Closed-loop management system for chronic diseases

Abstract

The invention relates to the technical field of chronic disease tracking management, in particular to a chronic disease closed-loop management system, which comprises a data acquisition module; a data analysis module; a filing module; a referral analysis module; a team building module; an adjusting module; according to the method, the health condition of the patient is preliminarily analyzed based on the mercury column height measured by the blood pressure of the patient, and the health condition of the patient is further analyzed based on the data change trend in the historical data of the patient, so that misjudgment caused by high blood pressure measured at a time due to equipment problems is avoided; when the health condition of the patient is judged to be unqualified, whether the patient is referred is analyzed based on the screening hierarchy, and when the first examination is common examination, referral further examination is carried out, so that misjudgment caused by factors such as environment is avoided, the analysis accuracy of the health condition of the patient is improved, and the accuracy of health condition analysis is improved. When the health state of the patient is judged to be unqualified, a management team is established, so that the patient can perform nearby revisit, and the reasonable utilization degree of medical resources is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of chronic disease tracking and management, and in particular to a chronic disease closed-loop management system. Background Art

[0002] Closed-loop management of chronic diseases is a comprehensive management model that aims to improve the health management level and quality of life of patients with chronic diseases through full-process and comprehensive management measures. Closed-loop management establishes an effective communication and information sharing mechanism between doctors and patients, and realizes the collaborative cooperation between doctors, patients and other medical institutions, thereby achieving full-process management and personalized treatment of chronic diseases. Existing technologies guide the prevention and treatment of chronic diseases through sports tracking monitoring, health information push, etc. Chinese patent application number: CN201510764597.1 discloses a chronic disease tracking management system based on a mobile terminal and a closed-loop guidance method thereof, which is characterized by comprising: a chronic disease tracking management mobile terminal device composed of a registration unit, a questionnaire unit, a sports tracking monitoring unit, a health information push unit and a prescription communication unit, a chronic disease tracking remote service platform composed of a sports prescription generation unit and a user management unit, a health sign test module, a sports ability test module, and a health data cloud platform composed of a chronic disease management target reasoning unit and a data storage unit. The invention combines the convenience and portability of mobile terminal devices with Internet information technology to guide the prevention and treatment of chronic diseases of users, thereby scientifically and safely improving the effect of chronic disease management. It can be seen that the chronic disease tracking management system based on a mobile terminal and its closed-loop guidance method have the following problems: the medical resources for the patient's subsequent follow-up visits are not managed, and the patient continues to go to the initial diagnosis and treatment site, resulting in the medical resources not being reasonably utilized. Summary of the invention

[0003] To this end, the present invention provides a closed-loop management system for chronic diseases to overcome the problem in the prior art that medical resources for subsequent follow-up visits of patients are not managed, and patients continue to go to the initial diagnosis and treatment site, resulting in unreasonable use of medical resources.

[0004] To achieve the above objectives, the present invention provides a closed-loop management system for chronic diseases. It includes: A data acquisition module, which is used to acquire patient data and patient files through a terminal; A data analysis module, connected to the data acquisition module, for analyzing the patient's health status according to the patient data and the patient file acquired by the data acquisition module; A file creation module, which is connected to the data analysis module and is used to create a diagnosis file based on the analysis results of the data analysis module; A referral analysis module, which is connected to the data analysis module and the file building module, and is used to determine whether to refer the patient based on the screening level applied for the diagnosis; A team formation module, which is connected to the referral analysis module and is used to determine whether to form a team and the formation method based on the expert's diagnosis results; An adjustment module is connected to the data analysis module and the team building module, and is used to adjust corresponding parameters to corresponding values ​​based on the analysis results of the data analysis module and the team building module.

[0005] Furthermore, the data analysis module analyzes whether the patient's health status is qualified based on the mercury column height in the patient data. The data analysis module makes a secondary determination on whether the patient's health status is qualified based on the data change trend in the patient's historical data when the patient's health status is initially determined to be unqualified; When the data analysis module determines that the patient's health status is unqualified, the file creation module creates a diagnosis file, and the referral analysis module determines whether to refer the patient based on the screening level used for diagnosis.

[0006] Furthermore, the data analysis module draws a mercury column height-time curve based on the historical data in the patient file acquired by the data acquisition module, and determines whether the patient's health status is qualified based on the average value of the slope of each time node in the curve. When the data analysis module determines that the patient's health status is qualified, the adjustment module corrects the diagnosis cycle for the patient based on the average value; When the data analysis module determines that the patient's health condition is unqualified, the file creation module creates a diagnosis file, and the referral analysis module determines whether to refer the patient based on the screening level used for the diagnosis.

[0007] Furthermore, the referral analysis module determines whether the patient should be referred based on the screening level used for diagnosis. The referral analysis module refers the patient to a higher-level hospital to request a specialist to confirm the diagnosis when determining that the patient is to be referred; The referral analysis module forms a management team based on the hospital level when determining that the patient is not to be referred.

[0008] Furthermore, the team building module determines whether the management team building standards are met based on the expert's diagnosis results, and builds a management team based on the hospital level when it is determined that the management team building standards are met.

[0009] Furthermore, when determining that the management team formation standard is not met, the adjustment module selects the mercury column adjustment coefficient α to adjust the first preset mercury column height D1 to a corresponding value.

[0010] Furthermore, the team building module builds a management team based on the hospital level. The team building module determines the attending physician and selects township doctors to build a team based on the township where the patient is located; The team building module determines that the township doctor sends a request to the superior hospital, and the superior hospital designates a doctor for remote guidance based on the request.

[0011] Furthermore, the adjustment module adjusts the patient's follow-up period based on the ratio of the average value to a preset average value.

[0012] Compared with the prior art, the beneficial effect of the present invention lies in that the present invention preliminarily analyzes the patient's health status based on the mercury column height measured by the patient's blood pressure, and further analyzes the patient's health status based on the data change trend in the patient's historical data, thereby avoiding misjudgment due to a single high blood pressure measurement caused by equipment problems, and analyzing whether to refer the patient based on the screening level when the patient's health status is determined to be unqualified, and referring the patient for examination and analysis when the first examination is a routine examination (such as a community physical examination), thereby avoiding misjudgment due to environmental factors and other factors, and improving the accuracy of the analysis of the patient's health status. When the patient's health status is determined to be unqualified, a management team is formed so that the patient can go for a follow-up visit nearby, thereby improving the rational utilization of medical resources and improving the efficiency of follow-up visits.

[0013] Furthermore, in the present invention, the more obvious the trend of blood pressure increase in the patient's historical data, the greater the average slope of the mercury column height-time curve, and the patient's health status is analyzed based on the slope of the curve, further improving the accuracy of the analysis of the patient's health status.

[0014] Furthermore, in the present invention, when the screening level of the patient's initial diagnosis is primary screening, the patient is referred to a higher-level hospital for further analysis, which further improves the accuracy of the analysis of the patient's health status.

[0015] Furthermore, in the present invention, the patient's blood pressure may occasionally rise due to environmental factors, and when the expert diagnoses that the patient's health condition is qualified, the first preset mercury column height is adjusted higher, thereby improving the analysis accuracy of the patient's health condition and improving the diagnosis efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 This is the structural diagram of the closed-loop management system for chronic diseases; Figure 2 A flowchart for preliminary analysis of whether the patient's health status is qualified; Figure 3 A flow chart for secondary analysis of whether the patient's health status is qualified; Figure 4 Flowchart for analyzing whether patients were referred. DETAILED DESCRIPTION

[0017] In order to make the objects and advantages of the present invention more clearly understood, the present invention is further described below in conjunction with embodiments; it should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0018] It should be pointed out that the data in this embodiment are obtained by comprehensive analysis and evaluation of the historical data of the system of the present invention in the six months before this determination and the corresponding historical determination results. Before this detection, the system of the present invention comprehensively determines the values ​​of the preset parameter standards for this determination based on the evaluation values ​​of the 37,383 retrieval results detected cumulatively in the first three months. It can be understood by those skilled in the art that the system of the present invention can determine the single parameter mentioned above by selecting the value with the highest proportion as the preset standard parameter according to the data distribution, using weighted summation to use the obtained value as the preset standard parameter, substituting each historical data into a specific formula and using the value obtained by the formula as the preset standard parameter or other selection methods, as long as the system of the present invention can clearly define the different specific situations in the single determination process through the obtained values.

[0019] The preferred embodiments of the present invention are described below with reference to the accompanying drawings. It should be understood by those skilled in the art that these embodiments are only used to explain the technical principles of the present invention and are not intended to limit the protection scope of the present invention.

[0020] It should be noted that, in the description of the present invention, terms such as "up", "down", "left", "right", "inside" and "outside" indicating directions or positional relationships are based on the directions or positional relationships shown in the drawings. This is merely for the convenience of description and does not indicate or imply that the device or element must have a specific orientation, be constructed and operated in a specific orientation. Therefore, it cannot be understood as a limitation on the present invention.

[0021] In addition, it should be noted that in the description of the present invention, unless otherwise clearly specified and limited, the terms "installed", "connected", and "connected" should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection, or it can be indirectly connected through an intermediate medium, or it can be the internal communication of two components. For those skilled in the art, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0022] See also Figure 1 As shown, it is a structural block diagram of a closed-loop management system for chronic diseases.

[0023] The present invention provides a chronic disease closed-loop management system, comprising: A data acquisition module, which is used to acquire patient data and patient files through a terminal; A data analysis module, connected to the data acquisition module, for analyzing the patient's health status according to the patient data and the patient file acquired by the data acquisition module; A file creation module, which is connected to the data analysis module and is used to create a diagnosis file based on the analysis results of the data analysis module; A referral analysis module, which is connected to the data analysis module and the file building module, and is used to determine whether to refer the patient based on the screening level applied for the diagnosis; A team formation module, which is connected to the referral analysis module and is used to determine whether to form a team and the formation method based on the expert's diagnosis results; An adjustment module is connected to the data analysis module and the team building module, and is used to adjust corresponding parameters to corresponding values ​​based on the analysis results of the data analysis module and the team building module.

[0024] See also Figure 2 As shown, it is a flowchart for preliminary analysis of whether the patient's health status is qualified.

[0025] Specifically, the data analysis module determines a preliminary determination method of whether the patient's health status is qualified based on the height of the mercury column in the patient data, wherein: The first preliminary determination method is that the data analysis module determines that the patient's health status is qualified; the first preliminary determination method satisfies that the height of the mercury column is less than or equal to the first preset mercury column height in the data analysis module; The second preliminary determination method is that the data analysis module determines whether the patient's health status is qualified based on the data change trend in the patient's historical data; the second preliminary determination method satisfies that the mercury column height is greater than the first preset mercury column height and is less than or equal to the second preset mercury column height in the data analysis module; The third preliminary judgment method is that the data analysis module determines that the patient's health status is unqualified, the file creation module establishes a diagnosis file, and the referral analysis module determines whether to refer the patient based on the screening level used for diagnosis; the third preliminary judgment method satisfies that the mercury column height is greater than the second preset mercury column height.

[0026] In the embodiment of the present invention, the first preset mercury column height is 88 mm for the diastolic pressure mercury column height, and the second preset mercury column height is 99 mm for the diastolic pressure mercury column height.

[0027] The present invention preliminarily analyzes the patient's health condition based on the mercury column height measured by the patient's blood pressure, and further analyzes the patient's health condition based on the data change trend in the patient's historical data, thereby avoiding misjudgment due to a high blood pressure measured in a single time due to equipment problems. When it is determined that the patient's health condition is unqualified, whether to refer the patient is determined based on the screening level analysis, and when the first examination is a routine examination (such as a community physical examination), it is recommended to go to the hospital for further examination and analysis, thereby avoiding misjudgment due to environmental factors and other factors, thereby improving the accuracy of the analysis of the patient's health condition, and forming a management team when it is determined that the patient's health condition is unqualified, so that the patient can go for a follow-up visit nearby, thereby improving the rational utilization of medical resources and improving the efficiency of follow-up visits.

[0028] See also Figure 3 As shown, it is a flowchart for secondary analysis of whether the patient's health status is qualified.

[0029] Specifically, the data analysis module draws a mercury column height-time curve based on the historical data in the patient file acquired by the data acquisition module under the second preliminary determination method, and determines a determination method for whether the patient's health status is qualified based on the average value of the slope of each time node in the curve, wherein: The first determination method is that the data analysis module determines that the patient's health status is qualified, and modifies the diagnosis cycle for the patient based on the average value; the first determination method satisfies that the average value is less than or equal to the preset average value in the data analysis module; The second judgment method is that the data analysis module determines that the patient's health condition is unqualified, the file creation module establishes a diagnosis file, and the referral analysis module determines whether to refer the patient based on the screening level used for diagnosis; the second judgment method satisfies that the average value is greater than the preset average value.

[0030] In the embodiment of the present invention, the preset average value is 0.8.

[0031] In the present invention, the more obvious the blood pressure increase trend in the patient's historical data, the greater the average slope of the mercury column height-time curve, and the patient's health status is analyzed based on the slope of the curve, further improving the accuracy of the analysis of the patient's health status.

[0032] See also Figure 4 As shown, it is a flow chart for analyzing whether patients should be referred.

[0033] Specifically, the referral analysis module determines whether the patient meets the referral criteria based on the screening level applied for the diagnosis, wherein: The first processing method is that the referral analysis module determines to refer the patient to a higher-level hospital to request a specialist to confirm the diagnosis; the first processing method satisfies that the screening level is grassroots screening; The second processing method is that the referral analysis module determines to form a management team based on the hospital level; the second processing method satisfies that the screening level is hospital diagnosis.

[0034] In the present invention, when the screening level of the patient's initial diagnosis is primary screening, the patient is referred to a higher-level hospital for further analysis, which further improves the accuracy of the analysis of the patient's health status.

[0035] Specifically, the team building module determines whether the management team building standard is met based on the expert's diagnosis result under the first processing mode, wherein: The first analysis method is that the team formation module determines that it does not meet the management team formation standards; the first analysis method satisfies the expert's diagnosis result that the health status is qualified; The second analysis method is that the team building module determines that the management team building standards are met and builds a management team based on the hospital level; the second analysis method satisfies the expert's diagnosis result that the health status is unqualified.

[0036] Specifically, the adjustment module selects the mercury column adjustment coefficient α to adjust the first preset mercury column height D1 to a corresponding value in the first analysis mode, and sets the adjusted mercury column height D1'=α×D10, where D10 is the first preset mercury column height before adjustment.

[0037] In the embodiment of the present invention, the mercury column adjustment coefficient α is 1.08, and the first preset mercury column height is lower than the second preset mercury column height.

[0038] In the present invention, the patient's blood pressure may occasionally rise due to environmental factors, and when the expert diagnoses that the patient's health condition is qualified, the first preset mercury column height is adjusted higher, thereby improving the analysis accuracy of the patient's health condition and improving the diagnosis efficiency.

[0039] Specifically, the team building module determines the way to build the management team based on the hospital level, where: The first formation method is that the team formation module determines that the attending doctor selects township doctors to form a team based on the township where the patient is located; the first formation method satisfies that the hospital where the patient is located is a first-level hospital; The second formation method is that the team formation module determines that the township doctor sends a request to the superior hospital, and the superior hospital designates a doctor for remote guidance based on the request; the second formation method satisfies that the hospital where the patient is located is a secondary hospital.

[0040] In the embodiment of the present invention, the first-level hospital is a county-level or above hospital, and the second-level hospital is a township hospital.

[0041] Specifically, the adjustment module determines an adjustment method for the follow-up period of the patient based on the ratio of the average value to the preset average value under the first determination method, wherein: The first adjustment method is that the adjustment module selects the first adjustment coefficient β1 to adjust the re-visit period T to the corresponding value, and sets the adjusted re-visit period T'=β1×T0, where T0 is the initial re-visit period before adjustment; the first adjustment method satisfies that the ratio is less than or equal to the preset ratio in the data analysis module; The second adjustment method is that the adjustment module selects the second adjustment coefficient β2 to adjust the follow-up period T to a corresponding value, and sets the adjusted follow-up period T'=β2×T0; the second adjustment method satisfies that the ratio is greater than the preset ratio.

[0042] In the embodiment of the present invention, the first adjustment coefficient is 0.5, the second adjustment coefficient is 0.6, and the initial follow-up cycle is 2 times / month.

[0043] So far, the technical solutions of the present invention have been described in conjunction with the preferred embodiments shown in the accompanying drawings. However, it is easy for those skilled in the art to understand that the protection scope of the present invention is obviously not limited to these specific embodiments. Without departing from the principle of the present invention, those skilled in the art can make equivalent changes or substitutions to the relevant technical features, and the technical solutions after these changes or substitutions will fall within the protection scope of the present invention.

[0044] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. For those skilled in the art, the present invention may have various modifications and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A closed-loop management system for chronic diseases, characterized in that: include: A data acquisition module, which is used to acquire patient data and patient files through a terminal; A data analysis module, connected to the data acquisition module, for analyzing the patient's health status according to the patient data and the patient file acquired by the data acquisition module; A file creation module, which is connected to the data analysis module and is used to create a diagnosis file based on the analysis results of the data analysis module; A referral analysis module, which is connected to the data analysis module and the file building module, and is used to determine whether to refer the patient based on the screening level applied for the diagnosis; A team formation module, which is connected to the referral analysis module and is used to determine whether to form a team and the formation method based on the expert's diagnosis results; An adjustment module is connected to the data analysis module and the team building module, and is used to adjust corresponding parameters to corresponding values ​​based on the analysis results of the data analysis module and the team building module.

2. The closed-loop management system for chronic diseases according to claim 1, characterized in that: The data analysis module analyzes whether the patient's health status is qualified based on the mercury column height in the patient data. The data analysis module makes a secondary determination on whether the patient's health status is qualified based on the data change trend in the patient's historical data when the patient's health status is initially determined to be unqualified; When the data analysis module determines that the patient's health status is unqualified, the file creation module creates a diagnosis file, and the referral analysis module determines whether to refer the patient based on the screening level used for diagnosis.

3. The closed-loop management system for chronic diseases according to claim 2, characterized in that: The data analysis module draws a mercury column height-time curve based on the historical data in the patient file acquired by the data acquisition module, and determines whether the patient's health status is qualified based on the average value of the slope of each time node in the curve. When the data analysis module determines that the patient's health status is qualified, the adjustment module corrects the diagnosis cycle for the patient based on the average value; When the data analysis module determines that the patient's health condition is unqualified, the file creation module creates a diagnosis file, and the referral analysis module determines whether to refer the patient based on the screening level used for the diagnosis.

4. The closed-loop management system for chronic diseases according to claim 3, characterized in that: The referral analysis module determines whether the patient should be referred based on the screening level applied for diagnosis. The referral analysis module refers the patient to a higher-level hospital to request a specialist to confirm the diagnosis when determining that the patient is to be referred; When the referral analysis module determines that the patient is not to be referred, a management team is formed based on the hospital level.

5. The closed-loop management system for chronic diseases according to claim 4, characterized in that: The team building module determines whether the management team building standards are met based on the expert's diagnosis results, and builds a management team based on the hospital level when it is determined that the management team building standards are met.

6. The closed-loop management system for chronic diseases according to claim 5, characterized in that: When determining that the management team formation standard is not met, the adjustment module selects the mercury column adjustment coefficient α to adjust the first preset mercury column height D1 to a corresponding value.

7. The closed-loop management system for chronic diseases according to claim 6, characterized in that: The team building module builds a management team based on the hospital level. The team building module determines the attending physician and selects township doctors to build a team based on the township where the patient is located; The team building module determines that the township doctor sends a request to the superior hospital, and the superior hospital designates a doctor for remote guidance based on the request.

8. The closed-loop management system for chronic diseases according to claim 7, characterized in that: The adjustment module adjusts the patient's follow-up period based on the ratio of the average value to a preset average value.

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