CN115330569A - Automatic balancing method for burden difference and medical resources of children tumor diseases - Google Patents
Automatic balancing method for burden difference and medical resources of children tumor diseases Download PDFInfo
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Abstract
The invention provides an automatic balancing method for burden difference and medical resources of children tumor diseases, which comprises the following steps: acquiring child disease diagnosis data based on a medical insurance database, and screening the disease diagnosis data to obtain child tumor disease data; analyzing the children tumor disease data, determining a children tumor disease frequency index and a medical resource utilization index, and determining the burden difference of the children tumor disease; and formulating a medical resource balancing strategy based on the burden difference of the children tumor diseases, and balancing the medical resources of the children tumor diseases based on the medical resource balancing strategy. The frequency index of the tumor diseases of the children and the utilization index of the medical resources are accurately and effectively analyzed, so that the burden difference of the diseases is accurately obtained, and the medical resources are effectively balanced through the burden difference, so that the burden of the diseases and the medical resources are effectively balanced, and the utilization effect of the medical resources is guaranteed.
Description
Technical Field
The invention relates to the technical field of medical data processing, in particular to an automatic balancing method for burden difference and medical resources of children tumor diseases.
Background
Currently, china, as the largest developing and most populated countries in the world, has the largest number of childhood cancer patients in the world, with over 4.5 million new cases per year, and their number and proportion are rapidly increasing, however, no research is involved with childhood cancer burden, while these population-based studies do not take into account the burden of health care utilization, which is an important measure of health accessibility and disease prognosis;
the current standard medical resources cannot be automatically balanced with the burden of diseases in real time, so that the medical resources are unreasonably utilized and distributed, and the treatment effect of different areas or on the tumor diseases of children is reduced;
thus, the present invention provides an automatic balancing method for burden difference and medical resources of neoplastic diseases in children.
Disclosure of Invention
The invention provides an automatic balancing method for burden difference of children tumor diseases and medical resources, which is used for analyzing data of the children tumor diseases to accurately and effectively analyze frequency indexes of the children tumor diseases and utilization indexes of the medical resources, so that the burden difference of the diseases is accurately obtained, and the medical resources are effectively balanced through the burden difference, so that the effective balance of the burden of the diseases and the medical resources is realized, and the utilization effect of the medical resources is guaranteed.
The invention provides an automatic balancing method for burden difference and medical resources of children tumor diseases, which comprises the following steps:
step 1: acquiring child disease diagnosis data based on a medical insurance database, and screening the disease diagnosis data to obtain child tumor disease data;
step 2: analyzing the children tumor disease data, determining a children tumor disease frequency index and a medical resource utilization index, and determining the burden difference of the children tumor disease based on the tumor disease frequency index and the medical resource utilization index;
and step 3: and formulating a medical resource balancing strategy based on the burden difference of the children tumor diseases, and balancing the medical resources of the children tumor diseases based on the medical resource balancing strategy.
Preferably, the method for automatically balancing the burden difference of the children tumor diseases and the medical resources comprises the following steps of 1, acquiring the diagnosis data of the children tumor diseases based on a medical insurance database, wherein the diagnosis data comprises:
acquiring a data calling request, analyzing the data calling request, and determining a service data type corresponding to the data calling request;
extracting the type identification of the business data type, accessing the medical insurance database based on the type identification, matching with an index table of the medical insurance database, and determining a target data layer where the business data type is located;
and extracting child disease diagnosis data corresponding to the service data type based on the target data layer, and packaging and transmitting the child disease diagnosis data to a data access terminal.
Preferably, the method for automatically balancing burden difference of the children's tumor diseases and medical resources, wherein the step 1 of screening the disease diagnosis data to obtain the children's tumor disease data comprises:
acquiring the obtained child disease diagnosis data, acquiring historical child tumor disease data, and extracting data characteristics of the historical child tumor disease data;
taking the data characteristics as target conditions, and taking the target conditions as a clustering center to perform clustering processing on the child disease diagnosis data;
and determining the Hamming distance between the child disease diagnosis data and the target condition based on the clustering processing result, judging the child disease diagnosis data with the Hamming distance smaller than a preset threshold value as child tumor disease data, and finishing the screening of the child disease diagnosis data.
Preferably, the method for automatically balancing the burden difference of the children tumor diseases and the medical resources is used for completing screening of the children disease diagnosis data, and comprises the following steps:
acquiring the obtained children tumor disease data, and extracting the basic information of children from the children tumor disease data, wherein the basic information comprises age, gender and ethnicity;
verifying the extracted basic information and judging whether the basic information of the children is missing or not;
if the basic information of the children is missing, judging the children corresponding to the current basic information as abnormal individuals, and removing the current basic information to obtain standard children tumor disease data;
otherwise, judging that the basic information corresponding to the child is finished, and finishing the verification of the basic information.
Preferably, the method for automatically balancing the burden difference of the pediatric neoplastic disease and the medical resources to obtain the standard pediatric neoplastic disease data comprises:
acquiring the obtained standard children tumor disease data, and determining the age bracket of an individual corresponding to the children tumor disease data based on the basic information of the standard children tumor disease data;
performing first classification on the standard child tumor disease data based on the age groups to obtain first classification results, and determining the gender of an individual corresponding to the standard child tumor disease data in each first classification based on the first classification results;
performing second classification on the first classification result based on the gender to obtain a second classification result, and determining the ethnicity of the individual corresponding to the standard child tumor disease data in each second classification based on the second classification result;
and performing third classification on the second classification result based on the ethnicity to obtain a third classification result, determining privacy data in the basic information of the standard children tumor disease data based on the third classification result, and performing anonymization processing on the privacy data.
Preferably, the method for automatically balancing burden difference of children's tumor diseases and medical resources, in step 2, analyzing the data of children's tumor diseases to determine a frequency index of children's tumor diseases and a utilization index of medical resources, includes:
acquiring the obtained children tumor disease data, and determining classification indexes of the children tumor disease data, wherein the classification indexes comprise age, gender and nationality;
classifying the children tumor disease data based on the classification indexes to obtain a target subdata set, and determining the number of newly-increased children tumor patients in the current year and the total number of susceptible children in the current year in each target subdata in the target subdata set;
determining the incidence rate corresponding to each target subdata based on the number of newly-increased children tumor patients in the current year and the total number of susceptible children in the current year;
meanwhile, determining the number of children patients diagnosed and living to the current year before the target time period and the number of people participating in the current year in each target subdata, and determining the prevalence rate of the target time period corresponding to each target subdata based on the number of children patients diagnosed and living to the current year before the target time period and the number of people participating in the current year;
and obtaining the child tumor disease frequency index based on the morbidity and the morbidity of the target time period.
Preferably, the method for automatically balancing the burden difference of the child tumor disease and the medical resource, in step 2, analyzing the child tumor disease data to determine a child tumor disease frequency index and a medical resource utilization index, further includes:
acquiring the obtained children tumor disease data, and grouping the children tumor disease data based on gender, age and nationality to obtain a sub-data group;
generating a treatment expense access request based on the children tumor disease data in each sub data set, and accessing a preset patient treatment expense use database based on the treatment expense access request;
acquiring the total medical insurance reimbursement cost of each child patient within one year after the diagnosis is confirmed based on the preset patient treatment cost usage database, determining the medical insurance reimbursement proportion, and obtaining the treatment cost corresponding to each sub-data group based on the medical insurance reimbursement proportion and the total medical insurance reimbursement cost;
acquiring a consumption index of the current year, and correcting the total medical insurance reimbursement cost based on the consumption index to obtain the treatment cost of the patient corresponding to each sub-data set;
meanwhile, the name of the medical institution for the patient of each child and the total number of the medical institutions for the patient are extracted from the data of the children tumor diseases, and the name characteristics of the names of the medical institutions for the patient are sequentially determined based on the total number of the medical institutions for the patient, wherein at least one name of the medical institution for the patient is selected;
the names of the medical institutions for treatment are deduplicated based on the name features to obtain a target medical institution name set for treatment, and each target medical institution name in the target medical institution name set for treatment is searched in a preset medical institution grade search library to obtain the medical grade of each target medical institution for treatment;
drawing a medical treatment institution flow graph of each child patient based on the total number of medical treatment institutions for each child patient, and performing grade marking on each medical treatment institution based on the medical grade of each target medical treatment institution in the medical treatment institution flow graph;
obtaining the flow direction information of the medical treatment institution of each child patient based on the labeling result;
and obtaining a medical resource utilization index based on the treatment cost of the patient and the flow information of the medical institution.
Preferably, the method for automatically balancing the burden difference of the pediatric neoplastic diseases and the medical resources, wherein in step 2, the determining the burden difference of the pediatric neoplastic diseases based on the neoplastic disease frequency index and the medical resource utilization index comprises:
acquiring a tumor disease frequency index and a medical resource utilization index, and determining the number of children suffering from tumor diseases in each year based on the tumor disease frequency index;
meanwhile, determining the treatment cost and the type of a medical institution for treatment of each child patient with the tumor disease based on the medical resource utilization index;
the difference in the burden of childhood neoplastic disease is based on the number of childhood neoplastic diseases that are present per year and the cost of treatment and type of medical facility in which the visit is made.
Preferably, the method for automatically balancing burden difference of children's tumor diseases and medical resources, in step 3, a medical resource balancing strategy is formulated based on the burden difference of children's tumor diseases, and medical resources of children's tumor diseases are balanced based on the medical resource balancing strategy, includes:
acquiring the obtained burden difference of the child tumor disease, and determining the treatment expense payment capacity of the family suffering from the child tumor disease and the treatment grade of the medical institution;
constructing a medical resource balance strategy based on the treatment expense payment capacity and the treatment grade of the medical institution, and grading the treatment grade of the medical institution based on the medical resource balance strategy;
determining a target medical resource set required by the children tumor disease in the treatment process, and performing resource access on a preset medical resource distribution center based on the target medical resource set;
determining medical resource storage information of the preset medical resource distribution center based on the resource access, and determining the distribution amount of medical resources of the medical treatment structure with different treatment levels based on the medical resource storage information;
determining the treatment quantity of the medical treatment structure for treating the children tumor diseases, the utilization rate of the medical resources and the material loss coefficient based on the tumor disease frequency index and the medical resource utilization index, and correcting the distribution quantity of the medical resources based on the treatment quantity of the children tumor diseases, the utilization rate of the medical resources and the material loss coefficient to obtain the target distribution quantity of the medical resources of the medical treatment structure for treating different treatment grades;
simultaneously, determining the geographic position characteristics of the medical treatment structures of different treatment levels, and determining the step payment cost of medical resources required by the medical treatment institutions for the child tumor diseases with different degrees of illness based on the geographic position characteristics;
and completing the balance processing of the medical resources based on the target allocation amount of the medical resources and the payment for the ladder payment of the medical resources.
Preferably, the method for automatically balancing the burden difference of the children tumor diseases and the medical resources is used for completing the balancing treatment of the medical resources, and comprises the following steps:
acquiring a balance processing result of the medical resources, and monitoring medical resource storage information of a preset medical resource distribution center, treatment grades of medical institutions for treatment and treatment quantity of the children tumor diseases by different medical institutions for treatment in real time based on the balance processing result;
and when the medical resource storage information of the preset medical resource distribution center, the treatment grade of the medical treatment institution and the treatment quantity of the different medical treatment institutions for treating the children tumor diseases are judged to be changed based on the monitoring result, the medical resources are subjected to balance treatment again.
Additional features and advantages of the invention will be set forth in the description which follows, and in part will be obvious from the description, or may be learned by the practice of the invention. The objectives and other advantages of the invention will be realized and attained by the structure particularly pointed out in the written description and claims hereof as well as the appended drawings.
The technical solution of the present invention is further described in detail by the accompanying drawings and embodiments.
Drawings
The accompanying drawings, which are included to provide a further understanding of the invention and are incorporated in and constitute a part of this specification, illustrate embodiments of the invention and together with the description serve to explain the principles of the invention and not to limit the invention. In the drawings:
FIG. 1 is a flow chart of a method for automatically balancing burden difference and medical resources for pediatric neoplastic disease in accordance with an embodiment of the present invention;
FIG. 2 is a flowchart of step 1 of the method for automatically balancing burden difference and medical resources for pediatric neoplastic disease according to an embodiment of the present invention;
FIG. 3 is a flowchart of step 2 of the method for automatically balancing the burden difference of the neoplastic disease in children with medical resources according to the embodiment of the present invention.
Detailed Description
The preferred embodiments of the present invention will be described in conjunction with the accompanying drawings, and it will be understood that they are described herein for the purpose of illustration and explanation and not limitation.
Example 1:
the embodiment provides an automatic balancing method for burden difference and medical resources of children tumor diseases, as shown in fig. 1, comprising the following steps:
step 1: acquiring child disease diagnosis data based on a medical insurance database, and screening the disease diagnosis data to obtain child tumor disease data;
and 2, step: analyzing the children tumor disease data, determining a children tumor disease frequency index and a medical resource utilization index, and determining the burden difference of the children tumor disease based on the tumor disease frequency index and the medical resource utilization index;
and 3, step 3: and formulating a medical resource balancing strategy based on the burden difference of the children tumor diseases, and balancing the medical resources of the children tumor diseases based on the medical resource balancing strategy.
In this embodiment, the medical insurance database is set in advance and is used for storing disease diagnosis data, demographic characteristics, identification numbers, nationalities, cost information and the like of children of different genders and ages.
In this embodiment, the child disease diagnosis data refers to diagnosis data corresponding to various disease types occurring in the course of a visit of a child.
In this embodiment, the screening of the disease diagnosis data refers to determining the type of the acquired children disease diagnosis data, so as to extract children tumor disease data from the acquired disease diagnosis data.
In this embodiment, the pediatric tumor disease frequency index refers to the incidence of pediatric tumors and the prevalence within a certain time period.
In this embodiment, the medical resource utilization index refers to the treatment cost of the child patient, the flow direction of the hospital, and the like.
In this embodiment, the difference in burden of the childhood tumor disease refers to a difference in burden of the childhood tumor disease on the family treatment cost, the degree of influence of the morbidity and mortality of the childhood tumor disease on the society, the severity of the childhood tumor disease, and the like.
In this embodiment, the medical resource balancing policy refers to a method of automatically balancing medical resources according to the burden difference of diseases.
The beneficial effects of the above technical scheme are: through analyzing the children tumor disease data, the frequency index of the children tumor disease and the utilization index of the medical resources are accurately and effectively analyzed, so that the burden difference of the diseases is accurately acquired, and finally, the medical resources are effectively balanced through the burden difference, so that the burden of the diseases and the medical resources are effectively balanced, and the utilization effect of the medical resources is guaranteed.
Example 2:
on the basis of embodiment 1, this embodiment provides an automatic balancing method for burden difference and medical resources of children's tumor diseases, as shown in fig. 2, in step 1, acquiring children's disease diagnosis data based on a medical insurance database, including:
acquiring a data calling request, analyzing the data calling request, and determining a service data type corresponding to the data calling request;
extracting the type identification of the business data type, accessing the medical insurance database based on the type identification, matching with an index table of the medical insurance database, and determining a target data layer where the business data type is located;
and extracting child disease diagnosis data corresponding to the service data type based on the target data layer, and packaging and transmitting the child disease diagnosis data to a data access terminal.
In this embodiment, the data retrieval request is generated by the data access terminal for accessing the medical insurance database.
In this embodiment, the service data type refers to a data type to be retrieved included in the data retrieval request, and may specifically be disease diagnosis data or identity information and the like
In this embodiment, the type identifier is a tag label used to tag different service data types, so as to facilitate corresponding data retrieval operations according to the type identifier.
In this embodiment, the target data layer refers to a data application layer corresponding to the type of business data stored in the medical insurance database.
The beneficial effects of the above technical scheme are: through analyzing the data calling request, the data types needing to be called are accurately and effectively judged, so that corresponding data are called from the medical insurance database, convenience is provided for determining the burden difference of the tumor diseases of the children, and convenience is provided for balancing the burden difference and medical resources.
Example 3:
on the basis of embodiment 1, this embodiment provides an automatic balancing method for burden difference and medical resources of a pediatric neoplastic disease, as shown in fig. 3, the screening of the disease diagnosis data in step 1 to obtain pediatric neoplastic disease data includes:
acquiring the obtained child disease diagnosis data, acquiring historical child tumor disease data, and extracting data characteristics of the historical child tumor disease data;
taking the data characteristics as target conditions, and taking the target conditions as a clustering center to perform clustering processing on the child disease diagnosis data;
and determining the Hamming distance between the child disease diagnosis data and the target condition based on the clustering processing result, judging the child disease diagnosis data with the Hamming distance smaller than a preset threshold value as child tumor disease data, and finishing the screening of the child disease diagnosis data.
In this embodiment, the historical data of the childhood tumor disease is set in advance, and is used to provide a reference basis for screening the data of the childhood tumor disease from the data of the childhood tumor disease diagnosis.
In this embodiment, the target condition refers to the condition for screening the children's tumor disease data as the children's disease diagnosis data, so as to realize effective screening of the children's disease diagnosis data.
In this embodiment, the data characteristics refer to the value characteristics of the data of the neoplastic disease in children, the association characteristics between the data, and the like.
In this embodiment, the hamming distance is used to characterize the distance between the child disease diagnosis data and the target condition, and a smaller hamming distance indicates that the child disease diagnosis data satisfies the current target condition, i.e. the child tumor disease data is about likely to be.
In this embodiment, the preset threshold is set in advance, and is used for measuring the maximum range that can satisfy the target condition, and may be adjusted.
The beneficial effects of the above technical scheme are: the data characteristics of the children's tumor diseases are determined, so that the children's disease diagnosis data can be accurately and effectively screened according to the data characteristics, the reliability of the children's tumor disease data selected from the children's disease diagnosis data is ensured, and the accurate judgment of the disease burden difference is guaranteed.
Example 4:
on the basis of embodiment 3, this embodiment provides an automatic balancing method for burden difference and medical resources of children's tumor diseases, and completes screening of children's disease diagnosis data, including:
acquiring the obtained children tumor disease data, and extracting the basic information of children from the children tumor disease data, wherein the basic information comprises age, gender and nationality;
verifying the extracted basic information and judging whether the basic information of the children is missing or not;
if the basic information of the children is missing, judging the children corresponding to the current basic information as abnormal individuals, and removing the current basic information to obtain standard children tumor disease data;
otherwise, judging that the basic information corresponding to the child is finished, and finishing the verification of the basic information.
In this embodiment, verifying the extracted basic information means verifying the age, sex, nationality, and the like included in the acquired basic information of the child, respectively, and verifying whether or not there is a child whose basic information is missing.
In this embodiment, the abnormal individual refers to a child with a missing basic information.
In this embodiment, the step of labeling the data of the child tumor disease refers to the final data of the child tumor disease obtained by extracting data with information missing in the obtained data of the child tumor disease.
The beneficial effects of the above technical scheme are: the acquired children's tumor disease data are verified, and the children's tumor disease data with basic information loss are removed, so that the accuracy of the finally obtained children's tumor disease data is guaranteed, and convenience and guarantee are provided for guaranteeing the accuracy of the burden difference of the children's tumor diseases.
Example 5:
on the basis of embodiment 4, this embodiment provides an automatic balancing method for burden difference and medical resources of children's tumor diseases, and obtains standard children's tumor disease data, including:
acquiring the obtained standard children tumor disease data, and determining the age bracket of an individual corresponding to the children tumor disease data based on the basic information of the standard children tumor disease data;
performing first classification on the standard children tumor disease data based on the age groups to obtain first classification results, and determining the sex of an individual corresponding to the standard children tumor disease data in each first classification based on the first classification results;
performing second classification on the first classification result based on the gender to obtain a second classification result, and determining the ethnicity of the individual corresponding to the standard child tumor disease data in each second classification based on the second classification result;
and performing third classification on the second classification result based on the ethnicity to obtain a third classification result, determining privacy data in the basic information of the standard children tumor disease data based on the third classification result, and performing anonymization processing on the privacy data.
In this embodiment, the first classification refers to classifying the children's tumor disease data according to age, specifically, children aged 0-14 years, and children aged 0-4 years, children aged 5-9 years, and children aged 10-14 years are classified into one group.
In this embodiment, the second classification refers to classifying the data of the neoplastic disease of children belonging to the same sex in each age group into one group according to the result of the first classification.
In this embodiment, the third classification refers to classifying the data of the neoplastic disease of children of the same family in the same sex into one group according to the second classification result.
In this embodiment, the anonymization process refers to anonymizing the private data in each class according to the final classification result, where the private data may specifically be the name of the child, and the like.
The beneficial effects of the above technical scheme are: the obtained standard children tumor disease data are classified according to age groups, sexes and nationalities, anonymization processing is carried out on the privacy data of the children according to classification results, protection of children privacy is guaranteed, and meanwhile convenience and guarantee are provided for accurately judging burden difference of the children tumor diseases.
Example 6:
on the basis of embodiment 1, this embodiment provides an automatic balancing method for burden difference and medical resources of a child tumor disease, and in step 2, analyzing the child tumor disease data to determine a child tumor disease frequency index and a medical resource utilization index, including:
acquiring the obtained children tumor disease data, and determining classification indexes of the children tumor disease data, wherein the classification indexes comprise age, gender and nationality;
classifying the children tumor disease data based on the classification indexes to obtain a target subdata set, and determining the number of newly-increased children tumor patients in the current year and the total number of susceptible children in the current year in each target subdata in the target subdata set;
determining the incidence rate corresponding to each target subdata based on the number of newly-increased children tumor patients in the current year and the total number of susceptible children in the current year;
meanwhile, determining the number of children patients diagnosed and living to the current year before the target time period and the number of people participating in the current year in each target subdata, and determining the prevalence rate of the target time period corresponding to each target subdata based on the number of children patients diagnosed and living to the current year before the target time period and the number of people participating in the current year;
and obtaining the child tumor disease frequency index based on the morbidity and the morbidity of the target time period.
In this embodiment, the classification index refers to a standard for classifying the data of the child tumor diseases, so that the data of the child tumor diseases are effectively classified, and convenience is provided for accurately determining the frequency index of the child tumor diseases.
In this embodiment, the target sub-data sets refer to categories obtained by classifying the data of the pediatric tumor diseases according to the classification indexes.
In this example, the susceptible total number of children refers to the total number of susceptible children, which is considered to be the total number of all eligible study populations participating in the year, since children's tumors are rare diseases and the incidence rate is generally below 300 per million.
In this embodiment, the target time period is set in advance, typically five years.
In this embodiment, acquire newly-increased children tumor patient number in this year and the susceptible children's total number of people of participating in the guarantor in this year in predetermineeing the age bracket to based on newly-increased children tumor patient number in this year and the susceptible children's total number of people of participating in the guarantor in this year calculate the incidence of disease of children tumor disease, and based on the incidence of disease calculates the life-span of children tumor disease to the sick children in predetermineeing the age bracket, concrete step includes:
the incidence of neoplastic disease in children was calculated according to the following formula:
wherein eta represents the incidence of the tumor diseases of the children, and the value range is (0, 1); alpha represents the number of people with the children tumor disease in a preset age group before a preset time period;
representing the number of people with the children tumor diseases in a preset age group after a preset time end, and the value is more than alpha; m represents the total number of susceptible children participating in the current year;
the life-reducing number of children with tumor diseases to sick children in a preset age group is calculated according to the following formula:
wherein T represents the number of life-reducing years of the sick child in a preset age group; mu represents an error factor, and the value range is (0.02, 0.05); i represents the current number of children with tumor in a predetermined age group, and the value range is [1,n ]](ii) a n represents the total number of children with tumor diseases in a preset age range; t represents tumor diseases in a preset age groupLife expectancy of the sick child; q i Representing the life value of the i-th child in the preset age group when the child dies; eta represents the incidence of the tumor diseases of the children, and the value range is (0, 1);
comparing the number of the life-reducing years obtained by calculation with a preset time threshold;
if the life-reducing number is less than or equal to a preset time threshold value, judging that the life-reducing number of the children with the tumor diseases to sick children in a preset age group is normal;
otherwise, judging that the life-reducing years of the children with the tumor diseases in the preset age group are abnormal, and influencing the residual life of the children with the tumor diseases in the preset age group.
The life expectancy is an ideal life value determined through a plurality of experiments.
The preset time threshold is set in advance and is used for measuring whether the life reduction years of the children in the preset age bracket exceed the normal attenuation range.
The beneficial effects of the above technical scheme are: the children tumor disease data are accurately and effectively classified according to the gender, the age and the nationality, and the incidence and the prevalence of each type of the children tumor disease are accurately and effectively analyzed according to the classification result, so that the frequency index of the children tumor disease is accurately and effectively acquired, and convenience and guarantee are provided for accurately determining the burden difference of the children tumor disease.
Example 7:
on the basis of embodiment 1, this embodiment provides an automatic balancing method for burden difference and medical resources of a child tumor disease, in step 2, analyzing the child tumor disease data to determine a child tumor disease frequency index and a medical resource utilization index, further including:
acquiring the obtained children tumor disease data, and grouping the children tumor disease data based on gender, age and nationality to obtain a sub-data group;
generating a treatment expense access request based on the children tumor disease data in each sub data set, and accessing a preset patient treatment expense use database based on the treatment expense access request;
acquiring the total medical insurance reimbursement cost of each child patient within one year after the diagnosis is confirmed based on the preset patient treatment cost usage database, determining the medical insurance reimbursement proportion, and obtaining the treatment cost corresponding to each sub-data group based on the medical insurance reimbursement proportion and the total medical insurance reimbursement cost;
acquiring a consumption index of the current year, and correcting the total medical insurance reimbursement cost based on the consumption index to obtain the treatment cost of the patient corresponding to each sub-data set;
meanwhile, the name of each medical institution for the patient of each child and the total number of the medical institutions for the patient are extracted from the data of the children tumor diseases, and the name characteristics of the medical institutions for the patient are sequentially determined based on the total number of the medical institutions for the patient, wherein at least one medical institution for the patient is provided;
removing the duplication of the names of the medical institutions for treatment based on the name characteristics to obtain a target medical institution name set, and searching each target medical institution name in the target medical institution name set in a preset medical institution grade search library to obtain the medical grade of each target medical institution for treatment;
drawing a medical treatment institution flow diagram of each child patient based on the total number of the medical treatment institutions of each child patient, and performing grade marking on each medical treatment institution based on the medical grade of each target medical treatment institution in the medical treatment institution flow diagram;
obtaining the medical institution flow direction information of each child patient for treatment based on the labeling result;
and obtaining a medical resource utilization index based on the treatment cost of the patient and the flow information of the medical institution.
In this embodiment, the sub-data set refers to each type of data obtained by classifying the data of the neoplastic disease in children according to gender, age, and ethnicity.
In this embodiment, the treatment cost access request is used to access a pre-set patient treatment cost usage database for the purpose of obtaining medical costs of children with childhood oncology diseases.
In this embodiment, the pre-set patient treatment cost usage database is pre-set for storing treatment costs of different children with childhood tumor diseases.
In this embodiment, the medical insurance reimbursement ratio is used to characterize the ratio of the self-fee to the reimbursement.
In this example, the consumption index is used to characterize the consumption level of the commodity price in the current year in order to correct the treatment cost of sick children.
In this embodiment, the visiting medical institution name refers to the name of the visiting medical institution.
In this embodiment, the name features refer to features of names of different medical institutions for treatment, including special characters and the like.
In this embodiment, the target medical institution name set refers to a medical institution name set that is obtained without duplication after the acquired medical institution names are deduplicated.
In this embodiment, the preset medical institution level search library is set in advance, and is used for storing treatment levels of different treatment levels, specifically, the treatment levels may be three-level or two-level, and the like.
In this embodiment, the visit medical facility flow diagram is for all hospitals that characterize a child's visit during the course of the visit.
The beneficial effects of the above technical scheme are: through analyzing children's tumor disease data, realize carrying out accurate effectual judgement to children's tumor disease treatment expense at the in-process of seeing a doctor, secondly, through analyzing children's tumor disease data, realize effectively obtaining the medical institution of seeing a doctor of the children that suffer from the disease of difference, through treatment expense and the medical institution flow direction of seeing a doctor, realize carrying out accurate effectual analysis to children's tumor disease's relevant medical resource utilization index, thereby for accurate analysis children's tumor disease's burden difference provide the guarantee, the rate of accuracy that the burden difference is confirmed has been ensured.
Example 8:
on the basis of embodiment 1, this embodiment provides an automatic balancing method for burden difference of children's tumor diseases and medical resources, and in step 2, determining the burden difference of children's tumor diseases based on the tumor disease frequency index and the medical resource utilization index includes:
acquiring a tumor disease frequency index and a medical resource utilization index, and determining the number of children suffering from tumor diseases in each year based on the tumor disease frequency index;
meanwhile, determining the treatment cost and the type of a medical institution for treatment of each child patient with the tumor disease based on the medical resource utilization index;
the difference in the burden of childhood neoplastic disease is based on the number of childhood neoplastic diseases that are present per year and the cost of treatment and type of medical facility in which the visit is made.
The beneficial effects of the above technical scheme are: the treatment cost and the number of patients suffering from the children tumor diseases are accurately and effectively grasped by reliably analyzing the data of the children tumor diseases according to the acquired frequency indexes of the children tumor diseases and the medical resource utilization indexes, and the burden difference of the children tumor diseases is accurately and effectively acquired through the treatment cost and the population characteristics, so that the medical resources are accurately and effectively balanced.
Example 9:
on the basis of embodiment 1, this embodiment provides an automatic balancing method for burden difference and medical resources of a pediatric neoplastic disease, and in step 3, a medical resource balancing policy is formulated based on the burden difference of the pediatric neoplastic disease, and the balancing of the medical resources of the pediatric neoplastic disease based on the medical resource balancing policy includes:
acquiring the obtained burden difference of the child tumor disease, and determining the treatment expense payment capacity of the family suffering from the child tumor disease and the treatment grade of the medical institution;
constructing a medical resource balance strategy based on the treatment expense payment capacity and the treatment grade of the medical institution, and grading the treatment grade of the medical institution based on the medical resource balance strategy;
determining a target medical resource set required by the children tumor disease in the treatment process, and performing resource access on a preset medical resource distribution center based on the target medical resource set;
determining medical resource storage information of the preset medical resource distribution center based on the resource access, and determining the distribution amount of medical resources of the medical treatment structure with different treatment levels based on the medical resource storage information;
determining the treatment quantity of the medical treatment structure for seeing a doctor on the children tumor diseases, the utilization rate of the medical resources and the material loss coefficient based on the tumor disease frequency index and the medical resource utilization index, and correcting the distribution quantity of the medical resources based on the treatment quantity of the children tumor diseases, the utilization rate of the medical resources and the material loss coefficient to obtain the target distribution quantity of the medical resources of the medical treatment structure for seeing a doctor at different treatment levels;
simultaneously, determining the geographic position characteristics of the medical treatment structures of different treatment levels, and determining the step payment cost of medical resources required by the medical treatment institutions for the child tumor diseases with different degrees of illness based on the geographic position characteristics;
the balancing process for the medical resource is completed based on the target allocation amount of the medical resource and the tiered payment for the medical resource.
In this embodiment, the medical resource balancing policy refers to a policy for realizing corresponding allocation and charging of medical resources according to the payment capability of different sick children and the treatment level of the medical institution.
In this embodiment, the set of target medical resources refers to medical resources that are needed in the treatment of pediatric tumors.
In this embodiment, the preset medical resource allocation center is set in advance, and is used for allocating the stored medical resources and storing and recording the existing medical resources.
In this embodiment, the medical resource storage information refers to the number and the type of the medical resources currently owned by the preset medical resource allocation center.
In this embodiment, determining the allocation amounts of the medical resources to the medical treatment facilities of different treatment levels based on the medical resource storage information means that the medical treatment facilities of higher treatment levels have an appropriate amount of multi-allocated medical resources.
In this embodiment, the material loss factor refers to a waste condition caused by the medical institution in the use process of the medical resource.
In this embodiment, the target dispensing amount refers to a medical resource that can be allocated to a different medical institution after correcting the determined dispensing amount.
In this embodiment, the geographic location feature is suitable for representing the geographic location of different medical institutions for medical treatment, and may specifically be a township, a county city, a province, and the like.
In this embodiment, the step payment means that the payment capability of the medical resource varies with the geographic location characteristics, and the charging condition of the medical resource with different degrees of illness is determined according to the payment capability and the location of the medical institution, specifically, the charging in the remote area is low, and the charging in the well-developed area is high.
The beneficial effects of the above technical scheme are: the payment capacity of families with the child tumor diseases and the treatment grade of the medical institution for seeing a doctor are accurately and effectively acquired according to the burden difference, the allocation amount of medical resources and the charging standard of the medical resources are accurately and reliably established according to the payment capacity of treatment cost and the treatment grade of the medical institution for seeing a doctor, so that the burden difference of the medical resources and the child tumor diseases is accurately and effectively balanced, great convenience is provided for different children with the child tumor diseases in the treatment process, and the treatment effect is improved.
Example 10:
on the basis of embodiment 9, this embodiment provides an automatic balancing method for burden difference and medical resources of a pediatric neoplastic disease, and the method completes balancing processing of the medical resources, and includes:
acquiring a balance processing result of the medical resources, and monitoring medical resource storage information of a preset medical resource distribution center, treatment grades of medical institutions attending a doctor and treatment quantity of the children tumor diseases by different medical institutions attending the doctor in real time based on the balance processing result;
and when the medical resource storage information of the preset medical resource distribution center, the treatment grade of the medical treatment institution and the treatment quantity of the different medical treatment institutions for treating the children tumor diseases are judged to be changed based on the monitoring result, the medical resources are subjected to balance treatment again.
The beneficial effects of the above technical scheme are: the parameters influencing the difference between the medical resources and the burden of the disease are monitored in real time, and the medical resources are balanced when the parameters are changed and are processed again, so that the effective balance between the difference between the burden of the disease and the medical resources is guaranteed, a treatment basis is provided for sick children, and the treatment effect is improved.
It will be apparent to those skilled in the art that various changes and modifications may be made in the present invention without departing from the spirit and scope of the invention. Thus, if such modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include such modifications and variations.
Claims (10)
1. A method for automatically balancing burden differences and medical resources for neoplastic disease in children, comprising:
step 1: acquiring child disease diagnosis data based on a medical insurance database, and screening the disease diagnosis data to obtain child tumor disease data;
step 2: analyzing the children tumor disease data, determining a children tumor disease frequency index and a medical resource utilization index, and determining the burden difference of the children tumor disease based on the tumor disease frequency index and the medical resource utilization index;
and 3, step 3: and formulating a medical resource balancing strategy based on the burden difference of the children tumor diseases, and balancing the medical resources of the children tumor diseases based on the medical resource balancing strategy.
2. The method for automatically balancing burden difference of children's tumor diseases and medical resources according to claim 1, wherein in step 1, the obtaining of children's disease diagnosis data based on the medical insurance database comprises:
acquiring a data calling request, analyzing the data calling request, and determining a service data type corresponding to the data calling request;
extracting the type identification of the business data type, accessing the medical insurance database based on the type identification, matching with an index table of the medical insurance database, and determining a target data layer where the business data type is located;
and extracting child disease diagnosis data corresponding to the service data type based on the target data layer, and packaging and transmitting the child disease diagnosis data to a data access terminal.
3. The method of claim 1, wherein the screening of disease diagnosis data in step 1 to obtain children's tumor disease data comprises:
acquiring the obtained child disease diagnosis data, acquiring historical child tumor disease data, and extracting data characteristics of the historical child tumor disease data;
taking the data characteristics as target conditions, and taking the target conditions as a clustering center to perform clustering processing on the child disease diagnosis data;
and determining the Hamming distance between the child disease diagnosis data and the target condition based on the clustering processing result, judging the child disease diagnosis data with the Hamming distance smaller than a preset threshold value as child tumor disease data, and finishing the screening of the child disease diagnosis data.
4. The method of claim 3, wherein the screening of childhood disease diagnosis data is accomplished by the automated balance of burden difference and medical resources for childhood tumor disease comprising:
acquiring the obtained children tumor disease data, and extracting the basic information of children from the children tumor disease data, wherein the basic information comprises age, gender and nationality;
verifying the extracted basic information, and judging whether the basic information of the children is missing or not;
if the basic information of the children is missing, judging that the children corresponding to the current basic information are abnormal individuals, and removing the current basic information to obtain standard children tumor disease data;
otherwise, judging that the basic information corresponding to the child is finished, and finishing the verification of the basic information.
5. The method of claim 4, wherein obtaining standard pediatric neoplastic disease data comprises:
acquiring the obtained standard children tumor disease data, and determining the age bracket of an individual corresponding to the children tumor disease data based on the basic information of the standard children tumor disease data;
performing first classification on the standard child tumor disease data based on the age groups to obtain first classification results, and determining the gender of an individual corresponding to the standard child tumor disease data in each first classification based on the first classification results;
performing second classification on the first classification result based on the gender to obtain a second classification result, and determining the ethnicity of the individual corresponding to the standard child tumor disease data in each second classification based on the second classification result;
and performing third classification on the second classification result based on the ethnicity to obtain a third classification result, determining privacy data in the basic information of the standard children tumor disease data based on the third classification result, and performing anonymization processing on the privacy data.
6. The method of claim 1, wherein the step 2 of analyzing the data of the pediatric neoplastic diseases to determine a frequency index of the pediatric neoplastic diseases and a medical resource utilization index comprises:
acquiring the obtained children tumor disease data, and determining classification indexes of the children tumor disease data, wherein the classification indexes comprise age, gender and nationality;
classifying the children tumor disease data based on the classification indexes to obtain a target subdata set, and determining the number of newly-increased children tumor patients in the current year and the total number of susceptible children in the current year in each target subdata in the target subdata set;
determining the incidence rate corresponding to each target subdata based on the number of newly-increased children tumor patients in the current year and the total number of susceptible children in the current year;
meanwhile, determining the number of children patients diagnosed before the target time period and living to the current year and the number of people participating in the current year in each target subdata, and determining the prevalence rate of the target time period corresponding to each target subdata based on the number of children patients diagnosed before the target time period and living to the current year and the number of people participating in the current year;
and obtaining the child tumor disease frequency index based on the morbidity and the morbidity of the target time period.
7. The method of claim 1, wherein in step 2, the children's tumor disease data is analyzed to determine a frequency index of children's tumor diseases and a utilization index of medical resources, further comprising:
acquiring the obtained children tumor disease data, and grouping the children tumor disease data based on gender, age and nationality to obtain a sub-data group;
generating a treatment expense access request based on the children tumor disease data in each sub data set, and accessing a preset patient treatment expense use database based on the treatment expense access request;
acquiring the total medical insurance reimbursement cost of each child patient within one year after the diagnosis is confirmed based on the preset patient treatment cost usage database, determining the medical insurance reimbursement proportion, and obtaining the treatment cost corresponding to each sub-data group based on the medical insurance reimbursement proportion and the total medical insurance reimbursement cost;
acquiring the consumption index of the current year, and correcting the total medical insurance reimbursement cost based on the consumption index to obtain the treatment cost of the patient corresponding to each subdata set;
meanwhile, the name of the medical institution for the patient of each child and the total number of the medical institutions for the patient are extracted from the data of the children tumor diseases, and the name characteristics of the names of the medical institutions for the patient are sequentially determined based on the total number of the medical institutions for the patient, wherein at least one name of the medical institution for the patient is selected;
removing the duplication of the names of the medical institutions for treatment based on the name characteristics to obtain a target medical institution name set, and searching each target medical institution name in the target medical institution name set in a preset medical institution grade search library to obtain the medical grade of each target medical institution for treatment;
drawing a medical treatment institution flow graph of each child patient based on the total number of medical treatment institutions for each child patient, and performing grade marking on each medical treatment institution based on the medical grade of each target medical treatment institution in the medical treatment institution flow graph;
obtaining the flow direction information of the medical treatment institution of each child patient based on the labeling result;
and obtaining a medical resource utilization index based on the treatment cost of the patient and the flow information of the medical institution.
8. The method of claim 1, wherein the step 2 of determining the burden difference of the pediatric neoplastic disease based on the neoplastic disease frequency index and the medical resource utilization index comprises:
acquiring a tumor disease frequency index and a medical resource utilization index, and determining the number of children suffering from tumor diseases in each year based on the tumor disease frequency index;
meanwhile, determining the treatment cost and the type of the medical institution of each child patient with the tumor disease at the time of treatment based on the medical resource utilization index;
the difference in the burden of childhood neoplastic disease is based on the number of childhood neoplastic diseases that are present per year and the cost of treatment and type of medical facility in which the visit is made.
9. The method according to claim 1, wherein the step 3 of establishing a medical resource balancing strategy based on the burden difference of the pediatric neoplastic disease and balancing the medical resource of the pediatric neoplastic disease based on the medical resource balancing strategy comprises:
acquiring the obtained burden difference of the child tumor disease, and determining the treatment expense payment capacity of the family suffering from the child tumor disease and the treatment grade of the medical institution;
constructing a medical resource balance strategy based on the treatment expense payment capacity and the treatment grade of the medical institution, and grading the treatment grade of the medical institution based on the medical resource balance strategy;
determining a target medical resource set required by the children tumor disease in the treatment process, and performing resource access on a preset medical resource distribution center based on the target medical resource set;
determining medical resource storage information of the preset medical resource distribution center based on the resource access, and determining the distribution amount of medical resources of the medical treatment structure with different treatment levels based on the medical resource storage information;
determining the treatment quantity of the medical treatment structure for seeing a doctor on the children tumor diseases, the utilization rate of the medical resources and the material loss coefficient based on the tumor disease frequency index and the medical resource utilization index, and correcting the distribution quantity of the medical resources based on the treatment quantity of the children tumor diseases, the utilization rate of the medical resources and the material loss coefficient to obtain the target distribution quantity of the medical resources of the medical treatment structure for seeing a doctor at different treatment levels;
simultaneously, determining the geographic position characteristics of the medical treatment structures of different treatment levels, and determining the step payment cost of medical resources required by the medical treatment institution for the child tumor diseases with different degrees of illness based on the geographic position characteristics;
the balancing process for the medical resource is completed based on the target allocation amount of the medical resource and the tiered payment for the medical resource.
10. The method of claim 9, wherein balancing the medical resource comprises:
acquiring a balance processing result of the medical resources, and monitoring medical resource storage information of a preset medical resource distribution center, treatment grades of medical institutions for treatment and treatment quantity of the children tumor diseases by different medical institutions for treatment in real time based on the balance processing result;
and when the medical resource storage information of the preset medical resource distribution center, the treatment grade of the medical institution and the treatment quantity of different medical institutions for treatment of the tumor diseases of the children are determined to be changed based on the monitoring result, carrying out balance treatment on the medical resources again.
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN116523333A (en) * | 2023-04-18 | 2023-08-01 | 四川省疾病预防控制中心 | Comprehensive evaluation method for disease burden |
| CN116631638A (en) * | 2023-05-11 | 2023-08-22 | 上海麦色医疗科技有限公司 | Medical data multichannel search system based on artificial intelligence |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN116523333A (en) * | 2023-04-18 | 2023-08-01 | 四川省疾病预防控制中心 | Comprehensive evaluation method for disease burden |
| CN116631638A (en) * | 2023-05-11 | 2023-08-22 | 上海麦色医疗科技有限公司 | Medical data multichannel search system based on artificial intelligence |
| CN116631638B (en) * | 2023-05-11 | 2023-12-12 | 上海麦色医疗科技有限公司 | Medical data multichannel search system based on artificial intelligence |
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