MNL model formula. ij Sorting from small to large; S42: Generate a random floating-point number p in the range of (0, 1), if P ik ≤pik+1 , then the residents at the settlement i choose to choose the medical facility k.
[0062] When this embodiment is implemented, it is necessary to P ij Sort from smallest to largest. For each competitive selection of medical facilities, the present invention makes a decision by generating a random number between 0 and 1. Residents choose a medical facility every time they compete at random, but with P ij is proportional to the size of P ij The larger the value is, the higher the probability of choosing medical facility j is.
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