CN117409913A - Medical service method and platform based on cloud technology - Google Patents
Medical service method and platform based on cloud technology Download PDFInfo
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Abstract
The invention provides a medical service method and a platform based on cloud technology, wherein the method comprises the steps of acquiring registration and login information of a user through a registration and login port; acquiring diagnosis and treatment requirements and basic disease information of a patient through a diagnosis and treatment requirement window, recommending a department to visit according to the basic disease information, generating a diagnosis and treatment record and storing in real time; unified management is carried out on diagnosis and treatment records of patients; classifying and summarizing the diagnosis and treatment records; providing personalized medical advice according to the analysis result; setting different viewing rights for the diagnosis and treatment record; generating a checking process record file, setting checking time length for the diagnosis and treatment record, wherein the platform comprises a registration and login module, a diagnosis and treatment module, a record management module and a checking module, and realizing medical resource sharing by the method and the platform, thereby improving diagnosis and treatment efficiency and reducing risks of data leakage and abuse; enhancing the quality and effectiveness of medical services.
Description
Technical Field
The invention relates to the technical field of medical services, in particular to a medical service method and platform based on a cloud technology.
Background
The medical field is increasingly demanding for the storage, processing and sharing of data. Medical data includes medical records of patients, test results, image data and the like, and has the characteristics of huge and complex. The traditional local storage mode is difficult to meet the requirements of data management and security, and secondly, the popularization of the mobile internet and the common use of intelligent equipment also promote the development of a medical service platform. Patients and doctors are not limited to the traditional face-to-face diagnosis and treatment mode, but can realize various service forms such as online reservation, online consultation, remote monitoring and the like through the mobile equipment.
Disclosure of Invention
The invention provides a medical service method and a platform based on a cloud technology, which are used for realizing medical data sharing and reducing the risk of information leakage.
The invention provides a medical service method based on cloud technology, which comprises the following steps:
s1, acquiring registration and login information of a user through a registration and login port;
s2, acquiring diagnosis and treatment requirements and basic disease information of a patient through a diagnosis and treatment requirement window, recommending a department to visit according to the basic disease information, generating a diagnosis and treatment record, and storing the diagnosis and treatment record to a cloud end in real time;
S3, unified management is carried out on diagnosis and treatment records of patients; classifying and summarizing the diagnosis and treatment records; analyzing the diagnosis and treatment record of the patient to obtain an analysis result, and providing personalized medical advice according to the analysis result;
s4, setting different viewing authorities for the diagnosis and treatment record; and acquiring the check records aiming at the same diagnosis and treatment record in real time, generating a check process record file, and setting check time length aiming at the diagnosis and treatment record.
Further, a medical service method based on cloud technology, the S1 includes:
the patient registers through the patient port, wherein the registration comprises the steps of filling in the name, the identification card number, the contact mode, the medical insurance information, the login mode and the password of the patient; the platform authenticates and audits the authentication information, and personal account information is generated after the audit is passed;
a doctor registers through a doctor port, wherein the doctor registration comprises doctor name, qualification and practice information; and accessing a medical institution official network through an API interface, acquiring medical institution information and doctor information, and associating and corresponding the information registered through the doctor port with the information in the medical institution.
Further, a medical service method based on cloud technology, the S2 includes:
Acquiring diagnosis and treatment requirements and basic disease information of a patient through a diagnosis and treatment requirement window; the diagnosis and treatment requirements comprise on-line diagnosis and treatment and off-line diagnosis and treatment; if the patient selects on-line diagnosis and treatment, recommending according to the on-line doctor scheduling of the corresponding department; if the user selects offline diagnosis and treatment, the user performs reservation recommendation according to offline doctor scheduling of the corresponding department;
extracting characteristics of patient illness description through basic patient illness state information, matching with class characteristics of departments, and recommending to visit departments and doctors according to matching results;
predicting the specific treatment time of the patient according to the doctor scheduling selected by the patient;
generating diagnosis and treatment records in real time and uploading the diagnosis and treatment records to a cloud end;
and setting an evaluation and feedback window to evaluate and feed back the doctor, the system and the treatment effect.
Further, a medical service method based on cloud technology, the S3 includes:
classifying and grading the cases according to the disease types; extracting disease characteristics, generating a disease characteristic library, hiding personal information of patients, performing statistical analysis, and displaying analysis results; providing a plurality of classification modes and carrying out statistical display;
summarizing the diagnosis and treatment cases of the same doctor to obtain doctor diagnosis and treatment records; the diagnosis and treatment records of doctors are arranged according to the diagnosis and treatment time, and the diagnosis results are summarized; evaluating the doctor's treatment experience based on the summary results;
Summarizing the treatment records of the same patient to obtain case summarizing information of the patient; the summarized information comprises index information and specific information; the specific information comprises specific diagnosis information, examination information and medication records;
establishing index information for the visit record of the same patient, wherein the index information comprises a first index, a second index and a third index;
the first index is the name, sex, date of birth, and contact information of the patient; the second index is on-line diagnosis and treatment and off-line diagnosis and treatment; the third index is identity information, diagnosis and treatment departments and diagnosis and treatment time; the identity information comprises identity card or medical insurance card information; the patient can check the own visit record according to the index;
analyzing the diagnosis and treatment record of the patient to obtain an analysis result, and providing personalized medical advice according to the analysis result.
Further, a medical service method based on cloud technology, the S4 includes:
setting an encryption type storage scheme for patient information; encrypting basic information of a patient and encrypting diagnosis and treatment records;
classifying diagnosis and treatment records of patients according to disease diagnosis results; different inquiry authorities are set according to the classification result;
The classification includes non-sensitive information diseases and diseases including privacy;
for diagnosis and treatment records without sensitive information diseases, a patient directly checks own records through login information; the doctor directly checks the acquisition permission of the platform by sending an application to the platform in the period of patient treatment;
a diagnosis and treatment record for diseases including privacy classes; the patient logs in through the login information and checks the diagnosis and treatment record of the patient through the dynamic key or face recognition;
for common diseases comprising diagnosis and treatment records of privacy diseases, a doctor sends an application to a platform through a patient treatment number in a patient treatment period to acquire treatment record permission for checking the patient treatment in a home; in the period of patient treatment, a doctor checks the treatment record of non-home treatment of a patient by sending an application to a platform, and the platform sends the application to a patient or guardian for treatment and obtains the permission of the patient to open the corresponding treatment record after agreeing to the doctor;
for emergency, a special access window is set, diagnosis and treatment records of patients are called through platform authorization, and the records are carried out; the emergency situation includes a critical patient;
setting a checking period and a checking record time window, and obtaining recommended effective duration through machine learning; the recommended effective duration comprises a first effective duration and a second effective duration, wherein the first effective duration is the duration of a query window of a registered user of a patient port; the second effective duration is the effective duration of the doctor port query; wherein the doctor viewing period is a patient visit and/or treatment period;
Periodically checking and accessing the setting of the recommended effective duration, and comparing with the actual demand; updating the preset effective duration; the actual requirements comprise the time length requirements fed back by the patient port and the doctor port;
a log recording system is established to record all access operations to the data, including inquirer, inquiry time length and inquiry times; an alarm is given for the abnormal operation.
The invention provides a medical service platform based on a cloud technology, which comprises:
registration and login module: acquiring registration and login information of a user through a registration and login port;
diagnosis and treatment module: acquiring diagnosis and treatment requirements and basic disease information of a patient through a diagnosis and treatment requirement window, recommending a department to visit according to the basic disease information, generating a diagnosis and treatment record and storing the diagnosis and treatment record to a cloud in real time;
and a record management module: unified management is carried out on diagnosis and treatment records of patients; classifying and summarizing the diagnosis and treatment records; analyzing the diagnosis and treatment record of the patient, and providing personalized medical advice according to the analysis result;
and a viewing module: setting different viewing rights for the diagnosis and treatment record; acquiring a check record aiming at the same diagnosis and treatment record in real time, and generating a check process record file; and setting the checking time length for the diagnosis and treatment record.
Further, a medical service platform based on cloud technology, the registration and login module includes:
patient port: the patient registers through the patient port, wherein the registration comprises the steps of filling in the name, the identification card number, the contact mode, the medical insurance information, the login mode and the password of the patient; the platform authenticates and audits the authentication information, and personal account information is generated after the audit is passed;
doctor port: a doctor registers through a doctor port, wherein the doctor registration comprises doctor name, qualification and practice information; and accessing a medical institution official network through an API interface, acquiring medical institution information and doctor information, and associating and corresponding the information registered through the doctor port with the information in the medical institution.
Further, a medical service platform based on cloud technology, the diagnosis and treatment module includes:
diagnosis and treatment demand module: acquiring diagnosis and treatment requirements and basic disease information of a patient through a diagnosis and treatment requirement window; the diagnosis and treatment requirements comprise on-line diagnosis and treatment and off-line diagnosis and treatment; if the patient selects on-line diagnosis and treatment, recommending according to the on-line doctor scheduling of the corresponding department; if the user selects offline diagnosis and treatment, the user performs reservation recommendation according to offline doctor scheduling of the corresponding department;
And a recommendation module: extracting characteristics of patient illness description through basic patient illness state information, matching with class characteristics of departments, and recommending to visit departments and doctors according to matching results;
and a prediction module: predicting the specific treatment time of the patient according to the schedule of the doctor selected by the patient;
diagnosis and treatment record generation module: generating diagnosis and treatment records in real time and uploading the diagnosis and treatment records to a cloud end;
and an evaluation feedback module: and setting an evaluation and feedback window to evaluate and feed back the doctor, the system and the treatment effect.
Further, a medical service platform based on cloud technology, the record management module includes:
a first summarizing module: classifying and grading the cases according to the disease types; extracting disease characteristics, generating a disease characteristic library, hiding personal information of patients, performing statistical analysis, and displaying analysis results; providing a plurality of classification modes and carrying out statistical display;
and a second summarizing module: summarizing the diagnosis and treatment cases of the same doctor to obtain doctor diagnosis and treatment records; the diagnosis and treatment records of doctors are arranged according to the diagnosis and treatment time, and the diagnosis results are summarized; evaluating the doctor's treatment experience based on the summary results;
and a third summarizing module: summarizing the treatment records of the same patient to obtain case summarizing information of the patient; the summarized information comprises index information and specific information; the specific information comprises specific diagnosis information, examination information and medication records;
Establishing index information for the visit record of the same patient, wherein the index information comprises a first index, a second index and a third index;
the first index is the name, sex, date of birth, and contact information of the patient; the second index is on-line diagnosis and treatment and off-line diagnosis and treatment; the third index is identity information, diagnosis and treatment departments and diagnosis and treatment time; the identity information comprises identity card or medical insurance card information; the patient can check the own visit record according to the index;
medical advice module: analyzing the diagnosis and treatment record of the patient to obtain an analysis result, and providing personalized medical advice according to the analysis result.
Further, a medical service platform based on cloud technology, the viewing module includes:
an encryption module: setting an encryption type storage scheme for patient information; encrypting basic information of a patient and encrypting diagnosis and treatment records;
the classification authority setting module: classifying diagnosis and treatment records of patients according to disease diagnosis results; different inquiry authorities are set according to the classification result;
the classification includes non-sensitive information diseases and diseases including privacy;
for diagnosis and treatment records without sensitive information diseases, a patient directly checks own records through login information; the doctor directly checks the acquisition permission of the platform by sending an application to the platform in the period of patient treatment;
A diagnosis and treatment record for diseases including privacy classes; the patient logs in through the login information and checks the diagnosis and treatment record of the patient through the dynamic key or face recognition;
for common diseases comprising diagnosis and treatment records of privacy diseases, a doctor sends an application to a platform through a patient treatment number in a patient treatment period to acquire treatment record permission for checking the patient treatment in a home; in the period of patient treatment, a doctor checks the treatment record of non-home treatment of a patient by sending an application to a platform, and the platform sends the application to a patient or guardian for treatment and obtains the permission of the patient to open the corresponding treatment record after agreeing to the doctor;
for emergency, a special access window is set, diagnosis and treatment records of patients are called through platform authorization, and the records are carried out; the emergency situation includes a critical patient;
and (5) checking a setting module: setting a checking period and a checking record time window, and obtaining recommended effective duration through machine learning; the recommended effective duration comprises a first effective duration and a second effective duration, wherein the first effective duration is the duration of a query window of a registered user of a patient port; the second effective duration is the effective duration of the doctor port query; wherein the doctor viewing period is a patient visit and/or treatment period;
And a time length setting module: periodically checking and accessing the setting of the recommended effective duration, and comparing with the actual demand; updating the preset effective duration; the actual requirements comprise the time length requirements fed back by the patient port and the doctor port;
and a log recording module: a log recording system is established to record all access operations to the data, including inquirer, inquiry time length and inquiry times; an alarm is given for the abnormal operation.
The invention has the beneficial effects that: by the medical service platform and the method based on the cloud technology, the whole medical service flow can be more efficiently carried out; the user can acquire service through the registration and login ports at any time and any place without additional waiting and queuing; the real-time storage and cloud management of the diagnosis and treatment records enable the communication between doctors and patients to be quicker and more convenient; the diagnosis and treatment record is stored to the cloud, so that the safety and reliability of the data are ensured; by adopting different viewing authority settings, only authorized personnel can view sensitive information, so that risks of data leakage and abuse are reduced; providing personalized medical advice through analysis of the patient diagnosis and treatment record; based on cloud big data analysis and machine learning algorithm, the system can provide more accurate and targeted medical advice for patients according to the illness state and history record of the patients, and the quality and effect of medical service are enhanced; providing limited access time to ensure that doctors and other authorized personnel acquire the necessary information within a reasonable time frame while avoiding overseeing or misuse of access rights; limiting the viewing time window can reduce potential risks, reduce the possibility of misuse or leakage of patient information, and enhance data security; the setting of the viewing time window can also promote timely decision making and information flow, so that a doctor can quickly acquire and apply key diagnosis and treatment records, and the medical quality and efficiency are improved.
Drawings
FIG. 1 is a schematic diagram of a medical service method based on cloud technology;
fig. 2 is a schematic diagram of the medical service platform based on the cloud technology.
Detailed Description
In order that the above-recited objects, features and advantages of the present invention will be more clearly understood, a more particular description of the invention will be rendered by reference to specific embodiments thereof which are illustrated in the appended drawings. It should be noted that, in the case of no conflict, the embodiments of the present application and the features in the embodiments may be combined with each other.
In the following description, numerous specific details are set forth in order to provide a thorough understanding of the present invention, and the described embodiments are merely some, rather than all, embodiments of the present invention. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs. The terminology used herein in the description of the invention is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention.
The embodiment provides a medical service method based on cloud technology, which comprises the following steps:
s1, acquiring registration and login information of a user through a registration and login port;
s2, acquiring diagnosis and treatment requirements and basic disease information of a patient through a diagnosis and treatment requirement window, recommending a department to visit according to the basic disease information, generating a diagnosis and treatment record, and storing the diagnosis and treatment record to a cloud end in real time;
s3, unified management is carried out on diagnosis and treatment records of patients; classifying and summarizing the diagnosis and treatment records; analyzing the diagnosis and treatment record of the patient, and providing personalized medical advice according to the analysis result;
s4, setting different viewing authorities for the diagnosis and treatment record; acquiring a check record aiming at the same diagnosis and treatment record in real time, and generating a check process record file; and setting the checking time length for the diagnosis and treatment record.
The working principle of the technical scheme is as follows: the user provides personal identity information through the registration and login ports, wherein the personal identity information comprises a user name, a password and the like; this information will be used to verify the user identity and to obtain the corresponding access rights; providing diagnosis and treatment requirements and basic illness state information by a patient through a diagnosis and treatment requirement window; based on the information, the system recommends proper consultation departments or specialists to make the consultation by using the cloud algorithm and rules. Meanwhile, the system can also generate diagnosis and treatment records and store the diagnosis and treatment records into a cloud database in real time. The diagnosis and treatment records of the patients are uniformly stored and managed in the cloud. The system can sort, aggregate and analyze the records; by using a data analysis technology, the system can extract valuable information and modes and perform deep analysis on diagnosis and treatment records of patients; based on the analysis of the patient's medical records, the system may provide personalized medical advice. According to the illness state, the history record and the cloud big data analysis of the patient, the system can provide more accurate and targeted medical advice for the patient and help the patient to make better health decisions; by setting different viewing authorities, the system can control the access to the diagnosis and treatment record. Only authorized personnel can view the sensitive information, so that the safety and privacy protection of the data are ensured. The system also generates management information and a viewing process record file, and records all viewing operations on the diagnosis and treatment record. Meanwhile, the system can acquire the check records aiming at the same diagnosis and treatment record in real time, and limit the access time according to the set check duration.
The technical scheme has the effects that: the whole medical service flow can be more efficiently carried out through the support of cloud technology; the user can acquire service through the registration and login ports at any time and any place without additional waiting and queuing; the real-time storage and cloud management of the diagnosis and treatment records enable the communication between doctors and patients to be quicker and more convenient; the diagnosis and treatment record is stored to the cloud, so that the safety and reliability of the data are ensured; by adopting different viewing authority settings, only authorized personnel can view sensitive information, so that risks of data leakage and abuse are reduced; providing personalized medical advice through analysis of the patient diagnosis and treatment record; based on cloud big data analysis and machine learning algorithm, the system can provide more accurate and targeted medical advice for patients according to the illness state and history record of the patients, and the quality and effect of medical service are enhanced; providing limited access time to ensure that doctors and other authorized personnel acquire the necessary information within a reasonable time frame while avoiding overseeing or misuse of access rights; limiting the viewing time window can reduce potential risks, reduce the possibility of misuse or leakage of patient information, and enhance data security; the setting of the viewing time window can also promote timely decision making and information flow, so that a doctor can quickly acquire and apply key diagnosis and treatment records, and the medical quality and efficiency are improved.
In summary, the medical service method based on the cloud technology achieves the effects of high efficiency, data security, personalized advice and the like of medical services through the steps of registration and login, diagnosis and treatment requirement window, diagnosis and treatment record management, viewing authority setting and the like.
The embodiment relates to a medical service method based on cloud technology, wherein the S1 includes:
the patient registers through the patient port, wherein the registration comprises the steps of filling in the name, the identification card number, the contact mode, the medical insurance information, the login mode and the face identification information of the patient; the platform authenticates and audits the authentication information, and personal account information is generated after the audit is passed; multiple patient information can be added under the same account and the relationship with the account registrant is noted; the user can register and log in through the mobile terminal APP and the applet; the platform is developed by the authorities of hospitals.
A doctor registers through a doctor port, wherein the doctor registration comprises doctor name, qualification and practice information; and accessing a medical institution official network through an API interface, acquiring medical institution information and doctor information, and associating and corresponding the information registered through the doctor port with the information in the medical institution.
The working principle of the technical scheme is as follows: the patient registers through the patient port, fills in personal information including name, ID card number, contact way, medical insurance account number, etc., and selects a login way and sets up a password. In addition, authentication may also be performed using face recognition techniques. Such authentication information will be used to create a personal account number; the patient can register and log in through the mobile terminal APP or applet. The design ensures that the patient can access medical services at any time and any place, thereby being convenient and quick; the platform carries out auditing on authentication information submitted by the patient, so that the accuracy and the authenticity of the information are ensured; only after the authentication is passed, personal account information is generated for the patient so as to facilitate the subsequent medical service; under the same account, a plurality of patient information can be added, and the relation with the account registrant is noted; the design can facilitate the medical service operation of family members or guardians on behalf of patients; the doctor registers through doctor port, fills in personal information including name, qualification, practice information, etc. This authentication information will be used to create a doctor account; and accessing a medical institution official network through an API interface, acquiring medical institution information and doctor information, and associating and corresponding the information registered through the doctor port with a medical practitioner. This ensures the validity and authenticity of the services provided by the doctor on the platform.
The technical scheme has the effects that: the patient can enjoy personalized medical services through registration; medical service operation can be performed according to the needs of the user and the needs of family members, so that the fitting degree and convenience of medical service are improved; the mobile terminal APP or the applet is used for registering and logging in, so that a patient can access medical services at any time and any place without waiting for queuing in a hospital, and the medical efficiency and the user experience are improved; the platform carries out auditing on authentication information submitted by the patient, so that the accuracy and the authenticity of the information are ensured, and the credibility and the safety of platform service are improved; by associating the medical information of the doctor, the validity and the authenticity of the service provided by the doctor on the platform are ensured, and reliable medical resources are provided for patients.
In summary, the S1 part of the medical service method based on the cloud technology realizes the effects of personalized medical service, convenient access of the mobile terminal, verification and guarantee of authentication information, association of doctors and medical institutions and the like through the modes of registration and authentication of patients and doctors, association with medical institution information, access of the mobile terminal and the like.
The medical service method based on the cloud technology in this embodiment, the S2 includes:
Acquiring diagnosis and treatment requirements and basic disease information of a patient through a diagnosis and treatment requirement window; the diagnosis and treatment requirements comprise on-line diagnosis and treatment and off-line diagnosis and treatment; if the patient selects on-line diagnosis and treatment, recommending according to the on-line doctor scheduling of the corresponding department; if the user selects offline diagnosis and treatment, the user performs reservation recommendation according to offline doctor scheduling of the corresponding department;
extracting characteristics of patient illness description through basic patient illness state information, matching with class characteristics of departments, and recommending to visit departments and doctors according to matching results; if the patient makes a first visit, recommending a department according to the disease description, sorting doctors in the department according to the disease and history scores, and selecting proper doctors according to the sorting result by the patient; if the patient is the same disease review, recommending according to the previous selection;
predicting the specific treatment time of the patient according to the doctor scheduling selected by the patient; wherein the predicted wait time is:
the average diagnosis time of each case in the last month of the doctor, r is the number of queued cases in front of the patient, and D0 is the diagnosis starting time of the doctor; dmax is the longest visit time of the doctor in the last month, and b the number of visits of the doctor in the last month; k (K) r Queuing case history health indicators for the patient in front;
generating diagnosis and treatment records in real time and uploading the diagnosis and treatment records to a cloud end; the diagnosis and treatment records are divided into an on-line diagnosis and treatment record and an off-line diagnosis and treatment record; the on-line diagnosis and treatment record comprises on-line dialogue with a doctor, illness state description and doctor diagnosis and treatment advice; the offline diagnosis and treatment records comprise medical records, examination reports, prescriptions, hospitalization records and treatment effects;
setting an evaluation and feedback window, and evaluating and feeding back doctors, systems and treatment effects; wherein, the evaluation of the doctor comprises doctor attitude and doctor operation; the evaluation of the system comprises the good utilization degree and experience feeling of the system, and the feedback comprises the feedback of the treatment effect after the treatment.
The working principle of the technical scheme is as follows: the patient provides diagnosis and treatment requirements and basic illness state information through a diagnosis and treatment requirement window. The diagnosis and treatment requirements can select on-line diagnosis and treatment or off-line diagnosis and treatment. If online diagnosis and treatment are selected, the system recommends according to online doctor scheduling of the corresponding department; if the off-line diagnosis and treatment is selected, the system can conduct reservation recommendation according to the off-line doctor scheduling of the corresponding department; the system extracts the characteristics of patient condition descriptions and matches the characteristics of clinical treatment diseases in the department. Based on the matching results, the system recommends the appropriate department of diagnosis and doctor. For patients who visit for the first time, the system will recommend departments based on the disease descriptions and rank according to the physician's disease adequacy and historical scores, and the patient can select the appropriate physician based on the ranking results. For the patient with the same disease to be re-diagnosed, the system can recommend according to the previous selection;
The system predicts the time of their visit based on the patient's selected physician. The predicted wait time (D) is according to the formula
Calculating, wherein D0 is the expected doctor starting diagnosis time, da is the average diagnosis time of each case in the last month of the doctor, R is the number of queued cases in front of the patient, dmax is the longest diagnosis time in the last month of the doctor, and b is the diagnosis times in the last month of the doctor; according to the patient's condition of seeing a doctor, the system can generate corresponding diagnosis and treatment record to the high in the clouds in real time. Diagnosis and treatment records are divided into on-line diagnosis and treatment records and off-line diagnosis and treatment records. The on-line diagnosis and treatment record comprises information such as dialogue content with a doctor, illness state description, doctor diagnosis and treatment advice and the like. The offline diagnosis and treatment records comprise medical records, examination reports, prescriptions, hospitalization records, treatment effects and other information; collecting the evaluation of the user on the doctor attitude and the doctor by providing an evaluation window after doctor service for the user; the user can evaluate according to the self-diagnosis experience, the professional ability, attitude and communication of doctors and the like; and providing an evaluation feedback window for the system for the user, and collecting the user's usability degree and experience feeling of the system. The user can evaluate the system according to the aspects of interface friendliness, operation convenience, response speed and the like of the system; after the treatment is finished, a feedback window is provided for the patient, so that the patient can share Effects and feelings after treatment. The patient may describe whether himself is recovering or the condition of the symptom improvement.
The technical scheme has the effects that: through feature matching and sequencing, the system can accurately recommend proper medical departments and doctors according to the condition description and the medical requirements of patients, and the medical experience and treatment effect of the patients are improved; the system can predict the treatment time of the patient according to the doctor's treatment condition and the queuing condition of the patient, and perform queuing management. This helps to schedule the patient in advance, reduces latency, and improves the efficiency of medical services; the formula comprehensively considers a plurality of factors, not only considers the doctor's visit time and the number of times of visits, but also considers the historical health index of the queuing cases in front of the patient. Therefore, the patient treatment time can be more comprehensively estimated, and the situation that prediction is inaccurate due to the fact that only a single factor is considered is avoided; parameters in the formula can be adjusted according to the situation of each specific doctor, such as average visit time, longest visit time, visit times and the like in the last month. Therefore, personalized prediction can be performed according to the treatment conditions of different doctors, and the accuracy and reliability of prediction are improved. The historical health index of the previous queuing case of the patient is considered in the formula, and the patient is checked by K r Weighting the factors; therefore, the condition of the queuing case in front of the patient can be considered, and the actual condition can be better reflected in the prediction; by generating and uploading diagnosis and treatment records to the cloud, the system can record the diagnosis and treatment information of the patient in real time. Thus, timeliness and accuracy of the data can be ensured, and subsequent consulting and analysis are convenient; the system comprehensively records on-line and off-line diagnosis and treatment information, including conversations with doctors, illness state descriptions, doctor diagnosis and treatment suggestions and other information, medical records, examination reports, prescriptions, hospitalization records, treatment effects and the like. Thus, a comprehensive medical service record can be provided, and the patient and the doctor can manage the health condition of the patient together; the collection of doctor evaluations may provide important feedback information to hospitals and doctors for assessing the general performance of the doctors and improving medical services. Meanwhile, doctor evaluation can also help a patient to select a proper doctor, so that the quality and transparency of medical service are improved; is tied up withThe collection of system ratings helps to understand the user's satisfaction with system functions and performance and provides improved direction and optimization strategies. By collecting feedback of users, system developers can repair bug, add new functions and improve stability and user experience of the system; the collection of treatment effect feedback helps doctors and hospitals assess the effectiveness of treatment regimens and adjust treatment strategies based on the feedback information. In addition, feedback of the therapeutic effect can also help other patients to know the treatment condition of the disease, and increase the confidence of the patients to the treatment.
In summary, in the medical service method based on the cloud technology, the S2 part acquires the diagnosis and treatment requirements and basic disease information of the patient through the diagnosis and treatment requirement window, recommends departments and doctors according to feature matching, predicts the diagnosis and treatment time, generates and uploads a diagnosis and treatment record to the cloud, and achieves the effects of accurate recommendation, diagnosis and treatment time prediction, real-time record, cloud storage and the like; meanwhile, hospitals and systems can acquire precious feedback information from the angle of patients, so that medical services are improved, system functions are optimized, and overall medical quality and user satisfaction are improved.
The medical service method based on the cloud technology in this embodiment, the S3 includes:
classifying and grading the cases according to the disease types; extracting disease characteristics, generating a disease characteristic library, hiding personal information of patients, performing statistical analysis, and displaying analysis results; providing a plurality of classification modes and carrying out statistical display; comprises classifying according to patient ages to obtain a first classification; infant diseases, childhood diseases, adult diseases, senile diseases, etc., and performing a second classification according to different classification methods under the first classification; according to the diagnosis result of doctors, the diagnosis results are classified according to etiology: diseases can be classified into infectious diseases, hereditary diseases, immunological diseases, metabolic diseases, environmental related diseases, etc. according to the cause and cause of the disease; classification by organ or system: diseases can be classified into cardiovascular diseases, respiratory diseases, digestive diseases, urinary diseases, etc. according to affected organs or systems; classifying according to the development process: diseases can be classified into acute diseases, chronic diseases, recurrent diseases, etc. according to the progress of the diseases; classifying into a normal case, a severe case, a critical case and a rare case under the second classification;
Recording clinical symptoms, medication records and treatment effects of the diseases under the same second classification; medical research can be performed according to the summary record; the doctor logs in through the case summarization port to access and acquire the classification report for research;
summarizing the diagnosis and treatment cases of the same doctor to obtain doctor diagnosis and treatment records; the diagnosis and treatment records of doctors are arranged according to the diagnosis and treatment time, and the diagnosis results are summarized; evaluating the doctor's treatment experience based on the summary results;
summarizing the treatment records of the same patient to obtain case summarizing information of the patient;
the summarized information comprises index information and specific information; the specific information comprises specific diagnosis information, examination information and medication records;
establishing index information for the visit record of the same patient, wherein the index information comprises a first index, a second index and a third index;
the first index is the name, sex, date of birth and contact information of the patient; the second index is on-line diagnosis and treatment and off-line diagnosis and treatment; the third index is identity information, diagnosis and treatment departments and diagnosis and treatment time; the identity information comprises identity card or medical insurance card information; the patient can check the own visit record according to the index;
Recording according to the history of the patient; classifying the disease of the patient, the classification comprising a fourth classification, classifying the disease of the patient into a disease free of sensitive information and a disease comprising privacy;
fifth classification of the privacy-containing group of diseases, including acute disease, chronic disease, recurrent disease;
classifying the disease of the patient further comprises a sixth classification of common disease, severe disease, critical disease, rare disease;
analyzing the diagnosis and treatment record of the patient to obtain an analysis result, and providing personalized medical advice according to the analysis result; comprising the following steps:
the system firstly acquires relevant data from diagnosis and treatment records of patients, including medical history, test results, imaging examination reports and the like; such data may come from a hospital electronic medical record system, laboratory information management system, medical imaging system, etc.;
the collected data is cleaned and preprocessed, including interpolation and smoothing, error or incomplete data are removed, and different data sources are integrated and standardized, so that the consistency and the usability of the data are ensured;
selecting relevant features from the diagnosis and treatment record through a principal component analysis method;
deep analysis is carried out on diagnosis and treatment records of patients by adopting data analysis and mining technology; for example, applying machine learning algorithms, data mining techniques or artificial intelligence models, pattern recognition, anomaly detection, correlation analysis, etc., to time series data or specific disease data;
Identifying potential abnormal data points by comparing the patient diagnosis and treatment record with normal conditions or standard abnormal conditions;
Ei＝(Xi-μ)/(q3-q1)
ei is the offset; xi represents a detection value, mu represents a mean value obtained by the same data history record, and q1 and q3 represent 25% quantiles and 75% quantiles of data respectively; yi when Ei is greater than a threshold value, indicating Xi as a potential outlier data point;
obtaining health evaluation indexes according to the number, the deviation amount and the importance degree of abnormal data points and displaying the health evaluation indexes to a patient; simultaneously, the new diagnosis result is followed by the health index, and the change curve of the health index is recorded;
health assessment indexThe importance of the Zi abnormal data points; n is the number of outlier data points;
for some chronic or progressive diseases, applying a time series analysis method to predict future trend, periodicity and seasonal changes for time series of diagnosis and treatment record data;
according to the result of the data analysis, the system can generate personalized medical analysis reports related to the health state of the patient, the disease risk assessment, the treatment effect prediction and the like; these reports may be in the form of digitized text, charts, images, or visual interfaces;
based on the analysis results, the system may generate personalized medical advice for the physician, including treatment regimens for patient specific disease management, medication advice, healthy lifestyle guidance, and the like; at the same time, the system may also provide relevant educational information and self-administered advice to the patient.
Advice may relate to various aspects of medication, review planning, surgical options, rehabilitation planning, lifestyle changes, etc. to meet the specific needs and conditions of the patient; continuously tracking and updating medical advice according to feedback and treatment effects of the patient; by monitoring the progress and response of the patient, the treatment regimen can be optimized and adjusted to achieve better results.
The working principle of the technical scheme is as follows: classifying and grading cases according to different classification modes, such as age, etiology, organs or systems, development process and the like; extracting disease characteristics to generate a disease characteristic library: critical disease features are extracted from each case and combined into a disease feature library. In order to protect privacy of personal information of patients, statistical analysis is required to be performed after the personal information of the patients is hidden; carrying out statistical analysis on the cases hidden with the personal information, and displaying analysis results, wherein the analysis results possibly comprise statistical data of disease classification, distribution conditions of disease characteristics and the like; providing a plurality of classification modes, such as classification according to age, etiology, organs or systems, development process and the like, and then carrying out statistical display on each classification mode so that doctors and researchers can know the classification and characteristics of the diseases deeply; record clinical symptoms, medication records and treatment effect: clinical symptoms, medication records and treatment effects related to the disease records under the same classification are used for medical research; summarizing the cases of the same doctor, obtaining the diagnosis and treatment record of the doctor, and arranging and summarizing according to the diagnosis and treatment time and the diagnosis result, thereby evaluating the treatment experience of the doctor; and summarizing the visit records of the same patient to obtain the case summarization information of the patient. Establishing index information comprising personal information, on-line or off-line diagnosis and treatment modes, identity information, diagnosis and treatment departments and the like of patients, so that the patients can check own diagnosis records according to the index; matching the history visit record and the illness state information of the patient with the characteristics in the illness state characteristic library, providing personalized medical advice and sending the reminding to the patient; the medical advice is continuously tracked and updated, and the treatment regimen is optimized and adjusted based on the patient's feedback and treatment outcome.
The technical scheme has the effects that: comprehensive case management and analysis functions are provided, so that doctors and researchers are helped to better know the classification, characteristics and treatment effect of the diseases; through statistical analysis and display, the distribution condition, characteristic trend and the like of the diseases can be found, and a basis is provided for medical research; summarizing and evaluating diagnosis and treatment records of doctors, and helping to evaluate the treatment experience of the doctors and improve the medical quality; the patient can conveniently check the own visit records and know the classification and treatment condition of the diseases; by analyzing the patient diagnosis and treatment record to obtain an analysis result, the formula can identify potential abnormal data points by comparing the patient diagnosis and treatment record with normal conditions or standard abnormal conditions. The method is favorable for timely finding out abnormal conditions of patients, provides opportunities for early warning and intervention, and prevents further development of diseases; the mean, 25% quantile and 75% quantile of the same data history were used in the formula as reference statistics. Thus, the detection value of the patient can be compared with the statistical characteristic to accurately judge whether the patient is abnormal or not, and erroneous judgment caused by the individual numerical value is avoided; the formula calculates the health assessment index K through the number of abnormal data points, the deviation amount and the importance degree of the abnormal data points. The index comprehensively considers a plurality of factors of abnormal data points, can provide a comprehensive evaluation result and reflects the overall health state of the patient; and according to the calculated health evaluation index K, the result can be displayed to the patient. Thus, the patient can more intuitively know the health condition of the patient and take corresponding medical measures when necessary. Through the quantified indexes, the patient can intuitively know the health condition of the patient. The evaluation index can comprehensively consider the number, the deviation and the importance degree of the abnormal data points, provide an objective evaluation result, and help a patient to know the overall health state of the patient and whether a potential abnormal condition exists; when a new diagnosis result appears, the health evaluation index is updated. By updating the index, the patient can know the latest health condition and master the health change condition in time; the profile record of the health indicator may provide more detailed information; by recording the change trend of the index, the patient can know the change trend of the health state of the patient, including the trend of improvement or deterioration and possible influencing factors; according to the health evaluation index and the change curve record, a doctor can formulate a personalized health management scheme. For a patient's specific situation, a physician may give corresponding advice, treatment regimens, or health management measures to help the patient improve the health condition and prevent the underlying disease progression.
The personalized medical advice is provided according to the analysis result, and the personalized medical advice and the tracking update can provide a more accurate and effective treatment scheme so as to achieve a better treatment effect.
The medical service method based on the cloud technology in this embodiment, the S4 includes:
setting an encryption type storage scheme for patient information; encrypting basic information of a patient and encrypting diagnosis and treatment records; the basic information of the patient comprises the identity information (identity card or medical insurance card), address and contact information of the patient; encrypting the name part of the patient; age and gender are not encrypted;
classifying diagnosis and treatment records of patients according to disease diagnosis results; different inquiry authorities are set according to the classification result;
the classification includes non-sensitive information diseases and diseases including privacy; the disease without sensitive information is that privacy is not included, and the disease can be cured through short-term treatment, such as common cold, diarrhea, skin allergy, appendicitis, common trauma and the like; such diseases including privacy-like diseases include, but are not limited to, various chronic diseases, mental diseases, nodules, cancer, gender-like diseases, and the like;
for diagnosis and treatment records without sensitive information diseases, a patient directly checks own records through login information; the doctor directly checks the acquisition permission of the platform by sending an application to the platform in the period of patient treatment;
A diagnosis and treatment record for diseases including privacy classes; the patient logs in through the login information and checks the diagnosis and treatment record of the patient through the dynamic key or face recognition;
for common diseases comprising diagnosis and treatment records of privacy diseases, a doctor sends an application to a platform through a patient treatment number in a patient treatment period to acquire treatment record permission for checking the patient treatment in a home; in the period of patient treatment, a doctor checks the treatment record of non-home treatment of a patient by sending an application to a platform, and the platform sends the application to a patient or guardian for treatment and obtains the permission of the patient to open the corresponding treatment record after agreeing to the doctor;
for emergency, a special access window is set, diagnosis and treatment records of patients are called through platform authorization, and are recorded, the checking period is in the diagnosis and treatment stage, and the checking time window is not particularly limited; the emergency situation includes a critical patient; the emergency includes severe cases, critical cases, and rare cases.
Setting a checking period and a checking record time window, and obtaining recommended effective duration through machine learning; the recommended effective duration comprises a first effective duration and a second effective duration, wherein the first effective duration is the duration of a query window of a registered user of a patient port; the second effective duration is the effective duration of the doctor port query; wherein the doctor viewing period is a patient visit and/or treatment period;
Periodically checking and accessing the setting of the recommended effective duration, and comparing with the actual demand; updating the preset effective duration; the actual requirements comprise the time length requirements fed back by the patient port and the doctor port;
the effective duration of the query after the dynamic key is input and/or after the face recognition is:
the time window for opening the right of the corresponding visit record to the doctor is as follows:
wherein L is the report length in the patient diagnosis record; n the number of reports in a certain diagnosis and treatment record of the patient; l (L) a Average report length for all patients under the same disease classification; n (N) a An average report number for all patients under the same disease classification; j0 is a recommended first effective duration; f is the query times of the account owners of the diagnosis and treatment records of the patient, m is the overtime unremoved times of the query diagnosis and treatment records of the account owners; the same disease is classified into the aforementioned second classification; p is the number of times a doctor inquires about the patient case; q is the number of times the doctor inquires the patient record is overtime and is not withdrawn; c is the score of the authorized inquiring doctor, C a Average scoring for doctors in the same department of the platform; t0 is a recommended second effective duration; beta is an adjustment coefficient; the beta setting rule is that before and after the medical operation, the medical operation is that a bill prescribed by a doctor is used as a standard, and beta is set according to the importance of the medical operation, wherein the importance is an integer of 1-10, and the beta is consistent with the importance;
A log recording system is established to record all access operations to the data, including inquirer, inquiry time length and inquiry times; alerting an abnormal operation, the abnormal operation comprising: exceeding a set number or frequency of accesses, unauthorized accesses, etc.
The working principle of the technical scheme is as follows: the identity information, address and contact information of the patient, and name portion are stored encrypted, while age and gender are not. This can be achieved by using symmetric or asymmetric encryption algorithms, ensuring that the privacy and sensitive information of the patient is protected; diagnosis and treatment records of patients are classified according to disease diagnosis results, and are classified into common diseases and diseases including privacy. And encrypting and storing diagnosis and treatment records aiming at diseases containing privacy. This may employ a symmetric or asymmetric encryption algorithm to ensure that only authorized personnel can decrypt and view the records; and setting different inquiry authorities according to the grading result. For diagnosis and treatment records of common diseases, a patient can directly log in the system to check own records, and a doctor acquires permission to check by sending an application to a platform; for medical records of diseases containing privacy, the patient needs to be authenticated by login information and dynamic keys or face recognition to view his records. In the patient treatment period, a doctor sends an application to a platform according to the patient treatment number to acquire the viewing authority; the doctor who obtains the authority can only check the doctor's records of the patient, but cannot copy and screen capture; for the visit records of non-home visit, the doctor needs to send an application to the platform, and the platform can send the application to the patient or the guardian, and the permission of the corresponding visit record can be opened to the doctor after the patient agrees. Aiming at emergency, a special access window is set, diagnosis and treatment records of patients are called through platform authorization, and recording is carried out. This ensures that in case of emergency such as critical patients, a doctor can acquire diagnosis and treatment records of the patient in time; and obtaining recommended effective duration according to actual demands of a patient end and a doctor end through machine learning. This includes a first effective duration that is the duration of the patient registration user query window and a second effective duration that is the duration of the doctor query. The doctor's viewing period is the patient's visit and/or treatment period; periodically checking and accessing the setting of the recommended effective duration, comparing with the actual requirement, and updating the preset effective duration according to the feedback and the requirement of the patient end and the doctor end; and establishing a log record system to record all access operations to the data, wherein the access operations comprise inquirers, inquiry time duration and inquiry times. For abnormal operation, such as exceeding the set access times or frequency, unauthorized access and the like, an alarm is sent out and corresponding processing is carried out; through implementation of the technical scheme, the safety and privacy protection of the patient information can be ensured, and only authorized personnel can legally access and use the basic information and diagnosis and treatment record of the patient.
The technical scheme has the effects that: by encrypting the basic information and diagnosis and treatment records of the patient, the privacy of the patient and the safety of personal data are effectively protected, and unauthorized access and leakage risks are avoided; grading diagnosis and treatment records according to disease diagnosis results, setting different inquiry authorities, and only users with corresponding authorities can check related records to ensure that sensitive information is only accessed by authorized personnel; for diagnosis and treatment records of common diseases, patients and doctors can directly check through login information, and the operation is simple and convenient; for diseases containing privacy, a patient needs to log in and carry out identity verification through a dynamic key or face recognition, so that the safety of data is improved; aiming at emergency, a special access window is set, and authorized personnel can timely call the diagnosis and treatment record of a patient when necessary, so that the medical treatment work can be conveniently unfolded; recommending the most suitable query window duration according to feedback of a patient end and a doctor end through a machine learning algorithm, and providing limited access time by limiting the effective duration of query so as to ensure that doctors and other authorized personnel acquire necessary information within a reasonable time range and avoid excessively checking or abusing access rights; limiting the viewing time window can reduce potential risks, reduce the possibility of misuse or leakage of patient information, and enhance data security; the setting of the checking time window can also promote timely decision making and information flow, so that a doctor can quickly acquire and apply key diagnosis and treatment records, thereby improving the medical quality and efficiency; and periodically checking and accessing the setting of the recommended effective duration, comparing with the actual demand, updating the preset effective duration according to feedback, and ensuring the adaptability and optimizability of the system. A complete log recording system is established, all access operations to data are recorded, including inquirers, inquiry time length and inquiry times, abnormal operations can be monitored and alerted in time, and data security protection capability is improved.
In the formula, J1 represents the effective duration of inquiry, and T1 represents a time window for opening the corresponding doctor-seeing record permission to a doctor. These calculations are based on a number of factors, including the report length (L) and report number (N) of patient treatment records, the average report length (La) and average report number (Na) of all patients under the same disease category, the recommended first effective duration (J0), the number of queries (F) and timeout non-exit times (m) of the account owner, the number of times a doctor queries for this patient case (P) and timeout non-exit times (q), the score (C) of the authorized querying doctor and the average score (Ca) of the same department doctor on the platform. At the same time, the relation between the adjustment coefficient β and the importance of the medical procedure is also considered. By adjusting these factors, the effective duration of the query and the open time window of the rights can be determined, thereby achieving the following benefits and effects: by reasonably setting the effective duration, the method ensures that enough information is acquired in the query, avoids overlong or excessively short query time and improves the query efficiency; by limiting the inquiry time window, the permission of the corresponding visit record is ensured to be opened to the doctor only in a specific time, potential data leakage and abuse risk are reduced, and privacy safety of a patient is protected; according to diagnosis and treatment record characteristics of a patient and query behaviors of doctors, query time length and permission opening time window are dynamically adjusted, and more personalized and accurate medical services are provided. By reasonably setting the adjustment coefficient beta, the inquiring duration and the permission opening time window are flexibly adjusted according to the importance of medical operation, the medical procedure is optimized, and the medical efficiency is improved.
Through the technical scheme, the safety and privacy protection of the patient information can be effectively guaranteed, the fine authority management and user operation control are realized, and the efficiency and safety of medical data management are improved.
The embodiment provides a medical service platform based on cloud technology, wherein the platform comprises:
registration and login module: acquiring registration and login information of a user through a registration and login port;
diagnosis and treatment module: acquiring diagnosis and treatment requirements and basic disease information of a patient through a diagnosis and treatment requirement window, recommending a department to visit according to the basic disease information, generating a diagnosis and treatment record and storing the diagnosis and treatment record to a cloud in real time;
and a record management module: unified management is carried out on diagnosis and treatment records of patients; classifying and summarizing the diagnosis and treatment records; analyzing the diagnosis and treatment record of the patient, and providing personalized medical advice according to the analysis result;
and a viewing module: setting different viewing rights for the diagnosis and treatment record; acquiring a check record aiming at the same diagnosis and treatment record in real time, and generating a check process record file; and setting the checking time length for the diagnosis and treatment record.
The working principle of the technical scheme is as follows: the user provides personal identity information through the registration and login ports, wherein the personal identity information comprises a user name, a password and the like; this information will be used to verify the user identity and to obtain the corresponding access rights; providing diagnosis and treatment requirements and basic illness state information by a patient through a diagnosis and treatment requirement window; based on the information, the system recommends proper consultation departments or specialists to make the consultation by using the cloud algorithm and rules. Meanwhile, the system can also generate diagnosis and treatment records and store the diagnosis and treatment records into a cloud database in real time. The diagnosis and treatment records of the patients are uniformly stored and managed in the cloud. The system can sort, aggregate and analyze the records; by using a data analysis technology, the system can extract valuable information and modes and perform deep analysis on diagnosis and treatment records of patients; based on the analysis of the patient's medical records, the system may provide personalized medical advice. According to the illness state, the history record and the cloud big data analysis of the patient, the system can provide more accurate and targeted medical advice for the patient and help the patient to make better health decisions; by setting different viewing authorities, the system can control the access to the diagnosis and treatment record. Only authorized personnel can view the sensitive information, so that the safety and privacy protection of the data are ensured. The system also generates management information and a viewing process record file, and records all viewing operations on the diagnosis and treatment record. Meanwhile, the system can acquire the check records aiming at the same diagnosis and treatment record in real time, and limit the access time according to the set check duration.
The technical scheme has the effects that: the whole medical service flow can be more efficiently carried out through the support of cloud technology; the user can acquire service through the registration and login ports at any time and any place without additional waiting and queuing; the real-time storage and cloud management of the diagnosis and treatment records enable the communication between doctors and patients to be quicker and more convenient; the diagnosis and treatment record is stored to the cloud, so that the safety and reliability of the data are ensured; by adopting different viewing authority settings, only authorized personnel can view sensitive information, so that risks of data leakage and abuse are reduced; providing personalized medical advice through analysis of the patient diagnosis and treatment record; based on cloud big data analysis and machine learning algorithm, the system can provide more accurate and targeted medical advice for patients according to the illness state and history record of the patients, and the quality and effect of medical service are enhanced; providing limited access time to ensure that doctors and other authorized personnel acquire the necessary information within a reasonable time frame while avoiding overseeing or misuse of access rights; limiting the viewing time window can reduce potential risks, reduce the possibility of misuse or leakage of patient information, and enhance data security; the setting of the viewing time window can also promote timely decision making and information flow, so that a doctor can quickly acquire and apply key diagnosis and treatment records, and the medical quality and efficiency are improved.
In summary, the medical service method based on the cloud technology achieves the effects of high efficiency, data security, personalized advice and the like of medical services through the steps of registration and login, diagnosis and treatment requirement window, diagnosis and treatment record management, viewing authority setting and the like.
The medical service platform based on the cloud technology of the embodiment, the registration and login module includes:
patient port: the patient registers through the patient port, wherein the registration comprises the steps of filling in the name, the identification card number, the contact mode, the medical insurance information, the login mode and the password of the patient; the platform authenticates and audits the authentication information, and personal account information is generated after the audit is passed;
doctor port: a doctor registers through a doctor port, wherein the doctor registration comprises doctor name, qualification and practice information; and accessing a medical institution official network through an API interface, acquiring medical institution information and doctor information, and associating and corresponding the information registered through the doctor port with the information in the medical institution.
The working principle of the technical scheme is as follows: the patient registers through the patient port, fills in personal information including name, ID card number, contact way, medical insurance account number, etc., and selects a login way and sets up a password. In addition, authentication may also be performed using face recognition techniques. Such authentication information will be used to create a personal account number; the patient can register and log in through the mobile terminal APP or applet. The design ensures that the patient can access medical services at any time and any place, thereby being convenient and quick; the platform carries out auditing on authentication information submitted by the patient, so that the accuracy and the authenticity of the information are ensured; only after the authentication is passed, personal account information is generated for the patient so as to facilitate the subsequent medical service; under the same account, a plurality of patient information can be added, and the relation with the account registrant is noted; the design can facilitate the medical service operation of family members or guardians on behalf of patients; the doctor registers through doctor port, fills in personal information including name, qualification, practice information, etc. This authentication information will be used to create a doctor account; and accessing a medical institution official network through an API interface, acquiring medical institution information and doctor information, and associating and corresponding the information registered through the doctor port with a medical practitioner. This ensures the validity and authenticity of the services provided by the doctor on the platform.
The technical scheme has the effects that: the patient can enjoy personalized medical services through registration; medical service operation can be performed according to the needs of the user and the needs of family members, so that the fitting degree and convenience of medical service are improved; the mobile terminal APP or the applet is used for registering and logging in, so that a patient can access medical services at any time and any place without waiting for queuing in a hospital, and the medical efficiency and the user experience are improved; the platform carries out auditing on authentication information submitted by the patient, so that the accuracy and the authenticity of the information are ensured, and the credibility and the safety of platform service are improved; by associating the medical information of the doctor, the validity and the authenticity of the service provided by the doctor on the platform are ensured, and reliable medical resources are provided for patients.
In summary, the S1 part of the medical service method based on the cloud technology realizes the effects of personalized medical service, convenient access of the mobile terminal, verification and guarantee of authentication information, association of doctors and medical institutions and the like through the modes of registration and authentication of patients and doctors, association with medical institution information, access of the mobile terminal and the like.
The embodiment relates to a medical service platform based on cloud technology, and the diagnosis and treatment module comprises:
Diagnosis and treatment demand module: acquiring diagnosis and treatment requirements and basic disease information of a patient through a diagnosis and treatment requirement window; the diagnosis and treatment requirements comprise on-line diagnosis and treatment and off-line diagnosis and treatment; if the patient selects on-line diagnosis and treatment, recommending according to the on-line doctor scheduling of the corresponding department; if the user selects offline diagnosis and treatment, the user performs reservation recommendation according to offline doctor scheduling of the corresponding department;
and a recommendation module: extracting characteristics of patient illness description through basic patient illness state information, matching with class characteristics of departments, and recommending to visit departments and doctors according to matching results; if the patient makes a first visit, recommending a department according to the disease description, sorting doctors in the department according to the disease and history scores, and selecting proper doctors according to the sorting result by the patient; if the patient is the same disease review, recommending according to the previous selection;
and a prediction module: predicting the specific treatment time of the patient according to the doctor scheduling selected by the patient; wherein the predicted wait time is:
the average diagnosis time of each case in the last month of the doctor, r is the number of queued cases in front of the patient, and D0 is the diagnosis starting time of the doctor; dmax is the longest visit time of the doctor in the last month, and b the number of visits of the doctor in the last month; k (K) r Queuing case history health indicators for the patient in front;
diagnosis and treatment record generation module: generating diagnosis and treatment records in real time and uploading the diagnosis and treatment records to a cloud end; the diagnosis and treatment records are divided into an on-line diagnosis and treatment record and an off-line diagnosis and treatment record; the on-line diagnosis and treatment record comprises on-line dialogue with a doctor, illness state description and doctor diagnosis and treatment advice; the offline diagnosis and treatment records comprise medical records, examination reports, prescriptions, hospitalization records and treatment effects;
and an evaluation feedback module: setting an evaluation and feedback window, and evaluating and feeding back doctors, systems and treatment effects; wherein, the evaluation of the doctor comprises doctor attitude and doctor operation; the evaluation of the system comprises the good utilization degree and experience feeling of the system, and the feedback comprises the feedback of the treatment effect after the treatment.
The working principle of the technical scheme is as follows: the patient provides diagnosis and treatment requirements and basic illness state information through a diagnosis and treatment requirement window. The diagnosis and treatment requirements can select on-line diagnosis and treatment or off-line diagnosis and treatment. If online diagnosis and treatment are selected, the system recommends according to online doctor scheduling of the corresponding department; if the off-line diagnosis and treatment is selected, the system can conduct reservation recommendation according to the off-line doctor scheduling of the corresponding department; the system extracts the characteristics of patient condition descriptions and matches the characteristics of clinical treatment diseases in the department. Based on the matching results, the system recommends the appropriate department of diagnosis and doctor. For patients who visit for the first time, the system will recommend departments based on the disease descriptions and rank according to the physician's disease adequacy and historical scores, and the patient can select the appropriate physician based on the ranking results. For the patient with the same disease to be re-diagnosed, the system can recommend according to the previous selection;
The system predicts the time of their visit based on the patient's selected physician. The predicted wait time (D) is according to the formula
Calculating, wherein D0 is the expected doctor starting diagnosis time, da is the average diagnosis time of each case in the last month of the doctor, R is the number of queued cases in front of the patient, dmax is the longest diagnosis time in the last month of the doctor, and b is the diagnosis times in the last month of the doctor; according to the patient's condition of seeing a doctor, the system can generate corresponding diagnosis and treatment record to the high in the clouds in real time. Diagnosis and treatment records are divided into on-line diagnosis and treatment records and off-line diagnosis and treatment records. The on-line diagnosis and treatment record comprises information such as dialogue content with a doctor, illness state description, doctor diagnosis and treatment advice and the like. The offline diagnosis and treatment records comprise medical records, examination reports, prescriptions and inpatient recordsRecording information such as treatment effect and the like; collecting the evaluation of the user on the doctor attitude and the doctor by providing an evaluation window after doctor service for the user; the user can evaluate according to the self-diagnosis experience, the professional ability, attitude and communication of doctors and the like; and providing an evaluation feedback window for the system for the user, and collecting the user's usability degree and experience feeling of the system. The user can evaluate the system according to the aspects of interface friendliness, operation convenience, response speed and the like of the system; after the treatment is finished, a feedback window is provided for the patient, so that the patient can share the effect and the feeling after the treatment. The patient may describe whether himself is recovering or the condition of the symptom improvement. / >
The technical scheme has the effects that: through feature matching and sequencing, the system can accurately recommend proper medical departments and doctors according to the condition description and the medical requirements of patients, and the medical experience and treatment effect of the patients are improved; the system can predict the treatment time of the patient according to the doctor's treatment condition and the queuing condition of the patient, and perform queuing management. This helps to schedule the patient in advance, reduces latency, and improves the efficiency of medical services; the formula comprehensively considers a plurality of factors, not only considers the doctor's visit time and the number of times of visits, but also considers the historical health index of the queuing cases in front of the patient. Therefore, the patient treatment time can be more comprehensively estimated, and the situation that prediction is inaccurate due to the fact that only a single factor is considered is avoided; parameters in the formula can be adjusted according to the situation of each specific doctor, such as average visit time, longest visit time, visit times and the like in the last month. Therefore, personalized prediction can be performed according to the treatment conditions of different doctors, and the accuracy and reliability of prediction are improved. The historical health index of the previous queuing case of the patient is considered in the formula, and the patient is checked by K r Weighting the factors; therefore, the condition of the queuing case in front of the patient can be considered, and the actual condition can be better reflected in the prediction; by generating and uploading diagnosis and treatment records to the cloud, the system can record the diagnosis and treatment information of the patient in real time. Thus, timeliness and accuracy of the data can be ensured, and subsequent consulting and analysis are convenient; the system carries out on-line and off-line diagnosis and treatment informationComprehensive records including dialogue with the doctor, descriptions of the condition, doctor advice of diagnosis and treatment, etc., medical history, examination reports, prescriptions, hospitalization records, treatment effects, etc. Thus, a comprehensive medical service record can be provided, and the patient and the doctor can manage the health condition of the patient together; the collection of doctor evaluations may provide important feedback information to hospitals and doctors for assessing the general performance of the doctors and improving medical services. Meanwhile, doctor evaluation can also help a patient to select a proper doctor, so that the quality and transparency of medical service are improved; the collection of system ratings helps to understand the user's satisfaction with system functions and performance and provides improved direction and optimization strategies. By collecting feedback of users, system developers can repair bug, add new functions and improve stability and user experience of the system; the collection of treatment effect feedback helps doctors and hospitals assess the effectiveness of treatment regimens and adjust treatment strategies based on the feedback information. In addition, feedback of the therapeutic effect can also help other patients to know the treatment condition of the disease, and increase the confidence of the patients to the treatment.
In summary, in the medical service method based on the cloud technology, the S2 part acquires the diagnosis and treatment requirements and basic disease information of the patient through the diagnosis and treatment requirement window, recommends departments and doctors according to feature matching, predicts the diagnosis and treatment time, generates and uploads a diagnosis and treatment record to the cloud, and achieves the effects of accurate recommendation, diagnosis and treatment time prediction, real-time record, cloud storage and the like; meanwhile, hospitals and systems can acquire precious feedback information from the angle of patients, so that medical services are improved, system functions are optimized, and overall medical quality and user satisfaction are improved.
The embodiment relates to a medical service platform based on cloud technology, wherein the record management module comprises:
a first summarizing module: classifying and grading the cases according to the disease types; extracting disease characteristics, generating a disease characteristic library, hiding personal information of patients, performing statistical analysis, and displaying analysis results; providing a plurality of classification modes and carrying out statistical display; comprises classifying according to patient ages to obtain a first classification; infant diseases, childhood diseases, adult diseases, senile diseases, etc., and performing a second classification according to different classification methods under the first classification; according to the diagnosis result of doctors, the diagnosis results are classified according to etiology: diseases can be classified into infectious diseases, hereditary diseases, immunological diseases, metabolic diseases, environmental related diseases, etc. according to the cause and cause of the disease; classification by organ or system: diseases can be classified into cardiovascular diseases, respiratory diseases, digestive diseases, urinary diseases, etc. according to affected organs or systems; classifying according to the development process: diseases can be classified into acute diseases, chronic diseases, recurrent diseases, etc. according to the progress of the diseases; classifying into a normal case, a severe case, a critical case and a rare case under the second classification;
Recording clinical symptoms, medication records and treatment effects of the diseases under the same second classification; medical research can be performed according to the summary record; the doctor logs in through the case summarization port to access and acquire the classification report for research;
and a second summarizing module: summarizing the diagnosis and treatment cases of the same doctor to obtain doctor diagnosis and treatment records; the diagnosis and treatment records of doctors are arranged according to the diagnosis and treatment time, and the diagnosis results are summarized; evaluating the doctor's treatment experience based on the summary results; providing basis for subsequent experience communication;
and a third summarizing module: summarizing the treatment records of the same patient to obtain case summarizing information of the patient;
the summarized information comprises index information and specific information; the specific information comprises specific diagnosis information, examination information and medication records;
establishing index information for the visit record of the same patient, wherein the index information comprises a first index, a second index and a third index;
the first index is the name, sex, date of birth and contact information of the patient; the second index is on-line diagnosis and treatment and off-line diagnosis and treatment; the third index is identity information, diagnosis and treatment departments and diagnosis and treatment time; the identity information comprises identity card or medical insurance card information; the patient can check the own visit record according to the index;
Recording according to the history of the patient; classifying the disease of the patient, the classification comprising a fourth classification, classifying the disease of the patient into a disease free of sensitive information and a disease comprising privacy;
fifth classification of the privacy-containing group of diseases, including acute disease, chronic disease, recurrent disease;
classifying the disease of the patient further comprises a sixth classification of common disease, severe disease, critical disease, rare disease;
the analysis suggestion module: analyzing the diagnosis and treatment record of the patient to obtain an analysis result, and providing personalized medical advice according to the analysis result; comprising the following steps:
the system firstly acquires relevant data from diagnosis and treatment records of patients, including medical history, test results, imaging examination reports and the like; such data may come from a hospital electronic medical record system, laboratory information management system, medical imaging system, etc.;
the collected data is cleaned and preprocessed, including interpolation and smoothing, error or incomplete data are removed, and different data sources are integrated and standardized, so that the consistency and the usability of the data are ensured;
selecting relevant features from the diagnosis and treatment record through a principal component analysis method;
Deep analysis is carried out on diagnosis and treatment records of patients by adopting data analysis and mining technology; for example, applying machine learning algorithms, data mining techniques or artificial intelligence models, pattern recognition, anomaly detection, correlation analysis, etc., to time series data or specific disease data;
identifying potential abnormal data points by comparing the patient diagnosis and treatment record with normal conditions or standard abnormal conditions;
Ei＝(Xi-μ)/(q3-q1)
ei is the offset; xi represents a detection value, mu represents a mean value obtained by the same data history record, and q1 and q3 represent 25% quantiles and 75% quantiles of data respectively; yi when Ei is greater than a threshold value, indicating Xi as a potential outlier data point;
obtaining health evaluation indexes according to the number, the deviation amount and the importance degree of abnormal data points and displaying the health evaluation indexes to a patient; simultaneously, the new diagnosis result is followed by the health index, and the change curve of the health index is recorded;
health assessment indexThe importance of the Zi abnormal data points; n is the number of outlier data points;
for some chronic or progressive diseases, applying a time series analysis method to predict future trend, periodicity and seasonal changes for time series of diagnosis and treatment record data;
According to the result of the data analysis, the system can generate personalized medical analysis reports related to the health state of the patient, the disease risk assessment, the treatment effect prediction and the like; these reports may be in the form of digitized text, charts, images, or visual interfaces;
based on the analysis results, the system may generate personalized medical advice for the physician, including treatment regimens for patient specific disease management, medication advice, healthy lifestyle guidance, and the like; at the same time, the system may also provide relevant educational information and self-administered advice to the patient.
Advice may relate to various aspects of medication, review planning, surgical options, rehabilitation planning, lifestyle changes, etc. to meet the specific needs and conditions of the patient; continuously tracking and updating medical advice according to feedback and treatment effects of the patient; by monitoring the progress and response of the patient, the treatment regimen can be optimized and adjusted to achieve better results.
The working principle of the technical scheme is as follows: classifying and grading cases according to different classification modes, such as age, etiology, organs or systems, development process and the like; extracting disease characteristics to generate a disease characteristic library: critical disease features are extracted from each case and combined into a disease feature library. In order to protect privacy of personal information of patients, statistical analysis is required to be performed after the personal information of the patients is hidden; carrying out statistical analysis on the cases hidden with the personal information, and displaying analysis results, wherein the analysis results possibly comprise statistical data of disease classification, distribution conditions of disease characteristics and the like; providing a plurality of classification modes, such as classification according to age, etiology, organs or systems, development process and the like, and then carrying out statistical display on each classification mode so that doctors and researchers can know the classification and characteristics of the diseases deeply; record clinical symptoms, medication records and treatment effect: clinical symptoms, medication records and treatment effects related to the disease records under the same classification are used for medical research; summarizing the cases of the same doctor, obtaining the diagnosis and treatment record of the doctor, and arranging and summarizing according to the diagnosis and treatment time and the diagnosis result, thereby evaluating the treatment experience of the doctor; and summarizing the visit records of the same patient to obtain the case summarization information of the patient. Establishing index information comprising personal information, on-line or off-line diagnosis and treatment modes, identity information, diagnosis and treatment departments and the like of patients, so that the patients can check own diagnosis records according to the index; matching the history visit record and the illness state information of the patient with the characteristics in the illness state characteristic library, providing personalized medical advice and sending the reminding to the patient; the medical advice is continuously tracked and updated, and the treatment regimen is optimized and adjusted based on the patient's feedback and treatment outcome.
The technical scheme has the effects that: comprehensive case management and analysis functions are provided, so that doctors and researchers are helped to better know the classification, characteristics and treatment effect of the diseases; through statistical analysis and display, the distribution condition, characteristic trend and the like of the diseases can be found, and a basis is provided for medical research; summarizing and evaluating diagnosis and treatment records of doctors, and helping to evaluate the treatment experience of the doctors and improve the medical quality; the patient can conveniently check the own visit records and know the classification and treatment condition of the diseases; by analyzing the patient diagnosis and treatment record to obtain an analysis result, the formula can identify potential abnormal data points by comparing the patient diagnosis and treatment record with normal conditions or standard abnormal conditions. The method is favorable for timely finding out abnormal conditions of patients, provides opportunities for early warning and intervention, and prevents further development of diseases; the mean, 25% quantile and 75% quantile of the same data history were used in the formula as reference statistics. Thus, the detection value of the patient can be compared with the statistical characteristic to accurately judge whether the patient is abnormal or not, and erroneous judgment caused by the individual numerical value is avoided; the formula calculates the health assessment index K through the number of abnormal data points, the deviation amount and the importance degree of the abnormal data points. The index comprehensively considers a plurality of factors of abnormal data points, can provide a comprehensive evaluation result and reflects the overall health state of the patient; and according to the calculated health evaluation index K, the result can be displayed to the patient. Thus, the patient can more intuitively know the health condition of the patient and take corresponding medical measures when necessary. Through the quantified indexes, the patient can intuitively know the health condition of the patient. The evaluation index can comprehensively consider the number, the deviation and the importance degree of the abnormal data points, provide an objective evaluation result, and help a patient to know the overall health state of the patient and whether a potential abnormal condition exists; when a new diagnosis result appears, the health evaluation index is updated. By updating the index, the patient can know the latest health condition and master the health change condition in time; the profile record of the health indicator may provide more detailed information; by recording the change trend of the index, the patient can know the change trend of the health state of the patient, including the trend of improvement or deterioration and possible influencing factors; according to the health evaluation index and the change curve record, a doctor can formulate a personalized health management scheme. For a patient's specific situation, a physician may give corresponding advice, treatment regimens, or health management measures to help the patient improve the health condition and prevent the underlying disease progression.
The personalized medical advice is provided according to the analysis result, and the personalized medical advice and the tracking update can provide a more accurate and effective treatment scheme so as to achieve a better treatment effect.
The medical service platform based on the cloud technology of this embodiment, the look-up module includes:
an encryption module: setting an encryption type storage scheme for patient information; encrypting basic information of a patient and encrypting diagnosis and treatment records; the basic information of the patient comprises the identity information (identity card or medical insurance card), address and contact information of the patient; encrypting the name part of the patient; age and gender are not encrypted;
the classification authority setting module: classifying diagnosis and treatment records of patients according to disease diagnosis results; different inquiry authorities are set according to the classification result;
the classification includes non-sensitive information diseases and diseases including privacy; the disease without sensitive information is that privacy is not included, and the disease can be cured through short-term treatment, such as common cold, diarrhea, skin allergy, appendicitis, common trauma and the like; such diseases including privacy-like diseases include, but are not limited to, various chronic diseases, mental diseases, nodules, cancer, gender-like diseases, and the like;
For diagnosis and treatment records without sensitive information diseases, a patient directly checks own records through login information; the doctor directly checks the acquisition permission of the platform by sending an application to the platform in the period of patient treatment;
a diagnosis and treatment record for diseases including privacy classes; the patient logs in through the login information and checks the diagnosis and treatment record of the patient through the dynamic key or face recognition;
for common diseases comprising diagnosis and treatment records of privacy diseases, a doctor sends an application to a platform through a patient treatment number in a patient treatment period to acquire treatment record permission for checking the patient treatment in a home; in the period of patient treatment, a doctor checks the treatment record of non-home treatment of a patient by sending an application to a platform, and the platform sends the application to a patient or guardian for treatment and obtains the permission of the patient to open the corresponding treatment record after agreeing to the doctor;
for emergency, a special access window is set, diagnosis and treatment records of patients are called through platform authorization, and are recorded, the checking period is in the diagnosis and treatment stage, and the checking time window is not particularly limited; the emergency situation includes a critical patient; the emergency includes severe cases, critical cases, and rare cases.
And (5) checking a setting module: setting a checking period and a checking record time window, and obtaining recommended effective duration through machine learning; the recommended effective duration comprises a first effective duration and a second effective duration, wherein the first effective duration is the duration of a query window of a registered user of a patient port; the second effective duration is the effective duration of the doctor port query; wherein the doctor viewing period is a patient visit and/or treatment period;
and a time length setting module: periodically checking and accessing the setting of the recommended effective duration, and comparing with the actual demand; updating the preset effective duration; the actual requirements comprise the time length requirements fed back by the patient port and the doctor port;
the effective duration of the query after the dynamic key is input and/or after the face recognition is:
the time window for opening the right of the corresponding visit record to the doctor is as follows:
wherein L is the report length in the patient diagnosis record; n the number of reports in a certain diagnosis and treatment record of the patient; l (L) a Average report length for all patients under the same disease classification; n (N) a An average report number for all patients under the same disease classification; j0 is a recommended first effective duration; f is the query times of the account owners of the diagnosis and treatment records of the patient, m is the overtime unremoved times of the query diagnosis and treatment records of the account owners; the same disease is classified into the aforementioned second classification; p is the number of times a doctor inquires about the patient case; q is the number of times the doctor inquires the patient record is overtime and is not withdrawn; c is the score of the authorized inquiring doctor, C a Average scoring for doctors in the same department of the platform; t0 is a recommended second effective duration; beta is an adjustment coefficient; the beta setting rule is that before and after the medical operation, the medical operation is that a bill prescribed by a doctor is used as a standard, and beta is set according to the importance of the medical operation, wherein the importance is an integer of 1-10, and the beta is consistent with the importance;
and a log recording module: a log recording system is established to record all access operations to the data, including inquirer, inquiry time length and inquiry times; alerting an abnormal operation, the abnormal operation comprising: exceeding a set number or frequency of accesses, unauthorized accesses, etc.
The working principle of the technical scheme is as follows: the identity information, address and contact information of the patient, and name portion are stored encrypted, while age and gender are not. This can be achieved by using symmetric or asymmetric encryption algorithms, ensuring that the privacy and sensitive information of the patient is protected; diagnosis and treatment records of patients are classified according to disease diagnosis results, and are classified into common diseases and diseases including privacy. And encrypting and storing diagnosis and treatment records aiming at diseases containing privacy. This may employ a symmetric or asymmetric encryption algorithm to ensure that only authorized personnel can decrypt and view the records; and setting different inquiry authorities according to the grading result. For diagnosis and treatment records of common diseases, a patient can directly log in the system to check own records, and a doctor acquires permission to check by sending an application to a platform; for medical records of diseases containing privacy, the patient needs to be authenticated by login information and dynamic keys or face recognition to view his records. In the patient treatment period, a doctor sends an application to a platform according to the patient treatment number to acquire the viewing authority; the doctor who obtains the authority can only check the doctor's records of the patient, but cannot copy and screen capture; for the visit records of non-home visit, the doctor needs to send an application to the platform, and the platform can send the application to the patient or the guardian, and the permission of the corresponding visit record can be opened to the doctor after the patient agrees. Aiming at emergency, a special access window is set, diagnosis and treatment records of patients are called through platform authorization, and recording is carried out. This ensures that in case of emergency such as critical patients, a doctor can acquire diagnosis and treatment records of the patient in time; and obtaining recommended effective duration according to actual demands of a patient end and a doctor end through machine learning. This includes a first effective duration that is the duration of the patient registration user query window and a second effective duration that is the duration of the doctor query. The doctor's viewing period is the patient's visit and/or treatment period; periodically checking and accessing the setting of the recommended effective duration, comparing with the actual requirement, and updating the preset effective duration according to the feedback and the requirement of the patient end and the doctor end; and establishing a log record system to record all access operations to the data, wherein the access operations comprise inquirers, inquiry time duration and inquiry times. For abnormal operation, such as exceeding the set access times or frequency, unauthorized access and the like, an alarm is sent out and corresponding processing is carried out; through implementation of the technical scheme, the safety and privacy protection of the patient information can be ensured, and only authorized personnel can legally access and use the basic information and diagnosis and treatment record of the patient.
The technical scheme has the effects that: by encrypting the basic information and diagnosis and treatment records of the patient, the privacy of the patient and the safety of personal data are effectively protected, and unauthorized access and leakage risks are avoided; grading diagnosis and treatment records according to disease diagnosis results, setting different inquiry authorities, and only users with corresponding authorities can check related records to ensure that sensitive information is only accessed by authorized personnel; for diagnosis and treatment records of common diseases, patients and doctors can directly check through login information, and the operation is simple and convenient; for diseases containing privacy, a patient needs to log in and carry out identity verification through a dynamic key or face recognition, so that the safety of data is improved; aiming at emergency, a special access window is set, and authorized personnel can timely call the diagnosis and treatment record of a patient when necessary, so that the medical treatment work can be conveniently unfolded; recommending the most suitable query window duration according to feedback of a patient end and a doctor end through a machine learning algorithm, and providing limited access time by limiting the effective duration of query so as to ensure that doctors and other authorized personnel acquire necessary information within a reasonable time range and avoid excessively checking or abusing access rights; limiting the viewing time window can reduce potential risks, reduce the possibility of misuse or leakage of patient information, and enhance data security; the setting of the checking time window can also promote timely decision making and information flow, so that a doctor can quickly acquire and apply key diagnosis and treatment records, thereby improving the medical quality and efficiency; and periodically checking and accessing the setting of the recommended effective duration, comparing with the actual demand, updating the preset effective duration according to feedback, and ensuring the adaptability and optimizability of the system. A complete log recording system is established, all access operations to data are recorded, including inquirers, inquiry time length and inquiry times, abnormal operations can be monitored and alerted in time, and data security protection capability is improved.
In the formula, J1 represents the effective duration of inquiry, and T1 represents a time window for opening the corresponding doctor-seeing record permission to a doctor. These calculations are based on a number of factors, including the report length and number of patient records, the average report length and average report number for all patients under the same disease category, the recommended first effective duration, the number of queries (F) and timeout unretired times for the account owner, the number of times a doctor queries for this patient case and timeout unretired times, the score for the authorized querying doctor, and the average score for the same department doctor for the platform. At the same time, the relation between the adjustment coefficient β and the importance of the medical procedure is also considered. By adjusting these factors, the effective duration of the query and the open time window of the rights can be determined, thereby achieving the following benefits and effects: by reasonably setting the effective duration, the method ensures that enough information is acquired in the query, avoids overlong or excessively short query time and improves the query efficiency; by limiting the inquiry time window, the permission of the corresponding visit record is ensured to be opened to the doctor only in a specific time, potential data leakage and abuse risk are reduced, and privacy safety of a patient is protected; according to diagnosis and treatment record characteristics of a patient and query behaviors of doctors, query time length and permission opening time window are dynamically adjusted, and more personalized and accurate medical services are provided. By reasonably setting the adjustment coefficient beta, the inquiring duration and the permission opening time window are flexibly adjusted according to the importance of medical operation, the medical procedure is optimized, and the medical efficiency is improved.
Through the technical scheme, the safety and privacy protection of the patient information can be effectively guaranteed, the fine authority management and user operation control are realized, and the efficiency and safety of medical data management are improved.
It will be apparent to those skilled in the art that various modifications and variations can be made to the present invention without departing from the spirit or scope of the invention. Thus, it is intended that the present invention also include such modifications and alterations insofar as they come within the scope of the appended claims or the equivalents thereof.
Claims (10)
1. A cloud technology-based medical service method, the method comprising:
s1, acquiring registration and login information of a user through a registration and login port;
s2, acquiring diagnosis and treatment requirements and basic disease information of a patient through a diagnosis and treatment requirement window, recommending a department to visit according to the basic disease information, generating a diagnosis and treatment record, and storing the diagnosis and treatment record to a cloud end in real time;
s3, unified management is carried out on diagnosis and treatment records of patients; classifying and summarizing the diagnosis and treatment records; analyzing the diagnosis and treatment record of the patient to obtain an analysis result, and providing personalized medical advice according to the analysis result;
S4, setting different viewing authorities for the diagnosis and treatment record; and acquiring the check records aiming at the same diagnosis and treatment record in real time, generating a check process record file, and setting check time length aiming at the diagnosis and treatment record.
2. The cloud technology-based medical service method according to claim 1, wherein the S1 includes:
the patient registers through the patient port, wherein the registration comprises the steps of filling in the name, the identification card number, the contact mode, the medical insurance information, the login mode and the password of the patient; the platform authenticates and audits the authentication information, and personal account information is generated after the audit is passed;
a doctor registers through a doctor port, wherein the doctor registration comprises doctor name, qualification and practice information; and accessing a medical institution official network through an API interface, acquiring medical institution information and doctor information, and associating and corresponding the information registered through the doctor port with the information in the medical institution.
3. The cloud technology-based medical service method according to claim 1, wherein the S2 includes:
acquiring diagnosis and treatment requirements and basic disease information of a patient through a diagnosis and treatment requirement window; the diagnosis and treatment requirements comprise on-line diagnosis and treatment and off-line diagnosis and treatment; if the patient selects on-line diagnosis and treatment, recommending according to the on-line doctor scheduling of the corresponding department; if the user selects offline diagnosis and treatment, the user performs reservation recommendation according to offline doctor scheduling of the corresponding department;
Extracting characteristics of patient illness description through basic patient illness state information, matching with class characteristics of departments, and recommending to visit departments and doctors according to matching results;
predicting the specific treatment time of the patient according to the doctor scheduling selected by the patient;
generating diagnosis and treatment records in real time and uploading the diagnosis and treatment records to a cloud end;
and setting an evaluation and feedback window to evaluate and feed back the doctor, the system and the treatment effect.
4. The cloud technology-based medical service method according to claim 1, wherein the S3 includes:
classifying and grading the cases according to the disease types; extracting disease characteristics, generating a disease characteristic library, hiding personal information of patients, performing statistical analysis, and displaying analysis results; providing a plurality of classification modes and carrying out statistical display;
summarizing the diagnosis and treatment cases of the same doctor to obtain doctor diagnosis and treatment records; the diagnosis and treatment records of doctors are arranged according to the diagnosis and treatment time, and the diagnosis results are summarized; evaluating the doctor's treatment experience based on the summary results;
summarizing the treatment records of the same patient to obtain case summarizing information of the patient; the summarized information comprises index information and specific information; the specific information comprises specific diagnosis information, examination information and medication records;
Establishing index information for the visit record of the same patient, wherein the index information comprises a first index, a second index and a third index;
the first index is the name, sex, date of birth, and contact information of the patient; the second index is on-line diagnosis and treatment and off-line diagnosis and treatment; the third index is identity information, diagnosis and treatment departments and diagnosis and treatment time; the identity information comprises identity card or medical insurance card information; the patient can check the own visit record according to the index;
analyzing the diagnosis and treatment record of the patient to obtain an analysis result, and providing personalized medical advice according to the analysis result.
5. The cloud technology-based medical service method according to claim 1, wherein the S4 includes:
setting an encryption type storage scheme for patient information; encrypting basic information of a patient and encrypting diagnosis and treatment records;
classifying diagnosis and treatment records of patients according to disease diagnosis results; different inquiry authorities are set according to the classification result;
the classification includes non-sensitive information diseases and diseases including privacy;
for diagnosis and treatment records without sensitive information diseases, a patient directly checks own records through login information; the doctor directly checks the acquisition permission of the platform by sending an application to the platform in the period of patient treatment;
A diagnosis and treatment record for diseases including privacy classes; the patient logs in through the login information and checks the diagnosis and treatment record of the patient through the dynamic key or face recognition;
for common diseases comprising diagnosis and treatment records of privacy diseases, a doctor sends an application to a platform through a patient treatment number in a patient treatment period to acquire treatment record permission for checking the patient treatment in a home; in the period of patient treatment, a doctor checks the treatment record of non-home treatment of a patient by sending an application to a platform, and the platform sends the application to a patient or guardian for treatment and obtains the permission of the patient to open the corresponding treatment record after agreeing to the doctor;
for emergency, a special access window is set, diagnosis and treatment records of patients are called through platform authorization, and the records are carried out; the emergency situation includes a critical patient;
setting a checking period and a checking record time window, and obtaining recommended effective duration through machine learning; the recommended effective duration comprises a first effective duration and a second effective duration, wherein the first effective duration is the duration of a query window of a registered user of a patient port; the second effective duration is the effective duration of the doctor port query; wherein the doctor viewing period is a patient visit and/or treatment period;
Periodically checking and accessing the setting of the recommended effective duration, and comparing with the actual demand; updating the preset effective duration; the actual requirements comprise the time length requirements fed back by the patient port and the doctor port;
a log recording system is established to record all access operations to the data, including inquirer, inquiry time length and inquiry times; an alarm is given for the abnormal operation.
6. A cloud technology-based medical service platform, the platform comprising:
registration and login module: acquiring registration and login information of a user through a registration and login port;
diagnosis and treatment module: acquiring diagnosis and treatment requirements and basic disease information of a patient through a diagnosis and treatment requirement window, recommending a department to visit according to the basic disease information, generating a diagnosis and treatment record and storing the diagnosis and treatment record to a cloud in real time;
and a record management module: unified management is carried out on diagnosis and treatment records of patients; classifying and summarizing the diagnosis and treatment records; analyzing the diagnosis and treatment record of the patient, and providing personalized medical advice according to the analysis result;
and a viewing module: setting different viewing rights for the diagnosis and treatment record; acquiring a check record aiming at the same diagnosis and treatment record in real time, and generating a check process record file; and setting the checking time length for the diagnosis and treatment record.
7. The cloud-based healthcare platform of claim 6, wherein said registration and login module comprises:
patient port: the patient registers through the patient port, wherein the registration comprises the steps of filling in the name, the identification card number, the contact mode, the medical insurance information, the login mode and the password of the patient; the platform authenticates and audits the authentication information, and personal account information is generated after the audit is passed;
doctor port: a doctor registers through a doctor port, wherein the doctor registration comprises doctor name, qualification and practice information; and accessing a medical institution official network through an API interface, acquiring medical institution information and doctor information, and associating and corresponding the information registered through the doctor port with the information in the medical institution.
8. The cloud-based healthcare platform of claim 6, wherein the diagnosis and treatment module comprises:
diagnosis and treatment demand module: acquiring diagnosis and treatment requirements and basic disease information of a patient through a diagnosis and treatment requirement window; the diagnosis and treatment requirements comprise on-line diagnosis and treatment and off-line diagnosis and treatment; if the patient selects on-line diagnosis and treatment, recommending according to the on-line doctor scheduling of the corresponding department; if the user selects offline diagnosis and treatment, the user performs reservation recommendation according to offline doctor scheduling of the corresponding department;
And a recommendation module: extracting characteristics of patient illness description through basic patient illness state information, matching with class characteristics of departments, and recommending to visit departments and doctors according to matching results;
and a prediction module: predicting the specific treatment time of the patient according to the schedule of the doctor selected by the patient;
diagnosis and treatment record generation module: generating diagnosis and treatment records in real time and uploading the diagnosis and treatment records to a cloud end;
and an evaluation feedback module: and setting an evaluation and feedback window to evaluate and feed back the doctor, the system and the treatment effect.
9. The cloud-based healthcare platform of claim 6, wherein the record management module comprises:
a first summarizing module: classifying and grading the cases according to the disease types; extracting disease characteristics, generating a disease characteristic library, hiding personal information of patients, performing statistical analysis, and displaying analysis results; providing a plurality of classification modes and carrying out statistical display;
and a second summarizing module: summarizing the diagnosis and treatment cases of the same doctor to obtain doctor diagnosis and treatment records; the diagnosis and treatment records of doctors are arranged according to the diagnosis and treatment time, and the diagnosis results are summarized; evaluating the doctor's treatment experience based on the summary results;
And a third summarizing module: summarizing the treatment records of the same patient to obtain case summarizing information of the patient; the summarized information comprises index information and specific information; the specific information comprises specific diagnosis information, examination information and medication records;
establishing index information for the visit record of the same patient, wherein the index information comprises a first index, a second index and a third index;
the first index is the name, sex, date of birth, and contact information of the patient; the second index is on-line diagnosis and treatment and off-line diagnosis and treatment; the third index is identity information, diagnosis and treatment departments and diagnosis and treatment time; the identity information comprises identity card or medical insurance card information; the patient can check the own visit record according to the index;
the analysis suggestion module: analyzing the diagnosis and treatment record of the patient to obtain an analysis result, and providing personalized medical advice according to the analysis result.
10. The cloud-based healthcare platform of claim 5, wherein the viewing module comprises:
an encryption module: setting an encryption type storage scheme for patient information; encrypting basic information of a patient and encrypting diagnosis and treatment records;
The classification authority setting module: classifying diagnosis and treatment records of patients according to disease diagnosis results; different inquiry authorities are set according to the classification result;
the classification includes non-sensitive information diseases and diseases including privacy;
for diagnosis and treatment records without sensitive information diseases, a patient directly checks own records through login information; the doctor directly checks the acquisition permission of the platform by sending an application to the platform in the period of patient treatment;
a diagnosis and treatment record for diseases including privacy classes; the patient logs in through the login information and checks the diagnosis and treatment record of the patient through the dynamic key or face recognition;
for common diseases comprising diagnosis and treatment records of privacy diseases, a doctor sends an application to a platform through a patient treatment number in a patient treatment period to acquire treatment record permission for checking the patient treatment in a home; in the period of patient treatment, a doctor checks the treatment record of non-home treatment of a patient by sending an application to a platform, and the platform sends the application to a patient or guardian for treatment and obtains the permission of the patient to open the corresponding treatment record after agreeing to the doctor;
for emergency, a special access window is set, diagnosis and treatment records of patients are called through platform authorization, and the records are carried out; the emergency situation includes a critical patient;
And (5) checking a setting module: setting a checking period and a checking record time window, and obtaining recommended effective duration through machine learning; the recommended effective duration comprises a first effective duration and a second effective duration, wherein the first effective duration is the duration of a query window of a registered user of a patient port; the second effective duration is the effective duration of the doctor port query; wherein the doctor viewing period is a patient visit and/or treatment period;
and a time length setting module: periodically checking and accessing the setting of the recommended effective duration, and comparing with the actual demand; updating the preset effective duration; the actual requirements comprise the time length requirements fed back by the patient port and the doctor port;
and a log recording module: a log recording system is established to record all access operations to the data, including inquirer, inquiry time length and inquiry times; an alarm is given for the abnormal operation.
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| CN117831731A (en) * | 2024-03-04 | 2024-04-05 | 泛喜健康科技有限公司 | Online intelligent propulsion system of hospital based on artificial intelligence |
| CN117831731B (en) * | 2024-03-04 | 2024-05-28 | 泛喜健康科技有限公司 | Online intelligent propulsion system of hospital based on artificial intelligence |
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