CN110782987A - Medical data evaluation processing method and device, storage medium and electronic equipment - Google Patents
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Abstract
The invention discloses a medical data evaluation processing method, a medical data evaluation processing device, a computer readable storage medium and electronic equipment, and relates to the technical field of medical information processing. The evaluation processing method of the medical data comprises the following steps: acquiring medical data to be evaluated and disease types corresponding to the medical data to be evaluated; evaluating medical data to be evaluated by utilizing a first evaluation rule matched with the disease type to obtain a first evaluation result; acquiring a manual evaluation result aiming at the medical data to be evaluated as a second evaluation result; and if the first evaluation result is inconsistent with the second evaluation result and the second evaluation result is the positive evaluation result, acquiring a second evaluation rule corresponding to the second evaluation result, associating the second evaluation rule with the disease type, and visually displaying the association state of the second evaluation rule and the disease type. The medical data evaluation method and the medical data evaluation system can improve the medical data evaluation work efficiency.
Description
Technical Field
The present disclosure relates to the field of medical information processing technologies, and in particular, to an evaluation processing method for medical data, an evaluation processing apparatus for medical data, a computer-readable storage medium, and an electronic device.
Background
Under the background of rapid development of current social economy and continuous promotion of medical constitution reform, a large amount of medical data such as evaluation reports, identification reports and declaration data need to be evaluated. At present, most of medical data evaluation work is manual processing, and due to low manual processing efficiency, the problems of large evaluation workload, long evaluation time and the like are caused.
For example, in the management of chronic diseases in basic medical insurance outpatient service, it is necessary to perform an audit process on declaration data as to whether or not the disease category of the declaration data falls within the disease category range of medical insurance. Wherein, the auditing process comprises: firstly, the patient is registered in the corresponding diagnosis department, then, the doctor in the chronic department is asked to evaluate the disease category of the reported data, and then, the doctor signs and confirms in the evaluation application table. The auditing process causes the workload of doctors to be increased, the evaluation work efficiency is low, and the medical insurance declaration time is long.
It is to be noted that the information disclosed in the above background section is only for enhancement of understanding of the background of the present disclosure, and thus may include information that does not constitute prior art known to those of ordinary skill in the art.
Disclosure of Invention
The present disclosure is directed to a method and an apparatus for evaluating medical data, a computer-readable storage medium, and an electronic device, which overcome, at least to some extent, the problems of the prior art that the efficiency of evaluating medical data is low due to the limitations and disadvantages of the prior art.
According to a first aspect of the present disclosure, there is provided a method for evaluating and processing medical data, comprising: acquiring medical data to be evaluated and disease types corresponding to the medical data to be evaluated; evaluating medical data to be evaluated by utilizing a first evaluation rule matched with the disease type to obtain a first evaluation result; acquiring a manual evaluation result aiming at the medical data to be evaluated as a second evaluation result; and if the first evaluation result is inconsistent with the second evaluation result and the second evaluation result is the positive evaluation result, acquiring a second evaluation rule corresponding to the second evaluation result, associating the second evaluation rule with the disease type, and visually displaying the association state of the second evaluation rule and the disease type.
According to a second aspect of the present disclosure, there is provided an evaluation processing apparatus for medical data, comprising: the information acquisition module is used for acquiring medical data to be evaluated and disease types corresponding to the medical data to be evaluated; the data evaluation module is used for evaluating medical data to be evaluated by utilizing a first evaluation rule matched with the disease type to obtain a first evaluation result; the result acquisition module is used for acquiring a manual evaluation result aiming at the medical data to be evaluated as a second evaluation result; and the rule association module is used for acquiring a second evaluation rule corresponding to the second evaluation result if the first evaluation result is inconsistent with the second evaluation result and the second evaluation result is a positive evaluation result, associating the second evaluation rule with the disease type and visually displaying the association state of the second evaluation rule and the disease type.
Optionally, the profile assessment module comprises: the index obtaining unit is used for obtaining index information related to the disease type in the medical data to be evaluated; and the index evaluation unit is used for evaluating the index information by using a first evaluation rule matched with the disease type to obtain a first evaluation result.
Optionally, the rule association module includes: a quantity determination unit for determining the quantity of the historical evaluation records identical to the first evaluation result in the historical evaluation records based on the disease type, the index information and the first evaluation result; and the quantity judging unit is used for acquiring a second evaluation rule corresponding to the second evaluation result if the quantity of the historical evaluation records is greater than a preset threshold value.
Optionally, the evaluation processing device for medical data further comprises: and the rule removing module is used for removing the matching relation between the disease type and the first evaluation rule if the first evaluation result is inconsistent with the second evaluation result and the second evaluation result is a negative evaluation result.
Optionally, the rule association module includes: a rule determination unit for associating the second evaluation rule with the disease type if the second evaluation rule is included in the evaluation rule base.
Optionally, the evaluation processing device for medical data further comprises: and the rule storage module is used for storing the second evaluation rule into the evaluation rule base if the second evaluation rule is not contained in the evaluation rule base, associating the second evaluation rule with the disease type, and visually displaying the association state of the second evaluation rule and the disease type.
Optionally, the evaluation processing device for medical data further comprises: the rule determining module is used for determining a distinguishing rule between the second evaluation rule and the first evaluation rule if the second evaluation rule is not contained in the evaluation rule base; and the rule correction module is used for correcting the first evaluation rule based on the distinguishing rule and visually displaying the association state of the disease type and the corrected first evaluation rule.
Optionally, the evaluation processing device for medical data further comprises: and the report generation module is used for generating an evaluation report of the medical data to be evaluated based on the second evaluation result and carrying out visual display on the evaluation report.
According to a third aspect of the present disclosure, a computer-readable storage medium is provided, on which a computer program is stored, which when executed by a processor, implements the method of assessment processing of medical data as described above.
According to a fourth aspect of the present disclosure, there is provided an electronic device comprising: one or more processors; a storage device for storing one or more programs which, when executed by the one or more processors, cause the one or more processors to implement the method of assessment processing of medical data as described above.
Exemplary embodiments of the present disclosure have the following advantageous effects:
according to the technical scheme provided by some embodiments of the disclosure, firstly, medical data to be evaluated and a disease type corresponding to the medical data to be evaluated are obtained; then, evaluating the medical data to be evaluated by utilizing a first evaluation rule matched with the disease type to obtain a first evaluation result; secondly, acquiring a manual evaluation result aiming at the medical data to be evaluated as a second evaluation result; and then, if the first evaluation result is inconsistent with the second evaluation result and the second evaluation result is a positive evaluation result, acquiring a second evaluation rule corresponding to the second evaluation result, associating the second evaluation rule with the disease type, and visually displaying the association state of the second evaluation rule with the disease type. On one hand, the second evaluation is carried out on the medical data to be evaluated, the first evaluation result and the second evaluation result are obtained, and the first evaluation result and the second evaluation result are compared, so that whether the first evaluation rule corresponding to the disease type is correct or not can be fed back, and if the first rule is incorrect, the second evaluation rule can be adopted, so that the accuracy of the evaluation result of the medical data corresponding to the disease type in the subsequent evaluation is improved; in addition, the second evaluation rule is associated with the disease type, so that the server can directly start the second evaluation rule under the condition of evaluating the medical data to be evaluated subsequently, the evaluation accuracy of the medical data to be evaluated by the server is improved, the artificial workload is reduced, the evaluation working efficiency is improved, and the time for evaluating the medical data to be evaluated is further saved. On the other hand, the association status of the second rating rule and the disease type is visually displayed for the user to view.
It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the disclosure.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present disclosure and together with the description, serve to explain the principles of the disclosure. It is to be understood that the drawings in the following description are merely exemplary of the disclosure, and that other drawings may be derived from those drawings by one of ordinary skill in the art without the exercise of inventive faculty. In the drawings:
FIG. 1 schematically illustrates a flow chart of a method of assessment processing of medical data according to an exemplary embodiment of the present disclosure;
FIG. 2 schematically illustrates a diagram of a visual presentation of the status of an association between one disease type and a corresponding assessment rule according to an exemplary embodiment of the present disclosure;
FIG. 3 schematically illustrates a schematic diagram of a medical data assessment process flow according to an exemplary embodiment of the present disclosure;
FIG. 4 schematically illustrates a block diagram of an assessment processing apparatus of medical data according to an exemplary embodiment of the present disclosure;
FIG. 5 schematically illustrates a block diagram of a profile assessment module according to an exemplary embodiment of the present disclosure;
FIG. 6 schematically illustrates a block diagram of a rule association module according to an exemplary embodiment of the present disclosure;
FIG. 7 schematically shows a block diagram of an assessment processing apparatus of medical data according to another exemplary embodiment of the present disclosure;
FIG. 8 schematically illustrates a block diagram of a rule association module, according to another exemplary embodiment of the present disclosure;
FIG. 9 schematically shows a block diagram of an assessment processing apparatus of medical data according to another exemplary embodiment of the present disclosure;
FIG. 10 schematically shows a block diagram of an assessment processing apparatus of medical data according to another exemplary embodiment of the present disclosure;
FIG. 11 schematically shows a block diagram of an assessment processing apparatus of medical data according to another exemplary embodiment of the present disclosure;
fig. 12 schematically shows a block diagram of an electronic device according to an exemplary embodiment of the present disclosure.
Detailed Description
Example embodiments will now be described more fully with reference to the accompanying drawings. Example embodiments may, however, be embodied in many different forms and should not be construed as limited to the examples set forth herein; rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the concept of example embodiments to those skilled in the art. The described features, structures, or characteristics may be combined in any suitable manner in one or more embodiments. In the following description, numerous specific details are provided to give a thorough understanding of embodiments of the disclosure. One skilled in the relevant art will recognize, however, that the subject matter of the present disclosure can be practiced without one or more of the specific details, or with other methods, components, devices, steps, and the like. In other instances, well-known technical solutions have not been shown or described in detail to avoid obscuring aspects of the present disclosure.
In the present disclosure, the terms "comprises" and "comprising" are used in an open-ended fashion, and mean that there may be additional elements/components/etc. in addition to the listed elements/components/etc. In addition, the terms "first" and "second" used in the present disclosure are for the purpose of distinction only and should not be construed as a limitation of the present disclosure.
Furthermore, the drawings are merely schematic illustrations of the present disclosure and are not necessarily drawn to scale. The same reference numerals in the drawings denote the same or similar parts, and thus their repetitive description will be omitted. Some of the block diagrams shown in the figures are functional entities and do not necessarily correspond to physically or logically separate entities. These functional entities may be implemented in the form of software, or in one or more hardware modules or integrated circuits, or in different networks and/or processor devices and/or microcontroller devices.
The flow charts shown in the drawings are merely illustrative and do not necessarily include all of the steps. For example, some steps may be decomposed, and some steps may be combined or partially combined, so that the actual execution sequence may be changed according to the actual situation.
With the development of internet technology, the medical industry is gradually coming into the medical information era. However, a large amount of staff is still required for the medical management work. For example, medical insurance workers in hospitals need to assess whether the disease category declared by the insurance participants belongs to the disease category within the medical insurance reimbursement range. Firstly, the assessment work needs doctors of related disease categories to assess the disease categories of the declared data, then the doctors write assessment results in an assessment application form and sign and confirm the assessment results, and then medical insurance workers continue the subsequent process of medical insurance reimbursement according to the assessment results. The auditing process makes the auditing work complicated and the working efficiency of medical insurance workers low. In order to solve the problems, the present disclosure provides an evaluation processing method for medical data.
It should be noted that, in the exemplary embodiment of the present disclosure, the evaluation processing method of the medical data described below may be generally implemented by a server, that is, the respective steps of the evaluation processing method of the medical data may be executed by the server, in which case, the evaluation processing apparatus of the medical data may be configured in the server.
In addition, the evaluation processing method of the medical data may also be implemented by a terminal device (e.g., a mobile phone, a tablet, a personal computer, etc.), that is, the steps of the evaluation processing method of the medical data may be executed by the terminal device, in which case the evaluation processing means of the medical data may be configured in the terminal device.
As shown in fig. 1, the assessment processing method of medical data of the exemplary embodiment of the present disclosure may include the steps of:
s102, medical data to be evaluated and disease types corresponding to the medical data to be evaluated are obtained.
In an exemplary embodiment of the present disclosure, the medical data may be various medical-related disease description data, clinical diagnosis data, recovery advice data, and the like. After the server receives the medical data sent by each terminal device, it is usually necessary to classify the medical data into diseases, that is, to determine the disease type corresponding to the medical data. In this case, there is an evaluation process of the medical data, and in an exemplary embodiment of the present disclosure, such medical data that needs to be evaluated is determined as the medical data to be evaluated.
The disease type can be extracted from the content of the medical data to be evaluated, or can be directly obtained through the disease type input by the user. For example, the disease types may include diabetes, hypertension, heart disease, and the like.
For example, for the chronic disease management of basic medical insurance outpatient service, the paramedics submit medical data to be evaluated to medical insurance staff, and the medical insurance staff inputs personal information and disease types of the paramedics into the evaluation processing device of the medical data according to the medical data to be evaluated, or directly inputs the medical data to be evaluated into the evaluation processing device of the medical data after processing the medical data by using an optical character recognition technology.
S104, evaluating the medical data to be evaluated by utilizing a first evaluation rule matched with the disease type to obtain a first evaluation result.
In an exemplary embodiment of the present disclosure, the first evaluation rule may include a set of evaluation rules employed by the server in the case of evaluating the medical data to be evaluated corresponding to the disease type, and the first evaluation rule may be stored in the evaluation rule base. The evaluation rule base can be configured in the evaluation processing device of the medical data, and also can be configured in the server, and can be called from the server when the data to be evaluated is evaluated.
The first evaluation result may be a result obtained after the server evaluates the medical data to be evaluated. For example, a piece of medical information about diabetes includes: fasting plasma glucose was 5.0 mmol/l. If the evaluation rule of the server is that the fasting blood sugar is greater than 7.0mmol/l, the obtained evaluation result is that the medical data does not belong to diabetes.
According to one embodiment of the present disclosure, the medical data to be evaluated may contain index information related to a corresponding disease type, wherein the index information may include a historical diagnosis record, personal information of a user to whom the medical data to be evaluated belongs, and the like, for example, the historical diagnosis record may include a diagnosis certificate issued by a medical institution for the disease, a record of a drug related to the disease, an examination result in the process of treating the disease, and the like. Therefore, the server can obtain the index information related to the disease type in the medical data to be evaluated, and then evaluate the index information by using the first evaluation rule matched with the disease type to obtain a first evaluation result.
For example, a medical profile regarding diabetes is assessed. The diabetes related assessment rules in the assessment system include: 1. whether the medical data has a discharge summary or a disease diagnosis certificate issued by more than two medical institutions; 2. more than two blood sugar test reports: fasting blood sugar is more than 7.0mmol/l, and blood sugar is more than or equal to 11.1mmol/l in two hours under the condition of oral glucose tolerance test; 3. recording continuous use of hypoglycemic drugs or insulin in recent two years; 4. provide a report sheet of renal function, fundus contrast, electromyogram, positive report sheet of nerve examination, etc. If the above-mentioned rules are satisfied, the evaluation result of "the medical data is the medical data about diabetes" can be outputted.
The evaluation system may extract index information associated with each rule from the medical data, if the medical data has index information that is: disease diagnosis certificate, fasting blood sugar value of 10.0mmol/l, blood sugar more than or equal to 15.0mmol/l in two hours, hypoglycemic agent for multiple use, renal function report sheet, etc., the evaluation system can output the evaluation result that the medical data is the medical data about diabetes.
S106, acquiring a manual evaluation result aiming at the medical data to be evaluated as a second evaluation result.
The artificial evaluation result may be obtained according to the disease type and the index information in the medical data to be evaluated after the first evaluation result in step S104 is obtained, or may be obtained by using the first evaluation result as a reference and combining with the diagnosis experience of the disease type. In addition, the artificial evaluation result can also be obtained according to the disease type and the index information in the medical data to be evaluated after the medical data to be evaluated is obtained. It should be noted that, the present exemplary embodiment does not limit the process of obtaining the artificial evaluation result for the medical data to be evaluated, and both the method and the step that can achieve the artificial evaluation result for the medical data to be evaluated can be regarded as the protection scope of the present disclosure.
For example, a medical data concerning a chronic disease is evaluated, and it is necessary to determine whether the disease is a chronic disease. The content of the medical data comprises: disease diagnosis proves that the fasting blood sugar value is 10.0mmol/l, the blood sugar value in two hours is more than or equal to 15.0mmol/l, and the diabetes medicine is continuously used, etc. The doctor can obtain the "the medical data is about the chronic disease" according to the medical data.
And S108, if the first evaluation result is inconsistent with the second evaluation result and the second evaluation result is a positive evaluation result, acquiring a second evaluation rule corresponding to the second evaluation result, associating the second evaluation rule with the disease type, and visually displaying the association state of the second evaluation rule and the disease type.
In an exemplary embodiment of the present disclosure, the positive assessment result is a result of the medical data to be assessed passing the assessment. The negative evaluation result corresponding to the positive evaluation result is a result that the medical data to be evaluated fails to be evaluated. In the server, a positive rating result may be represented by 1, and a negative rating result may be represented by 0. Wherein, 1 can represent that under the condition of evaluating medical data to be evaluated, the index information of the medical data is contained in the evaluation rule range and passes the evaluation; 0 may represent that, in the case of evaluating the medical data to be evaluated, part of the index information of the medical data to be evaluated is not included in the range of the evaluation rule and fails to be evaluated.
The second evaluation rule may be a rule adopted by the person to evaluate the medical data to be evaluated. The association of the second evaluation rule with the disease type may be such that the evaluation of the disease type can be performed using the second evaluation rule, i.e. in the case of an evaluation of the medical data to be evaluated, an evaluation can be performed using a second evaluation rule which matches the disease type.
The association status of the second assessment rule and the disease type may be visually displayed, a graph or a table capable of representing the association relationship between the disease type and the second assessment rule may be used, and the visually displayed graph may be a tree structure diagram, a star structure diagram, or a connection line capable of representing the association relationship between the disease type and the second assessment rule, or the like. In an exemplary embodiment of the disclosure, the association status of the second evaluation rule and the disease type is visually displayed, and the relationship between the second evaluation rule and the disease type can be visually displayed for the user to view.
Referring to fig. 2, a visualization is presented for the association status between the disease type of diabetes and the matching assessment rule. The rating rules may include: 1. whether the medical data has a discharge summary or a disease diagnosis certificate issued by more than two medical institutions; 2. more than two blood sugar test reports; 3. continuously using the hypoglycemic agent within the last two years; 4. provide a report sheet of renal function, fundus contrast, electromyogram, etc.
The schematic diagram of the present exemplary embodiment may employ lines to connect the evaluation rule with diabetes, and show the association status between diabetes and the matching evaluation rule. That is, in the case where the above-mentioned rules are satisfied, the evaluation result of "the medical data is the medical data concerning diabetes" can be output. Other formats may be used for visualization, and a visualization format capable of displaying the association status of the assessment rule with the disease type may be used as the scope of the present disclosure.
According to one embodiment of the present disclosure, the number of historical assessment records in the historical assessment records that is the same as the first assessment result may be determined based on the disease type, the index information, and the first assessment result; and if the number of the historical evaluation records is larger than a preset threshold value, acquiring a second evaluation rule corresponding to a second evaluation result.
The predetermined threshold may be a natural number, such as 0, 1, 3, etc., that characterizes the historical rating record quantity threshold. The index information may be included in the medical data to be evaluated, that is, the present exemplary embodiment may also determine the same number of historical evaluation records as the first evaluation result in the historical evaluation records based on the type of disease, the medical data to be evaluated, and the first evaluation result.
According to another embodiment of the present disclosure, if the first evaluation result is inconsistent with the second evaluation result and the second evaluation result is a negative evaluation result, the matching relationship between the disease type and the first evaluation rule is released. That is, the second evaluation result indicates that part of the index information of the medical data to be evaluated is not included in the second evaluation rule range in the case of evaluating the medical data to be evaluated. In the exemplary embodiment, the second evaluation result is used as the target evaluation result, and the medical data to be evaluated matching the disease type cannot be evaluated by using the first evaluation rule.
It is further noted that in an exemplary embodiment of the present disclosure, the second rating rule is associated with the disease type if the second rating rule is included in the rating rule base. That is, the assessment repository may have stored therein second assessment rules for use in the manual assessment of the data to be assessed, but the assessment processing means of the medical data may not match the second assessment rules to the disease type, so that the second assessment rules cannot be enabled during the assessment process. Thus, the present disclosure may associate the second assessment rule with the disease type.
In addition, according to another embodiment of the present disclosure, if the second rating rule is not included in the rating rule base, the second rating rule may be stored in the rating rule base, and the second rating rule may be associated with the disease type, and the association status of the second rating rule with the disease type may be visually displayed.
In the embodiment of the present invention, the second evaluation rule is stored in the evaluation rule base, so that the rules of the evaluation rule base are complete, and the accuracy of the evaluation work is improved; then, the stored second evaluation rule is associated with the disease type, so that the working efficiency of evaluating the medical data to be evaluated is improved; and then, the stored association state of the second evaluation rule and the disease type is visually displayed, so that the user can conveniently view the association state.
It should be noted that, in order to save the storage space of the evaluation rule base and improve the storage utilization and the efficiency of the evaluation work, the second evaluation rule may be partially the same as the first evaluation rule, and in another exemplary embodiment of the present disclosure, if the second evaluation rule is not included in the evaluation rule base, the differentiation rule between the second evaluation rule and the first evaluation rule is determined; and modifying the first evaluation rule based on the distinguishing rule, and visually displaying the association state of the disease type and the modified first evaluation rule.
The differentiation rule in the present exemplary embodiment may be included in the second rating rule, but may not be included in the rating repository. The modification of the first evaluation rule may be to add the differentiation rule to the first evaluation rule, or to delete part of the rules of the first evaluation rule or to modify information of the relevant rule.
According to another embodiment of the present disclosure, after obtaining the assessment results, in order to enable the user to obtain the results of the medical data to be assessed, the user can view the results. The server can generate an evaluation report of the medical data to be evaluated based on the second evaluation result, and visually display the evaluation report.
Wherein, the evaluation report can contain the result of the evaluation of the medical data to be evaluated. If the first evaluation result is consistent with the second evaluation result, an evaluation report of the medical data to be evaluated can be generated according to the first evaluation result.
For example, assessing a medical profile for a chronic disease requires determining whether the disease is a chronic disease. The content of the medical data comprises: disease diagnosis certificate, fasting blood glucose value of 10.0mmol/l, blood glucose more than or equal to 15.0mmol/l in two hours, renal function report list, fundus contrast record, continuous use of hypertension medicine, etc.
The diabetes related assessment rules in the assessment system include: 1. whether the medical data has a discharge summary or a disease diagnosis certificate issued by more than two medical institutions; 2. more than two blood sugar test reports: fasting blood sugar is more than 7.0mmol/l, and blood sugar is more than or equal to 11.1mmol/l in two hours under the condition of oral glucose tolerance test; 3. recording continuous use of hypoglycemic drugs or insulin in recent two years; 4. provide a report sheet of renal function, fundus contrast, electromyogram, positive report sheet of nerve examination, etc. If the above-mentioned rules are satisfied, the evaluation result of "the medical data is the medical data about diabetes" can be outputted.
The evaluation system extracts that the disease type corresponding to the medical data is diabetes according to the medical data, then the evaluation rule matched with the diabetes is started, and the medical data which does not conform to the rule matched with the diabetes is obtained after evaluation, namely the medical data does not belong to the diabetes type, so that the evaluation result that the medical data is not the medical data related to the chronic disease is obtained.
However, the doctor determines that the medical data is data about the chronic disease according to the information of the continuous use of the hypertension drugs and the like in the medical data, namely that the medical data meets the condition of the chronic disease. That is, hypertension also belongs to the category of chronic diseases, and there is a deviation in the evaluation result obtained only by the evaluation rule of diabetes. Therefore, in order to improve the evaluation accuracy of the evaluation system, the evaluation rule of the doctor is obtained and is associated with the diabetes, and the rule is compared with the diabetes in the evaluation system, or the evaluation rule of the doctor is compared with the evaluation rule of the evaluation system, so as to determine a distinguishing rule, namely, the continuous use of the hypertension drug can also be used as one of the chronic diseases.
Fig. 3 is a schematic diagram illustrating a process flow for evaluating medical data according to an exemplary embodiment of the present disclosure. The specific process is as follows:
in step S302, the evaluation processing device for medical data may receive medical data to be evaluated; in step S304, a disease type corresponding to the medical data to be evaluated may be obtained, the disease type is determined, and then, a first evaluation rule corresponding to the disease type may be enabled from the evaluation rule base; in step S306, the medical data to be evaluated may be evaluated by using a first evaluation rule; in step S308, a first evaluation result may be obtained according to the evaluation in step S306; in step S310, a human evaluation result of the medical data to be evaluated may be obtained as a second evaluation result; in step S312, it is determined whether the first evaluation result is consistent with the second evaluation result, and if the first evaluation result is consistent with the second evaluation result, an evaluation report is directly generated and visually displayed; if the first evaluation result is inconsistent with the second evaluation result, executing step S314; in step S314, the type of the second evaluation result is determined, if the second evaluation result is a negative type, the matching relationship between the first evaluation rule and the disease type may be released, and if the second evaluation result is a positive type, step S316 is performed; in step S316, a second evaluation rule corresponding to the second evaluation result may be obtained, the second evaluation rule is associated with the disease type, and the association status of the second evaluation rule and the disease type is visually displayed; in step S318, a rating report may be generated and visually displayed according to the second rating result.
In addition, in step S302, index information related to assessment in the medical data to be assessed may also be extracted, and then, the index information is assessed by using a first assessment rule corresponding to a disease type. In step S316, if the second evaluation rule is not included in the evaluation rule base, a differentiation rule between the second evaluation rule and the first evaluation rule may also be determined, the first evaluation rule is modified based on the differentiation rule, and the association status between the disease type and the modified first evaluation rule is visually displayed. The evaluation processing method of the medical data of the exemplary embodiment of the disclosure can not only improve the efficiency of evaluation work, shorten the evaluation time of the medical data to be evaluated, and realize the informatization of medical industry management; the accuracy of the evaluation result can also be improved by comparing the first evaluation result with the second evaluation result.
It should be noted that although the various steps of the methods of the present disclosure are depicted in the drawings in a particular order, this does not require or imply that these steps must be performed in this particular order, or that all of the depicted steps must be performed, to achieve desirable results. Additionally or alternatively, certain steps may be omitted, multiple steps combined into one step execution, and/or one step broken down into multiple step executions, etc.
Further, there is also provided in the present exemplary embodiment an evaluation processing apparatus 400 of medical data, and referring to fig. 4, the evaluation processing apparatus 400 of medical data according to the exemplary embodiment of the present disclosure may include: an information acquisition module 401, a data evaluation module 403, a result acquisition module 405, and a rule association module 407.
The information obtaining module 401 is configured to obtain a medical data to be evaluated and a disease type corresponding to the medical data to be evaluated; the data evaluation module 403 is configured to evaluate the medical data to be evaluated by using a first evaluation rule matched with the disease type to obtain a first evaluation result; a result obtaining module 405, configured to obtain a manual evaluation result for the medical data to be evaluated as a second evaluation result; and the rule association module 407 is configured to, if the first evaluation result is inconsistent with the second evaluation result and the second evaluation result is a positive evaluation result, obtain a second evaluation rule corresponding to the second evaluation result, associate the second evaluation rule with the disease type, and visually display an association state of the second evaluation rule with the disease type.
Referring to fig. 5, the profile assessment module 403 may include, according to an exemplary embodiment of the present disclosure: an index acquisition unit 502 and an index evaluation unit 504.
The index obtaining unit 502 is configured to obtain index information related to a disease type in medical data to be evaluated; the index evaluation unit 504 is configured to evaluate the index information by using a first evaluation rule matching the disease type, so as to obtain a first evaluation result.
According to an exemplary embodiment of the present disclosure, referring to fig. 6, the rule association module 407 may include: a number determination unit 601 and a number judgment unit 603.
Wherein the number determination unit 601 is configured to determine a number of historical evaluation records among the historical evaluation records that is the same as the first evaluation result based on the disease type, the index information, and the first evaluation result; a quantity judgment unit 603, configured to, if the number of historical evaluation records is greater than the preset threshold, obtain a second evaluation rule corresponding to the second evaluation result.
According to another exemplary embodiment of the present disclosure, referring to fig. 7, the evaluation processing apparatus 700 of the medical data may further include, compared to the evaluation processing apparatus 400 of the medical data: a rule dismissal module 702 may be configured to perform: and if the first evaluation result is inconsistent with the second evaluation result and the second evaluation result is a negative evaluation result, removing the matching relation between the disease type and the first evaluation rule.
According to an exemplary embodiment of the present disclosure, referring to fig. 8, the rule association module 407 may include: the rule determining unit 801 may be configured to perform: associating the second rating rule with the disease type if the second rating rule is included in the rating rule base.
According to another exemplary embodiment of the present disclosure, referring to fig. 9, the evaluation processing apparatus 900 of the medical data may further include, compared to the evaluation processing apparatus 400 of the medical data: a rule storage module 902, which may be configured to perform: and if the second evaluation rule is not contained in the evaluation rule base, storing the second evaluation rule in the evaluation rule base, associating the second evaluation rule with the disease type, and visually displaying the association state of the second evaluation rule and the disease type.
According to another exemplary embodiment of the present disclosure, referring to fig. 10, the evaluation processing apparatus 1000 of the medical data may further include, compared to the evaluation processing apparatus 400 of the medical data: a rule determination module 1001 and a rule modification module 1003.
The rule determining module 1001 is configured to determine a distinguishing rule between the second evaluation rule and the first evaluation rule if the second evaluation rule is not included in the evaluation rule base; the rule modification module 1003 is configured to modify the first evaluation rule based on the differentiation rule, and visually display an association state between the disease type and the modified first evaluation rule.
According to another exemplary embodiment of the present disclosure, referring to fig. 11, the evaluation processing apparatus 1100 of the medical data may further include, compared to the evaluation processing apparatus 400 of the medical data: a report generation module 1102, which may be configured to perform: and generating an evaluation report of the medical data to be evaluated based on the second evaluation result, and visually displaying the evaluation report.
The details of each module/unit in the above-mentioned apparatus have been described in detail in the embodiments of the method section, and thus are not described again.
In an exemplary embodiment of the present disclosure, there is also provided a computer-readable storage medium having stored thereon a program product capable of implementing the above-described method of the present specification. In some possible embodiments, aspects of the invention may also be implemented in the form of a program product comprising program code means for causing a terminal device to carry out the steps according to various exemplary embodiments of the invention described in the above-mentioned "exemplary methods" section of the present description, when the program product is run on the terminal device.
In an exemplary embodiment of the present disclosure, an electronic device capable of implementing the above method is also provided.
As will be appreciated by one skilled in the art, aspects of the present invention may be embodied as a system, method or program product. Thus, various aspects of the invention may be embodied in the form of: an entirely hardware embodiment, an entirely software embodiment (including firmware, microcode, etc.) or an embodiment combining hardware and software aspects that may all generally be referred to herein as a "circuit," module "or" system.
An electronic device 1200 according to this embodiment of the invention is described below with reference to fig. 12. The electronic device 1200 shown in fig. 12 is only an example, and should not bring any limitation to the functions and the scope of use of the embodiments of the present invention.
As shown in fig. 12, the electronic device 1200 is embodied in the form of a general purpose computing device. The components of the electronic device 1200 may include, but are not limited to: the at least one processing unit 1210, the at least one memory unit 1220, the bus 1230 connecting the various system components (including the memory unit 1220 and the processing unit 1210), and the display unit 1240.
Wherein the storage unit stores program code, which may be executed by the processing unit 1210, to cause the processing unit 1210 to perform the steps according to various exemplary embodiments of the present invention described in the above section "exemplary methods" of the present description. For example, the processing unit 1210 may perform steps S102 to S108 as illustrated in fig. 1.
The storage unit 1220 may include a readable medium in the form of a volatile memory unit, such as a random access memory unit (RAM)12201 and/or a cache memory unit 12202, and may further include a read only memory unit (ROM) 12203.
The electronic device 1200 may also communicate with one or more external devices 1300 (e.g., keyboard, pointing device, bluetooth device, etc.), with one or more devices that enable a user to interact with the electronic device 1200, and/or with any devices (e.g., router, modem, etc.) that enable the electronic device 1200 to communicate with one or more other computing devices. Such communication may occur via input/output (I/O) interfaces 1250. Also, the electronic device 1200 may communicate with one or more networks (e.g., a Local Area Network (LAN), a Wide Area Network (WAN), and/or a public network such as the Internet) via the network adapter 1260. As shown, the network adapter 1260 communicates with the other modules of the electronic device 1200 via the bus 1230. It should be appreciated that although not shown, other hardware and/or software modules may be used in conjunction with the electronic device 1200, including but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data backup storage systems, among others.
Through the above description of the embodiments, those skilled in the art will readily understand that the exemplary embodiments described herein may be implemented by software, or by software in combination with necessary hardware. Therefore, the technical solution according to the embodiments of the present disclosure may be embodied in the form of a software product, which may be stored in a non-volatile storage medium (which may be a CD-ROM, a usb disk, a removable hard disk, etc.) or on a network, and includes several instructions to enable a computing device (which may be a personal computer, a server, a terminal device, or a network device, etc.) to execute the method according to the embodiments of the present disclosure.
Furthermore, the above-described figures are merely schematic illustrations of processes involved in methods according to exemplary embodiments of the invention, and are not intended to be limiting. It will be readily understood that the processes shown in the above figures are not intended to indicate or limit the chronological order of the processes. In addition, it is also readily understood that these processes may be performed synchronously or asynchronously, e.g., in multiple modules.
It should be noted that although in the above detailed description several modules or units of the device for action execution are mentioned, such a division is not mandatory. Indeed, the features and functionality of two or more modules or units described above may be embodied in one module or unit, according to embodiments of the present disclosure. Conversely, the features and functions of one module or unit described above may be further divided into embodiments by a plurality of modules or units.
Other embodiments of the disclosure will be apparent to those skilled in the art from consideration of the specification and practice of the disclosure disclosed herein. This application is intended to cover any variations, uses, or adaptations of the disclosure following, in general, the principles of the disclosure and including such departures from the present disclosure as come within known or customary practice within the art to which the disclosure pertains. It is intended that the specification and examples be considered as exemplary only, with a true scope and spirit of the disclosure being indicated by the following claims.
It will be understood that the present disclosure is not limited to the precise arrangements described above and shown in the drawings and that various modifications and changes may be made without departing from the scope thereof. The scope of the present disclosure is to be limited only by the terms of the appended claims.
Claims (11)
1. A method for evaluating and processing medical data, comprising:
acquiring medical data to be evaluated and a disease type corresponding to the medical data to be evaluated;
evaluating the medical data to be evaluated by utilizing a first evaluation rule matched with the disease type to obtain a first evaluation result;
acquiring a manual evaluation result aiming at the medical data to be evaluated as a second evaluation result;
and if the first evaluation result is inconsistent with the second evaluation result and the second evaluation result is a positive evaluation result, acquiring a second evaluation rule corresponding to the second evaluation result, associating the second evaluation rule with the disease type, and visually displaying the association state of the second evaluation rule and the disease type.
2. The method for evaluating medical data according to claim 1, wherein the evaluating the medical data to be evaluated by using the first evaluation rule matching with the disease type includes:
acquiring index information related to the disease type in the medical data to be evaluated;
and evaluating the index information by using a first evaluation rule matched with the disease type to obtain a first evaluation result.
3. The method for processing an assessment of medical data according to claim 2, wherein obtaining a second assessment rule corresponding to said second assessment result comprises:
determining the same number of historical assessment records as the first assessment result in the historical assessment records based on the disease type, the index information and the first assessment result;
and if the number of the historical evaluation records is larger than a preset threshold value, acquiring a second evaluation rule corresponding to the second evaluation result.
4. The method for processing an assessment of medical data according to claim 1, further comprising:
and if the first evaluation result is inconsistent with the second evaluation result and the second evaluation result is a negative evaluation result, releasing the matching relationship between the disease type and the first evaluation rule.
5. The method for rating a medical data according to any of claims 1 to 4, wherein associating the second rating rule with the disease type comprises:
associating said second rating rule with said disease type if said second rating rule is contained in a rating rule base.
6. The method for processing an assessment of medical data according to claim 5, further comprising:
if the second evaluation rule is not contained in the evaluation rule base, the second evaluation rule is stored in the evaluation rule base, the second evaluation rule is associated with the disease type, and the association state of the second evaluation rule and the disease type is visually displayed.
7. The method for processing an assessment of medical data according to claim 5, further comprising:
determining a discrimination rule between said second rating rule and said first rating rule if said second rating rule is not contained in said rating rule base;
and modifying the first evaluation rule based on the distinguishing rule, and visually displaying the association state of the disease type and the modified first evaluation rule.
8. The method for processing an assessment of medical data according to any of claims 1 to 4, further comprising:
and generating an evaluation report of the medical data to be evaluated based on the second evaluation result, and visually displaying the evaluation report.
9. An apparatus for evaluating and processing medical data, comprising:
the information acquisition module is used for acquiring medical data to be evaluated and disease types corresponding to the medical data to be evaluated;
the data evaluation module is used for evaluating the medical data to be evaluated by using a first evaluation rule matched with the disease type to obtain a first evaluation result;
the result acquisition module is used for acquiring a manual evaluation result aiming at the medical data to be evaluated as a second evaluation result;
and the rule association module is used for acquiring a second evaluation rule corresponding to the second evaluation result if the first evaluation result is inconsistent with the second evaluation result and the second evaluation result is a positive evaluation result, associating the second evaluation rule with the disease type and visually displaying the association state of the second evaluation rule and the disease type.
10. A computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, carries out a method for the assessment processing of medical data according to any one of claims 1 to 8.
11. An electronic device, comprising:
one or more processors;
a storage device for storing one or more programs which, when executed by the one or more processors, cause the one or more processors to implement the method for assessment processing of medical data according to any one of claims 1 to 8.
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