CN113743783A

CN113743783A - Credit evaluation method and device for medical institution

Info

Publication number: CN113743783A
Application number: CN202111033739.9A
Authority: CN
Inventors: 龙飞
Original assignee: Taikang Insurance Group Co Ltd; Taikang Pension Insurance Co Ltd
Current assignee: Taikang Insurance Group Co Ltd; Taikang Pension Insurance Co Ltd
Priority date: 2021-09-03
Filing date: 2021-09-03
Publication date: 2021-12-03

Abstract

The embodiment of the invention provides a credit evaluation method and a credit evaluation device for a medical institution, wherein the method comprises the following steps: acquiring an evaluation task pre-stored in a block chain platform; acquiring evaluation data of each medical institution to be evaluated in an evaluation time period based on the evaluation task; counting according to the evaluation indexes aiming at the evaluation data to obtain the statistical value of each evaluation index in each medical institution to be evaluated; mapping the statistical values of the same evaluation index in different medical institutions to be evaluated to the same value interval to obtain corresponding interval values; and calculating to obtain the credit score of each medical institution to be evaluated based on the interval numerical value and the index weight of each evaluation index. And generating a credit evaluation report based on the credit scores and the intermediate data, and storing the credit evaluation report to the blockchain platform so that the third-party platform acquires the credit evaluation report from the blockchain platform. The safety of the data and the public transparency of the data are realized based on the block chain technology, and the credit evaluation is guaranteed to be just enough and reliable.

Description

Credit evaluation method and device for medical institution

Technical Field

The invention relates to the technical field of credit evaluation, in particular to a credit evaluation method and device for a medical institution.

Background

The term "medical institution" refers to a general term for health institutions engaged in disease diagnosis and treatment activities according to legal procedures. The method has a great position in the national safety construction and development process, and also occupies the half-wall Jiangshan in the national medical guarantee.

At present, illegal events of medical institutions cause huge loss to national property. One important reason is that there is no fair and reliable platform for objectively and accurately evaluating the credit of each medical institution, so that it is impossible to supervise each medical institution.

Although some third-party institutions have provided credit ratings for various medical institutions, existing credit ratings are not fair and reliable for reasons of data security and other aspects.

Disclosure of Invention

The embodiment of the invention provides a credit evaluation method and device for medical institutions, and aims to solve the problem that the credit evaluation process of each medical institution is not fair and reliable in the prior art.

In a first aspect, an embodiment of the present invention provides a credit evaluation method for a medical institution, where the method includes:

acquiring an evaluation task pre-stored in a block chain platform; wherein the evaluation task comprises: the evaluation system comprises a plurality of evaluation indexes, index weights corresponding to the evaluation indexes, evaluation time periods and a plurality of medical institutions to be evaluated;

acquiring evaluation data of each medical institution to be evaluated in the evaluation time period based on the evaluation task;

for the evaluation data of each medical institution to be evaluated, counting each evaluation index in the evaluation data to obtain a statistical value of each evaluation index in each medical institution to be evaluated;

mapping the statistic values of the same evaluation index in different medical institutions to be evaluated to the same numerical value interval to obtain the interval numerical value of each evaluation index in each medical institution to be evaluated in the corresponding numerical value interval;

and calculating the credit score of each medical institution to be evaluated based on the interval numerical value of each evaluation index and the index weight for each medical institution to be evaluated.

Generating a credit evaluation report based on the credit score of the medical institution to be evaluated, the statistic value of each evaluation index in the medical institution to be evaluated, the interval value of each evaluation index in the medical institution to be evaluated and the index weight, and storing the credit evaluation report to the block chain platform so that a third-party platform can obtain the credit evaluation report from the block chain platform.

In a second aspect, an embodiment of the present invention further provides a credit evaluation device for a medical institution, where the device includes:

the task acquisition module is used for acquiring the evaluation tasks stored in the block chain platform in advance; wherein the evaluation task comprises: the evaluation system comprises a plurality of evaluation indexes, index weights corresponding to the evaluation indexes, evaluation time periods and a plurality of medical institutions to be evaluated;

the evaluation data acquisition module is used for acquiring the evaluation data of each medical institution to be evaluated in the evaluation time period based on the evaluation task;

the statistical module is used for counting each evaluation index in the evaluation data aiming at the evaluation data of each medical institution to be evaluated to obtain a statistical value of each evaluation index in each medical institution to be evaluated;

the mapping module is used for mapping the statistical values of the same evaluation indexes in different medical institutions to be evaluated to the same value interval to obtain the interval value of each evaluation index in each medical institution to be evaluated in the corresponding value interval;

the credit score module is used for calculating the credit score of each medical institution to be evaluated based on the interval numerical value of each evaluation index and the index weight for each medical institution to be evaluated;

and the evaluation report module is used for generating a credit evaluation report based on the credit score of the medical institution to be evaluated, the statistic value of each evaluation index in the medical institution to be evaluated, the interval value of each evaluation index in the medical institution to be evaluated and the index weight, and storing the credit evaluation report to the block chain platform so that a third-party platform can obtain the credit evaluation report from the block chain platform.

In still another aspect, the present invention further provides a computer-readable storage medium, on which a computer program is stored, and the computer program, when executed by a processor, implements the steps in the credit evaluation method for medical institutions as described above.

In the embodiment of the invention, the evaluation task pre-stored in the blockchain platform can be obtained, the evaluation task is used for performing credit evaluation on the medical institution, and the evaluation task is pre-stored in the blockchain platform and is based on the tamper-proof characteristic of the blockchain, so that not only can the data safety be ensured, but also the data can be made public and transparent, and the fairness of the credit evaluation is further improved. After the evaluation data for the medical institutions to be evaluated are acquired based on the evaluation tasks, statistics of the evaluation data based on the evaluation indexes can be obtained, so that statistics of each evaluation index in each medical institution to be evaluated can be obtained. In order to avoid overlarge statistical value difference of the same evaluation index in each medical institution to be evaluated, different statistical values corresponding to the same evaluation index are mapped to a reasonable value interval in a mapping mode. And then calculating to obtain a credit score for measuring the credibility of the medical institution based on the interval numerical values and the index weights of the evaluation indexes, then generating a credit evaluation report based on the credit score, the statistical numerical values, the interval numerical values and the index weights, and uploading the credit evaluation report to a block chain platform to ensure that the result of credit evaluation on the medical institution cannot be falsified and the credit evaluation result is transparent. In the embodiment of the invention, the evaluation tasks for evaluating the medical institutions and the evaluation results for credit evaluation of the medical institutions are all stored in the block chain platform, the data security and the data disclosure transparency are realized based on the block chain technology, and the credit evaluation is guaranteed to be sufficiently fair and reliable.

Drawings

In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings needed to be used in the description of the embodiments of the present invention will be briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art that other drawings can be obtained according to these drawings without inventive labor.

FIG. 1 is a flowchart illustrating the steps of a method for assessing credit in a medical facility, according to an embodiment of the present invention;

FIG. 2 is a schematic diagram of a storage structure of an evaluation task on a blockchain platform;

FIG. 3 is a schematic diagram of a storage structure of statistics on a block chain platform;

FIG. 4 is a block chain table showing the storage structure of interval values and credit scores;

FIG. 5 is a schematic diagram of a storage structure of main information in a blockchain platform;

FIG. 6 is a diagram illustrating a normal distribution model according to an embodiment of the present invention;

FIG. 7 is a diagram illustrating a benchmark distribution model according to an embodiment of the present invention;

FIG. 8 is a diagram illustrating another exemplary distribution model of the benchmarking values provided in accordance with an embodiment of the present invention;

FIG. 9 is a diagram illustrating a model of incremental distribution of baseline values according to an embodiment of the present invention;

fig. 10 is a schematic diagram of a high-quality index distribution model according to an embodiment of the present invention;

FIG. 11 is a diagram illustrating a descending order model according to an embodiment of the present invention;

FIG. 12 is a block diagram illustrating access to evaluation data according to an embodiment of the present invention;

fig. 13 is a schematic diagram illustrating an architecture of a credit evaluation method for a medical institution according to an embodiment of the present invention;

fig. 14 is a block diagram showing a credit evaluation apparatus of a medical institution according to an embodiment of the present invention;

fig. 15 is a block diagram of an electronic device according to an embodiment of the present invention.

Detailed Description

The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are some, not all, embodiments of the present invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.

It should be appreciated that reference throughout this specification to "one embodiment" or "an embodiment" means that a particular feature, structure or characteristic described in connection with the embodiment is included in at least one embodiment of the present invention. Thus, the appearances of the phrases "in one embodiment" or "in an embodiment" in various places throughout this specification are not necessarily all referring to the same embodiment. Furthermore, the particular features, structures, or characteristics may be combined in any suitable manner in one or more embodiments.

In various embodiments of the present invention, it should be understood that the sequence numbers of the following processes do not mean the execution sequence, and the execution sequence of each process should be determined by its function and inherent logic, and should not constitute any limitation to the implementation process of the embodiments of the present invention.

Referring to fig. 1, an embodiment of the present invention provides a credit evaluation method for a medical institution, including:

step 101: and acquiring the evaluation tasks stored in the block chain platform in advance.

It should be noted that the blockchain platform is a data platform based on blockchain technology. The evaluation task is used for credit evaluation of the medical institution, and comprises a plurality of items of data related to the credit evaluation, and specifically, the evaluation task comprises the following steps: the evaluation system comprises a plurality of evaluation indexes, index weights corresponding to the evaluation indexes, evaluation time periods and a plurality of medical institutions to be evaluated. Wherein, the index selection can be carried out according to local policy and supervision emphasis. Such as out-patient average cost, in-patient average cost, satisfaction score, violation event deduction, and the like. These are important indexes for credit evaluation of medical institutions, and indexes established by national bureau letters can be adopted, and index rules can be added in a custom mode if characteristic indexes of all parts exist. The index weight corresponding to the evaluation index can represent the importance degree of the evaluation index in measuring the credibility degree of the medical institution. The greater the index weight corresponding to the evaluation index, the more important the evaluation index is. Specifically, index weights according to national regulations are adopted, so that the confidence of the credit evaluation result is ensured. The evaluation time period is any time period preset by a user. It will be appreciated that typically we need only to assess whether the medical institution is trustworthy for a certain period of time. For example, whether a medical institution is credible in 2020 to 2021 is evaluated. The medical institution to be evaluated is an object of credit evaluation, and specifically, a social security/equipment system may be called to query the medical institution having signed a medical security agreement according to screening conditions such as hospital grades, hospital categories, overall planning areas, and the like, and the medical institution to be evaluated is taken as an evaluation object set.

Step 102: and acquiring evaluation data of each medical institution to be evaluated in the evaluation time period based on the evaluation task.

Note that evaluation data of a large number of medical institutions may be acquired in advance, and after acquiring an evaluation task, necessary evaluation data may be selected. I.e., the evaluation data of each medical institution to be evaluated during the evaluation period. The evaluation data is data associated with the medical institution to be evaluated, and can be used for credit evaluation of the medical institution to be evaluated.

Step 103: and counting each evaluation index in the evaluation data according to the evaluation data of each medical institution to be evaluated to obtain a statistical value of each evaluation index in each medical institution to be evaluated.

It should be noted that, in the case of counting the evaluation indexes, corresponding calculation is performed on the evaluation data to obtain a statistical value. For example, the evaluation index is: the average cost of the outpatient times is 100 yuan/time, wherein the number of the outpatient visits in the evaluation data is 10000 times, and the total charge of the outpatient times is 1000000 yuan.

Step 104: and mapping the statistical values of the same evaluation index in different medical institutions to be evaluated to the same value interval to obtain the interval value of each evaluation index in each medical institution to be evaluated in the corresponding value interval.

It should be noted that, in general, the difference between the statistics of the same evaluation index in different medical institutions to be evaluated is too obvious, which is not favorable for calculation. Therefore, after mapping each statistic of the same evaluation index to the same value interval, by controlling the value interval, the difference between each statistic of the same evaluation index can be reduced without affecting the numerical relationship between each statistic. For example, the value interval is [0,100], the value size of each statistic is from 100 to 100000, and after each statistic is mapped to [0,100], the value corresponding to the interval is located at [0,100], and here, the value corresponding to the interval of each statistic may be used as the statistic.

Step 105: and calculating the credit score of each medical institution to be evaluated based on the interval value and the index weight of each evaluation index aiming at each medical institution to be evaluated.

It should be noted that, for each medical institution to be evaluated, the interval numerical values of the evaluation indexes are weighted and summed to obtain the credit score of each medical institution to be evaluated. For example, the evaluation index includes a first index and a second index, the first index has a weight of 0.2, the second index has a weight of 0.3, the interval value of the first index is 100, and the interval value of the second index is 80, so that the credit score is 100 × 0.2+80 × 0.3 or 44. Here, the credit score is used to measure the credibility of the medical institution to be evaluated.

Step 106: and generating a credit evaluation report based on the credit score of the medical institution to be evaluated, the statistic value of each evaluation index in the medical institution to be evaluated, the interval value of each evaluation index in the medical institution to be evaluated and the index weight, and storing the credit evaluation report to the block chain platform so that the third-party platform can obtain the credit evaluation report from the block chain platform.

It should be noted that the credit rating report is a rating report meeting the national requirements, and has a fixed format and content requirements. Of course, the credit evaluation report may be a report designed by the user according to the requirement. The credit evaluation report includes the credit score of each medical institution to be evaluated, the statistical value of each evaluation index in the medical institution to be evaluated, the interval value of each evaluation index in the medical institution to be evaluated, and the index weight, wherein each item of data may be displayed in the credit evaluation report in any form, for example, directly displayed in the credit evaluation report in the form of characters and numbers, or displayed in the credit evaluation report in the form of a line graph, a bar graph, and the like, which is not limited herein. By chaining the credit evaluation report for storage, the third party platform can query the safe and reliable credit evaluation report through the blockchain platform without worrying about tampering with data on the blockchain. Preferably, the medical institutions to be evaluated can be ranked according to the ranking of the credit scores, and the ranking results are written into the credit evaluation report. It will be appreciated that a corresponding credit rating report may be generated for each rating task, and when the blockchain platform stores the credit rating report, the credit rating report is stored in association with its associated rating task. Thus, in the blockchain platform, the only credit evaluation report can be determined based on an evaluation task, and the only evaluation task can be determined based on a credit evaluation report.

Optionally, the method further comprises:

and storing the statistic values of the evaluation indexes in each medical institution to be evaluated and the interval values of the evaluation indexes in each medical institution to be evaluated into the block chain platform corresponding to the evaluation tasks.

Specifically, after the statistics of each evaluation index in each medical institution to be evaluated is obtained through calculation, the statistics of each evaluation index in each medical institution to be evaluated are immediately linked and stored; similarly, after the interval value of each evaluation index in each medical institution to be evaluated is obtained through calculation, the interval value of each evaluation index in each medical institution to be evaluated is immediately linked and stored, and preferably, after the credit score of each medical institution to be evaluated is obtained through calculation, the credit score of each medical institution to be evaluated is immediately linked and stored.

After storing the credit evaluation report to the blockchain platform, the method further comprises:

under the condition of receiving a traceability verification request, carrying out traceability and verification on a credit evaluation report to be verified based on target information stored on a blockchain platform, wherein the target information comprises: the evaluation index statistical values of the medical institutions to be evaluated under different evaluation tasks, the interval values of the evaluation indexes of the medical institutions to be evaluated and the credit evaluation report.

It should be noted that after the blockchain platform obtains the credit evaluation report from other channels or obtains the credit evaluation report from other channels, the third-party platform may initiate a traceability verification request if the reliability of the content cannot be trusted. Here, the traceability verification can verify not only the reliability of the credit evaluation report but also determine which part of the data is falsified when the credit evaluation report is not reliable. Here, a large amount of data corresponding to the evaluation task, for example, statistical data, interval values, credit evaluation reports, and the like, can be obtained every time the evaluation task is executed. Therefore, a large amount of data corresponding to the evaluation task that has already been executed is stored in the blockchain platform and used as target information for source tracing verification.

In the embodiment of the invention, in the process of generating the credit evaluation report, the intermediate data in the process of calculating the credit score is subjected to uplink storage, so that the data can be left, and the credit evaluation report can be traced and verified conveniently in the follow-up process.

Optionally, the block chain platform corresponds to a task identifier stored in the evaluation task; the source tracing verification request carries a target task identifier;

it is understood that data corresponding to different evaluation tasks can be distinguished in the blockchain platform, that is, after the evaluation task is determined, data corresponding to the evaluation task can be determined. Here, the data stored for the same evaluation task is the data stored for the same task identifier. Specifically, in the block chain platform, which data belong to the same evaluation task is determined through task identifiers in different storage nodes. Fig. 2 is a schematic diagram of a storage structure of an evaluation task on a blockchain platform, where task identifiers have uniqueness and task identifiers of different evaluation tasks are different. The index information set in the evaluation task is a set of evaluation indexes in the evaluation task, the main information set is a set of medical institutions to be evaluated in the evaluation task, the grade information is a rule for dividing credit grade based on credit score, and the evaluation task also includes other information, which is not shown in fig. 2. As shown in fig. 3, the storage structure diagram of the statistics on the block chain platform is shown, wherein the main body is the medical institution to be evaluated, the index is the evaluation index, and the value is the statistics. As shown in fig. 4, the block chain platform is a schematic diagram of a storage structure of interval values and credit scores, where a main body is a medical institution to be evaluated, an index is an evaluation index, a score is an interval value, and a main body score is a credit score. Here, for each body, the related information of the body may also be separately stored in the blockchain, as shown in fig. 5, which is a schematic diagram of a storage structure of the body information in the blockchain platform. The main body is a medical institution to be evaluated, the index is an evaluation index, the score is an interval numerical value, the numerical value is a statistic numerical value, the weight is an index weight, the main body score is a credit score, and the main body rating is a credit level. The deduction item set is related information of violation of medical treatment mechanism in the evaluation data.

Tracing and verifying the credit evaluation report to be verified based on target information stored on the block chain platform, wherein the tracing and verifying method comprises the following steps:

based on the target task identification, determining a target credit evaluation report under a target evaluation task in the block chain platform, interval values of evaluation indexes in each medical institution to be evaluated under the target evaluation task and statistic values of the evaluation indexes in each medical institution to be evaluated under the target evaluation task;

comparing the target credit evaluation report with the credit evaluation report to be verified, and determining that the credit evaluation report to be verified passes verification under the condition that the target credit evaluation report is the same as the credit evaluation report to be verified;

under the condition that the target credit evaluation report is different from the to-be-verified credit evaluation report, sequentially comparing the interval numerical value of each evaluation index in the to-be-verified medical institution under the target evaluation task with the interval numerical value in the to-be-verified credit evaluation report, comparing the statistic numerical value of each evaluation index in the to-be-verified medical institution under the target evaluation task with the statistic numerical value in the to-be-verified credit evaluation report, and determining a tampered data item in the to-be-verified credit evaluation report based on the comparison result, wherein the data item comprises the interval numerical value and the statistic numerical value in the to-be-verified credit evaluation report.

It should be noted that, in each of the comparison processes described above, the respective hash values may be calculated first, and whether the respective hash values are the same or not may be determined by comparing whether the respective hash values are the same, but the present invention is not limited thereto. If the interval value of each evaluation index in the medical institution to be evaluated under the target evaluation task is different from the interval value in the credit evaluation report to be verified, the interval value is falsified, and the credit evaluation report to be verified is not verified. It is understood that the number of the interval values to be compared with each other is plural, and the corresponding interval values need to be compared, for example, the interval value of the first evaluation index of the first to-be-evaluated medical institution in the target evaluation task is compared with the interval value of the first evaluation index of the first to-be-evaluated medical institution in the credit evaluation report to be verified, the interval value of the second evaluation index of the first to-be-evaluated medical institution in the target evaluation task is compared with the interval value of the second evaluation index of the first to-be-evaluated medical institution in the credit evaluation report to be verified, the interval value of the first evaluation index of the second to-be-evaluated medical institution in the target evaluation task is compared with the interval value of the first evaluation index of the second to-be-evaluated medical institution in the credit evaluation report to be verified, and the interval value of the second evaluation index of the second to-evaluated medical institution in the target evaluation task is compared with the interval value of the second evaluation index of the second to-be-verified medical institution in the credit evaluation report to be verified The interval values of the indexes are compared.

Similarly, if the statistics of each evaluation index in the medical institution to be evaluated under the target evaluation task is different from the statistics in the credit evaluation report to be verified, the statistics are falsified, and the credit evaluation report to be verified is not verified. The number of the statistics values to be compared with each other is multiple, and the corresponding statistics values need to be compared, which is not described herein again.

In the embodiment of the invention, the data corresponding to the credit evaluation report to be verified is determined based on the target task identifier in the traceability verification request and the task identifier of the data stored in the block chain platform, so that the traceability and verification of the credit evaluation report to be verified are realized.

Optionally, the evaluation task further comprises: presetting a distribution model, wherein the presetting the distribution model comprises: at least one of a normal distribution model, a benchmark value increasing distribution model, a benchmark value decreasing distribution model, a high-priority index distribution model, a low-priority index distribution model, a descending model and an ascending model.

It can be understood that, for example, the normal distribution model is shown in fig. 6, and fig. 6 is a schematic diagram of the normal distribution model provided by the embodiment of the present invention. Within the comparison range, the evaluation indexes are arranged in the order of small statistics value to large statistics value, the full score is 100 within the range of [ 5%, 95%), and 20 points are reduced for every 1% deviation outside the full-score interval. The approximation follows a normal distribution. Most of them get full score, and few get low score.

Fig. 7 shows an example of a scalar value distribution model, and fig. 7 is a schematic diagram of a scalar value distribution model according to an embodiment of the present invention. Within the comparison range, the evaluation indexes are arranged in the order from small to large according to the statistic value of the evaluation indexes, the full score is 100 within the range of +/-10% of the median, the distribution outside the full score interval deviates 1% every time, and is reduced by 3.3 points, and the lowest score is 0. The grading is fine, and the grading is accurate; the number of people with full score is moderate.

FIG. 8 is a diagram illustrating another exemplary distribution model of the benchmarks according to the present invention. The average value of the sample set is

The mark bar is used as a mark bar, and the mark bar is divided into 100 full marks correspondingly. Arranging the evaluation indexes in the order of the statistics from small to large, and separating the actual values of the left side and the right side

The closer, the higher the score, the further away

The farther away the score is lower.

C is a parameter and can be set to 2, but is not limited thereto.

Fig. 9 is a schematic diagram of a benchmark value incremental distribution model according to an embodiment of the present invention. In the comparison range, arranging according to the sequence of the statistics of the evaluation indexes from small to large, wherein the median is a qualified standard score; (80 points are recommended), high-quality (the higher the statistical value is, the better is), the highest value is 100 points when the distribution is 1 percent higher than the benchmark point; and when the distribution is 1 percent lower than the reference point, the N point is reduced, and the lowest 0 point is obtained.

The base value decreasing distribution model is opposite to the base value increasing distribution model, the base value decreasing distribution model is low and excellent, the lower the statistical value is, the better the statistical value is, the distribution is 1% when the statistical value is higher than the base value, the N is reduced, and the lowest 0 is obtained; when the distribution is 1 percent lower than the reference, M is added, and the maximum is 100 points; the graph is opposite to the curve of fig. 9, the higher the statistics, the lower the interval value.

High-quality index distribution model: fig. 10 shows a high-quality index distribution model, and fig. 10 is a schematic diagram of a high-quality index distribution model provided in an embodiment of the present invention. The evaluation indexes are arranged in the order of the statistics from small to large. And in the sorted set of the statistics, from the maximum statistics, sequentially intercepting intervals corresponding to 20% of the statistics in the set as full-scale intervals. If the statistic value is in the full-scale interval, the interval value corresponding to the statistic value is full-scale.

The interval value of the other evaluation index is (the statistic value of the evaluation index/the statistic value corresponding to the M-quantile) × 100. The statistical value corresponding to the M quantile is the statistical value occupying the minimum ratio in the full-scale interval, and the example is as follows: the statistics include: 2,6,10,14,25,31,35,25,65,88, when the index percentage is 20%, the statistics in the full-scale interval are 65 and 88, and the statistics corresponding to the M-quantile is 65, and the interval value of the evaluation index whose statistics is 2 is (2/65) × 100, and the interval value of the other evaluation indexes can be also used, which is not described in detail herein.

The low-priority index distribution model: the low-priority index distribution model is an example of the same data as the high-priority index distribution model shown in fig. 10: the statistics include: 2,6,10,14,25,31,35,25,65,88, the index values in the full-scale interval are 2 and 6, the statistic value corresponding to the M quantile is 6, and the interval value of the evaluation index with the statistic value of 10 is (6/10) × 100, and also the interval values of other evaluation indexes can be correspondingly calculated according to the low-priority index distribution model, which is not described in detail herein.

A descending order model: fig. 11 is a schematic diagram of a descending order model provided by an embodiment of the present invention, where the interval value is 100- (the hospital index name/maximum rank in the comparison range) x 100;

the descending model is suitable for the situation that the difference of actual statistics is large and magnitude difference occurs.

The ascending model and the descending model are opposite in schematic diagram and are also suitable for the conditions that the difference of statistics values is large and magnitude difference occurs.

It should be noted that the preset distribution model is preset to be constructed according to the characteristics of the evaluation data corresponding to the evaluation index. For example, in the benchmark value distribution model shown in fig. 8, the benchmark value is not actually a value, and in the index of medical insurance fund supervision, the benchmark value is often an interval. For example, for the index of executing the total budget, the budget execution rate is often a percentage, and the median is 90%, so if the budget execution rate reaches an interval of 80% -100%, the interval value of the index of executing the total budget is full 100 points, which means that the budget execution does not deviate much from the plan, if the budget execution rate exceeds or falls short of 80%, the budget is deducted according to the deviation, and if the budget execution rate exceeds or falls short of 80%, the budget execution rate exceeds 100% and is also deducted according to the deviation degree. For the interval value of the evaluation index, which is the total budget to be calculated, the benchmarking value distribution model shown in fig. 8 can be used for calculation.

For a high-quality index distribution model, for example, the evaluation index is a satisfaction index, and the higher the statistical value corresponding to the satisfaction index, the higher the interval value corresponding to the satisfaction index. That is, under the condition of calculating the interval value corresponding to the satisfaction index, the interval value can be calculated by adopting a high-quality index distribution model. For the low-priority index distribution model, for example, the evaluation index is an outpatient service average cost index, and the higher the statistical value corresponding to the outpatient service average cost index is, the lower the interval value corresponding to the outpatient service average cost index is, so that when the interval value corresponding to the outpatient service average cost index is calculated, the interval value corresponding to the outpatient service average cost index can be calculated by using, for example, the low-priority index distribution model. That is, the characteristics of the evaluation data corresponding to the evaluation indexes are different, and different distribution models can be adopted to calculate the interval numerical values.

Mapping the statistical values of the same evaluation index in different medical institutions to be evaluated to the same value interval to obtain the interval value of each evaluation index in each medical institution to be evaluated in the corresponding value interval, wherein the interval value comprises the following steps:

aiming at each evaluation index, sequencing all statistics values corresponding to the same evaluation index from small to large to obtain a statistics value sequence corresponding to each evaluation index;

respectively mapping each statistical value sequence to a target value interval according to the distribution form of a preset distribution model to obtain an interval value corresponding to each statistical value in the target value interval;

and determining the interval numerical value corresponding to each statistical value as the interval numerical value with the evaluation index of the statistical value.

In the embodiment of the invention, the interval numerical value of the evaluation index can be flexibly calculated by utilizing the preset distribution model.

Optionally, the evaluation task further comprises: a plurality of credit levels and a credit value interval corresponding to each credit level; the credit evaluation report comprises credit grades corresponding to each medical institution to be evaluated; the credit grade corresponding to the medical institution to be evaluated is the credit grade corresponding to the credit value interval to which the credit score of the medical institution to be evaluated belongs.

It should be noted that the credibility of the medical institution may be graded, so that the user may know the credibility of the medical institution more intuitively and conveniently. For example, a credit value range 1 of 90-100 points is set as a class a, a credit value range 2 of 80-90 points is set as a class B, a credit value range 3 of 70-80 points is set as a class C, a credit value range 4 of 60-70 points is set as a class D, and a credit value range below 60 points is set as a class E. And if the credit score of a certain to-be-evaluated medical institution is 95 points, and the 95 points are positioned in the credit value interval 1, the credit level of the to-be-evaluated medical institution is A level.

In the embodiment of the invention, the medical institution to be evaluated is conveniently classified by determining the credit level of the medical institution to be evaluated, and the user can conveniently and intuitively know the credibility of the medical institution to be evaluated through the credit level based on the credit evaluation report generated by the credit level.

Optionally, before acquiring the evaluation task pre-stored in the blockchain platform, the method further includes:

evaluation data associated with the medical institution is accessed from the medical insurance system and each medical institution.

It should be noted that by acquiring more comprehensive assessment data for credit assessment of a medical institution from different sources. It is understood that a two-dimensional code of a satisfaction questionnaire can be posted at a distinct location in a medical facility after a patient visit. The patient evaluates the satisfaction of the visit through a satisfaction questionnaire. The personnel of the national medical insurance bureau can carry out the assault examination on the medical institution regularly and irregularly, the audited problems can be converted into deduction items which are used as the numerical values of the auditing and examining indexes of the medical institution, and the lower the deduction value is, the better the deduction value is. The method is characterized in that a camera is erected in a medical institution, when a patient is in a doctor and is checked, the camera is used for carrying out face recognition and medical insurance card comparison, and if the patient is not in the doctor, the patient reports the medical insurance fund event for cheating. An infrared camera is erected at a hospital stay site of a medical institution, and if a patient stays in a hospital bed for a long time and does not stay in the hospital bed area, a medical insurance fund event is deceived for hanging the bed and reported. Every medical institution uploads medical and settlement related data to the medical insurance system every day. The numerical values of key indexes such as the average hospitalization day, the average outpatient time cost, the average hospitalization time cost and the like of the patient can be counted through medical record information, settlement information and settlement detail information. Therefore, the evaluation data comprises the evaluation data of the patient to the medical institution and the doctor, the audit data of the national auditors to the medical institution and the doctor, the violation events discovered by the monitoring equipment and the quantitative values of the key indexes of the medical institution through the medical data.

And performing data integration on the accessed evaluation data, and storing the evaluation data after the data integration to a target database.

It should be noted that data integration includes data cleansing and data normalization, i.e., removing useless data and unifying the remaining data into a standard.

As shown in fig. 12, which is a schematic diagram of an architecture for accessing evaluation data in an embodiment of the present invention, a hospital a may transmit satisfaction survey data, audit data, and monitoring data collected by monitoring equipment of the hospital a to a data access layer of a credit evaluation platform through HTTP (hypertext Transfer Protocol), and a hospital B may transmit satisfaction survey data, audit data, and monitoring data collected by monitoring equipment of the hospital B to the data access layer of the credit evaluation platform through HTTP. And the hospital A and the hospital B respectively report the respective service data to the medical insurance system, and the medical insurance system transmits the data to the data access layer. The data access layer comprises a C-end access adapter, a B-end access adapter, an intelligent monitoring access adapter and a medical insurance system access adapter, so that the access adapters access the four types of data, and the accessed data is subjected to data cleaning, standardization and persistence, wherein the persistence refers to the storage of the standardized data in storage equipment such as a disk.

Acquiring evaluation data of each medical institution to be evaluated in an evaluation time period based on the evaluation task, wherein the evaluation data comprises the following steps:

and obtaining the evaluation data of each medical institution to be evaluated in the evaluation time period from the target database.

In the embodiment of the invention, more comprehensive evaluation data are obtained from different channels, so that the accuracy of the credit score in the credit evaluation report can be improved.

establishing an evaluation task, setting evaluation indexes, setting index weight corresponding to each evaluation index, setting evaluation time period and selecting a medical institution to be evaluated;

and storing the created evaluation task to the blockchain platform.

In the embodiment of the invention, the user can create the evaluation task according to the requirement of the user and perform credit evaluation on the selected medical institution.

As shown in fig. 13, which is a schematic diagram of an architecture of a credit evaluation method for a medical institution according to an embodiment of the present invention, a part of a data access layer is the same as that shown in fig. 12, and is not described herein again.

And an evaluation management layer of the credit evaluation platform obtains an evaluation task by establishing the evaluation task, selecting an index, setting index weight, setting a grading method, setting a grade and selecting an evaluation subject, and stores the evaluation task to the block chain platform. The evaluation task creation specifically includes creating a task and selecting an evaluation year and an evaluation hospital grade, for example, hospitals such as 2020, official and third-class hospitals and comprehensive hospitals are set. Namely, the credit evaluation is carried out on the official, third-class and the like in 2020 years of the comprehensive hospital. And selecting indexes, specifically, selecting indexes according to local policies and supervision emphasis. Such as out-patient average cost, in-patient average cost, satisfaction score, violation event deduction, and the like. The indexes are important indexes for credit evaluation of hospitals, the credit evaluation platform provides some preset indexes, the indexes are indexes established according to national bureau texts, and index rules can be added in a custom mode if characteristic indexes of all parts are provided. And setting a scoring method, specifically providing a statistical algorithm model for a user to select. And setting index weight, specifically setting a weighted value for each index, and multiplying each index score by the corresponding index weight to give a final credit score of the medical institution when the indexes are used for credit evaluation on the medical institution. The ranking is set, specifically, providing that the ranking is set according to the credit score interval of the medical institution being evaluated, for example, 90-100 is ranked as a, 80-90 is ranked as B, 70-80 is ranked as C, 60-70 is ranked as D, and 60 is ranked as E below. And selecting an evaluation main body, wherein the evaluation main body is a medical institution to be evaluated, and calling a medical insurance system to inquire the medical institution signed with the medical insurance agreement according to screening conditions such as hospital grades, hospital categories, overall districts and the like to serve as a credit evaluation object set.

And the evaluation engine is used for acquiring the evaluation tasks on the blockchain platform and performing credit evaluation on the evaluation subject. The index value obtained by statistics is a statistical value of the evaluation index in each embodiment of the invention, the index branch is an interval value of the evaluation index in each embodiment of the invention, the algorithm model is a preset distribution model in each embodiment of the invention, and the credit rating is a credit level of the medical institution to be evaluated determined based on the credit score in each embodiment of the invention, which is not described herein again. In fig. 13, governments, banks, and insurers are all third-party platforms, and can obtain safe and reliable credit evaluation reports from the blockchain platform.

The credit evaluation method of the medical institution according to the embodiment of the present invention is described above, and the credit evaluation device of the medical institution according to the embodiment of the present invention will be described below with reference to the accompanying drawings.

Referring to fig. 14, an embodiment of the present invention further provides a credit evaluation apparatus for a medical institution, the apparatus including:

a task obtaining module 1401, configured to obtain an evaluation task pre-stored in a block chain platform; wherein, the evaluation task comprises: the evaluation system comprises a plurality of evaluation indexes, index weights corresponding to the evaluation indexes, evaluation time periods and a plurality of medical institutions to be evaluated;

an evaluation data acquisition module 1402, configured to acquire evaluation data of each medical institution to be evaluated within an evaluation time period based on the evaluation task;

the statistics module 1403 is configured to, for the evaluation data of each medical institution to be evaluated, perform statistics on each evaluation index in the evaluation data to obtain a statistic value of each evaluation index in each medical institution to be evaluated;

the mapping module 1404 is configured to map statistics of the same evaluation index in different medical institutions to be evaluated to the same value interval, so as to obtain an interval value of each evaluation index in each medical institution to be evaluated in the corresponding value interval;

a credit score module 1405, configured to calculate, for each medical institution to be evaluated, a credit score of each medical institution to be evaluated based on the interval value of each evaluation index and the index weight;

the evaluation report module 1406 is configured to generate a credit evaluation report based on the credit score of the medical institution to be evaluated, the statistical value of each evaluation index in the medical institution to be evaluated, the interval value of each evaluation index in the medical institution to be evaluated, and the index weight, and store the credit evaluation report to the block chain platform, so that the third-party platform obtains the credit evaluation report from the block chain platform.

Optionally, the apparatus further comprises:

the uploading module is used for storing the statistical values of all the evaluation indexes in each medical institution to be evaluated and the evaluation tasks corresponding to the interval values of all the evaluation indexes in each medical institution to be evaluated to the block chain platform;

the source tracing verification module is used for tracing and verifying the credit evaluation report to be verified based on target information stored on the blockchain platform under the condition that a source tracing verification request is received, wherein the target information comprises: the evaluation index statistical values of the medical institutions to be evaluated under different evaluation tasks, the interval values of the evaluation indexes of the medical institutions to be evaluated and the credit evaluation report.

Optionally, the block chain platform corresponds to a task identifier stored in the evaluation task, the source tracing verification request carries a target task identifier, and the target task identifier is the same as the task identifier of the target evaluation task in the block chain platform; the source tracing verification module comprises:

the first verification unit is used for determining a target credit evaluation report under a target evaluation task in the block chain platform, interval values of evaluation indexes in each medical institution to be evaluated under the target evaluation task and statistic values of the evaluation indexes in each medical institution to be evaluated under the target evaluation task based on the target task identifier;

the second verification unit is used for comparing the target credit evaluation report with the credit evaluation report to be verified and determining that the credit evaluation report to be verified passes verification under the condition that the target credit evaluation report is the same as the credit evaluation report to be verified;

and the source tracing unit is used for sequentially comparing the interval value of each evaluation index in the medical institution to be evaluated under the target evaluation task with the interval value in the credit evaluation report to be verified, comparing the statistic value of each evaluation index in the medical institution to be evaluated under the target evaluation task with the statistic value in the credit evaluation report to be verified under the target evaluation task, and determining a tampered data item in the credit evaluation report to be verified based on the comparison result, wherein the data item comprises the interval value and the statistic value in the credit evaluation report to be verified.

Optionally, the evaluation task further comprises: presetting a distribution model, wherein the presetting the distribution model comprises: at least one of a normal distribution model, a benchmark value incremental distribution model, a benchmark value decremental distribution model, a high-priority index distribution model, a low-priority index distribution model, a descending model and an ascending model;

the mapping module 1404 includes:

the sorting unit is used for sorting all the statistics values corresponding to the same evaluation index from small to large according to each evaluation index to obtain a statistics value sequence corresponding to each evaluation index;

the mapping unit is used for mapping each statistic value sequence to a target value interval according to the distribution form of a preset distribution model to obtain an interval value corresponding to each statistic value in the target value interval;

and the mapping determining unit is used for determining the interval numerical value corresponding to each statistic value as the interval numerical value with the evaluation index of the statistic value.

Optionally, the apparatus further comprises:

the data acquisition module is used for accessing evaluation data associated with the medical institutions from the medical insurance system and each medical institution;

the data integration module is used for integrating the accessed evaluation data and storing the evaluation data after data integration into a target database;

the evaluation data obtaining module 1402 is specifically configured to obtain, from the target database, evaluation data of each medical institution to be evaluated in an evaluation time period.

The credit evaluation device for the medical institution provided by the embodiment of the invention can realize each process realized by the credit evaluation method for the medical institution in the method embodiments of fig. 1 to 12, and is not described again to avoid repetition.

In the embodiment of the invention, the evaluation task pre-stored in the blockchain platform can be obtained, the evaluation task is used for performing credit evaluation on the medical institution, and the evaluation task is pre-stored in the blockchain platform and is based on the tamper-proof characteristic of the blockchain, so that not only can the data safety be ensured, but also the data can be made public and transparent, and the fairness of the credit evaluation is further improved. After the evaluation data aiming at the medical institution to be evaluated is obtained based on the evaluation task, the credit score for measuring the credibility of the medical institution is obtained based on the evaluation index, the index weight and the evaluation data, then the credit evaluation report is generated based on the credit score, and is uploaded to the block chain platform, so that the credit evaluation result of the medical institution is not falsified, and the credit evaluation result is guaranteed to be public and transparent. In the embodiment of the invention, the evaluation tasks for evaluating the medical institutions and the evaluation results for credit evaluation of the medical institutions are all stored in the block chain platform, the data security and the data disclosure transparency are realized based on the block chain technology, and the credit evaluation is guaranteed to be sufficiently fair and reliable.

On the other hand, the embodiment of the invention also provides electronic equipment, which comprises a processor, a communication interface, a memory and a communication bus, wherein the processor, the communication interface and the memory complete mutual communication through the communication bus;

a memory for storing a computer program;

and a processor for implementing the steps of the above-described medical institution's credit evaluation method when executing the program stored in the memory.

For example, fig. 15 shows a schematic physical structure diagram of an electronic device.

As shown in fig. 15, the electronic device may include: a processor (processor)1510, a communication Interface (Communications Interface)1520, a memory (memory)1530 and a communication bus 1540, wherein the processor 1510, the communication Interface 1520 and the memory 1530 communicate with each other via the communication bus 1540. The processor 1510 may call logic instructions in the memory 1530 to perform the following method:

acquiring an evaluation task pre-stored in a block chain platform; wherein, the evaluation task comprises: the evaluation system comprises a plurality of evaluation indexes, index weights corresponding to the evaluation indexes, evaluation time periods and a plurality of medical institutions to be evaluated;

acquiring evaluation data of each medical institution to be evaluated in an evaluation time period based on the evaluation task;

counting each evaluation index in the evaluation data aiming at the evaluation data of each medical institution to be evaluated to obtain a statistical value of each evaluation index in each medical institution to be evaluated;

mapping the statistical values of the same evaluation index in different medical institutions to be evaluated to the same value interval to obtain the interval value of each evaluation index in each medical institution to be evaluated in the corresponding value interval;

and calculating the credit score of each medical institution to be evaluated based on the interval value and the index weight of each evaluation index aiming at each medical institution to be evaluated.

And generating a credit evaluation report based on the credit score of the medical institution to be evaluated, the statistic value of each evaluation index in the medical institution to be evaluated, the interval value of each evaluation index in the medical institution to be evaluated and the index weight, and storing the credit evaluation report to the block chain platform so that the third-party platform can obtain the credit evaluation report from the block chain platform.

In addition, the logic instructions in the memory 1530 may be implemented in the form of software functional units and stored in a computer readable storage medium when the logic instructions are sold or used as independent products. Based on such understanding, the technical solution of the present invention may be embodied in the form of a software product, which is stored in a storage medium and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and other various media capable of storing program codes.

In still another aspect, an embodiment of the present invention further provides a computer-readable storage medium, on which a computer program is stored, where the computer program is implemented by a processor to execute the credit evaluation method of a medical institution provided in the foregoing embodiments, for example, the method includes:

Finally, it should be noted that: the above examples are only intended to illustrate the technical solution of the present invention, but not to limit it; although the present invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; and such modifications or substitutions do not depart from the spirit and scope of the corresponding technical solutions of the embodiments of the present invention.

Claims

1. A method for credit rating of a medical institution, the method comprising:

2. The method of claim 1, further comprising:

storing the statistic value of each evaluation index in each medical institution to be evaluated and the interval value of each evaluation index in each medical institution to be evaluated to the block chain platform corresponding to the evaluation task;

after the storing the credit evaluation report to the blockchain platform, the method further comprises:

under the condition of receiving a traceability verification request, carrying out traceability and verification on a credit evaluation report to be verified based on target information stored on the blockchain platform, wherein the target information comprises: the statistical value of the evaluation index of each medical institution to be evaluated under different evaluation tasks, the interval value of the evaluation index of each medical institution to be evaluated and a credit evaluation report.

3. The method according to claim 2, wherein the blockchain platform stores a task identifier corresponding to the evaluation task, the traceability verification request carries a target task identifier, and the target task identifier is the same as the task identifier of the target evaluation task in the blockchain platform; the tracing and verifying the credit evaluation report to be verified based on the target information stored on the blockchain platform comprises the following steps:

based on the target task identification, determining a target credit evaluation report under a target evaluation task in the block chain platform, an interval numerical value of each evaluation index in each to-be-evaluated medical institution under the target evaluation task, and a statistic numerical value of each evaluation index in each to-be-evaluated medical institution under the target evaluation task;

under the condition that a target credit evaluation report is different from the to-be-verified credit evaluation report, sequentially comparing the interval value of each evaluation index in the to-be-verified medical institution under the target evaluation task with the interval value in the to-be-verified credit evaluation report, comparing the statistic value of each evaluation index in the to-be-verified medical institution under the target evaluation task with the statistic value in the to-be-verified credit evaluation report, and determining a tampered data item in the to-be-verified credit evaluation report based on the comparison result, wherein the data item comprises the interval value and the statistic value in the to-be-verified credit evaluation report.

4. The method of claim 1, wherein the evaluation task further comprises: presetting a distribution model, wherein the presetting the distribution model comprises: at least one of a normal distribution model, a benchmark value incremental distribution model, a benchmark value decremental distribution model, a high-priority index distribution model, a low-priority index distribution model, a descending model and an ascending model;

the mapping of the statistical values of the same evaluation indexes in different medical institutions to be evaluated to the same value interval to obtain the interval value of each evaluation index in each medical institution to be evaluated in the corresponding value interval includes:

for each evaluation index, sequencing all statistics values corresponding to the same evaluation index from small to large to obtain a statistics value sequence corresponding to each evaluation index;

mapping each statistic value sequence to a target value interval according to the distribution form of the preset distribution model to obtain an interval value corresponding to each statistic value in the target value interval;

5. The method of claim 1, wherein the evaluation task further comprises: a plurality of credit levels and a credit value interval corresponding to each credit level; the credit evaluation report comprises credit grades corresponding to each medical institution to be evaluated; the credit level corresponding to the medical institution to be evaluated is the credit level corresponding to the credit value interval to which the credit score of the medical institution to be evaluated belongs.

6. The method of claim 1, wherein prior to said obtaining an evaluation task pre-stored on a blockchain platform, the method further comprises:

accessing evaluation data associated with the medical institution from the medical insurance system and each medical institution;

performing data integration on the accessed evaluation data, and storing the evaluation data after the data integration to a target database;

the acquiring of the evaluation data of each medical institution to be evaluated in the evaluation time period based on the evaluation task includes:

7. A credit evaluation apparatus for a medical institution, the apparatus comprising:

8. The apparatus of claim 7, further comprising:

the uploading module is used for storing the statistical values of the evaluation indexes in each medical institution to be evaluated and the interval values of the evaluation indexes in each medical institution to be evaluated to the block chain platform corresponding to the evaluation tasks;

the source tracing verification module is configured to, on a condition that a source tracing verification request is received, perform source tracing and verification on a credit evaluation report to be verified based on target information stored on the blockchain platform, where the target information includes: the statistical value of the evaluation index of each medical institution to be evaluated under different evaluation tasks, the interval value of the evaluation index of each medical institution to be evaluated and a credit evaluation report.

9. An electronic device, comprising: a processor, a communication interface, a memory, and a communication bus; the processor, the communication interface and the memory complete mutual communication through a communication bus;

a memory for storing a computer program;

a processor for implementing the steps of the method of credit assessment of a medical institution as claimed in any of claims 1 to 6 when executing the program stored on the memory.

10. A computer-readable storage medium, characterized in that a computer program is stored on the computer-readable storage medium, which computer program, when being executed by a processor, carries out the steps of the method for credit evaluation of a medical institution according to any one of claims 1 to 6.