Internet economic service management system based on data analysis

Abstract

The present invention discloses an Internet economic service management system based on data analysis, which belongs to the field of data processing technology. It is used to solve the technical problems of poor initiative and pertinence of autonomous integration and utilization of online medical services of Internet economy and resource sharing interaction in existing solutions. Data processing and integrated calculation and analysis are performed on the target of online consultation from the dimensions of consultation time and consultation fee to determine the consultation status of the corresponding target and classify and mark it. For the targets with poor consultation effect in the previous active monitoring and analysis, the big data of consultations with the same cause of consultation is efficiently and conveniently obtained through the Internet platform, and integrated and analyzed and screened to obtain excellent medical resources including several recommended doctors. The excellent medical resources obtained are used to actively and pertinently share and recommend medical resources to abnormal targets marked in the previous analysis, thereby improving the autonomous integration and utilization of online medical services of Internet economy and the initiative and pertinence of resource sharing interaction.

Description

Technical Field

[0001] The present invention relates to the technical field of data processing, and in particular to an Internet economic service management system based on data analysis. Background Art

[0002] Internet economic services refer to the process of providing various economic activities and services through digital and networked means based on the Internet technology platform.

[0003] When existing Internet economic service management solutions are implemented in the online medical field, most of them still remain at the online communication and interaction between doctors and patients. There are barriers to medical information and excellent medical resource information. For patients with poor medical results, they cannot rely on the Internet platform to efficiently and conveniently obtain excellent medical resources of the same type of medical treatment and make online shared, integrated and recommended recommendations. There is a defect that the patient's medical data cannot be processed and analyzed online and the matching Internet medical resource prompts and services cannot be adaptively provided to different patients. This leads to the poor initiative and pertinence of the autonomous integration and utilization of online medical services in the Internet economy and resource sharing and interaction. Summary of the invention

[0004] The purpose of the present invention is to provide an Internet economic service management system based on data analysis, which is used to solve the technical problems of the autonomous integration and utilization of Internet economic online medical services and the poor initiative and pertinence of resource sharing interaction in existing solutions.

[0005] The purpose of the present invention can be achieved through the following technical solutions:

[0006] Internet economic service management system based on data analysis, including:

[0007] The target consultation data monitoring and processing module is used to monitor and count the basic information of all targets that implement online consultation on the online consultation platform, and to process and filter the basic information to obtain normal targets and abnormal targets;

[0008] Among them, the target's consultation duration data and consultation fee data are counted and processed, and the corresponding consultation necessity is obtained through calculation, and the consultation type of the target is screened and marked according to the consultation necessity;

[0009] The marked target evaluation and recommendation module is used to proactively push consultation information on the medical status and recommended medical resources to the marked abnormal targets through the online consultation platform, and to count and combine the status consultation results and recommended consultation results confirmed by the abnormal targets to obtain a feedback result set, conduct a necessity analysis on the feedback result set, and proactively push excellent medical resource information with the same confirmed cause to the marked abnormal targets in an adaptive manner;

[0010] Among them, the status consultation results and recommended consultation results in the feedback result set are traversed and counted. If the traversed status consultation result is that the medical treatment is invalid and the recommended consultation result is agreed, a recommendation instruction is generated and the excellent medical resource information with the same confirmed cause of the disease is actively pushed to the abnormal target. The excellent medical resource information is composed of a combination of several recommended doctors and their respective medical departments and hospitals obtained through analysis.

[0011] Preferably, when the target conducts online consultation through the online consultation platform, the target's identity information is obtained through authorization, and the obtained identity information is input into the medical consultation database associated with the online consultation platform for retrieval to obtain the first medical consultation time and its corresponding confirmed cause.

[0012] Preferably, the acquisition interval time Tj is calculated based on the first visit time and the target's current consultation time, and all the consultation fees Fj paid by the target since the first visit time are obtained;

[0013] Extract the target interval time and the consultation fee value and calculate the consultation necessity μ corresponding to the target through the formula; the calculation formula of consultation necessity μ is: In the formula, Tj is the standard interval duration corresponding to the same confirmed cause, Fj is the standard medical fee corresponding to the same confirmed cause; α1 is the duration correction factor corresponding to the same confirmed cause; α2 is the fee correction factor corresponding to the same confirmed cause.

[0014] Preferably, the steps of obtaining the duration correction factor α1 and the cost correction factor α2 corresponding to the same confirmed cause of disease include:

[0015] Active treatment result statistics are implemented for all targets with the same diagnosed cause in history, and targets with feedback of treatment results and completed treatment are marked as effective targets;

[0016] The treatment duration and treatment cost corresponding to all targets are counted and sorted and combined respectively to obtain the treatment duration sequence and treatment cost sequence;

[0017] According to the treatment time sequence and treatment cost sequence, the corresponding total treatment time Z1 and total treatment cost Z2 are calculated, as well as the median treatment time z1 corresponding to the treatment time sequence and the median treatment cost z2 corresponding to the treatment cost sequence;

[0018] The duration correction factor α1 and the cost correction factor α2 are calculated by the correction factor formula; the correction factor formula is: αk = (Zk-zk) / Zk; wherein k = 1, 2.

[0019] Preferably, when screening and marking the targets according to the consultation necessity, the consultation necessity is input into the consultation analysis and recognition model for data analysis and output of the corresponding target identification value, and the targets are dynamically marked according to the target identification value;

[0020] The target identification value contains a value of 0 or 1; the expression of the consulting analysis recognition model is: In the formula, μ′ is the consultation necessity threshold;

[0021] According to the target identification value whose output value is 0, the target is marked as a normal target, and according to the target identification value whose output value is 1, the target is marked as an abnormal target.

[0022] Preferably, according to the recommended instructions, the doctors who have historically prescribed medicines for the same confirmed cause of illness are counted and marked as alternative doctors, the total number of times the alternative doctors have historically prescribed medicines for the same confirmed cause of illness is counted, and the treatment effects of the corresponding targets of the same confirmed cause of illness are traced and the total number of effective treatments is counted, the treatment durations and treatment costs corresponding to different effective treatment targets are obtained, and the corresponding median treatment durations and median treatment costs are calculated based on the statistical treatment durations and treatment costs corresponding to all effective treatment targets.

[0023] Preferably, the total number of times Cz, the total number of effective treatments Cr, the median treatment duration Cs, and the median treatment cost Cf of the candidate doctors' corresponding historical prescriptions for the same confirmed cause are extracted and sorted and combined to obtain a candidate monitoring sequence;

[0024] According to the alternative monitoring sequence, the implementation status degree η corresponding to the alternative doctor is calculated through the implementation status formula.

[0025] Preferably, the implementation state formula is: Where Cz′, Cr′, Cs′, and Cf′ are the total number of standard prescriptions for the same diagnosed cause, the total number of standard patients, the standard treatment duration, and the standard treatment cost, respectively; c1, c2, c3, and c4 are all proportional coefficients, and 0<c3≤c4<c2≤c1<1.

[0026] Preferably, all candidate doctors are sorted in descending order according to the numerical value of the implementation status, and the top K candidate doctors are marked as recommended doctors. At the same time, the treatment departments and hospitals to which all recommended doctors belong are obtained and combined to obtain excellent medical resource information.

[0027] Compared with the existing solutions, the present invention achieves the following beneficial effects:

[0028] The present invention processes data from the dimensions of consultation duration and consultation cost for online consultation and performs integrated calculations to obtain the corresponding consultation necessity, and determines the consultation status of the corresponding target and classifies and marks it by performing data analysis on the consultation necessity. This can not only digitally represent the consultation status corresponding to targets with different confirmed causes of disease, but also provide reliable data support for the subsequent active analysis, recommendation and push of excellent medical resource information for different marked targets.

[0029] The present invention aims at the targets with poor medical treatment results in the early stage of active monitoring and analysis. It efficiently and conveniently obtains the big data of medical treatments with the same cause of treatment through the Internet platform, integrates and analyzes and screens to obtain excellent medical resources including several recommended doctors, and actively identifies and obtains excellent medical resources to actively share and recommend medical resources for abnormal targets marked in the early stage of analysis, thereby improving the autonomous integration and utilization of online medical services in the Internet economy and the initiative and pertinence of resource sharing interaction. BRIEF DESCRIPTION OF THE DRAWINGS

[0030] The present invention will be further described below in conjunction with the accompanying drawings.

[0031] Figure 1 This is a module block diagram of the Internet economic service management system based on data analysis of the present invention. DETAILED DESCRIPTION

[0032] 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 operation and maintenance personnel in this field without creative work are within the scope of protection of the present invention.

[0033] like Figure 1 As shown, the present invention is an Internet economic service management system based on data analysis, including a target consultation data monitoring and processing module, a marked target evaluation and recommendation module, an online consultation platform and a medical consultation database;

[0034] The target consultation data monitoring and processing module is used to monitor and count the basic information of all targets implementing online consultation on the online consultation platform, and to process and filter the basic information monitored and counted to obtain normal targets and abnormal targets; including:

[0035] When the target consults online through the online consultation platform, the target's identity information is obtained through authorization. The identity information includes the target's medical consultation number or ID number, and the obtained identity information is input into the medical consultation database associated with the online consultation platform for retrieval and traversal to obtain the first medical consultation time and its corresponding confirmed cause. The interval time Tj is calculated based on the first medical consultation time and the target's current consultation time, as well as all medical consultation fees Fj paid by the target since the first medical consultation time; the unit of the interval time is day, and the unit of the medical consultation fee is yuan;

[0036] It should be noted that the target is patients who have received offline medical treatment and who can receive follow-up consultation and consultation through the online resource platform; the main body of the online consultation platform is the hospital where the patient received offline medical treatment; the online consultation platform can be a webpage, a mini program or a public account;

[0037] Extract the target interval time and the consultation fee value and calculate the consultation necessity μ corresponding to the target through the formula; the calculation formula of consultation necessity μ is: Where, Tj is the standard interval duration corresponding to the same confirmed cause, Fj is the standard medical fee corresponding to the same confirmed cause; α1 is the duration correction factor corresponding to the same confirmed cause; α2 is the fee correction factor corresponding to the same confirmed cause;

[0038] It should be noted that in the embodiment of the present invention, the consultation necessity is obtained by integrating and calculating the historical medical data of the online consultation target in different aspects. According to the consultation necessity, the overall medical situation of the target can be digitally represented, and reliable overall medical data support can be provided for the subsequent analysis of the medical status of the target.

[0039] The steps for obtaining the duration correction factor α1 and the cost correction factor α2 corresponding to the same confirmed cause include:

[0040] Active treatment result statistics are implemented for all targets with the same diagnosed cause in history, and targets with feedback of treatment results and completed treatment are marked as effective targets;

[0041] The treatment duration and treatment cost corresponding to all targets are counted and sorted and combined respectively to obtain the treatment duration sequence and treatment cost sequence;

[0042] According to the treatment time sequence and treatment cost sequence, the corresponding total treatment time Z1 and total treatment cost Z2 are calculated, as well as the median treatment time z1 corresponding to the treatment time sequence and the median treatment cost z2 corresponding to the treatment cost sequence;

[0043] The duration correction factor α1 and the cost correction factor α2 are calculated by the correction factor formula; the correction factor formula is: αk = (Zk-zk) / Zk; where k = 1, 2;

[0044] When screening and marking the targets according to the consultation necessity, the consultation necessity is input into the consultation analysis and recognition model for data analysis and output of the corresponding target identification value, and the targets are dynamically marked according to the target identification value;

[0045] It should be noted that by processing data from the total treatment time dimension and the total treatment cost dimension corresponding to the same historical cause of medical treatment and calculating the corresponding time correction factor and cost correction factor, and by referring to the time correction factor and cost correction factor in the target consultation necessity calculation process, the reliability of the consultation necessity calculation can be effectively improved; the consultation analysis and recognition model is established based on the isolation forest algorithm and combined with the consultation necessity big data of all historical identical diagnosed causes;

[0046] Among them, the target identification value contains a value of 0 or 1, which respectively indicates that the corresponding consultation status is normal or abnormal; the expression of the consultation analysis recognition model is: In the formula, μ′ is the consultation necessity threshold, which is determined based on the median of the consultation necessity of all historical cases with the same diagnosed cause;

[0047] According to the target identification value whose output value is 0, the target is marked as a normal target, and according to the target identification value whose output value is 1, the target is marked as an abnormal target;

[0048] In the embodiment of the present invention, data processing and integrated calculation are performed on the target of online consultation from the dimensions of consultation duration and consultation fee to obtain the corresponding consultation necessity, and data analysis is performed on the consultation necessity to determine the consultation status of the corresponding target and classify and mark it. This can not only realize the digital representation of the consultation status corresponding to the targets with different confirmed causes of disease, but also provide reliable data support for the subsequent active analysis, recommendation and push of excellent medical resource information for different marked targets.

[0049] The marked target evaluation and recommendation module is used to proactively push consultations on the medical status and recommended medical resources to the marked abnormal targets through the online consultation platform, and to count and combine the status consultation results and recommended consultation results confirmed by the abnormal targets to obtain a feedback result set, conduct a necessity analysis on the feedback result set, and proactively push excellent medical resource information with the same confirmed cause to the marked abnormal targets in an adaptive manner; including:

[0050] Among them, the status consultation result includes whether the medical consultation is effective or invalid after confirmation by the target; the medical resource recommendation consultation includes whether the medical consultation is agreed or not after confirmation by the target;

[0051] The status consultation results and recommended consultation results in the feedback result set are traversed and counted. If the traversed status consultation result is invalid and the recommended consultation result is agreed, a recommendation instruction is generated and excellent medical resource information with the same confirmed cause is actively pushed to the abnormal target;

[0052] It should be noted that if the traversed status consultation result is invalid consultation or the recommended consultation result is agreed and one of them does not exist, a silent instruction is generated and the excellent medical resource information with the same confirmed cause is not actively pushed to the abnormal target;

[0053] According to the recommended instructions, the doctors who have prescribed the same confirmed cause of disease in history are counted and marked as alternative doctors. Among them, in order to count the doctors who have prescribed the same confirmed cause of disease in history, the hospital where they are located needs to be authorized in advance to share the medical big data with the online consultation platform. The hospital can be a tertiary hospital scattered across the country. The total number of times the alternative doctors have prescribed the same confirmed cause in history is counted. Here, statistics can be performed based on the medical database associated with the hospital where the alternative doctors are located, and the treatment effects of the targets corresponding to the same confirmed cause of disease are traced and the total number of effective treatments is counted. The treatment effects are actively traced and counted based on the online consultation platform to obtain the treatment time and treatment costs corresponding to different effective treatment targets. The corresponding median treatment time and treatment cost are calculated based on the statistical treatment time and treatment cost corresponding to all effective treatment targets;

[0054] Extract the total number of times Cz, the total number of effective treatments Cr, the median treatment duration Cs, and the median treatment cost Cf of the candidate doctors’ corresponding history, and sort and combine them to obtain the candidate monitoring sequence;

[0055] According to the alternative monitoring sequence, the implementation status formula is used to calculate the implementation status degree η corresponding to the alternative doctor; the implementation status formula is: Where, Cz′, Cr′, Cs′, and Cf′ are the total number of standard prescriptions for the same diagnosed cause, the total number of standard patients, the standard treatment duration, and the standard treatment cost, respectively; c1, c2, c3, and c4 are all proportionality coefficients, and 0<c3≤c4<c2≤c1<1. The specific value of the proportionality coefficient is not restricted as long as the restriction condition is met. The proportionality coefficient is used to differentiate the importance of the corresponding calculation of different data items in the calculation process;

[0056] All candidate doctors are sorted in descending order according to the value of the implementation status, and the first K candidate doctors are marked as recommended doctors, where K is a positive integer, and the specific value can be 3. At the same time, the treatment departments and hospitals to which all recommended doctors belong are obtained and combined to obtain excellent medical resource information.

[0057] In the embodiment of the present invention, for targets with poor medical treatment results identified in previous active monitoring and analysis, big data on medical treatments with the same cause of treatment is efficiently and conveniently obtained through the Internet platform and integrated and analyzed to obtain excellent medical resources including several recommended doctors. The excellent medical resources actively identified and obtained are used to actively share and recommend medical resources for abnormal targets marked in the previous analysis, thereby improving the autonomous integration and utilization of online medical services in the Internet economy and the initiative and pertinence of resource sharing interaction.

[0058] In addition, the formulas involved in the above are all dimensionless and numerical calculations. They are a formula that is closest to the actual situation obtained by collecting a large amount of data and simulating it with simulation software.

[0059] In the several embodiments provided by the present invention, it should be understood that the disclosed system can be implemented in other ways. For example, the above-described embodiments of the invention are only illustrative, for example, the division of modules is only a logical function division, and there may be other division methods in actual implementation.

[0060] The modules described as separate components may or may not be physically separated, and the components shown as modules may or may not be physical modules, and may be located in one place or distributed on multiple network modules. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0061] In addition, each functional module in each embodiment of the present invention may be integrated into one processing module, or each module may exist physically separately, or two or more modules may be integrated into one module. The above-mentioned integrated module may be implemented in the form of hardware or in the form of hardware plus software functional modules.

[0062] It is obvious to those skilled in the art that the present invention is not limited to the details of the above exemplary embodiments, and that the present invention can be implemented in other specific forms without departing from the basic features of the present invention.

[0063] Finally, it should be noted that the above embodiments are only used to illustrate the technical solution of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, ordinary operation and maintenance personnel in the field should understand that the technical solution of the present invention can be modified or replaced by equivalents without departing from the spirit and scope of the technical solution of the present invention.

Claims

1. An Internet economic service management system based on data analysis, characterized in that: include: The target consultation data monitoring and processing module is used to monitor and count the basic information of all targets that implement online consultation on the online consultation platform, and to process and filter the basic information to obtain normal targets and abnormal targets; Among them, when the target conducts online consultation through the online consultation platform, the target's identity information is obtained through authorization, and the obtained identity information is input into the consultation database associated with the online consultation platform for retrieval and traversal to obtain the first consultation time and its corresponding confirmed cause of disease; Calculate the interval time Tj based on the first visit time and the target's current consultation time, and obtain all the consultation fees Fj paid by the target since the first visit time; Extract the target interval time and the consultation fee value and calculate the consultation necessity μ corresponding to the target through the formula; the calculation formula of consultation necessity μ is: ; Where Tj0 is the standard interval duration corresponding to the same confirmed cause, Fj0 is the standard medical fee corresponding to the same confirmed cause; α1 is the duration correction factor corresponding to the same confirmed cause; α2 is the fee correction factor corresponding to the same confirmed cause; The steps for obtaining the duration correction factor α1 and the cost correction factor α2 corresponding to the same confirmed cause include: Active treatment result statistics are implemented for all targets with the same diagnosed cause in history, and targets with feedback of treatment results and completed treatment are marked as effective targets; The treatment duration and treatment cost corresponding to all targets are counted and sorted and combined respectively to obtain the treatment duration sequence and treatment cost sequence; According to the treatment time sequence and treatment cost sequence, the corresponding total treatment time Z1 and total treatment cost Z2 are calculated, as well as the median treatment time z1 corresponding to the treatment time sequence and the median treatment cost z2 corresponding to the treatment cost sequence; The duration correction factor α1 and the cost correction factor α2 are calculated by the correction factor formula; the correction factor formula is: αk=(Zk-zk) / Zk; where k=1, 2; Count and process the target's consultation duration and consultation fee data, obtain the corresponding consultation necessity through calculation, and filter and mark the target's consultation type according to the consultation necessity; The marked target evaluation and recommendation module is used to proactively push consultation information on the medical status and recommended medical resources to the marked abnormal targets through the online consultation platform, and to count and combine the status consultation results and recommended consultation results confirmed by the abnormal targets to obtain a feedback result set, conduct a necessity analysis on the feedback result set, and proactively push excellent medical resource information with the same confirmed cause to the marked abnormal targets in an adaptive manner; Among them, the status consultation results and recommended consultation results in the feedback result set are traversed and counted. If the traversed status consultation result is that the medical treatment is invalid and the recommended consultation result is agreed, a recommendation instruction is generated and the excellent medical resource information with the same confirmed cause of the disease is actively pushed to the abnormal target. The excellent medical resource information is composed of a combination of several recommended doctors and their respective medical departments and hospitals obtained through analysis.

2. The Internet economic service management system based on data analysis according to claim 1 is characterized in that: When screening and marking the targets according to the consultation necessity, the consultation necessity is input into the consultation analysis and recognition model for data analysis and output of the corresponding target identification value, and the targets are dynamically marked according to the target identification value; The target identification value contains a value of 0 or 1; the expression of the consulting analysis recognition model is: ; In the formula, μ´ is the consultation necessity threshold; According to the target identification value whose output value is 0, the target is marked as a normal target, and according to the target identification value whose output value is 1, the target is marked as an abnormal target.

3. The Internet economic service management system based on data analysis according to claim 2 is characterized in that: According to the recommended instructions, the doctors who have historically prescribed the same confirmed cause of illness are counted and marked as alternative doctors. The total number of times the alternative doctors have historically prescribed the same confirmed cause of illness is counted, and the treatment effects of the corresponding targets of the same confirmed cause are traced and the total number of effective treatments is counted. The treatment duration and treatment costs corresponding to different effective treatment targets are obtained, and the corresponding median treatment duration and median treatment cost are calculated based on the statistical treatment duration and treatment costs corresponding to all effective treatment targets.

4. The Internet economic service management system based on data analysis according to claim 3 is characterized in that: Extract the total number of times Cz, the total number of effective treatments Cr, the median treatment duration Cs, and the median treatment cost Cf of the candidate doctors’ corresponding history, and sort and combine them to obtain the candidate monitoring sequence; According to the alternative monitoring sequence, the implementation status degree η corresponding to the alternative doctor is calculated through the implementation status formula.

5. The Internet economic service management system based on data analysis according to claim 4 is characterized in that: The implementation status formula is: ; Wherein, Cz´, Cr´, Cs´, Cf´ are the standard total number of prescriptions for the same diagnosed cause, the standard total number of patients, the standard treatment duration, and the standard treatment cost respectively; c1, c2, c3, and c4 are all proportional coefficients, and 0<c3≤c4<c2≤c1<1.

6. The Internet economic service management system based on data analysis according to claim 5 is characterized in that: All candidate doctors are sorted in descending order according to the value of the implementation status, and the top K candidate doctors are marked as recommended doctors. At the same time, the treatment departments and hospitals to which all recommended doctors belong are obtained and combined to obtain excellent medical resource information.

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