CN108538372A - Medical service price adjustment method, apparatus, server and storage medium - Google Patents
Medical service price adjustment method, apparatus, server and storage medium Download PDFInfo
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Abstract
The present invention is applicable in price and regulates and controls field, provides a kind of medical service price adjustment method, apparatus, server and storage medium, this method and includes：Medical services data are extracted in HIS databases, it establishes price adjustment model and generates initial population, bee is employed to carry out neighborhood search, first individual evaluation is carried out to the fitness of each individual, and generate the first population, obtain the first optimum individual in the first population, then observation bee carries out neighborhood search, second individual evaluation is carried out to the fitness of each individual, and generate the second population, obtain the second optimum individual in the second population, when it is more than to preset evaluation number to evaluate number, the maximum individual of fitness in first and second optimum individuals is determined as to the optimal price adjustment factor set of price adjustment model, otherwise it jumps to and bee is employed to carry out neighborhood search, to pass through the cooperation of all kinds of honeybees in artificial bee colony, find optimal medical services price adjustment scheme, with Added Management, personnel rationally adjust medical service prices.
Description
Technical field
The invention belongs to price regulation and control field more particularly to a kind of medical service price adjustment method, apparatus, server and
Storage medium.
Background technology
Currently, medical service prices are mainly formulated by departments of government, existing price be mainly price department according to
What the mode that material cost is calculated was formulated, the price and cost of each charging item are deviated from.Using survey fees, Laboratory Fee as representative
Dependence medical instrument Cost of Medical Treatment project, price is high and at low cost, and hospital is to pursue high profit to lead to over-treatment
The phenomenon that；Using diagnosis and treatment expense, Operation Fee as embodiment medical worker's labour value Cost of Medical Treatment project of representative, it is priced low and cost
Height can not embody the professional skill value of medical staff, can not form positive incentive to medical staff, be easy to cause doctor's steering
It the high profits service entry such as examines, check, forming vicious circle.If directly the project of some embodiment labor technology values is carried
High charge standard can then improve the whole medical treatment expense of patient, be caused stress to government and patient.If directly reduce some according to
The expenses standard for relying medical instrument, then can cause stress the normal operation of hospital, it is therefore desirable to ensure patient medical general branch
Go out it is constant in the case of, Cost of Medical Treatment item target structure is adjusted.
Invention content
It is an object of the invention to utilize former years hospital's big data, provide a kind of medical service price adjustment method, apparatus,
Server and storage medium, it is intended to it solves that due to the prior art a kind of effective medical service price adjustment method can not be provided,
Change present hospitals income depends on medical instrument inspection unduly and medical worker's technical ability value can not be in medical service prices
The problem of effectively embodying.
On the one hand, the present invention provides a kind of medical service price adjustment method, the method includes following step：
Target medical data is extracted in HIS databases, is established according to the target medical data for adjusting medical clothes
The price adjustment model for price of being engaged in, and generate the initial population of the price adjustment model；
Bee, which is employed, by the local optimum individual guiding in the initial population in each individual neighbor scope carries out first
Neighborhood search carries out the first individual evaluation, according to the first individual evaluation knot to the fitness of each individual in first neighborhood
Fruit updates each local optimum individual in the initial population, and generates the first population, and first most in acquisition first population
Excellent individual；
Preset ratio excellent individual is chosen in first population, is guided by the preset ratio excellent individual
It observes bee and carries out the second neighborhood search, the second individual evaluation is carried out to the fitness of each individual in second neighborhood, according to
Second individual evaluation result updates the preset ratio excellent individual, and generates the second population, obtains in second population
Second optimum individual；
It is optimal by described first and second when the number of first and second individual evaluation is more than default evaluation number
The maximum individual of fitness is determined as the optimal price adjustment factor set of the price adjustment model in individual, otherwise by described second
Group is set as the initial population, jumps to through the local optimum individual guiding in initial population in each individual neighbor scope
It employs bee and carries out the first neighborhood search.
On the other hand, the present invention provides a kind of medical service price adjustment device, described device includes：
Model foundation unit is built for extracting target medical data in HIS databases according to the target medical data
The price adjustment model for adjusting medical service prices is found, and generates the initial population of the price adjustment model；
The first group of generation units, for passing through the local optimum in the initial population in each individual neighbor scope
Body guiding employs bee and carries out the first neighborhood search, and carrying out the first individual to the fitness of each individual in first neighborhood comments
Valence updates each local optimum individual in the initial population according to the first individual evaluation result, and generates the first population, obtains
First optimum individual in first population；
Second group of generation units, for choosing preset ratio excellent individual in first population, by described
Preset ratio excellent individual guiding observation bee carries out the second neighborhood search, to the fitness of each individual in second neighborhood
The second individual evaluation is carried out, the preset ratio excellent individual is updated according to the second individual evaluation result, and generate second
Group obtains the second optimum individual in second population；And
Output unit is recycled, is used for when the number of first and second individual evaluation is more than default evaluation number, it will
The maximum individual of fitness is determined as the optimal price adjustment factor of the price adjustment model in first and second optimum individual
Otherwise group sets second population to the initial population, jump to through each individual neighbor scope in initial population
Interior local optimum individual guiding employs bee and carries out the first neighborhood search.
On the other hand, the present invention also provides a kind of server, including memory, processor and it is stored in the storage
In device and the computer program that can run on the processor, the processor are realized when executing the computer program such as institute
The step of stating medical service price adjustment method.
On the other hand, the present invention also provides a kind of computer readable storage medium, the computer readable storage mediums
It is stored with computer program, is realized such as the medical service price adjustment method when computer program is executed by processor
Step.
The present invention extracts medical services data in HIS databases, establishes price adjustment model and generates initial population, employs
It hires bee and carries out neighborhood search, the first individual evaluation is carried out to the fitness of each individual, and generate the first population, obtain the first
First optimum individual in group, then observes bee and carries out neighborhood search, and the second individual evaluation is carried out to the fitness of each individual, and
The second population is generated, the second optimum individual in the second population is obtained, when it is more than to preset evaluation number to evaluate number, by the first He
The maximum individual of fitness is determined as the optimal price adjustment factor set of price adjustment model in second optimum individual, otherwise jumps to and employs
It hires bee and carries out neighborhood search, to by the cooperation of all kinds of honeybees in artificial bee colony, find optimal medical services price adjustment scheme,
With Added Management, personnel rationally adjust medical service prices, change hospital revenue and depend on medical instrument present situation unduly, carry
The skilled labour value of medical worker in high medical services.
Description of the drawings
Fig. 1 is the implementation flow chart for the medical service price adjustment method that the embodiment of the present invention one provides；
Fig. 2 is the structural schematic diagram of medical service price adjustment device provided by Embodiment 2 of the present invention；And
Fig. 3 is the structural schematic diagram for the server that the embodiment of the present invention three provides.
Specific implementation mode
In order to make the purpose , technical scheme and advantage of the present invention be clearer, with reference to the accompanying drawings and embodiments, right
The present invention is further elaborated.It should be appreciated that the specific embodiments described herein are merely illustrative of the present invention, and
It is not used in the restriction present invention.
The specific implementation of the present invention is described in detail below in conjunction with specific embodiment：
Embodiment one：
Fig. 1 shows the implementation process for the medical service price adjustment method that the embodiment of the present invention one provides, for the ease of
Illustrate, illustrate only with the relevant part of the embodiment of the present invention, details are as follows：
In step S101, target medical data is extracted in HIS databases, is established according to target medical data for adjusting
The price adjustment model of whole medical service prices, and generate the initial population of price adjustment model.
The embodiment of the present invention is suitable for medical service price adjustment system or hospital salary management system.Implement in the present invention
In example, target medical data is extracted in HIS (Hospital Information System, hospital information system) database,
The price adjustment model for adjusting medical service prices is established further according to target medical data, and generates price adjustment model
Initial population.The target medical data includes charging item unit price and the charges frequency of the charging item, the HIS data
Library can be the HIS databases for storing all medical service of hospital data of place (for example, county, city), receive user
The embodiment of the present invention is executed when being adjusted to the medical service item price in the place, so that price adjustment more meets this
The actual conditions in place.
Medical data in HIS databases includes usually many inconsistent or even missing medical data, it is preferred that
After extracting target medical data, outlier detection and amendment are carried out to target medical data, to revised target medical treatment number
According to logarithmetics processing is carried out, to obtain that treated, target medical data is convenient for keep the target medical data of extraction discrete
Follow-up data calculates.Specifically, when data are less than lower bound QL- 1.5IQR is more than upper bound QUWhen+1.5IQR, which is abnormal
Value, wherein interquartile-range IQR IQR=F-1(0.75)-F-1(0.25), lower quartile QL=F-1(0.25), upper quartile QU=F-1
(0.75), to it is simple, directly find out exceptional value.When finding exceptional value, the influence in order to avoid the exceptional value to result,
Can the corresponding single datum of suppressing exception value, it is also possible in HIS databases the average value of identical items to original exceptional value into
Row is replaced, and revised target medical data is then carried out logarithmetics processing with the target medical data that obtains that treated.Make
For illustratively, it is 98 yuan that the embodiment of the present invention, which finds a single injection Master Cost, and the injection material expense is excessively high, it may be determined that
This 98 yuan are registered Master Cost as exceptional value, at this point, the data that this single sign Master Cost is 98 yuan are deleted, or will
The average value of all single injection Master Costs replaces " 98 " this numerical value, then data that Lagrange's interpolation is fitted
Instead of " 98 " this numerical value.Further, logarithmetics processing is carried out to preprocessed data, to make a large amount of pretreatment numbers of extraction
Strong point is discrete as possible, is convenient for follow-up data processing.
In embodiments of the present invention, under the premise of patient medical expense total expenditure is held essentially constant, price tune is established
Integral mould, which can be by solving the adjustment ratio of each charging item, and reaches raising medical worker and curing
Treat the purpose that skilled labour is worth in service fee.Specifically, it establishes with drag：
Wherein, yoldRefer to the patient medical expense total expenditure before price adjustment, ynewRefer to the patient medical expense general branch after price adjustment
Go out, miRefer to the frequency of i-th of charge item, aiRepresent the unit price of i-th of charge item, xiRefer to i-th of price adjustment factor, the price adjustment
The factor, that is, price adjustment ratio.In model above, in principle, patient medical expense total expenditure is basically unchanged, i.e., need to meet yold
With ynewDifference y want as small as possible, and the project (for example, injection, night care etc.) that healthcare practitioner's labour value is high
The price adjustment factor be more than 1, conversely, project that healthcare practitioner's labour value is low the price adjustment of (for example, B ultrasound, clap X-ray etc.) because
Son is less than 1, at this point, Medical Treatment Price adjustment problem is converted to each price adjustment factor optimal solution found out and function y is made to obtain minimum value
The problem of, therefore, after establishing Optimized model, the initial population of the price adjustment factor set of optimization price adjustment model is generated, just
Beginningization relevant parameter, in order to found out subsequently through artificial bee colony model above price adjustment factor set optimal solution.Wherein, readjust prices
Factor set is the combination of all price adjustment factors.
In embodiments of the present invention, adjustment medical service prices are in line with " up-regulation can embody healthcare practitioner's labour value
Item price, lower the objectivized labour item price such as large scale equipment inspection " principle, it is therefore preferred that in price adjustment mould
After type establishes, cluster point is carried out to the price adjustment factor for factor set of readjusting prices in price adjustment model by preset clustering algorithm
Area, and the initial population of price adjustment model is generated, to reduce in price adjustment factor set the range for the factor of readjusting prices, reduce follow-up people
The search iteration number of the optimal solution preocess of worker bee group hunting substantially reduces the time that artificial bee colony searches optimal solution, specifically
Ground, the preset clustering algorithm can be that (Iterative Selforganizing DataAnalysis, iteration is from group by ISODATA
Organization data parser) algorithm, it is further preferred that during carrying out cluster subregion using ISODATA algorithms, in iteration
When updating cluster centre, former cluster centre is with updated cluster centre apart from absolute value of the difference | | tj-t′j| | ＜ dmin,j∈1,
2,…,NcIt remains unchanged, to further reduce the iterations of algorithm, shortens the time of calculating, improve the calculating of algorithm
Efficiency, wherein tj、t′jThe respectively front and back position of cluster centre update, dminFor the minimum of the front and back distance of cluster centre variation
Value.As illustratively, by the low B ultrasound of healthcare practitioner's labour value, X-ray, the corresponding price adjustment factor of nuclear magnetic resonance project
Subregion is clustered between 0.5 to 0.6, by the high injection of healthcare practitioner's labour value, the corresponding price adjustment of night care project
Factor Cluster subregion is between 1.3 to 1.4.
In specific implementation process, after the initial population for generating price adjustment model, according at the beginning of the population of artificial bee colony
Beginningization formula generates the random value of one group of multidimensional, multidimensional random value is set to the individual in initial population, according to Optimized model
The fitness for calculating each individual in initial population, to initialize initial population and relevant parameter, wherein relevant parameter can
Including the fitness of each individual in initial population individual amount, initial population, maximum evaluation number (default evaluation number), a
Body continuously updates maximum times (default update threshold value) of failure etc., each individual of population is one group of above-mentioned model
Solution, factor set of as readjusting prices.Specifically, according to the initialization of population formula in artificial bee colony algorithm, it is random to generate one group of multidimensional
Value, i-th of multidimensional random value are expressed as Xi=(Xi,1,Xi,2...), i=1,2 ..., SN, SN are population at individual quantity.It will be more
Dimension random value is set as the individual in initial population, and according to the model of structure calculate each individual fitness (feasible solution
It is good and bad).Wherein, the initialization of population formula in artificial bee colony is：In formula, Xij
Component is tieed up for the jth of i-th of multidimensional random value,The minimum value of component is tieed up for preset jth,For preset jth point
The maximum value of amount, rand0,1Random value between 0-1, fitness calculation formula are：
In formula, fitiFor i-th of individual XiFitness, f (Xi) it is XiFunctional value relative to optimization problem.
In step s 102, bee is employed by the local optimum individual guiding in initial population in each individual neighbor scope
The first neighborhood search is carried out, the first individual evaluation is carried out to the fitness of each individual in the first neighborhood, is commented according to the first individual
Valence result updates each local optimum individual in initial population, and generates the first population, obtains in the first population first optimal
Body.
In embodiments of the present invention, it is that each individual establishes a neighbor scope in initial population, neighbor scope is believed that
It is every scope of activities (search range) for employing bee, which is searched out according to fitness individual in each neighbor scope
Local optimum individual in enclosing, then employ bee to carry out neighborhood search by the guiding of these local optimum individuals, make that beekeeping equipment is employed to have
Good directionality, to accelerate convergence rate, for the ease of subsequent descriptions, the neighborhood search that this is employed to bee progress is known as
First neighborhood search, then the first individual evaluation is carried out to the fitness of each individual in the first neighborhood, with to each first neighborhood
The superiority-inferiority of individual is evaluated (the first individual evaluation), updates each local optimum individual according to evaluation result, will be each
Local optimum individual in first neighborhood remains, and constitutes the first population, passes through superiority-inferiority between individual in the first population
Evaluation obtains the first optimum individual (optimum individual of the first population) in the first population.
It specifically, can be according to individual current in initial population and its in initial population during generating the first population
Distance average between its individual establishes the neighbor scope of the individual, as individual XiWith individual XjDistance dij＜ rmdiWhen,
It is believed that individual XjIt is individual XiNeighbours, wherein r is parameter preset, mdiFor individual XiWith other individuals in initial population
Distance average.The formula for employing bee to carry out neighborhood search by the guiding of optimum individual in each neighbor scope is：Vi,j=
Xi,j+rand0,1·(Xnbest-Xi,j), wherein Vi,jFirst new is obtained after neighborhood search for i-th of individual in initial population
Body ViJth dimension, Xi,jFor i-th of individual X in initial populationiJth dimension, XnbestFor i-th individual neighbor scope in most
Excellent individual.
In step s 103, preset ratio excellent individual is chosen in the first population, it is outstanding a by preset ratio
Body guiding observation bee carries out the second neighborhood search, and the second individual evaluation, root are carried out to the fitness of each individual in the second neighborhood
Preset ratio excellent individual is updated according to the second individual evaluation result, and generates the second population, second most in the second population of acquisition
Excellent individual.
In embodiments of the present invention, for the ease of subsequent descriptions, the neighborhood search which carries out is known as the second neighbour
Domain search, during generating the second population, specifically, according to the fitness of the first population kind individual, in the first population kind
B=qSN excellent individual is chosen according to preset ratio q, the sequence of preset ratio excellent individual is upset, according to presetting the
One probability PstrWith the second probability 1-PstrThe preset ratio excellent individual is divided into first part individual floor (Pstr·B)
With second part individual B-floor (PstrB), then searched using preset first by first part individual guiding observation bee
Rope public affairs Formula Vi,j'=XPbest,j+φ·(Xi,j-Xk,j) the second neighborhood search is carried out, and observation bee is guided by second part individual
Formula V is searched for using preset secondi,j'=Xbest,j+φ·(Xpbest,j-Xi,j) the second neighborhood search is carried out, then to each the
The superiority-inferiority of two neighborhoods individual is evaluated (the first individual evaluation) to update preset ratio excellent individual, is constituted second
Group, and by the evaluation of superiority-inferiority between individual in the second population, obtain in the second population the second optimum individual (the second population
Optimum individual), to significantly reduce search, the selection pressure of observation bee, improve the neighborhood search efficiency of observation bee.Its
In, XPbestFor the individual randomly selected from preset ratio excellent individual, XkIt is randomly selected from the second population
Different from individual XiWith individual XPbestIndividual, XbestFor the optimum individual in the second population, XiFor preset ratio excellent individual
In i-th individual, V 'iFor i-th of individual X in preset ratio excellent individualiNew obtained after second neighborhood search
Body, φ are a random real number in [- 1,1].
Preferably, during carrying out the second neighborhood search, when the fitness that the first search formula searches individual is big
When the fitness of first part's individual, the promotion degree of the first search formula is obtained, when the second search formula searches individual
When fitness is more than the fitness of second part individual, the promotion degree of the second search formula is obtained, it is then public according to the first search
The promotion degree of the promotion degree of formula and the second search formula updates the first probability and the second probability, finally judges to select in the first population
It takes whether the selection number of preset ratio excellent individual is more than default selected threshold, selected threshold is not up to when choosing number
When, it jumps to and preset ratio excellent individual is divided by first part's individual and second according to default first probability and the second probability
Some individuals, to effectively improve the effect by observing the neighborhood search that bee carries out, which is to choose preset ratio
The frequency threshold value of a excellent individual.Specifically, in the promotion degree for searching for formula according to the promotion degree of the first search formula and second
When updating the first probability and the second probability, formula aID is first passed through1=ID1/floor(Pstr·B)、aID2=ID2/(B-floor
(PstrB the average promotion degree of the first search formula and the second search formula)) is calculated, then passes through formulaUpdated first probability and the second probability are calculated,
In, aID1For the average promotion degree of the first search formula, aID2For the average promotion degree of the second search formula, ID1For the first search
The promotion degree of formula, ID2For the promotion degree of the second search formula.
Preferably, during updating the preset ratio excellent individual according to individual evaluation result, when second
There is the individual of update failure in group and the individual continuously the update frequency of failure reaches default when updating threshold value, using search bee with
The individual that machine generates substitutes the individual of update failure, to can not find other more excellent individuals near an individual when observation bee
When, by investigating bee transfer search region, improve search efficiency.
In step S104, judge whether the number of the first and second individual evaluations is more than default evaluation number, is to hold
Row step S106, it is no to then follow the steps S105.
In embodiments of the present invention, in initialization, the evaluation number of the first and second individual evaluations (is referred to as commenting
Valence total degree) it is 0, when often completing evaluation individual in one time first or the second neighborhood, evaluation total degree is updated, when
When evaluating total degree and being more than preset evaluation number, execution step S106 is no to then follow the steps S105.
In step S105, when the number of the first and second individual evaluations is no more than default evaluation number, by second
Group is set as initial population.
In embodiments of the present invention, when the number of the first and second individual evaluations is no more than default evaluation number, by the
Two populations are set as the initial population of next iterative process, then jump to step S102, with enter price adjustment model price adjustment because
The following iteration optimization process of son.
In step s 106, when the number of the first and second individual evaluations is more than default evaluation number, by first and the
The maximum individual of fitness is determined as the optimal price adjustment factor set of price adjustment model in two optimum individuals.
It in embodiments of the present invention, will when the evaluation number of the first and second individual evaluations is more than default evaluation number
The maximum individual of fitness is determined as the optimal price adjustment factor set of price adjustment model, completion pair in first and second optimum individuals
The solution procedure of the price adjustment model optimal solution of foundation.
In embodiments of the present invention, medical services data are extracted in HIS databases, are established price adjustment model and are generated
Initial population employs bee to carry out neighborhood search, carries out the first individual evaluation to the fitness of each individual, and generate the first
Group obtains the first optimum individual in the first population, then observes bee and carries out neighborhood search, to the fitness of each individual progress the
Two individual evaluations, and the second population is generated, the second optimum individual in the second population is obtained, when evaluation number is more than default evaluation time
When number, the maximum individual of fitness in the first and second optimum individuals is determined as to the optimal price adjustment factor of price adjustment model
Otherwise group jumps to and bee is employed to carry out neighborhood search, to by the cooperation of all kinds of honeybees in artificial bee colony, find optimal doctor
Service price adjustment scheme is treated, changes hospital revenue and depends on medical instrument present situation unduly, and then improve medical worker in medical services
Skilled labour is worth.
Embodiment two：
Fig. 2 shows the structures of medical service price adjustment device provided by Embodiment 2 of the present invention, for convenience of description,
Illustrate only with the relevant part of the embodiment of the present invention, including：
Model foundation unit 21 is established for extracting target medical data in HIS databases according to target medical data
Price adjustment model for adjusting medical service prices, and generate the initial population of price adjustment model；
The first group of generation units 22, for passing through the local optimum individual in initial population in each individual neighbor scope
Guiding employs bee and carries out the first neighborhood search, and the first individual evaluation is carried out to the fitness of each individual in the first neighborhood, according to
First individual evaluation result updates each local optimum individual in initial population, and generates the first population, obtains in the first population
First optimum individual；
Second group of generation units 23 pass through default ratio for choosing preset ratio excellent individual in the first population
Example excellent individual guiding observation bee carries out the second neighborhood search, and second is carried out to the fitness of each individual in the second neighborhood
Body is evaluated, and is updated preset ratio excellent individual according to the second individual evaluation result, and generate the second population, is obtained the second population
In the second optimum individual；And
Output unit 24 is recycled, for when the number of the first and second individual evaluations is more than default evaluation number, by the
One and second the maximum individual of fitness in optimum individual be determined as the optimal price adjustment factor set of price adjustment model, otherwise by
Two populations are set as initial population, and trigger the first group of generation unit units 22 and execute through each individual neighbour in initial population
It occupies the guiding of the local optimum individual in range and employs bee the first neighborhood search of progress.
Wherein, model foundation unit 21 further includes：
Data processing unit 211 carries out target medical data for extracting target medical data in HIS databases
Outlier detection and amendment carry out logarithmetics processing to revised target medical data, with the target medical treatment that obtains that treated
Data；And
Initial population generation unit 212, for target medical data to be established for adjusting medical services according to treated
The price adjustment model of price carries out the price adjustment factor for factor set of readjusting prices in price adjustment model by preset clustering algorithm
Subregion is clustered, and generates the initial population of price adjustment model.
Second group of generation units 23 further include：
Individual substituting unit 231, for connecting when the individual that there is the individual for updating failure and update failure in the second population
When the continuous update frequency of failure reaches default update threshold value, the individual of update failure is substituted using the individual that search bee generates at random.
In embodiments of the present invention, medical services data are extracted in HIS databases, are established price adjustment model and are generated
Initial population employs bee to carry out neighborhood search, carries out the first individual evaluation to the fitness of each individual, and generate the first
Group obtains the first optimum individual in the first population, then observes bee and carries out neighborhood search, to the fitness of each individual progress the
Two individual evaluations, and the second population is generated, the second optimum individual in the second population is obtained, when evaluation number is more than default evaluation time
When number, the maximum individual of fitness in the first and second optimum individuals is determined as to the optimal price adjustment factor of price adjustment model
Otherwise group jumps to and bee is employed to carry out neighborhood search, to by the cooperation of all kinds of honeybees in artificial bee colony, find optimal doctor
Service price adjustment scheme is treated, personnel rationally adjust medical service prices with Added Management, change hospital revenue and depend on unduly
Medical instrument present situation, and then improve the skilled labour value of medical worker in medical services.
In embodiments of the present invention, each unit of medical service price adjustment device can be by corresponding hardware or software unit
It realizes, each unit can be independent soft and hardware unit, can also be integrated into a soft and hardware unit, herein not limiting
The present invention.The specific implementation mode of each unit can refer to the description of embodiment one, and details are not described herein.
Embodiment three：
Fig. 3 shows that the structure for the server that the embodiment of the present invention three provides illustrates only and this hair for convenience of description
The bright relevant part of embodiment.
The server of the embodiment of the present invention includes processor 30, memory 31 and is stored in memory 31 and can locate
The computer program 32 run on reason device 30.The processor 30 realizes above-mentioned medical service prices tune when executing computer program 32
Step in adjusting method embodiment, such as step S101 to S106 shown in FIG. 1.Alternatively, processor 30 executes computer program
The function of each unit in above-mentioned medical service price adjustment device embodiment, such as unit 21 to 24 shown in Fig. 2 are realized when 32
Function.
In embodiments of the present invention, when which executes computer program, medical services number is extracted in HIS databases
According to establishing price adjustment model and generate initial population, bee is employed to carry out neighborhood search, to the fitness of each individual progress the
One individual evaluation, and the first population is generated, the first optimum individual in the first population is obtained, bee is then observed and carries out neighborhood search,
Second individual evaluation is carried out to the fitness of each individual, and generates the second population, obtains the second optimum individual in the second population,
When it is more than to preset evaluation number to evaluate number, the maximum individual of fitness in the first and second optimum individuals is determined as price
Otherwise the optimal price adjustment factor set for adjusting model jumps to and bee is employed to carry out neighborhood search, to by all kinds of in artificial bee colony
Optimal medical services price adjustment scheme is found in the cooperation of honeybee, and with Added Management, personnel rationally adjust medical service prices
It is whole, change hospital revenue and depend on medical instrument present situation unduly, and then improves the skilled labour value of medical worker in medical services.
The processor realizes that the step in above-mentioned medical service price adjustment embodiment of the method can when executing computer program
The description of reference implementation example one, details are not described herein.
Example IV：
In embodiments of the present invention, a kind of computer readable storage medium is provided, which deposits
Computer program is contained, which realizes when being executed by processor in above-mentioned medical service price adjustment embodiment of the method
The step of, such as step S101 to S106 shown in FIG. 1.Alternatively, the computer program realizes above-mentioned doctor when being executed by processor
Treat the function of each unit in service price adjusting apparatus embodiment, such as the function of unit 21 to 24 shown in Fig. 2.
In embodiments of the present invention, after which is executed by processor, medical services are extracted in HIS databases
Data establish price adjustment model and generate initial population, and bee is employed to carry out neighborhood search, are carried out to the fitness of each individual
First individual evaluation, and the first population is generated, the first optimum individual in the first population is obtained, bee progress neighborhood is then observed and searches
Rope carries out the second individual evaluation to the fitness of each individual, and generates the second population, obtains in the second population second optimal
The maximum individual of fitness in first and second optimum individuals is determined as by body when it is more than to preset evaluation number to evaluate number
Otherwise the optimal price adjustment factor set of price adjustment model jumps to and bee is employed to carry out neighborhood search, to by artificial bee colony
Optimal medical services price adjustment scheme is found in the cooperation of all kinds of honeybees, and with Added Management, personnel close medical service prices
Reason adjustment changes hospital revenue and depends on medical instrument present situation unduly, and then improves the skilled labour of medical worker in medical services
Value.
The computer program realizes the step in above-mentioned medical service price adjustment embodiment of the method when being executed by processor
The description of embodiment one is can refer to, details are not described herein.
The computer readable storage medium of the embodiment of the present invention may include can carry computer program code any
Entity or device, recording medium, for example, the memories such as ROM/RAM, disk, CD, flash memory.
The foregoing is merely illustrative of the preferred embodiments of the present invention, is not intended to limit the invention, all essences in the present invention
All any modification, equivalent and improvement etc., should all be included in the protection scope of the present invention made by within refreshing and principle.
Claims (10)
1. a kind of medical service price adjustment method, which is characterized in that the method includes following step：
Target medical data is extracted in HIS databases, is established according to the target medical data for adjusting medical services valence
The price adjustment model of lattice, and generate the initial population of the price adjustment model；
Bee, which is employed, by the local optimum individual guiding in the initial population in each individual neighbor scope carries out the first neighborhood
Search carries out the first individual evaluation, more according to the first individual evaluation result to the fitness of each individual in first neighborhood
Each local optimum individual in the new initial population, and the first population is generated, first optimal is obtained in first population
Body；
Preset ratio excellent individual is chosen in first population, is guided and is observed by the preset ratio excellent individual
Bee carries out the second neighborhood search, the second individual evaluation is carried out to the fitness of each individual in second neighborhood, according to second
Individual evaluation result updates the preset ratio excellent individual, and generates the second population, obtains second in second population
Optimum individual；
When the number of first and second individual evaluation is more than default evaluation number, by first and second optimum individual
The middle maximum individual of fitness is determined as the optimal price adjustment factor set of the price adjustment model, otherwise sets second population
It is set to the initial population, jumps to and is employed by the local optimum individual guiding in initial population in each individual neighbor scope
Bee carries out the first neighborhood search.
2. the method as described in claim 1, which is characterized in that target medical data is extracted in HIS databases, according to described
Target medical data establishes the price adjustment model for adjusting medical service prices, and generates the first of the price adjustment model
The step of beginning population, including：
The target medical data is extracted in HIS databases, and outlier detection and amendment are carried out to the target medical data,
Logarithmetics processing is carried out to the revised target medical data, with the target medical data that obtains that treated；
Treated that the target medical data establishes the price adjustment model for adjusting medical service prices according to described, leads to
It crosses preset clustering algorithm and cluster subregion is carried out to the price adjustment factor for factor set of readjusting prices in the price adjustment model, and generate institute
State the initial population of price adjustment model.
3. the method as described in claim 1, which is characterized in that update the preset ratio according to the second individual evaluation result
The step of excellent individual, including：
When the continuous update frequency of failure of individual for the individual and described update failure that there is update failure in second population reaches
When to default update threshold value, the individual of the update failure is substituted using the individual that search bee generates at random.
4. the method as described in claim 1, which is characterized in that by the preset ratio excellent individual guide observation bee into
The step of the second neighborhood search of row, including：
The preset ratio excellent individual is divided into first part's individual and second according to default first probability and the second probability
Some individuals, the sum of first probability and the second probability are 1；
It guides the observation bee to search for formula using preset first by first part's individual and carries out second neighborhood
Search, and guide the observation bee adjacent using preset second search formula progress described second by the second part individual
Domain search.
5. method as claimed in claim 4, which is characterized in that guide the observation bee to use by first part's individual
Preset first search formula carries out second neighborhood search, and guides the observation bee to adopt by the second part individual
The step of formula carries out second neighborhood search is searched for preset second, including：
When the fitness that the first search formula searches individual is more than the fitness of first part individual, institute is obtained
State the promotion degree of the first search formula；
When the fitness that the second search formula searches individual is more than the fitness of second part individual, institute is obtained
State the promotion degree of the second search formula；
The promotion degree of the promotions degree and the second search formula of searching for formula according to described first update first probability with
Second probability；
Judge whether the number of the selection is more than default selected threshold, when the selection number is not up to the selected threshold
When, jump to according to preset the first probability and the second probability by the preset ratio excellent individual be divided into first part's individual with
Second part individual.
6. a kind of medical service price adjustment device, which is characterized in that described device includes：
Model foundation unit is established according to the target medical data and is used for extracting target medical data in HIS databases
In the price adjustment model of adjustment medical service prices, and generate the initial population of the price adjustment model；
The first group of generation units, for being drawn by the local optimum individual in the initial population in each individual neighbor scope
It leads and employs bee the first neighborhood search of progress, the first individual evaluation, root are carried out to the fitness of each individual in first neighborhood
Each local optimum individual in the initial population is updated according to the first individual evaluation result, and generates the first population, described in acquisition
First optimum individual in first population；
Second group of generation units, for choosing preset ratio excellent individual in first population, by described default
Ratio excellent individual guiding observation bee carries out the second neighborhood search, is carried out to the fitness of each individual in second neighborhood
Second individual evaluation updates the preset ratio excellent individual according to the second individual evaluation result, and generates the second population, obtains
Take the second optimum individual in second population；And
Output unit is recycled, is used for when the number of first and second individual evaluation is more than default evaluation number, it will be described
The maximum individual of fitness is determined as the optimal price adjustment factor set of the price adjustment model in first and second optimum individuals, no
It then sets second population to the initial population, jumps to through the office in initial population in each individual neighbor scope
Portion's optimum individual guiding employs bee and carries out the first neighborhood search.
7. device as claimed in claim 6, which is characterized in that the model foundation unit further includes：
Data processing unit carries out the target medical data abnormal for extracting target medical data in HIS databases
It value analysis and corrects, logarithmetics processing is carried out to the revised target medical data, with the target that obtains that treated
Medical data；And
Initial population generation unit, for treated according to, the target medical data is established for adjusting medical services
The price adjustment model of price, by preset clustering algorithm to the price adjustment factor for factor set of readjusting prices in the price adjustment model
Cluster subregion is carried out, and generates the initial population of the price adjustment model.
8. device as claimed in claim 6, which is characterized in that the second group of generation units further include：
Individual substituting unit, for connecting when the individual that there is the individual and described update failure for updating failure in second population
When the continuous update frequency of failure reaches default update threshold value, of the update failure is substituted using the individual that search bee generates at random
Body.
9. a kind of server, including memory, processor and it is stored in the memory and can transports on the processor
Capable computer program, which is characterized in that the processor realizes such as claim 1 to 5 times when executing the computer program
The step of one the method.
10. a kind of computer readable storage medium, the computer-readable recording medium storage has computer program, feature to exist
In when the computer program is executed by processor the step of any one of such as claim 1 to 5 of realization the method.
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