Method, device, system and equipment for disease course management and storage medium

Abstract

The embodiment of the invention discloses a disease course management method, device, system and equipment and a storage medium, the method, device and equipment are applied to a server side in a disease course management system, the disease course management system further comprises a medical care side and a patient side, and the method comprises the following steps: obtaining previous detection data of a patient on a body index from a medical record file of the patient, the corresponding previous detection time is determined; wherein information in the medical record file is input by the medical care terminal and / or the patient terminal; determining a correlation coefficient between previous detection data and previous detection time; determining the rationality of the doctor seeing scheme adopted by the patient based on the correlation coefficient to obtain a rationality judgment result; the rationality judgment result is used for performing subsequent disease course management on the patient. According to the method, the rationality of the doctor seeing scheme adopted by the patient is traced by analyzing the correlation coefficient between the previous detection data and the previous detection time recorded in the medical record file of the patient, and scientific and effective disease course management service can be provided for the patient.

Description

Technical Field

[0001] This application relates to the field of medical informatization technology, and in particular, to a method, device, system, equipment and storage medium for course management. Background Art

[0002] Course management is a patient-centered care model. In the existing course management process, the diseases of patients can be analyzed through the disease data rechecked at the time of the patient's admission diagnosis, so that a course management plan suitable for the patient, such as a follow-up plan, can be obtained by combining the analysis results and the patient's disease duration.

[0003] However, the existing solutions do not comprehensively analyze the patient's historical medical treatment situations. For example, it is impossible to know whether the medical treatment plans adopted by the patient in the past period are reasonable. Therefore, it is difficult to provide scientific and effective management and care for the patient in the subsequent course management, which is not conducive to establishing a harmonious doctor-patient relationship. Summary of the Invention

[0004] At least one method, device, system, equipment and storage medium for course management are provided in the embodiments of this application.

[0005] The technical solution of this application is realized as follows:

[0006] In a first aspect, an embodiment of this application provides a method for course management, which is applied to a server in a course management system. The course management system further includes a medical staff terminal and a patient terminal. The method includes: obtaining the historical detection data of the patient's physical indicators and the corresponding historical detection times from the patient's medical record file; wherein, the information in the medical record file is input by the medical staff terminal and / or the patient terminal; determining the correlation coefficient between the historical detection data and the historical detection times; determining the rationality of the medical treatment plan adopted by the patient based on the correlation coefficient to obtain a rationality judgment result; the rationality judgment result is used for the subsequent course management of the patient.

[0007] In a second aspect, an embodiment of this application provides a device in a course management system. The course management system further includes a medical staff terminal and a patient terminal. The device includes: a first obtaining unit, configured to obtain the historical detection data of the patient's physical indicators and the corresponding historical detection times from the patient's medical record file; wherein, the information in the medical record file is input by the medical staff terminal and / or the patient terminal; a first determining unit, configured to determine the correlation coefficient between the historical detection data and the historical detection times; a second determining unit, configured to determine the rationality of the medical treatment plan adopted by the patient based on the correlation coefficient to obtain a rationality judgment result; the rationality judgment result is used for the subsequent course management of the patient.

[0008] In a third aspect, an embodiment of the present application provides a system for disease course management. The system includes: a server, a medical staff terminal, and a patient terminal; the medical staff terminal and / or the patient terminal are used to input information in the patient's medical record file; the server is used to: obtain the historical test data of the patient's physical indicators and the corresponding historical test times from the medical record file; determine the correlation coefficient between the historical test data and the historical test times, and determine the rationality of the treatment plan adopted by the patient based on the correlation coefficient to obtain a rationality judgment result; the rationality judgment result is used for subsequent disease course management of the patient.

[0009] In a fourth aspect, an embodiment of the present application provides a device for disease course management. The device includes a memory and a processor; wherein, the memory is used to store computer-executable instructions; the processor is connected to the memory and is used to implement the method as described in the first aspect by executing the computer-executable instructions.

[0010] In a fifth aspect, an embodiment of the present application provides a computer-readable storage medium. The computer-readable storage medium stores a computer program, and when the computer program is executed by at least one processor, it implements the method as described in the first aspect.

[0011] In the embodiment of the present application, the server in the disease course management system can determine the rationality of the treatment plan adopted by the patient based on the correlation coefficient between the historical test data and the historical test times recorded in the patient's medical record file to obtain a rationality judgment result. Further, the rationality judgment result can be used for subsequent disease course management of the patient. In this way, it is beneficial to provide a more scientific and effective disease course management service for the patient. BRIEF DESCRIPTION OF THE DRAWINGS

[0012] The accompanying drawings herein are incorporated into the specification and constitute a part of this specification. These drawings illustrate embodiments consistent with the present application and are used together with the specification to explain the technical solutions of the present application.

[0013] Figure 1 It is a schematic flowchart of a method for disease course management provided by an embodiment of the present application;

[0014] Figure 2 It is a schematic diagram of a system for disease course management provided by an embodiment of the present application;

[0015] Figure 3 It is a schematic diagram of the composition structure of a device in a disease course management system provided by an embodiment of the present application;

[0016] Figure 4 It is a schematic diagram of a hardware entity of a device for disease course management in an embodiment of the present application. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0017] In order to understand the features and technical content of the embodiments of the present application in more detail, the implementation of the embodiments of the present application will be described in detail below with reference to the accompanying drawings. The attached drawings are only for reference and explanation, and are not used to limit the embodiments of the present application.

[0018] Unless otherwise defined, all technical and scientific terms used in the embodiments of the present application have the same meaning as commonly understood by those skilled in the technical field to which the present application belongs. The terms used in the embodiments of the present application are only for the purpose of describing the embodiments of the present application and are not intended to limit the present application.

[0019] In the following description, reference is made to "some embodiments", which describe a subset of all possible embodiments. However, it can be understood that "some embodiments" can be the same subset or different subsets of all possible embodiments, and can be combined with each other without conflict. It should also be noted that the terms "first / second / third" involved in the embodiments of the present application are only used to distinguish similar objects and do not represent a specific order for the objects. It can be understood that "first / second / third" can be interchanged in a specific order or sequence when allowed, so that the embodiments of the present application described here can be implemented in an order other than that illustrated or described here.

[0020] It should be understood that the term " / and" in the embodiments of the present application is only a description of the association relationship between associated objects, indicating that three relationships can exist. For example, A and / or B can represent: A exists alone, A and B exist simultaneously, and B exists alone. In addition, the character " / " in this article generally represents an "or" relationship between the preceding and following associated objects.

[0021] Disease course management is a patient-centered care model. In the existing disease course management process, the diseases of patients can be analyzed through the disease data rechecked during the patient's admission diagnosis, so that a disease course management plan suitable for the patient, such as a follow-up plan, can be obtained by combining the analysis results and the patient's disease duration.

[0022] However, the existing solutions do not comprehensively analyze the patient's historical medical treatment situations. For example, it is impossible to know whether the medical treatment plans adopted by the patient in the past period are reasonable. Therefore, it is difficult to provide scientific and effective management and care for the patient in the subsequent disease course management, which is not conducive to establishing a harmonious doctor-patient relationship.

[0023] In view of this, the embodiments of the present application provide a method, device, system, equipment, and storage medium for disease course management. This method can trace the rationality of the treatment plan adopted by the patient by analyzing the correlation coefficient between the previous test data and the previous test times recorded in the patient's medical record file. Further, a subsequent disease course management plan can be formulated for the patient according to the rationality of the treatment plan adopted by the patient. In this way, it is beneficial to provide more scientific and effective disease course management services for the patient.

[0024] The following will describe each embodiment of the present application in detail with reference to the accompanying drawings.

[0025] Figure 1 It shows a method for disease course management provided by an embodiment of the present application. This method can be executed, for example, by the server in the disease course management system. As Figure 1 shown, this method may include:

[0026] S101, obtain the previous test data of the patient's physical indicators and the corresponding previous test times from the patient's medical record file; wherein, the information in the medical record file is input by the medical staff terminal and / or the patient terminal.

[0027] In this step, the server can obtain the previous test data of the patient's physical indicators and the corresponding previous test times from the patient's medical record file. Among them, the physical indicators refer to the indicators used to reflect the patient's health status, such as heart rate, blood pressure, blood sugar, pulse rate, etc.

[0028] For example, assuming the physical indicator is blood pressure (such as systolic or diastolic pressure), then the server can obtain the blood pressure data measured by the patient previously (i.e., the previous test data) and the measurement time when the blood pressure data was measured each time (i.e., the corresponding previous test times) from the patient's medical record file. For example, the previously measured blood pressure data and the corresponding measurement times are: on March 1st, the patient's blood pressure was 160 / 100 mmHg; on March 8th, the patient's blood pressure was 120 / 80 mmHg; on March 15th, the patient's blood pressure was 150 / 95 mmHg; on April 1st, the patient's blood pressure was 110 / 85 mmHg. Among them, 160, 120, 150, and 110 represent the patient's systolic blood pressure test data; 100, 80, 95, and 85 represent the patient's diastolic blood pressure test data.

[0029] In some embodiments, the patient's medical record file may include, for example, at least one of the following contents a to d:

[0030] a. Personal information of the patient input by the patient terminal.

[0031] The patient's personal information may include, for example, but is not limited to at least one of the following: patient contact information, height, weight, work situation, smoking and alcohol consumption, allergy history, past medical history, family medical history. Such personal information may be manually input and submitted by the patient at the patient terminal, for example.

[0032] b. The patient's previous medical reports entered at the patient terminal.

[0033] The patient's previous medical reports may be uploaded to the patient terminal in the form of pictures, for example. The patient terminal may obtain the text in the uploaded pictures and then enter the obtained text into the patient's medical record file.

[0034] c. The patient's vital sign information collected by wearable devices and entered at the patient terminal.

[0035] The patient's vital sign information may be collected by the patient through wearable devices and then the collected data may be uploaded to the patient terminal, for example.

[0036] d. The patient's medical reports entered at the medical staff terminal.

[0037] In one example, after the patient completes a medical visit at the hospital, the medical staff may upload the data recorded in the medical report to the medical staff terminal; in another example, the medical staff may also query the patient's previous medical reports in the medical management system platform based on the patient's personal information and then upload the data recorded in the patient's previous medical reports to the medical staff terminal. Among them, the medical management system platform may be, for example, a hospital information system (HIS), an electronic medical record (EMR), an Internet hospital, or other systems.

[0038] S102. Determine the correlation coefficient between the previous test data and the previous test times.

[0039] After the server obtains the patient's previous test data on physical indicators and the corresponding previous test times, it may determine the correlation coefficient P between the previous test data and the previous test times. The calculation formula for the correlation coefficient P is:

[0040]

[0041] where T represents the previous test times, G represents the corresponding previous test data; Cov(T, G) is the covariance between T and G, D(T) is the variance of T, and D(G) is the variance of G.

[0042] It should be noted that when calculating P, the previous detection times T need to be converted into corresponding discrete time points first. For example, if the previous detection times are March 1st, March 8th, March 15th, and April 1st respectively, then after converting the previous detection times into discrete time points, March 1st is recorded as the 1st day, March 8th is recorded as the 8th day, March 15th is recorded as the 15th day, and April 1st is recorded as the 32nd day.

[0043] Suppose the patient's blood pressure on March 1st is 160 / 100 mmHg; on March 8th, the patient's blood pressure is 120 / 80 mmHg; on March 15th, the patient's blood pressure is 150 / 95 mmHg; on April 1st, the patient's blood pressure is 110 / 85 mmHg. Then, when G represents the patient's systolic blood pressure, the correlation coefficient P between the previous detection data and the previous detection times is:

[0044]

[0045] Among them, 14 is the average value of the discrete time points 1, 8, 15, and 32, and 135 is the average value of the systolic blood pressure detection data corresponding to each discrete time point.

[0046] When G represents the patient's diastolic blood pressure, the correlation coefficient P between the previous detection data and the previous detection times is:

[0047]

[0048] Among them, 14 is the average value of the discrete time points 1, 8, 15, and 32, and 90 is the average value of the diastolic blood pressure detection data corresponding to each discrete time point.

[0049] S103. Determine the rationality of the treatment plan adopted by the patient based on the correlation coefficient, and obtain a rationality judgment result; this rationality judgment result is used for subsequent disease course management of the patient.

[0050] In some embodiments, determining the rationality of the treatment plan adopted by the patient based on the correlation coefficient includes: in the case where the absolute value of the correlation coefficient is less than the first threshold (hereinafter referred to as case #1), it is determined that the treatment plan adopted by the patient is unreasonable; in the case where the absolute value of the correlation coefficient is greater than or equal to the first threshold and there are at least N detection data among the previous detection data that do not fall within the first numerical range (hereinafter referred to as case #2), it is determined that the treatment plan adopted by the patient is unreasonable.

[0051] Among them, N is a predefined positive integer; the first threshold can be determined by medical staff according to experience or actual scenarios, for example; the first numerical range can be determined according to the normal index range of physical indicators.

[0052] For example, assume the physical indicator is low blood pressure. Then, the first numerical range can be determined according to the low blood pressure range of normal people (i.e., the normal indicator range of low blood pressure). In one example, the first numerical range can be determined as the normal indicator range of low blood pressure. For example, if the normal indicator range of low blood pressure is 60 - 85 mmHg, then the first numerical range can be determined as 60 - 85 mmHg; in another example, medical staff can, based on personal experience, determine the first numerical range as a numerical range slightly higher or slightly lower than this normal indicator range. For example, the first numerical range can be determined as 50 - 75 mmHg, or 70 - 95 mmHg.

[0053] In the above Case #1, if the absolute value of the correlation coefficient is less than the first threshold, it can be determined that the treatment plan adopted by the patient is unreasonable.

[0054] For example, assume the first threshold is 0.1. According to the calculation result in S102, when G represents the patient's high blood pressure, the correlation coefficient P = 0.042. Since |0.042| < 0.1, it can be determined that the treatment plan adopted by the patient is unreasonable.

[0055] It can be understood that when the absolute value of the correlation coefficient P is small (for example, when the absolute value of P is less than the first threshold), it means that the previous detection times T and the corresponding previous detection data G are not correlated or have a small correlation, indicating that the treatment plan adopted by the patient fails to enable the patient to recover according to the expected recovery process. That is to say, there is a problem with the treatment plan used by the patient, or in other words, the treatment plan adopted by the patient is unreasonable. In this case, if medical staff use this treatment plan to treat the patient again later, it may lead to ineffective treatment or missed the best treatment time for the patient.

[0056] In the above Case #2, if the absolute value of the correlation coefficient is greater than or equal to the first threshold, and there are at least N detection data among the previous detection data that do not fall within the first numerical range, it can be determined that the treatment plan adopted by the patient is unreasonable.

[0057] For example, assume the first threshold is 0.1, N is 2, and the first numerical range is 60 - 85 mmHg. According to the calculation result in S102, when G represents the patient's low blood pressure, the correlation coefficient P = -0.43. Since |-0.43| > 0.1, and among the previous low blood pressure detection data 100 mmHg, 80 mmHg, 95 mmHg, 85 mmHg, there are 2 detection data (100 mmHg and 95 mmHg) that do not fall within 60 - 85 mmHg, it can be determined that the treatment plan adopted by the patient is unreasonable.

[0058] It can be understood that when the absolute value of the correlation coefficient P is relatively large (for example, when the absolute value of P is greater than or equal to the first threshold), it indicates that the correlation between the previous detection times T and the corresponding previous detection data G is relatively large, and it is negatively or positively correlated. At this time, if there are multiple (such as at least N) detection data among the previous detection data G that do not fall within the first numerical range, it indicates that the treatment plan adopted by the patient fails to enable the patient to recover according to the expected recovery process. That is to say, there is a problem with the treatment plan used by the patient, or in other words, the treatment plan adopted by the patient is unreasonable. In this case, if the medical staff use this treatment plan to treat the patient again later, it may lead to ineffective treatment or missed the best treatment time for the patient.

[0059] In some embodiments, for the above situation #2, the subsequent detection data of the patient can be focused on. For example, when the absolute value of the correlation coefficient is greater than or equal to the first threshold, it can be determined whether there are multiple detection data among the subsequent several detection data of the patient that do not fall within the first numerical range. If there are multiple detection data among the subsequent detection data of the patient that do not fall within the first numerical range, it indicates that the treatment plan adopted by the patient fails to enable the patient to recover according to the expected recovery process, and thus it can be determined that the treatment plan adopted by the patient is unreasonable.

[0060] In the embodiments of the present application, the obtained rationality judgment result can be used for subsequent disease course management of the patient. For example, when the treatment plan adopted by the patient is unreasonable, the follow-up frequency of the patient can be increased, and the treatment plan can be adjusted in a timely manner to avoid the deterioration of the patient's condition caused by improper formulation of the treatment plan by the medical staff; for another example, when the treatment plan adopted by the patient is reasonable, the follow-up frequency of the patient can be reduced to avoid unnecessary interference with the patient's daily life. In this way, it is beneficial to provide more scientific and effective management and care for the patient in subsequent disease course management, and thus establish a harmonious doctor-patient relationship.

[0061] In some embodiments, the method may further include: obtaining the registration type of the patient; querying the medical records related to the registration type in the medical record file of the patient to obtain at least one relevant medical record; dividing at least one relevant medical record into corresponding medical record sets based on the types of at least one relevant medical record; wherein, the medical record sets include: specialized disease medical record set, chronic disease medical record set, and common disease medical record set.

[0062] Among them, the registration type can be, for example, the registration department, such as the Department of Cardiology, the Department of Respiratory Medicine, etc.

[0063] For example, assume that the registration department (type of registration) of a patient is the Department of Cardiology. Since the Department of Cardiology includes arrhythmia, coronary heart disease, heart failure, and cardiomyopathy, the medical records related to this type of registration are the medical records corresponding to arrhythmia, coronary heart disease, heart failure, and cardiomyopathy. Furthermore, it is possible to query from the patient's medical record file whether there are medical records corresponding to arrhythmia, coronary heart disease, heart failure, or cardiomyopathy. For example, there are medical records corresponding to arrhythmia and coronary heart disease in the patient's medical record file. Since arrhythmia and coronary heart disease are chronic diseases, the medical records corresponding to arrhythmia and coronary heart disease in the patient's medical record file can be classified into the set of chronic disease medical records.

[0064] According to the method of this embodiment, by classifying the medical records in the patient's medical record file based on the type of registration of the patient, it is beneficial to maintain and manage the patient's medical record file. For example, the medical records in the set of chronic disease medical records can be sent to the medical staff responsible for chronic diseases, the medical records in the set of specialized disease medical records can be sent to the medical staff responsible for specialized diseases, and the medical records in the set of common disease medical records can be sent to the medical staff responsible for common diseases to achieve specialized responsibility and specialized treatment of diseases. In addition, since the medical records not related to the type of registration are not put into the medical record set, the medical records irrelevant to the patient's consultation items can be excluded. In this way, the medical staff do not need to analyze the excluded medical records, thereby reducing the workload of the medical staff.

[0065] In some embodiments, historical test data of the patient's physical indicators are obtained from the patient's medical record file, including: for each relevant medical record, if the test data recorded in the relevant medical record falls within the second numerical range, then the relevant medical record is removed from the corresponding medical record set; the remaining medical records in each medical record set are determined as valid medical records; and historical test data of the patient's physical indicators are obtained from the valid medical records.

[0066] Among them, the second numerical range can be determined according to the normal indicator range of the disease corresponding to the relevant medical record. In one example, the second numerical range can be determined as the normal indicator range of the disease corresponding to the relevant medical record. In another example, the medical staff can, according to personal experience, determine the second numerical range as a numerical range slightly higher or slightly lower than the normal indicator range.

[0067] It can be understood that if the test data recorded in a certain relevant medical record falls within the second numerical range, it can indicate that the patient has recovered or the degree of illness is relatively light. Therefore, this relevant medical record has little or low reference value. Thus, the relevant medical record can be removed from the medical record set.

[0068] According to the method of this embodiment, valid medical records can be screened out from the patient's medical record file, and then historical test data of the patient's physical indicators can be obtained from the valid medical records, and the correlation coefficient between the historical test data and the historical test time can be determined. That is to say, if a certain medical record is a valid medical record, the correlation coefficient between the historical test data recorded in the valid medical record and the historical test time can be determined, and the rationality of the treatment plan adopted by the patient can be analyzed based on the correlation coefficient; if a certain medical record does not belong to a valid medical record, or in other words, if a certain medical record is an invalid medical record, the calculation of the correlation coefficient and the judgment of the rationality of the treatment plan can be avoided. In this way, the number of medical records to be processed can be reduced, thereby improving work efficiency.

[0069] In some embodiments, the method may further include: sending each valid medical record to the medical staff terminal. By deleting some medical records with little or no reference value and retaining the valid medical records, and sending the retained valid medical records to the medical staff terminal, in this way, medical staff do not need to analyze and diagnose invalid medical records, thus reducing the time for medical staff to analyze and diagnose and improving the work efficiency of medical staff.

[0070] In some embodiments, the method may further include: inferring the type of disease for which the patient seeks medical treatment based on the patient's registration type and the patient's medical record file; determining a recommended department for the patient based on the disease type; and sending the recommended department to the patient terminal.

[0071] For example, assuming that the patient's registration type is cardiology and the patient's medical record file contains medical records related to arrhythmia and coronary heart disease, then it can be inferred that the diseases for which the patient seeks medical treatment may be arrhythmia or coronary heart disease, and the diseases for which medical treatment is sought belong to chronic diseases. Thus, the server can match the corresponding department based on this inference result and then recommend the matched department to the patient terminal for the patient's reference to avoid the patient wandering between different departments.

[0072] In some embodiments, the method may further include: obtaining the follow-up questionnaire uploaded by the medical staff terminal; sending the follow-up questionnaire to the patient terminal; obtaining the feedback on the follow-up questionnaire uploaded by the patient terminal; and sending the feedback to the medical staff terminal.

[0073] Exemplarily, medical staff can create a follow-up questionnaire for a patient based on the patient's medical visit information, and upload the created follow-up questionnaire to the server through the medical staff terminal. After the server obtains the follow-up questionnaire uploaded by the medical staff terminal, it can send the follow-up questionnaire to the patient terminal. The patient can provide feedback on the questions involved in the follow-up questionnaire on the patient terminal in combination with their own situation (such as medication situation, exercise situation, diet situation, and recovery situation, etc.). After the server obtains the feedback uploaded by the patient terminal, it can send the feedback to the medical staff terminal, so that medical staff can understand the patient's rehabilitation progress, and then adjust the subsequent follow-up plan (or follow-up schedule). This embodiment strengthens the connection and communication between medical staff and patients by establishing a follow-up mechanism, which is beneficial to the patient's post-diagnosis recovery, helps to establish a harmonious doctor-patient relationship, and enhances the hospital's brand image.

[0074] In some embodiments, when the patient's disease belongs to chronic disease / special disease, a follow-up plan for chronic disease / special disease can be formulated for the patient; when the patient's disease belongs to common disease, there is no need to formulate a follow-up plan.

[0075] The embodiment of the present application also provides a system for disease course management. Figure 2 It is a schematic diagram of a system 200 for disease course management provided by an embodiment of the present application. As Figure 2 shown, the system 200 includes: a server 201, a medical staff terminal 202, and a patient terminal 203. Among them, the medical staff terminal 202 and / or the patient terminal 203 can be used to input the information in the patient's medical record file; the server 201 can be used to: obtain the historical test data of the patient's physical indicators from the medical record file, as well as the corresponding historical test times; determine the correlation coefficient between the historical test data and the historical test times, and determine the rationality of the treatment plan adopted by the patient based on the correlation coefficient to obtain a rationality judgment result; the rationality judgment result is used for subsequent disease course management of the patient.

[0076] It should be understood that the server 201 can be used to implement the corresponding functions of the server in the above-mentioned disease course management method, and the patient terminal 203 and the medical staff terminal 202 can be used to implement the corresponding functions of the patient terminal and the medical staff terminal in the above-mentioned disease course management method respectively. For the sake of brevity, they will not be elaborated here.

[0077] To facilitate the understanding of the embodiments of the present application, a possible implementation process of the disease course management method provided by the embodiments of the present application is introduced below.

[0078] In this implementation process, the disease course management system includes a server, a patient terminal, and a medical staff terminal (or called a medical staff PC terminal). Among them, the patient terminal includes a patient file construction module, and the medical staff terminal includes a patient medical visit module, a patient follow-up plan construction module, and a patient recovery situation collection module.

[0079] The functions of each module will be introduced separately below.

[0080] Patient file construction module: used to construct a patient medical record file based on the patient's personal relevant information, previous medical reports and health data, update the constructed patient medical record file according to the current medical report and the patient's recovery situation, and transmit the updated patient medical record file to the patient's disease course database.

[0081] Patient visit module: used to transmit the patient medical record file and the patient's registration information (such as the type of registration) to the server, so that the server can select a matching disease course management function / service for the patient based on the patient medical record file and the patient's registration information. Further, the server can screen the patient's previous medical records to obtain valid medical records. By analyzing the test data recorded in the valid medical records, it can be known whether the treatment plan adopted by the patient is reasonable, so as to facilitate medical staff to formulate an appropriate treatment plan for the patient.

[0082] Exemplarily, after the server obtains the patient medical record file and the patient's registration type, it can screen the keywords or related words related to the registration type in the patient's personal medical record file according to the obtained registration type, and screen out the files recording the keywords or related words and put them into the corresponding medical record sets respectively. Then, the test data recorded in the patient medical records in the set can be compared with the second numerical range (such as the normal index range of the corresponding disease). Taking the normal index range of the corresponding disease as the second numerical range as an example, if the test data recorded in the patient medical record is within the normal index range of the corresponding disease, it means that the test data recorded in the patient medical record meets the standard. At this time, the medical record recording the qualified test data can be removed from the medical record set; if the test data recorded in the patient medical record is not within the normal index range of the corresponding disease, it means that the test data recorded in the patient medical record does not meet the standard. At this time, the medical record recording the unqualified test data can be determined as a valid medical record. Further, the server can send the determined valid medical records to the medical staff side. In this way, the medical staff can preliminarily understand the patient's condition based on the screened valid medical records, thereby reducing the number of patient examinations and further reducing the patient's treatment cost.

[0083] Patient follow-up plan construction module: used for medical staff to construct a follow-up plan suitable for the patient according to the patient's medical report.

[0084] Patient recovery situation collection module: used for medical staff to select whether to add temporary follow-up tasks according to the execution results of the patient follow-up plan and the patient's recovery situation, change the follow-up plan according to the newly added temporary follow-up tasks of the medical staff, and update the patient's disease course database according to the patient's recovery situation.

[0085] A possible implementation process of the disease course management method provided by the embodiments of the present application may include the following steps 1 to 4.

[0086] Step 1: Generate the patient's personal medical record file.

[0087] In this step, the patient can be guided to submit personal information (corresponding to the personal information in the foregoing embodiments), previous medical report information, and health monitoring data on the mobile terminal. The patient's personal medical record file can be generated based on the information submitted by the patient and the patient's medical history queried by the medical staff according to the patient's personal information on the medical management system platform.

[0088] Among them, the personal information can be submitted manually by the patient on the mobile terminal (patient side). The personal information submitted manually by the patient on the mobile terminal can be used as the basic information in the patient file. As an example, the basic information can include: patient contact information, height, weight, work situation, smoking and alcohol consumption situation, allergy history, past medical history, family medical history, and other information.

[0089] The previous medical report information can be uploaded to the mobile terminal in the form of pictures. The mobile terminal obtains the medical text in the uploaded previous medical report pictures and inputs the obtained medical text into the location of the past medical history in the personal medical record file. The previous medical report information submitted by the patient can be used as the past medical history in the patient file.

[0090] The health monitoring data can be, for example, the patient's vital sign information collected by wearable devices, or can also be obtained through the patient's historical medical records. The health monitoring data submitted by the patient can be used as the past disease recovery data in the patient file.

[0091] In some embodiments, the medical staff can query the patient's medical history on the medical management system platform according to the information submitted by the patient, and then can supplement the previous medical report information and health monitoring data manually input by the patient according to the queried patient's medical history. Among them, the medical management system platform can be, for example, systems such as HIS, EMR, and Internet hospitals.

[0092] Based on the personal information manually input by the patient, the supplemented previous medical report information and health monitoring data of the patient, the patient's personal medical record file can be generated.

[0093] Step 2: Classify the patient-related medical records based on the patient's registration type and screen out the valid medical records.

[0094] In this step, the server can screen the patient-related medical records based on the patient's registration type and send the screening result to the corresponding medical staff terminal. The step of screening the patient-related medical records can include the following steps 21) and 22):

[0095] 21) According to the type of patient registration, screen the keywords or related words related to the disease in the patient's personal medical record file, and screen out the medical records containing the keywords or related words and put them into sets X, Y, and Z respectively.

[0096] Exemplarily, X = {x 1 , x 2 , x 3 , …, x n}; Y = {y 1 , y 2 , y 3 , …, y m}; Z = {z 1 , z 2 , z 3 , …, z v}.

[0097] Among them, X represents the set of specialized disease medical records, n represents the total number of specialized disease medical records; Y represents the set of general disease medical records, m represents the total number of general disease medical records; Z represents the set of chronic disease medical records, and v represents the total number of chronic disease medical records.

[0098] For example, if the patient's registered department (type of registration) is the Department of Cardiology, since the Department of Cardiology includes arrhythmia, coronary heart disease, heart failure, and cardiomyopathy, the keywords (or related words) related to this type of registration are arrhythmia, coronary heart disease, heart failure, and cardiomyopathy. Furthermore, the medical records containing the above keywords can be screened out from the patient's personal medical record file. Since arrhythmia, coronary heart disease, heart failure, and cardiomyopathy are chronic diseases, the screened medical records should be put into set Z.

[0099] In some embodiments, the server can obtain the registration analysis result of the patient based on the above patient registration type and the patient's personal medical record file. For example, it is known that the patient's registration type is the Department of Cardiology, and the patient's medical record file contains medical records related to arrhythmia, coronary heart disease, heart failure, and cardiomyopathy. Then it can be inferred that the disease the patient is seeking treatment for may be one of arrhythmia, coronary heart disease, heart failure, and cardiomyopathy, and the disease being treated belongs to chronic diseases. That is, the registration analysis result is: the disease the patient is seeking treatment for is one of arrhythmia, coronary heart disease, heart failure, and cardiomyopathy, and the disease being treated belongs to chronic diseases. In some embodiments, the server can also determine the recommended department for the patient based on this registration analysis result and send the recommended department to the corresponding patient terminal of the patient to avoid the patient wandering between different departments.

[0100] 21) Compare the test data recorded in the medical records in the above medical record set with the second numerical range. Among them, the second numerical range can be determined according to the normal index range of the corresponding disease. For example, medical staff can use the normal index range of the corresponding disease as the second numerical range, or, according to personal experience, medical staff can use a numerical range slightly higher or slightly lower than the normal index range as the second numerical range. For ease of understanding, in the following text, an example is given where the second numerical range is the normal index range of the corresponding disease for illustrative purposes.

[0101] After comparison, if the test data recorded in the medical record is within the normal index range of the corresponding disease, it means that the test data recorded in the medical record meets the standard. At this time, the medical record recording the test data that meets the standard can be removed from the medical record set; if the test data recorded in the medical record is not within the normal index range of the corresponding disease, it means that the test data recorded in the medical record does not meet the standard. At this time, the medical record recording the test data that does not meet the standard can be determined as a valid medical record, and the visit time data and related test data (related indicators) of the valid medical record can be collected. Among them, a valid medical record can also be understood as a medical record in which the recorded data has reference value; an invalid medical record can also be understood as a medical record of a related disease that has been cured through treatment and does not relapse.

[0102] In some embodiments, after the server filters out the valid medical records, it can also send the filtered valid medical records to the medical staff terminal for medical staff to refer to. By deleting some invalid medical records and retaining the valid medical records, the time for medical staff to analyze and diagnose can be reduced, thereby improving the work efficiency of medical staff.

[0103] According to the technical solutions in Step 1 and Step 2 above, first, patients can be guided to submit personal relevant information and relevant medical history records on the mobile terminal before diagnosis to generate a patient personal medical record file; then, the server in the disease course management system can classify the relevant medical records of the patient based on the patient's registration type; further, the server can filter out the valid medical records from the medical record set and transmit the filtered valid medical records to the medical staff terminal, so that medical staff can preliminarily understand the patient's condition based on the filtered valid medical records, thereby reducing the number of patient examinations and further reducing the patient's treatment cost.

[0104] Step 3: Medical staff formulate a matching treatment plan for the patient based on the valid medical records filtered out in Step 2. The method for formulating a matching treatment plan is as follows:

[0105] Construct a reference value model for the treatment plan based on the previous visit time data (corresponding to the previous test data in the foregoing embodiments) and relevant indicators (corresponding to the previous test data in the foregoing embodiments) recorded in the valid medical records screened in step two. This reference value model for the treatment plan can be used to determine the rationality of the treatment plan adopted by the patient. Thus, a conclusion as to whether this treatment plan has reference value can be drawn based on whether the treatment plan adopted by the patient is reasonable.

[0106] Exemplarily, the reference value model for the treatment plan can be expressed as:

[0107]

[0108] Wherein, T represents the visit time recorded in the medical record (corresponding to the previous test time in the foregoing embodiments). When calculating using the visit time, the visit time T needs to be first converted into the corresponding discrete time value; G represents the relevant indicator value detected at the corresponding visit time recorded in the medical record (corresponding to the previous test data in the foregoing embodiments); P is the correlation coefficient between the visit time T and the relevant indicator G; Cov(T, G) represents the covariance between the visit time T and the relevant indicator G, D(T) represents the variance of the patient's visit time T, and D(G) represents the variance of the patient's relevant indicator G.

[0109] By calculating the correlation coefficient between the visit time T and the relevant indicator G, the reference value of the treatment plan adopted by the patient during this period can be judged.

[0110] In one example, when P = 0, it indicates that the visit time T and the relevant indicator G in the valid case are not correlated, indicating that the patient has not recovered according to the expected recovery process. That is to say, there is a problem with the treatment plan used in the patient's medical record, or in other words, the treatment plan adopted by the patient is unreasonable. In this case, if the medical staff use this treatment plan to treat the patient again later, it may lead to ineffective treatment or missed the best treatment time for the patient. Therefore, this treatment plan has reference value.

[0111] In another example, when P ≠ 0, it indicates that the visit time T and the relevant indicator G in the valid medical record are negatively or positively correlated. At this time, if the relevant indicators in the later stage of the patient's visit are repeatedly within the predefined standard range (corresponding to the first numerical range in the foregoing embodiments), it indicates that the patient has recovered according to the expected recovery process. That is to say, there are no abnormal features in the patient under this treatment plan, the patient is suitable for this treatment plan, or in other words, the treatment plan adopted by the patient is reasonable. In this case, when the medical staff make a visit later, there is no need to consider the situation that this treatment plan causes abnormal features in the patient. Therefore, this treatment plan has no reference value.

[0112] If P≠0, and the relevant indicators in the later stage of the patient's visit are within the standard range multiple times, it indicates that the treatment plan matching the patient is the treatment plan for the patient within the visit time T. Then, medical staff do not need to modify this treatment plan. If P = 0, or if P≠0 and the relevant indicators in the later stage of the patient's visit are not within the standard range, then medical staff can determine the root cause of the change in the relevant indicators during the visit time according to the change of the relevant indicators during the visit time, and then modify the treatment plan during the visit time according to the determination result. The modified treatment plan is the treatment plan matching the patient.

[0113] It should be noted that in some scenarios, the situation of P≈0 can be regarded as the situation of P = 0. Among them, P≈0 can also be understood as that the absolute value of P is less than a first threshold close to 0 (such as 0.1).

[0114] For ease of understanding, the solution of step three will be exemplarily described below with examples.

[0115] Suppose a patient has hypertension, and the records of previous medical reports in the patient's valid medical records are as follows: on March 1, the patient's blood pressure was 160 / 100 mmHg; on March 8, the patient's blood pressure was 120 / 80 mmHg; on March 15, the patient's blood pressure was 150 / 95 mmHg; on April 1, the patient's blood pressure was 110 / 85 mmHg. Analyze the patient's condition trend based on the treatment plan reference value model:

[0116] First, convert the visit time to discrete time points: March 1 is recorded as the 1st day, March 8 is recorded as the 8th day, March 15 is recorded as the 15th day, and April 1 is recorded as the 32nd day. Then:

[0117] When the relevant indicator G represents the patient's high blood pressure:

[0118]

[0119] Among them, 14 is the average value of the discrete time points 1, 8, 15, and 32, and 135 is the average value of the high blood pressure detection data corresponding to each discrete time point. According to the above calculation results, P = 0.042≈0, indicating that the patient's high blood pressure is not related to the visit time. That is to say, the treatment plan adopted by the patient is unreasonable, and this treatment plan has reference value.

[0120] When the relevant indicator G represents the patient's low blood pressure:

[0121]

[0122] Among them, 14 is the average value of discrete time points 1, 8, 15, and 32, and 90 is the average value of the low-pressure detection data corresponding to each discrete time point. According to the above calculation results, P = -0.43 < 0, indicating that there is a negative correlation between the patient's low blood pressure and the visit time and the correlation is moderate, and there are indicators among the patient's subsequent relevant index values that do not fall within the standard range (the normal range of low blood pressure is 60 - 85 mmHg). Based on the analysis results, it can be known that the patient's condition has not recovered according to the expected recovery process, and it can be judged that there is a problem with the patient's visit plan this time. Or rather, the visit plan adopted by the patient is unreasonable. If the medical staff uses this plan to treat the patient again in the later stage, it will lead to ineffective treatment or miss the best treatment time for the patient. Therefore, this visit plan has reference value.

[0123] According to the method of this embodiment, the output result of the visit plan reference value model can be used to judge whether the visit plan adopted by the patient is reasonable, which is beneficial for medical staff to formulate a suitable visit plan based on the patient's visit record and avoid formulating a plan that is not applicable to the patient himself.

[0124] Step Four: Formulate a corresponding follow-up plan for the patient according to the patient's visit information to ensure an effective connection between medical staff and the patient, avoid the impact of ineffective implementation of medical advice on the treatment effect, and is beneficial to establishing a harmonious doctor-patient relationship.

[0125] Exemplarily, when the patient's disease type belongs to a specific disease, the follow-up plan includes:

[0126] 1) Medical staff construct a patient-specific disease follow-up plan according to the patient's specific disease visit report information;

[0127] 2) Transmit the specific disease follow-up plan to the patient's client through the network;

[0128] 3) The patient receives and executes the specific disease follow-up plan, and transmits his own execution situation and the recovery situation feedback after the patient's execution to the medical staff side.

[0129] For example, the patient can give feedback on his own medication situation, exercise situation, diet situation, and recovery situation regarding the specific disease follow-up plan formulated by the medical staff. The medical staff can adjust the subsequent specific disease follow-up plan according to the patient's feedback content. In this way, it is beneficial to reduce the patient's recovery time.

[0130] When the patient belongs to a chronic disease, the follow-up plan includes:

[0131] 1) Construct a patient chronic disease follow-up plan according to the patient's chronic disease visit report information;

[0132] 2) Transmit the chronic disease follow-up plan to the patient's client through the network;

[0133] 3) The patient receives and executes the chronic disease follow-up plan, and transmits their own execution situation and the recovery situation feedback after the patient's execution to the medical staff side.

[0134] For example, the patient can give feedback on their medication situation, exercise situation, diet situation, and recovery situation according to the chronic disease follow-up plan formulated by the medical staff. The medical staff can adjust the subsequent chronic disease follow-up plan based on the patient's feedback. In this way, it is beneficial to reduce the patient's recovery time.

[0135] When the patient has a common disease, there is no need to construct a follow-up plan.

[0136] In some embodiments, the disease course management system can automatically obtain patient information to generate follow-up objects through docking interfaces with systems such as HIS, EMR, and Internet hospitals. As an example, during the follow-up process, medical staff can use multi-path follow-up, such as phone calls, text messages, WeChat, etc. The patient can follow the hospital's WeChat official account on the patient side to receive whole-course health management information.

[0137] In some embodiments, medical staff can understand the patient's medical treatment situation and follow-up situation in real time through the medical staff side, such as: the time of each admission and discharge, discharge summary, previous follow-up records, etc. During the follow-up process, medical staff can also view the patient's relevant hospitalization information (such as patient basic information, discharge summary, medical record information, test reports, etc.) through the medical staff side to improve the quality of follow-up. The disease course management system also supports providing personalized health management tools, supporting the recording and automatic evaluation of health monitoring indicators, and the data is structured and available.

[0138] According to the above implementation process, the solution of the embodiment of the present application can solve the following problems in the prior art:

[0139] 1) The existing disease course management system lacks an understanding of the patient's health status before the patient is admitted to the hospital for diagnosis. Doctors need the patient's cooperation to perform relevant examinations before diagnosis to further understand the patient's condition.

[0140] In view of the disadvantages of this technology, the embodiments of this application propose a solution for constructing a patient medical record file before the patient sees a doctor. Among them, the method for constructing a patient medical record file includes: guiding the patient to submit personal relevant information, previous medical report information, and health monitoring data on the mobile terminal, and generating a personal medical record file based on the information submitted by the patient and the patient's medical history queried by medical staff in the medical management system platform according to the patient's personal information; classifying the patient's relevant medical records based on the patient's registration type, and screening out valid medical records from them; medical staff formulating a matching treatment plan for the patient according to the screened valid medical records; formulating a corresponding follow-up plan for the patient according to the patient's medical treatment information; the patient feeding back on their medication situation, exercise situation, diet situation, and recovery situation based on the follow-up plan formulated in step 4, and the medical staff changing the follow-up plan according to the patient's feedback content. As an implementation method, the content fed back by the patient can also be stored in the patient's medical record file.

[0141] 2) The existing disease course management system cannot achieve specialized treatment for specific diseases when guiding patients to see a doctor, resulting in patients wandering between different departments and reducing the patient experience.

[0142] In view of the disadvantages of this technology, the embodiments of this application propose a solution for achieving specialized treatment for specific diseases for patients. The method for a patient to achieve specialized treatment for specific diseases includes: analyzing the patient's registration type, and selecting a matching disease course management function / service for the patient based on the registration type; in the case where the patient has a specific disease, screening the patient's medical records for the specific disease, and formulating a suitable treatment plan for the patient according to the screened valid medical records (valid historical medical treatment information for the specific disease); in the case where the patient has a common disease, screening the patient's medical records for the common disease, and formulating a suitable treatment plan for the patient according to the screened valid medical records (valid historical medical treatment information for the common disease); in the case where the patient has a chronic disease, screening the patient's medical records for the chronic disease, and formulating a suitable treatment plan for the patient according to the screened valid medical records (valid historical medical treatment information for the chronic disease).

[0143] 3) The existing disease course management system cannot achieve follow-up, resulting in the weakening of the connection between patients and medical staff after seeing a doctor, and unable to ensure that patients follow medical advice after diagnosis, which is not conducive to the post-diagnosis recovery of patients.

[0144] In view of the disadvantages of this technology, the embodiments of this application propose a solution for constructing a perfect follow-up plan. The method for constructing a follow-up plan includes:

[0145] When the patient's disease type belongs to a specific disease: constructing a patient's follow-up plan for the specific disease according to the patient's medical treatment report information for the specific disease; transmitting the follow-up plan for the specific disease to the patient's client through the network; the patient receiving and executing the follow-up plan for the specific disease, and transmitting their execution situation and the recovery situation feedback by the patient after execution to the medical staff side.

[0146] When the patient has a chronic disease: construct a chronic disease follow-up plan for the patient based on the information in the patient's chronic disease medical report; transmit the chronic disease follow-up plan to the patient's client through the network; the patient receives and executes the chronic disease follow-up plan, and transmits his own execution situation and the recovery situation feedback after the patient's execution to the medical staff side.

[0147] When the patient has an ordinary disease, there is no need to construct a follow-up plan.

[0148] The technical solution of the embodiment of the present application can produce the following beneficial effects:

[0149] 1) Construct a patient medical record file before the patient sees a doctor; construct a reference value model for the treatment plan based on the medical treatment time data and related indicators of the valid medical record; formulate an effective treatment plan for the patient based on the treatment plan reference model. In this way, it can be avoided that the medical staff worsen the patient's condition due to improper medical treatment.

[0150] 2) It can achieve specialized treatment for the patient. By analyzing the types of registration of the patient, select a matching course management function / service for the patient, avoid the patient wandering between departments, further shorten the patient's medical treatment time, and improve the success rate of the patient's medical treatment.

[0151] 3) A perfect follow-up plan is constructed. Medical staff can formulate a perfect follow-up plan for the patient according to the medical report information of the patient, and update the follow-up plan at any time according to the patient's compliance with medical advice and recovery situation, strengthening the connection and communication between medical staff and patients, being beneficial to the patient's post-treatment recovery, helping to establish a harmonious doctor-patient relationship, enhancing the brand image of the hospital, and reflecting the public welfare nature of the hospital.

[0152] The preferred embodiments of the present application have been described in detail above in conjunction with the accompanying drawings. However, the present application is not limited to the specific details in the above embodiments. Within the scope of the technical concept of the present application, various simple modifications can be made to the technical solution of the present application, and these simple modifications all belong to the protection scope of the present application. For example, in the various specific technical features described in the above specific embodiments, they can be combined in any suitable way without contradiction. To avoid unnecessary repetition, the present application will not separately describe various possible combination methods. Again, for example, any combination can be made between various different embodiments of the present application, as long as it does not violate the idea of the present application, it should also be regarded as the content disclosed by the present application. Again, for example, on the premise of no conflict, the various embodiments described in the present application and / or the technical features in each embodiment can be combined arbitrarily with the prior art, and the technical solutions obtained after the combination should also fall within the protection scope of the present application.

[0153] Based on the foregoing embodiments, the embodiments of the present application provide corresponding devices for disease course management. The device includes each module included and each sub-module included in each module, and can be implemented by a processor in a computer device with information processing capabilities; of course, it can also be implemented by specific logic circuits; in the process of implementation, the processor can be a central processing unit (CPU), a microprocessor unit (MPU), a digital signal processor (DSP), or a field programmable gate array (FPGA), etc.

[0154] Figure 3 FIG. 4 shows the composition structure of a device 300 in a disease course management system provided by an embodiment of the present application. The disease course management system further includes a medical staff terminal and a patient terminal. As Figure 3 shown, the device 300 may include:

[0155] A first acquisition unit 301, configured to acquire the previous detection data of the patient's physical indicators and the corresponding previous detection times from the patient's medical record file; wherein, the information in the medical record file is input by the medical staff terminal and / or the patient terminal; a first determination unit 302, configured to determine the correlation coefficient between the previous detection data and the previous detection times; a second determination unit 303, configured to determine the rationality of the treatment plan adopted by the patient based on the correlation coefficient, and obtain a rationality judgment result; the rationality judgment result is used for subsequent disease course management of the patient.

[0156] In some embodiments, the second determination unit 303 is specifically configured to: determine that the treatment plan adopted by the patient is unreasonable when the absolute value of the correlation coefficient is less than a first threshold; determine that the treatment plan adopted by the patient is unreasonable when the absolute value of the correlation coefficient is greater than or equal to the first threshold and at least N detection data in the previous detection data do not fall within a first numerical range; wherein, N is a predefined positive integer; the first numerical range is determined according to the normal index range of the physical indicator.

[0157] In some embodiments, the device 300 further includes: a second acquisition unit, configured to acquire the registration type of the patient; a query unit, configured to query the medical records related to the registration type in the patient's medical record file to obtain at least one related medical record; a classification unit, configured to divide at least one related medical record into corresponding medical record sets based on the types of at least one related medical record; wherein, the medical record sets include: a special disease medical record set, a chronic disease medical record set, and a general disease medical record set.

[0158] In some embodiments, the first acquisition unit 301 is specifically configured to: for each relevant medical record, if the detection data recorded in the relevant medical record falls within a second numerical range, remove the relevant medical record from the corresponding medical record set; wherein, the second numerical range is determined according to the normal index range of the disease corresponding to the relevant medical record; determine the remaining medical records in each medical record set as valid medical records; and obtain the patient's previous detection data of physical indicators from the valid medical records.

[0159] In some embodiments, the device 300 further includes: an inference unit, configured to infer the disease type of the patient's visit based on the patient's registration type and the patient's medical record file; a third determination unit, configured to determine a recommended department for the patient to visit based on the disease type; and a second sending unit, configured to send the recommended department for the patient to visit to the patient terminal.

[0160] In some embodiments, the device 300 further includes: a third acquisition unit, configured to acquire the follow-up questionnaire uploaded by the medical staff terminal; a third sending unit, configured to send the follow-up questionnaire to the patient terminal; a fourth acquisition unit, configured to acquire the feedback on the follow-up questionnaire uploaded by the patient terminal; and a fourth sending unit, configured to send the feedback to the medical staff terminal.

[0161] In some embodiments, the patient's medical record file includes: the patient's personal information entered by the patient terminal, the patient's previous medical reports, and the patient's vital sign information collected by the wearable device; and / or, the patient's medical reports entered by the medical staff terminal.

[0162] The description of the above device embodiments is similar to the description of the above method embodiments, and has similar beneficial effects to the method embodiments. In some embodiments, the functions or modules included in the device provided by the embodiments of the present application can be used to execute the methods described in the above method embodiments. For the technical details not disclosed in the device embodiments of the present application, please refer to the description of the method embodiments of the present application for understanding.

[0163] It should be noted that in the embodiments of the present application, if the above method is implemented in the form of software functional modules and sold or used as an independent product, it can also be stored in a computer-readable storage medium. Based on such an understanding, the technical solution of the embodiments of the present application, in essence or the part that contributes to the related technology, can be embodied in the form of a software product. The software product is stored in a storage medium and includes several instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the methods described in the various embodiments of the present application. The aforementioned storage medium includes: various media such as USB flash drives, mobile hard disks, read-only memories (ROM), magnetic disks, or optical discs that can store program codes. In this way, the embodiments of the present application are not limited to any specific hardware, software, or firmware, or any combination among hardware, software, and firmware.

[0164] The embodiments of the present application further provide a device for disease course management, including a memory and a processor. The memory stores a computer program that can run on the processor, and when the processor executes the program, it implements some or all of the steps in the above method.

[0165] The embodiments of the present application further provide a chip. The chip includes: a processor for calling and running a computer program from a memory, so that a device installed with the chip executes some or all of the steps in the above method.

[0166] The embodiments of the present application further provide a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, it implements some or all of the steps in the above method. The computer-readable storage medium can be transient or non-transient.

[0167] The embodiments of the present application further provide a computer program, including computer-readable code. When the computer-readable code runs in a device (such as a client; or a cryptographic machine), the processor in the device executes some or all of the steps in the above method.

[0168] The embodiments of the present application further provide a computer program product. The computer program product includes a non-transient computer-readable storage medium storing a computer program. When the computer program is read and executed by a computer, it implements some or all of the steps in the above method. The computer program product can be specifically implemented by means of hardware, software, or a combination thereof. In some embodiments, the computer program product is specifically embodied as a computer storage medium, and in other embodiments, the computer program product is specifically embodied as a software product, such as a software development kit (SDK), etc.

[0169] It should be noted here that the descriptions of the above embodiments tend to emphasize the differences between the embodiments, and the similarities or similarities can be referred to each other. The descriptions of the above embodiments of the device, chip, storage medium, computer program, and computer program product are similar to the descriptions of the above method embodiments and have beneficial effects similar to those of the method embodiments. For the technical details not disclosed in the embodiments of the device, chip, storage medium, computer program, and computer program product of the present application, please refer to the descriptions of the method embodiments of the present application for understanding.

[0170] Figure 4 FIG. is a schematic diagram of a hardware entity of a device for disease course management in an embodiment of the present application. The device may be a server in a disease course management system. Figure 4 The illustrated disease course management device 400 includes a processor 410. The processor 410 can call and run a computer program from a memory to implement the method in the embodiments of the present application.

[0171] In some embodiments, as Figure 4 shown, the device 400 may further include a memory 420. Among them, the processor 410 can call and run a computer program from the memory 420 to implement the method in the embodiments of the present application. Among them, the memory 420 may be a separate device independent of the processor 410 or integrated in the processor 410.

[0172] In some embodiments, as Figure 4 shown, the device 400 may further include a transceiver 430. The processor 410 can control the transceiver 430 to communicate with other devices. Specifically, it can send information or data to other devices or receive information or data sent by other devices. Among them, the transceiver 430 may include a transmitter and a receiver. The transceiver 430 may further include an antenna, and the number of antennas may be one or more.

[0173] In some embodiments, the device 400 may specifically be a server in the disease course management system of the embodiments of the present application, and the device 400 can implement the corresponding processes implemented by the server in the disease course management system in the various methods of the embodiments of the present application. For the sake of brevity, it will not be described in detail here.

[0174] It should be understood that the "one embodiment", "an embodiment" or "some embodiments" mentioned throughout the specification mean that the specific features, structures or characteristics related to the embodiment are included in at least one embodiment of the present application. Therefore, the appearances of "in one embodiment", "in an embodiment" or "in some embodiments" throughout the specification do not necessarily refer to the same embodiment. In addition, these specific features, structures or characteristics can be combined in one or more embodiments in any suitable manner. It should be understood that in various embodiments of the present application, the magnitudes of the serial numbers of the above steps / processes do not mean the order of execution. The order of execution of each step / process should be determined by its function and internal logic, and should not constitute any limitation to the implementation process of the embodiments of the present application. The serial numbers of the embodiments of the present application above are only for description and do not represent the advantages or disadvantages of the embodiments.

[0175] It should be noted that in this article, the term "comprising", "including" or any other variant thereof is intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements not only includes those elements but also includes other elements not expressly listed, or further includes elements inherent to such process, method, article or device. Without further limitation, an element defined by the phrase "including a..." does not exclude the existence of additional identical elements in the process, method, article or device including such element.

[0176] In several embodiments provided in the present application, it should be understood that the disclosed devices and methods can be implemented in other ways. The device embodiments described above are merely illustrative. For example, the division of the units or modules is only a logical function division. In actual implementation, there may be other division methods. For example, multiple units or components can be combined, or can be integrated into another system, or some features can be ignored, or not executed. In addition, the couplings, direct couplings or communication connections between the components shown or discussed with each other can be through some interfaces. The indirect couplings or communication connections of the devices or units can be electrical, mechanical or other forms.

[0177] The units described above as separate components may or may not be physically separated, and the components shown as units may or may not be physical units; they can be located in one place or distributed to multiple network units; some or all of the units can be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0178] In addition, in each embodiment of the present application, each functional unit can be entirely integrated into one processing unit, or each unit can be separately regarded as one unit, or two or more units can be integrated into one unit; the above integrated unit can be implemented in the form of hardware, or in the form of a combination of hardware and software functional units.

[0179] Those of ordinary skill in the art can understand that all or part of the steps for implementing the above method embodiments can be completed by hardware related to program instructions. The foregoing program can be stored in a computer-readable storage medium. When the program is executed, it performs the steps including the above method embodiments; and the foregoing storage medium includes: removable storage devices, read-only memory (ROM), magnetic disks, or optical discs and other various media that can store program codes.

[0180] Alternatively, if the above integrated unit of the present application is implemented in the form of a software functional module and sold or used as an independent product, it can also be stored in a computer-readable storage medium. Based on such an understanding, the technical solution of the present application, in essence, or the part that contributes to the related technology, can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes several instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the methods described in the various embodiments of the present application. And the foregoing storage medium includes: removable storage devices, ROM, magnetic disks, or optical discs and other various media that can store program codes.

[0181] The above is only the implementation mode of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art within the technical scope disclosed by the present application can easily think of changes or substitutions, which should all be covered by the protection scope of the present application.

Claims

1. A method for disease course management, characterized in that, it is applied to the server in a disease course management system, and the disease course management system further includes a medical staff terminal and a patient terminal. The method includes: Obtaining the historical test data of the patient's physical indicators and the corresponding historical test times from the patient's medical record file; wherein, the information in the medical record file is input by the medical staff terminal and / or the patient terminal; Determining the correlation coefficient between the historical test data and the historical test times; Based on the correlation coefficient, determining the rationality of the treatment plan adopted by the patient to obtain a rationality judgment result; the rationality judgment result is used for subsequent disease course management of the patient.

2. The method according to claim 1, characterized in that, the determining the rationality of the treatment plan adopted by the patient based on the correlation coefficient includes: When the absolute value of the correlation coefficient is less than a first threshold, determining that the treatment plan adopted by the patient is unreasonable; When the absolute value of the correlation coefficient is greater than or equal to the first threshold and at least N test data in the historical test data do not fall within a first numerical range, determining that the treatment plan adopted by the patient is unreasonable; wherein, N is a predefined positive integer; the first numerical range is determined according to the normal index range of the physical indicator.

3. The method according to claim 1 or 2, characterized in that, the method further includes: Obtaining the registration type of the patient; Querying the medical records related to the registration type in the patient's medical record file to obtain at least one related medical record; Based on the types of the at least one related medical record, classifying the at least one related medical record into corresponding medical record sets; wherein, the medical record sets include: a special disease medical record set, a chronic disease medical record set, and a general disease medical record set.

4. The method according to claim 3, characterized in that, the obtaining the historical test data of the patient's physical indicators from the patient's medical record file includes: For each of the related medical records, if the test data recorded in the related medical record falls within a second numerical range, removing the related medical record from the corresponding medical record set; wherein, the second numerical range is determined according to the normal index range of the disease corresponding to the related medical record; Determining the remaining medical records in each medical record set as valid medical records; Obtaining the historical test data of the patient's physical indicators from the valid medical records.

5. The method according to claim 3, characterized in that, the method further includes: Inferring the disease type of the patient's visit based on the patient's registration type and the patient's medical record file; Based on the disease type, determining a recommended department for the patient to visit; Sending the recommended department for the patient to visit to the patient terminal.

6. The method according to claim 1 or 2, characterized in that, the method further includes: Obtaining the follow-up questionnaire uploaded by the medical staff terminal; Sending the follow-up questionnaire to the patient terminal; Obtaining the feedback on the follow-up questionnaire uploaded by the patient terminal; Sending the feedback to the medical staff terminal.

7. The method according to claim 1 or 2, characterized in that, The medical record file of the patient includes: Personal information of the patient entered by the patient side, previous medical reports of the patient, and vital sign information of the patient collected by a wearable device; and / or, Medical reports of the patient entered by the medical staff side.

8. A device in a disease course management system, Characterized in that, The disease course management system further includes a medical staff side and a patient side, and the device includes: A first acquisition unit, configured to acquire previous detection data of the patient's physical indicators and corresponding previous detection times from the patient's medical record file; wherein, the information in the medical record file is entered by the medical staff side and / or the patient side; A first determination unit, configured to determine the correlation coefficient between the previous detection data and the previous detection times; A second determination unit, configured to determine the rationality of the treatment plan adopted by the patient based on the correlation coefficient, and obtain a rationality judgment result; the rationality judgment result is used for subsequent disease course management of the patient.

9. A disease course management system, Characterized in that, The system includes: a server, a medical staff side and a patient side; The medical staff side and / or the patient side is used to enter information in the patient's medical record file; The server is configured to: acquire previous detection data of the patient's physical indicators and corresponding previous detection times from the medical record file; Determine the correlation coefficient between the previous detection data and the previous detection times, Determine the rationality of the treatment plan adopted by the patient based on the correlation coefficient, and obtain a rationality judgment result; the rationality judgment result is used for subsequent disease course management of the patient.

10. A disease course management device, Characterized in that, The device includes: A memory, configured to store computer-executable instructions; A processor, connected to the memory, and configured to implement the method according to any one of claims 1 to 7 by executing the computer-executable instructions.

11. A computer-readable storage medium, Characterized in that, The computer-readable storage medium stores a computer program, and when the computer program is executed by at least one processor, the method according to any one of claims 1 to 7 is implemented.

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