Digital medical cloud curative effect evaluation method and system

Abstract

The invention discloses a digital medical cloud curative effect evaluation method and system, and relates to the technical field of health management. Obtaining customer data; performing four-dimensional curative effect evaluation classification and naming based on the acquired customer data; based on a four-dimensional scoring system, performing curative effect scoring on the classified customer data, and dividing the customers into invalid customers, valid customers and valid customers according to a scoring result; and the expert rechecks the scoring result and gives corresponding measures to different clients according to the scoring result. Through clinical curative effect data collected by an evaluation scale and the like, the treatment effect of a single disease is explored, a curative effect comprehensive evaluation index and an evaluation dynamic monitoring mechanism are thinking and established, and the medical quality is promoted to be improved.

Description

Technical Field

[0001] The present invention relates to the field of health management technology, and in particular to a digital medical cloud efficacy evaluation method and system. Background Art

[0002] Chronic diseases have become the world's "number one killer", causing nearly 36 million deaths each year, accounting for more than 60% of the world's total deaths. The continuous spread of chronic diseases has brought a heavy economic burden to the country. Chronic diseases account for 69% of the disease burden, far exceeding the disease burden caused by infectious diseases and other injuries. Therefore, the prevention, control and treatment of chronic diseases are of great significance to the country and the people, both now and in the future.

[0003] Before the disease occurs, a series of preventive measures can be taken to prevent the occurrence of the disease. Treating diseases before they occur is also a preventive concept, and its core lies in preventing the occurrence and development of diseases through preventive measures and treatment methods. Treating diseases before they occur can be prevented through functional medicine and traditional Chinese medicine methods. The theory of treating diseases before they occur originated from the Yellow Emperor's Canon of Internal Medicine, which emphasizes the importance of "preventing problems before they happen". It includes paying attention to mental conditioning, paying attention to diet and daily life, and strengthening physical exercise. Prevent the invasion of pathogens by avoiding contact with adverse environments and enhancing physical resistance. In the case of disease, early diagnosis and treatment and correct treatment methods can prevent the further development and deterioration of the disease. According to the laws of disease development and change, strive for early diagnosis and take correct treatment. After mastering the laws of disease transmission and change, certain preventive treatments are carried out in a timely manner for certain pathological changes that are about to occur, and the development of the disease is actively and effectively controlled.

[0004] At present, there is no perfect evaluation system for the above situation, which cannot achieve prevention and active and effective control of disease development. Therefore, it is an urgent problem for technical personnel in this field to propose a digital medical cloud efficacy evaluation method and system, explore the treatment effect of a single disease through the clinical efficacy data collected by the evaluation scale, and consider the establishment of a comprehensive efficacy evaluation index and dynamic evaluation monitoring mechanism to promote the improvement of medical quality. Summary of the invention

[0005] In view of this, the present invention provides a digital medical cloud efficacy evaluation method and system to solve the technical problems existing in the prior art.

[0006] In order to achieve the above object, the present invention adopts the following technical solution:

[0007] A digital medical cloud efficacy evaluation method includes the following steps:

[0008] S1 Data acquisition step: obtain customer data;

[0009] S2 Data processing steps: Classify and name the four-dimensional efficacy evaluation based on the acquired customer data;

[0010] S3 Four-dimensional efficacy evaluation steps: Based on the four-dimensional scoring system, the classified customer data is scored for efficacy, and the customers are divided into: ineffective customers, effective customers and significantly effective customers according to the scoring results;

[0011] S4 Expert Review Step: Experts review the scoring results and provide corresponding measures for different customers based on the scoring results.

[0012] In the above method, optionally, the customer data in S1 includes:

[0013] New users’ registration information, appointment information, and consultation information;

[0014] Identity information, appointment information, consultation information and physical physiological data of old users.

[0015] In the above method, optionally, the four dimensions in S2 include: laboratory indicators or equipment detection indicators, imaging indicators, somatosensory indicators, and clinical medication.

[0016] The above method is optional, and the specific content of S3 is:

[0017] The two examination indicators after each treatment of the customer are entered into the system. The system gives a score to the filled-in indicator data according to the set scoring system. Customers with a score less than or equal to 65 are invalid customers, those with a score between 65-80 are valid customers, and those with a score greater than or equal to 80 are valid customers.

[0018] In the above method, optionally, S3 also includes laboratory indicators or equipment detection indicators, imaging indicators, somatosensory indicators, and clinical medications, and the system is scored according to corresponding proportions of 50%, 20%, 20% and 10%.

[0019] The above method is optional. In S4, invalid customers enter closed-loop management, and valid customers and effective customers enter the PDCA efficacy management cycle.

[0020] A digital medical cloud efficacy evaluation system, which executes any one of the digital medical cloud efficacy evaluation methods described above, comprises a data acquisition module, a data processing module, a four-dimensional efficacy evaluation module and an expert review module connected in sequence;

[0021] Data acquisition module, used to acquire customer data;

[0022] The data processing module is used to classify and name the efficacy evaluation in four dimensions based on the acquired customer data;

[0023] The four-dimensional efficacy evaluation module is used to evaluate the efficacy of the classified customer data based on the four-dimensional scoring system, and divide the customers into ineffective customers, effective customers and markedly effective customers according to the scoring results;

[0024] The expert review module is used for experts to review the scoring results and provide corresponding measures for different customers based on the scoring results.

[0025] The above system may optionally further include a display module for displaying data of each module of the system.

[0026] It can be seen from the above technical solutions that, compared with the prior art, the present invention provides a digital medical cloud efficacy evaluation method and system, which has the following beneficial effects:

[0027] Ensure the objectivity and authenticity of the evaluation results and provide a scientific basis for improving the quality of medical services. Through rigorous evaluation methods, the system can effectively screen out inappropriate medical measures and promote the scientific and rational use of medical intervention measures. BRIEF DESCRIPTION OF THE DRAWINGS

[0028] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on the provided drawings without paying creative work.

[0029] Figure 1 This is a flow chart of a digital medical cloud efficacy evaluation method disclosed in the present invention;

[0030] Figure 2 A block diagram of a digital medical cloud efficacy evaluation system disclosed in the present invention;

[0031] Figure 3 It is a schematic diagram of the user efficacy evaluation stage disclosed in the present invention;

[0032] Figure 4 This is a schematic diagram of the PCD circulation health management model disclosed in the present invention;

[0033] Figure 5 This is an example diagram for judging whether the Class B indicators in the biochemical dimension disclosed in the present invention are effective or not. DETAILED DESCRIPTION

[0034] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0035] In this application, relational terms such as first and second, etc. are used only to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. The terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of more restrictions, the elements defined by the sentence "comprise one..." do not exclude the existence of other identical elements in the process, method, article or device including the elements.

[0036] See also Figure 1 and Figure 3 As shown, the present invention discloses a digital medical cloud efficacy evaluation method, comprising the following steps:

[0037] S1 Data acquisition step: obtain customer data;

[0038] S2 Data processing steps: Classify and name the efficacy evaluation in four dimensions based on the acquired customer data;

[0039] S3 Four-dimensional efficacy evaluation steps: Based on the four-dimensional scoring system, the classified customer data is scored for efficacy, and the customers are divided into: ineffective customers, effective customers and significantly effective customers according to the scoring results;

[0040] S4 Expert Review Step: Experts review the scoring results and provide corresponding measures for different customers based on the scoring results.

[0041] Furthermore, the customer data in S1 includes:

[0042] New users’ registration information, appointment information, and consultation information;

[0043] Identity information, appointment information, consultation information and physical physiological data of old users.

[0044] Furthermore, the four dimensions in S2 include: laboratory indicators or equipment detection indicators, imaging indicators, somatosensory indicators, and clinical medication.

[0045] Specifically, in the biochemical dimension: the test values ​​of the HIS system are obtained according to the biochemical indicators configured for each project and are divided into three categories, namely Class A, Class B, and Class C, to judge whether they are effective or not, and assign effectiveness scores. Finally, the weighted average and base sum of the effectiveness scores of all biochemical indicators are performed, of which the main indicators account for 70% and the secondary indicators account for 30%.

[0046] Category A means that the lower the value of the test indicator, the better. For example, in the C13 breath test, if the C13 value is between 0-4, it is negative, indicating that there is no infection and the result is relatively good. On the contrary, the larger the C13 value, the positive is, indicating infection with Helicobacter pylori and need treatment.

[0047] Category B means that the test index has an ideal range of values. High or low values ​​are inappropriate. For example, the ideal range of 25-hydroxyvitamin D is 40-60. Values ​​that are too high or too low will cause uncomfortable clinical symptoms.

[0048] Category C means that the higher the value of the test indicator, the better. For example, in the seven blood lipid items, the high-density lipoprotein cholesterol, in clinical practice, the higher the test value, the better.

[0049] Image dimension: Based on the image results of each item, the text content of the established observed nodules is obtained, and the score is reflected by the changes in the size of the nodules, such as the name and area. For example, if the first ultrasound examination shows fatty liver (moderate to severe), and the ultrasound examination after the treatment project is completed shows fatty liver (mild), it means that the treatment is effective.

[0050] The score is checked based on the scores before and after treatment: 1 point corresponds to 10% effectiveness, and the average score after deducting each symptom and symptom dimension is the effective score. For example: A client has eczema and joint pain. The sum of the difference between the 4 dimensions before and after eczema is 24 points, and the sum of the difference between the 3 dimensions before and after joint pain is 18 points. The average score is 6 points, the effective improvement rate is 60%, and the symptom dimension score is 6 points.

[0051] Medication dimension: judged based on the amount of medication before and after treatment: reducing the dosage by 2 / 3 or more: 80-100 points, reducing the dosage by more than 1 / 3: 60-79 points, reducing the dosage by less than 1 / 3: 30-59 points.

[0052] The four dimensions are flexibly weighted according to the proportions of each treatment project. In order to ensure the fairness and scientificity of the project efficacy evaluation, the medication dimension and the physical sensation dimension cannot account for 100% alone, and must be configured together with the biochemical dimension to participate in the score calculation.

[0053] See also Figure 5 The figure shown is an example of judging whether the Class B indicators in the biochemical dimension are effective or not.

[0054] Furthermore, the specific content of S3 is:

[0055] The two examination indicators after each treatment of the customer are entered into the system. The system gives a score to the filled-in indicator data according to the set scoring system. Customers with a score less than or equal to 65 are invalid customers, those with a score between 65-80 are valid customers, and those with a score greater than or equal to 80 are valid customers.

[0056] Furthermore, S3 also includes laboratory indicators or equipment detection indicators, imaging indicators, somatosensory indicators, and clinical medications, and the system is scored according to the corresponding proportions of 50%, 20%, 20%, and 10%.

[0057] There are special cases, such as when only three or two of the four dimensions are reviewed, then the percentages will be reallocated according to the corresponding proportions.

[0058] Furthermore, ineffective customers in S4 enter closed-loop management, and effective customers and significantly effective customers enter the PDCA efficacy management cycle.

[0059] Closed-loop management: The health manager, attending physician and primary physician jointly organize and analyze the customer's information, analyze and discuss the frequency of treatment in the hospital, degree of cooperation, daily diet and other living habits, and conduct joint consultation with other experts when necessary. Improve the plan according to the current situation and improve the customer's treatment effect.

[0060] PDCA efficacy management cycle (see Figure 4 As shown): A cycle of climbing stairs. After one cycle is completed, the therapeutic effect will be improved one step. Then the next cycle will be planned, executed and improved again, and the improvement will continue.

[0061] The expert review includes: whether the indicators and data have improved; whether the symptoms and physical sensations have improved; whether the medication is accurate; whether the communication is in sync and whether the expectations are reasonable.

[0062] Furthermore, it also includes a database for data storage: health managers regularly upload clients’ biochemical indicators, imaging indicators, physical indicators and clinical medications, and keep records;

[0063] and Figure 1 Corresponding to the method, the present invention also discloses a digital medical cloud efficacy evaluation system for executing any of the digital medical cloud efficacy evaluation methods described above. For a specific structural diagram, see Figure 2 As shown, it includes a data acquisition module, a data processing module, a four-dimensional efficacy evaluation module and an expert review module connected in sequence;

[0064] Data acquisition module, used to acquire customer data;

[0065] The data processing module is used to classify and name the efficacy evaluation in four dimensions based on the acquired customer data;

[0066] The four-dimensional efficacy evaluation module is used to evaluate the efficacy of the classified customer data based on the four-dimensional scoring system, and divide the customers into ineffective customers, effective customers and markedly effective customers according to the scoring results;

[0067] The expert review module is used for experts to review the scoring results and provide corresponding measures for different customers based on the scoring results.

[0068] The health manager will enter the client’s primary and secondary indicators into the system for sharing;

[0069] Primary and secondary indicators: Each treatment item has its corresponding primary and secondary indicators. For example, body composition and body fat percentage are the primary indicators, and blood sugar - glycosylated hemoglobin, fasting blood sugar, insulin resistance level, total cholesterol and triglycerides are all secondary indicators.

[0070] Health butler follow-up: The customer goes to the hospital for treatment according to the treatment recommendations given by the attending specialist. The health butler follows up on a daily basis, reminding the customer to adjust their diet, improve their lifestyle, etc. After the treatment, the relevant indicators are reviewed. The health butler organizes the data required for the four dimensions of efficacy evaluation and uploads them to the system.

[0071] Furthermore, it also includes a display module for displaying data of each module of the system.

[0072] A digital medical cloud efficacy evaluation system displays the customer's basic information (name, gender, age), treatment items, treatment time, attending physician, primary physician, and health manager.

[0073] Each embodiment in this specification is described in a progressive manner, and the same or similar parts between the embodiments can refer to each other, and each embodiment focuses on the differences from other embodiments. In particular, for the system or system embodiment, since it is basically similar to the method embodiment, the description is relatively simple, and the relevant parts can refer to the partial description of the method embodiment. The system and system embodiments described above are merely schematic, wherein the units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the scheme of this embodiment. Ordinary technicians in this field can understand and implement it without creative work.

[0074] The above description of the disclosed embodiments enables one skilled in the art to implement or use the present invention. Various modifications to these embodiments will be apparent to one skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present invention. Therefore, the present invention will not be limited to the embodiments shown herein, but rather to the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A digital medical cloud efficacy evaluation method, characterized in that: The following steps are involved: S1 Data acquisition step: obtain customer data; S2 Data processing steps: Classify and name the four-dimensional efficacy evaluation based on the acquired customer data; S3 Four-dimensional efficacy evaluation steps: Based on the four-dimensional scoring system, the classified customer data is scored for efficacy, and the customers are divided into: ineffective customers, effective customers and significantly effective customers according to the scoring results; S4 Expert Review Step: Experts review the scoring results and provide corresponding measures for different customers based on the scoring results.

2. A digital medical cloud efficacy evaluation method according to claim 1, characterized in that: Customer data in S1 includes: New users’ registration information, appointment information, and consultation information; Identity information, appointment information, consultation information and physical physiological data of old users.

3. A digital medical cloud efficacy evaluation method according to claim 2, characterized in that: The four dimensions in S2 include: laboratory indicators or equipment detection indicators, imaging indicators, physical sensation indicators, and clinical medication.

4. A digital medical cloud efficacy evaluation method according to claim 3, characterized in that: The specific contents of S3 are: The two examination indicators after each treatment of the customer are entered into the system. The system gives a score to the filled-in indicator data according to the set scoring system. Customers with a score less than or equal to 65 are invalid customers, those with a score between 65-80 are valid customers, and those with a score greater than or equal to 80 are valid customers.

5. A digital medical cloud efficacy evaluation method according to claim 4, characterized in that: S3 also includes laboratory indicators or equipment detection indicators, imaging indicators, physical sensation indicators, and clinical medications, and the system is scored according to the corresponding proportions of 50%, 20%, 20%, and 10%.

6. A digital medical cloud efficacy evaluation method according to claim 5, characterized in that: In S4, ineffective customers enter closed-loop management, and effective customers and significantly effective customers enter the PDCA efficacy management cycle.

7. A digital medical cloud efficacy evaluation system, characterized in that: A digital medical cloud efficacy evaluation method according to any one of claims 1 to 6 is implemented, comprising a data acquisition module, a data processing module, a four-dimensional efficacy evaluation module and an expert review module connected in sequence; Data acquisition module, used to acquire customer data; The data processing module is used to classify and name the efficacy evaluation in four dimensions based on the acquired customer data; The four-dimensional efficacy evaluation module is used to evaluate the efficacy of the classified customer data based on the four-dimensional scoring system, and divide the customers into ineffective customers, effective customers and markedly effective customers according to the scoring results; The expert review module is used for experts to review the scoring results and provide corresponding measures for different customers based on the scoring results.

8. A digital medical cloud efficacy evaluation system according to claim 9, characterized in that: It also includes a display module for displaying data from each module of the system.

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