CN117219243A - Cardiovascular disease assessment and management system - Google Patents
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Abstract
The application discloses a cardiovascular disease evaluation and management system, which relates to the technical field of management systems, and comprises a diagnosis judging module, a diagnosis prompting module, a diagnosis recommending module and a terminal device, wherein the diagnosis judging module is used for judging whether a patient needs to make a diagnosis after analyzing patient data, when judging that the patient needs to make a diagnosis, the terminal device is used for sending a diagnosis prompt to the patient, and when the patient needs to make a diagnosis, the recommending module is awakened, after acquiring a plurality of data of cardiovascular internal medicine of a plurality of hospitals, the recommending module is used for generating diagnosis recommending values for the plurality of hospitals, and after sequencing the plurality of hospitals according to the diagnosis recommending values, the sequencing result is sent to the patient through the terminal device, and the bigger the diagnosis recommending value is, the more suitable the hospital for the patient to make a diagnosis, and the recommending index is higher. The management system can effectively remind the patient to make a diagnosis in time and improve the diagnosis efficiency and effect of the patient.
Description
Technical Field
The application relates to the technical field of management systems, in particular to a cardiovascular disease assessment and management system.
Background
Cardiovascular disease (CVD) including hypertension, coronary heart disease, stroke and other cardiovascular diseases, which cause death and long-term chronic health problems in millions of people, is one of the major health problems worldwide, and the occurrence and development of cardiovascular disease is often associated with a variety of risk factors including hypertension, high cholesterol, smoking, unhealthy diet, lack of exercise, obesity, diabetes, genetic factors, age and sex, etc., which can interact, increasing the risk of cardiovascular disease.
The prior art has the following defects:
the existing management system usually only prompts the patient to visit according to a specified period, however, when the body of the patient is abnormal, the management system does not prompt, so that the patient is not in time to visit, and when the patient needs to visit, the management system does not comprehensively evaluate treatment to the hospital to visit, and the patient cannot know which hospital is more suitable for the treatment, so that the treatment efficiency and the treatment effect of the patient are affected.
Disclosure of Invention
The application aims to provide a cardiovascular disease assessment and management system which aims to solve the defects in the background technology.
In order to achieve the above object, the present application provides the following technical solutions: a cardiovascular disease assessment and management system comprises a drug management module, an information management module, a diagnosis judgment module, a recommendation module, a diagnosis recording module and a reporting module:
the medicine management module: recording the prescribed and over-the-counter drug amounts of the patient, providing medication instructions, and generating a drug plan;
and an information management module: storing data relating to the patient;
the diagnosis judging module is used for: after analyzing the patient data, judging whether the patient needs to make a diagnosis, when judging that the patient needs to make a diagnosis, sending a diagnosis prompt to the patient through the terminal equipment, and waking up the recommendation module when the patient needs to make a diagnosis;
and a recommendation module: after acquiring a plurality of pieces of data of cardiovascular internal medicine of a plurality of hospitals, generating diagnosis recommended values for the plurality of hospitals, sequencing the plurality of hospitals according to the diagnosis recommended values, and sending sequencing results to a patient through terminal equipment;
the diagnosis recording module: for recording patient visit data;
and a reporting module: for generating a health report of the patient.
Preferably, the diagnosis judgment module calculates the last diagnosis time index, heart rate abnormality index and respiratory frequency fluctuation amplitude to obtain the diagnosis coefficient jz x The expression is:
jz x ＝jl s +jl s (a 1 yc x +a 2 hx b )；
in the formula jl s For the last visit time index, yc x Hx is the heart rate abnormality index b For amplitude of respiratory rate fluctuation, a 1 、a 2 Proportional coefficients of heart rate abnormality index and respiratory rate fluctuation amplitude, respectively, and a 1 、a 2 Are all greater than 0.
Preferably, if the diagnosis factor jz x The patient diagnosis judgment module judges that the patient needs to be diagnosed, sends a diagnosis prompt to the patient through the terminal equipment, and if the diagnosis coefficient jz is not less than the diagnosis threshold value x The diagnosis judgment module judges that the patient does not need to visit the diagnosis.
Preferably, the recommendation module comprehensively calculates the distance index, the department operation index, the average treatment efficiency of the department, and the number of people waiting for treatment in the department to obtain the treatment recommendation value tj z The expression is:
in the middle of，ks y To the department operation index, jz x For average diagnosis efficiency in departments, yh z Is distance index, dj r For the patients waiting for the doctor in the department, alpha, beta and gamma are the average doctor efficiency, the distance index and the proportionality coefficient of the patients waiting for the doctor in the department, and the alpha, beta and gamma are all more than 0.
Preferably, the recommendation module obtains a visit recommendation tj z Then, the hospital recommends a value tj according to the visit z And sequencing from big to small, and sending sequencing results to a patient through terminal equipment.
Preferably, the calculation expression of the average diagnosis efficiency of the department is as follows:
where a= {0,1,2,..b }, b is the number of patients visited on the day of the department, xl a Indicating the speed of the visit for patient a.
Preferably, the calculation expression of the heart rate abnormality index is:
where i= {1, 2, 3,..n }, n represents the number of records of data points, n is a positive integer, X i Representing the time difference between adjacent heart beats at the ith data point,mean value of heart beat interval and heart rate abnormality index yc x The greater the fluctuation in heart rate of the patient, the more abnormality is indicated.
8. The cardiovascular disease assessment and management system of claim 2, wherein: the calculation expression of the respiratory frequency fluctuation amplitude is as follows:
in the formula, h s Respiratory rate, h, for real-time monitoring min ～h max Is a stable range of respiratory frequencies.
Preferably, the logic for acquiring the time index of the last visit from the distance is: if the time limit number of the follow-up is greater than 1 day, the previous visit time index jl s When the number of days from the review time is 1 day or less, the last visit time index jl s ＝2。
Preferably, the logic for obtaining the department operation index is: if the cardiovascular department of the hospital runs on the same day, ks y =1, if the cardiovascular department of the hospital is not running on the same day, ks y ＝0。
In the technical scheme, the application has the technical effects and advantages that:
1. according to the application, after the patient data is analyzed by the diagnosis judging module, whether the patient needs to be diagnosed is judged, when the patient needs to be diagnosed, the diagnosis prompt is sent to the patient through the terminal equipment, and when the patient needs to be diagnosed, the recommending module is awakened, after the recommending module acquires a plurality of items of data of cardiovascular internal medicine of a plurality of hospitals, diagnosis recommending values are generated for the plurality of hospitals, after the plurality of hospitals are ordered according to the diagnosis recommending values, the ordering result is sent to the patient through the terminal equipment, the bigger the diagnosis recommending value is, the more suitable the hospital is for the patient to visit, the recommendation index is higher, and the managing system can effectively remind the patient to visit in time, and improves the diagnosis efficiency and effect of the patient.
Drawings
In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for the embodiments will be briefly described below, and it is apparent that the drawings in the following description are only some embodiments described in the present application, and other drawings may be obtained according to these drawings for a person having ordinary skill in the art.
FIG. 1 is a block diagram of a system according to the present application.
Detailed Description
For the purpose of making the objects, technical solutions and advantages of the embodiments of the present application more apparent, the technical solutions of the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present application, and it is apparent that the described embodiments are some embodiments of the present application, but not all embodiments of the present application. All other embodiments, which can be made by those skilled in the art based on the embodiments of the application without making any inventive effort, are intended to be within the scope of the application.
Example 1: referring to fig. 1, the cardiovascular disease evaluation and management system of the present embodiment includes a drug management module, an information management module, a diagnosis judgment module, a recommendation module, a diagnosis recording module, and a report module:
A. the medicine management module: the system is used for managing the medication of a patient, can record the prescription medication quantity and the non-prescription medication quantity of the patient, provide medication guidance and generate a medication plan, and can also send out a reminder to ensure that the patient takes the medication on time, and the medication data of the patient is sent to the information management module;
patient information input: entering basic information of a patient into a system, wherein the basic information comprises names, contact information, birthdays, sexes and possible allergic information and drug sensitivity;
prescription management: recording detailed information of prescription drugs and non-prescription drugs prescribed by doctors; the information for each drug should include drug name, dosage, frequency of use, instructions for use, and date of start of the drug;
medication inventory management: tracking a current inventory of medications for the patient; this ensures that the patient does not lack or have excess medication, thereby avoiding medication disruption or waste;
drug administration guidance: providing medication instructions for each medicament, including administration time, administration mode (such as oral administration, injection, etc.), whether the medicament needs to be taken along with meals, etc.; this can help the patient take the medicine correctly;
generating a medication plan: the system can automatically generate a drug schedule of the patient, and details the drugs and time required to be taken every day; this may be presented to the patient in the form of a form, calendar, or reminder notification;
reminding service: setting a medicine reminding service to ensure that a patient takes medicine on time; the reminding can be sent to the patient through short messages, emails, mobile phone application program notifications or telephone reminding and the like;
drug interaction examination: the system should be able to check if there is a potential interaction between the different drugs taken by the patient; if there is a risk, the system may provide a warning and advise the healthcare professional to make the adjustment;
and (3) monitoring the drug effect: tracking the medication effect of a patient, including monitoring physiological parameters (e.g., blood pressure, heart rate, blood glucose level, etc.) and side effects of the medication; this can help medical professionals assess the effectiveness of treatment and adjust medication therapy plans;
drug history: maintaining a medication history of the patient, including previously used medications, reasons for the medication change, and events and responses during treatment;
drug information review: providing medical professionals and patients with access to medication information, including medication instructions, side effect information, and warnings.
B. And an information management module: for storing patient-related data, including name, contact, emergency contacts, and medical insurance information, patient medication data and patient treatment data are also provided, and the patient data are sent to a treatment judgment module and a report module;
patient information input: entering basic information of a patient into a system, wherein the basic information comprises names, birthdays, sexes, addresses, contact phones, email addresses and the like; ensuring the accuracy of such information for effective contact with the patient;
emergency contact information: recording emergency contact information of a patient, including names, telephone numbers and relations; this is very important for contacting a family or emergency contacts in an emergency situation;
medical insurance information: recording medical insurance information of a patient, including insurance company names, insurance policy numbers, validity periods and the like; this helps manage medical costs and claims;
and (3) medication data management: logging data related to the medication of the patient into the system; this includes prescription drugs, over-the-counter drugs, dosages, usage, time of administration, start date and end date information; ensuring that the data are updated in time;
and (3) treatment data management: recording patient visit data, including medical history, disease diagnosis, medical examination results, surgical history, treatment plans, and the like; this helps the medical professional to understand the patient's condition and treatment history to make better decisions;
privacy and security: the sensitive information of the patient is ensured to be properly protected, and the privacy regulation and medical confidentiality requirements are met; implementing appropriate security measures to prevent unauthorized access or data leakage;
data update and maintenance: patient information is updated periodically to ensure accuracy of the data; in addition, patient information is maintained, including data backup, storage and recovery policies, to prevent data loss;
data access rights: ensuring that only authorized medical professionals and staff can access the patient's information; implementing proper authority control and identity verification measures;
data sharing: allowing a legally authorized medical institution or medical professional to access and share patient information, if needed, for cooperative treatment;
communication and notification: ensure that the system is able to communicate and notify effectively with patients, medical professionals, and other interested parties, including appointment confirmations, reminders, and emergency notifications.
C. The diagnosis judging module is used for: after analyzing the patient data, judging whether the patient needs to make a diagnosis, when judging that the patient needs to make a diagnosis, sending a diagnosis prompt to the patient through the terminal equipment, and waking up the recommendation module when the patient needs to make a diagnosis.
D. And a recommendation module: after acquiring a plurality of pieces of data of cardiovascular internal medicine of a plurality of hospitals, generating diagnosis recommendation values for the plurality of hospitals, sequencing the plurality of hospitals according to the diagnosis recommendation values, and then sending sequencing results to patients through terminal equipment, wherein the larger the diagnosis recommendation values are, the more suitable the hospitals are for the patients to visit, the higher the recommendation index is, and the diagnosis efficiency and effect of the patients can be improved.
E. The diagnosis recording module: the system comprises an information management module, a diagnosis data acquisition module, a diagnosis data storage module and a diagnosis data storage module, wherein the information management module is used for storing diagnosis data of a patient;
and (3) entering diagnosis data: the medical professional enters relevant data into the diagnosis recording module when the patient makes a diagnosis; such data includes medical history, symptoms, physical examination results, laboratory examination results, medical images (such as X-ray or ultrasound images), diagnostic information, treatment plans, prescribed medications, and the like;
data normalization: ensuring that the entered data conforms to standardized medical terms and coding systems for subsequent data analysis and sharing;
follow-up records: recording each patient's follow-up condition, including progress of treatment, patient's response, changes in physiological parameters, etc.; this helps the medical professional track the patient's condition and the effect of the treatment;
and (3) image management: correlating medical image data (e.g., MRI, CT scan, cardiac ultrasound, etc.) with a patient's visit record; this allows doctors to view and compare images at different time points at any time to make diagnosis and treatment decisions;
diagnosis and treatment plan records: recording doctor diagnosis and treatment plans for the patient, including recommended treatment methods, surgical plans, drug prescriptions, and rehabilitation recommendations;
data validation and review: after the data is input, data verification and examination are carried out to ensure the accuracy and the integrity of the data; this helps to reduce errors and inconsistencies;
data transmission to the information management module: transmitting the entered visit data to an information management module to update the patient's medical records and history; this ensures centralized storage and easy access of the data;
privacy and security: appropriate security measures are taken to protect the privacy and data security of the patient; only authorized medical professionals can access and modify the visit record;
data sharing: the legally authorized medical institutions or medical professionals are allowed to access and share patient records of visits to assist in diagnosis and treatment, as needed.
F. And a reporting module: generating a health report of the patient, including disease status, treatment progress, and the like;
and (3) data retrieval: retrieving data relating to the health status and treatment history of the patient from the information management module and the visit record module; this includes disease diagnosis, medical imaging, laboratory examination results, medication records, diagnostic procedures, etc.;
data integration: integrating the retrieved data into a unified report, ensuring that all necessary information is contained; this may involve data cleansing, formatting, and conversion;
report generation: generating a health report from the integrated data using the appropriate templates and report generating tools; the report should include clear title, patient name, date, doctor information, and main content;
summary of disease states: providing a summary of the patient's disease state, including a summary of the current diagnosis, severity of the condition, any associated symptoms or discomfort, and treatment plan;
treatment progress: recording the patient's treatment progress, including current treatment regimen, medication dose, medication response, and any treatment plan modifications;
laboratory and inspection results: including recent laboratory tests and medical imaging results such as blood tests, electrocardiography, ultrasound tests, etc.; this helps doctors and patients to understand the physiological condition of the disease;
and (3) drug administration record: providing a current medication record including medication name, dosage, usage, and frequency of administration; information of any adverse drug reactions or side effects may also be included;
physician orders and advice: providing the patient with doctor advice and treatment plans, including lifestyle advice, diet advice, exercise plans, etc.;
follow-up plan: the time and place of the next follow-up or examination is suggested to ensure that the patient continues to receive the necessary medical care;
report review: medical professionals should carefully examine the report to ensure that the information is accurate and complete and accords with clinical practice;
report publishing and sharing: sending the generated statement-of-health to the patient, typically in the form of an email, a patient portal, or a paper report; at the same time, reports are shared to other medical professionals to coordinate care and treatment;
data security: ensuring that the generated report is properly protected and meets the requirements of privacy regulations and medical confidentiality; only authorized personnel can access and view these reports.
According to the application, after the patient data is analyzed by the diagnosis judging module, whether the patient needs to be diagnosed is judged, when the patient needs to be diagnosed, the diagnosis prompt is sent to the patient through the terminal equipment, and when the patient needs to be diagnosed, the recommending module is awakened, after the recommending module acquires a plurality of items of data of cardiovascular internal medicine of a plurality of hospitals, diagnosis recommending values are generated for the plurality of hospitals, after the plurality of hospitals are ordered according to the diagnosis recommending values, the ordering result is sent to the patient through the terminal equipment, the bigger the diagnosis recommending value is, the more suitable the hospital is for the patient to visit, the recommendation index is higher, and the managing system can effectively remind the patient to visit in time, and improves the diagnosis efficiency and effect of the patient.
Example 2: after analyzing the patient data, the diagnosis judging module judges whether the patient needs to make a diagnosis, and when judging that the patient needs to make a diagnosis, the diagnosis judging module sends a diagnosis prompt to the patient through the terminal equipment and wakes up the recommending module when the patient needs to make a diagnosis;
wherein:
the diagnosis judging module analyzes patient data, wherein the patient data comprises a time index of the last diagnosis, a heart rate abnormality index and a respiratory frequency fluctuation amplitude;
the diagnosis judgment module comprehensively calculates the last diagnosis time index, heart rate abnormality index and respiratory frequency fluctuation amplitude to obtain a diagnosis coefficient jz x The expression is:
jz x ＝jl s +jl s (a 1 yc x +a 2 hx b )；
in the formula jl s For the last visit time index, yc x Hx is the heart rate abnormality index b For amplitude of respiratory rate fluctuation, a 1 、a 2 Proportional coefficients of heart rate abnormality index and respiratory rate fluctuation amplitude, respectively, and a 1 、a 2 Are all greater than 0.
From the diagnosis coefficient jz x From the calculated expression of (a), the diagnosis coefficient jz x The larger the value, the more the patient needs to visit, therefore, if the visit coefficient jz x The patient diagnosis judgment module judges that the patient needs to be diagnosed, sends a diagnosis prompt to the patient through the terminal equipment, and if the diagnosis coefficient jz is not less than the diagnosis threshold value x The diagnosis judgment module judges that the patient does not need to visit the diagnosis.
The logic for acquiring the last visit time index is as follows: when the previous visit of the patient is completed, the hospital generates the next review time limit for the patient, and if the number of days from the review time limit is more than 1 day, the previous visit time index jl is calculated s When the number of days from the review time is 1 day or less, the last visit time index jl s ＝2。
The heart rate abnormality index acquisition logic is: first, the heart beat intervals (in milliseconds) over a period of time are recorded, these intervals are the time differences between adjacent heart beats, which can be obtained from electrocardiogram data or heart rate monitoring equipment, the average of these heart beat intervals (average heart beat interval, NN average) is calculated, the difference between each heart beat interval and the average heart beat interval is calculated, then the square of these differences is calculated, the average of these squared differences is calculated, finally, the square root of this average is taken to obtain the standard deviation, i.e. a measure of HRV, the calculation expression is:
where i= {1, 2, 3,..n }, n represents the number of records of data points, n is a positive integer, X i Representing the distance between adjacent heartbeats at the ith data pointThe difference in time between the two times is,mean value of heart beat interval and heart rate abnormality index yc x The greater the fluctuation in heart rate of the patient, the more abnormality is indicated.
The calculated expression of the respiratory frequency fluctuation amplitude is:
in the formula, h s Respiratory rate, h, for real-time monitoring min ～h max For the respiratory rate stability range, the larger the respiratory rate fluctuation amplitude is, the more the respiratory rate monitored in real time deviates from the respiratory rate stability range, the more the patient is abnormal.
After the recommendation module acquires a plurality of items of data of cardiovascular internal medicine of a plurality of hospitals, a diagnosis recommendation value is generated for the plurality of hospitals, and the plurality of hospitals are ranked according to the diagnosis recommendation value.
The recommendation module acquires a plurality of pieces of data of cardiovascular internal medicine of a plurality of hospitals, wherein the plurality of pieces of data comprise distance indexes, department operation indexes, average department treatment efficiency and the number of people waiting for treatment in the department;
the recommendation module comprehensively calculates the distance index, the department operation index, the average treatment efficiency of the department and the number of people waiting for treatment in the department to obtain a treatment recommendation value tj z The expression is:
wherein ks is y To the department operation index, jz x For average diagnosis efficiency in departments, yh z Is distance index, dj r For the patients waiting for the doctor in the department, alpha, beta and gamma are the average doctor efficiency, the distance index and the proportionality coefficient of the patients waiting for the doctor in the department, and the alpha, beta and gamma are all more than 0.
Acquiring a recommended diagnosis value tj z Later, the patient is in the cityIs based on the recommended value tj of the medical treatment of the patient in the cardiovascular department z After the sorting is sequentially performed from large to small, the sorting result is sent to the patient through the terminal equipment, and the bigger the diagnosis recommendation value is, the more suitable the hospital is for the patient to visit, the higher the recommendation index is, and the diagnosis efficiency and effect of the patient can be improved.
In the application, the following components are added:
the acquisition logic of the department operation index is as follows: if the cardiovascular department of the hospital runs on the same day, ks y =1, if the cardiovascular department of the hospital is not running on the same day, ks y =0, i.e. when the cardiovascular department is not running on the day of the hospital, the hospital is not selected.
The calculation expression of the average treatment efficiency of the department is as follows:
where a= {0,1,2,..b }, b is the number of patients visited on the day of the department, xl a The higher the average treatment efficiency of the department, the better the treatment efficiency of the cardiovascular department of the hospital, the more worth recommending.
The distance index acquisition logic is as follows: obtaining the distance between the address of the patient and the hospital through navigation software, and obtaining a distance index yh z For the distance between the patient's address and the hospital, a hospital with a short distance to the patient is recommended preferentially.
The number dj of waiting for consultation in department r The more patients waiting for a doctor in a department are acquired through a queuing system of a hospital, the longer the patient needs to wait in a queuing way when arriving at a cardiovascular department of the hospital, so that recommendation is not performed.
The above formulas are all formulas with dimensions removed and numerical values calculated, the formulas are formulas with a large amount of data collected for software simulation to obtain the latest real situation, and preset parameters in the formulas are set by those skilled in the art according to the actual situation.
In the description of the present specification, the descriptions of the terms "one embodiment," "example," "specific example," and the like, mean that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the present application. In this specification, schematic representations of the above terms do not necessarily refer to the same embodiments or examples. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples.
The preferred embodiments of the application disclosed above are intended only to assist in the explanation of the application. The preferred embodiments are not intended to be exhaustive or to limit the application to the precise form disclosed. Obviously, many modifications and variations are possible in light of the above teaching. The embodiments were chosen and described in order to best explain the principles of the application and the practical application, to thereby enable others skilled in the art to best understand and utilize the application. The application is limited only by the claims and the full scope and equivalents thereof.
Claims (10)
1. A cardiovascular disease assessment and management system, characterized by: the system comprises a medicine management module, an information management module, a diagnosis judgment module, a recommendation module, a diagnosis recording module and a reporting module:
the medicine management module: recording the prescribed and over-the-counter drug amounts of the patient, providing medication instructions, and generating a drug plan;
and an information management module: storing data relating to the patient;
the diagnosis judging module is used for: after analyzing the patient data, judging whether the patient needs to make a diagnosis, when judging that the patient needs to make a diagnosis, sending a diagnosis prompt to the patient through the terminal equipment, and waking up the recommendation module when the patient needs to make a diagnosis;
and a recommendation module: after acquiring a plurality of pieces of data of cardiovascular internal medicine of a plurality of hospitals, generating diagnosis recommended values for the plurality of hospitals, sequencing the plurality of hospitals according to the diagnosis recommended values, and sending sequencing results to a patient through terminal equipment;
the diagnosis recording module: for recording patient visit data;
and a reporting module: for generating a health report of the patient.
2. The cardiovascular disease assessment and management system of claim 1, wherein: the diagnosis judgment module comprehensively calculates the last diagnosis time index, the heart rate abnormality index and the respiratory frequency fluctuation amplitude to obtain a diagnosis coefficient jz x The expression is:
jz x ＝jl s +jl s (a 1 yc x +a 2 hx b )；
in the formula jl s For the last visit time index, yc x Hx is the heart rate abnormality index b For amplitude of respiratory rate fluctuation, a 1 、a 2 Proportional coefficients of heart rate abnormality index and respiratory rate fluctuation amplitude, respectively, and a 1 、a 2 Are all greater than 0.
3. The cardiovascular disease assessment and management system of claim 2, wherein: if the diagnosis coefficient jz x The patient diagnosis judgment module judges that the patient needs to be diagnosed, sends a diagnosis prompt to the patient through the terminal equipment, and if the diagnosis coefficient jz is not less than the diagnosis threshold value x The diagnosis judgment module judges that the patient does not need to visit the diagnosis.
4. A cardiovascular disease assessment and management system according to claim 3, wherein: the recommendation module comprehensively calculates and obtains a diagnosis recommendation value tj from the distance index, the department operation index, the average diagnosis efficiency of the department and the number of people waiting for the diagnosis of the department z The expression is:
wherein ks is y To the department operation index, jz x For average diagnosis efficiency in departments, yh z Is distance index, dj r For the patients waiting for the consultation in the department,alpha, beta and gamma are respectively proportional coefficients of average treatment efficiency, distance index and the number of patients waiting for treatment in the department, and the alpha, beta and gamma are all larger than 0.
5. The cardiovascular disease assessment and management system according to claim 4, wherein: the recommendation module obtains a diagnosis recommendation value tj z Then, the hospital recommends a value tj according to the visit z And sequencing from big to small, and sending sequencing results to a patient through terminal equipment.
6. The cardiovascular disease assessment and management system according to claim 4, wherein: the calculation expression of the average diagnosis efficiency of the department is as follows:
where a= {0,1,2,..b }, b is the number of patients visited on the day of the department, xl a Indicating the speed of the visit for patient a.
7. The cardiovascular disease assessment and management system of claim 2, wherein: the calculation expression of the heart rate abnormality index is as follows:
where i= {1, 2, 3,..n }, n represents the number of records of data points, n is a positive integer, X i Representing the time difference between adjacent heart beats at the ith data point,mean value of heart beat interval and heart rate abnormality index yc x The greater the fluctuation in heart rate of the patient, the more abnormality is indicated.
8. The cardiovascular disease assessment and management system of claim 2, wherein: the calculation expression of the respiratory frequency fluctuation amplitude is as follows:
in the formula, h s Respiratory rate, h, for real-time monitoring min ～h max Is a stable range of respiratory frequencies.
9. The cardiovascular disease assessment and management system of claim 2, wherein: the logic for acquiring the time index of the last visit from the distance is as follows: if the time limit number of the follow-up is greater than 1 day, the previous visit time index jl s When the number of days from the review time is 1 day or less, the last visit time index jl s ＝2。
10. The cardiovascular disease assessment and management system according to claim 4, wherein: the acquisition logic of the department operation index is as follows: if the cardiovascular department of the hospital runs on the same day, ks y =1, if the cardiovascular department of the hospital is not running on the same day, ks y ＝0。
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| CN117409942B (en) * | 2023-12-14 | 2024-03-08 | 山东新时代药业有限公司 | Intelligent medical information management method and system |
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