Integrated auxiliary prevention and control method for accurate diagnosis and treatment of infectious diseases of elderly patients

Abstract

The invention relates to the technical field of medical information processing, in particular to an integrated auxiliary prevention and control method for accurate diagnosis and treatment of infectious diseases of elderly patients, which comprises the following steps: acquiring medicine taking time change characteristics of each elderly patient; obtaining the incidence frequency degree of each elderly patient; according to the medicine taking time change characteristics, the incidence frequency degree and the medicine taking duration of the elderly patients, the medicine resistance degree of each elderly patient is obtained; obtaining the contact closeness degree of each cross path node; clustering all the elderly patients according to the drug resistance degree difference between the elderly patients to obtain two class clusters; the risk degree of each cross path node is obtained according to the number ratio, the drug resistance degree and the contact closeness degree of the elderly patients in the class cluster with the high drug resistance degree in the cross path nodes; and determining the final drug resistance degree of each elderly patient. According to the method, the accuracy of determining the drug resistance degree of the elderly patient is improved, so that the elderly patient with high drug resistance degree can be better determined.

Description

Technical Field

[0001] The present invention relates to the technical field of medical information processing, and in particular to an integrated auxiliary prevention and control method for accurate diagnosis and treatment of infectious diseases in elderly patients. Background Art

[0002] The integrated auxiliary prevention and control of infectious diseases in elderly patients with precise diagnosis and treatment aims to improve the prevention and control capabilities of infectious diseases in elderly patients. As elderly patients age, their immune systems will gradually weaken and be disturbed by various infectious diseases, so elderly patients usually take a lot of antibiotics to resist bacterial infections. However, since antibiotics can reduce the sensitivity of bacteria to antibiotics, medical staff need to determine the current drug resistance of elderly patients based on their current medication history before formulating treatment plans for them.

[0003] Existing methods only evaluate the length of time elderly patients have taken medication when determining their degree of drug resistance. Since drug-resistant bacteria can be transmitted through direct contact between elderly patients, causing other elderly patients to also be infected with resistant bacteria or develop drug resistance, this will lead to deviations in determining the degree of drug resistance in elderly patients, and the degree of drug resistance in elderly patients will be inaccurately determined, and thus elderly patients with high levels of drug resistance cannot be well identified. Summary of the invention

[0004] To solve the above problems, the present invention provides an integrated auxiliary prevention and control method for accurate diagnosis and treatment of infectious diseases in elderly patients.

[0005] The present invention provides an integrated auxiliary prevention and control method for accurate diagnosis and treatment of infectious diseases in elderly patients using the following technical solutions:

[0006] An embodiment of the present invention provides an integrated auxiliary prevention and control method for accurate diagnosis and treatment of infectious diseases in elderly patients, the method comprising the following steps:

[0007] Among a number of elderly patients, obtain the duration of each elderly patient's use of prescription drugs purchased during each visit to the doctor in the past six months, the time of each visit, and the daily driving route;

[0008] According to the changes in the duration of taking prescription drugs purchased by elderly patients each time they see a doctor, the characteristics of the changes in medication time for each elderly patient are obtained; according to the changes in the time interval between each visit and the last visit of an elderly patient, the frequency of illness for each elderly patient is obtained; according to the characteristics of the changes in medication time, the frequency of illness, and the duration of medication taken by elderly patients, the degree of drug resistance of each elderly patient is obtained;

[0009] According to the driving paths of all elderly patients, several cross-path nodes are obtained; according to the length of stay of all elderly patients at the cross-path nodes in the past six months and the number of elderly patients, the contact density of each cross-path node is obtained; according to the differences in drug resistance among the elderly patients, all elderly patients are clustered to obtain two clusters; according to the proportion of elderly patients in the cluster with high drug resistance in the cross-path nodes, the drug resistance level and the contact density, the risk level of each cross-path node is obtained;

[0010] The drug resistance level is corrected according to the risk level of elderly patients at multiple cross-path nodes to obtain the final drug resistance level of each elderly patient; based on the size of the final drug resistance level, a number of elderly patients with high drug resistance levels are screened out.

[0011] Furthermore, the method of obtaining the change characteristics of medication time for each elderly patient according to the change in the duration of taking the prescription drugs purchased by the elderly patient each time when seeing a doctor includes the following specific steps:

[0012] For any elderly patient, the difference between the length of time the elderly patient can take the prescription drugs purchased each time he sees a doctor and the length of time the elderly patient can take the prescription drugs purchased during the last visit to the doctor is used as the elderly patient's medication time change parameter, and the average value of all the elderly patient's medication time change parameters is used as the elderly patient's medication time change feature.

[0013] Furthermore, the frequency of illness of each elderly patient is obtained according to the change of the time interval between each visit to the doctor and the last visit to the doctor, and the specific steps include the following:

[0014] For any elderly patient, the time interval between each visit and the last visit is recorded as the time characteristic of each visit, the difference between the time characteristic of each visit and the time characteristic of the last visit is taken as the initial time interval characteristic of the elderly patient, the average value of all initial time interval characteristics of the elderly patient's visits is taken as the first change characteristic of the elderly patient's time interval between visits; the reciprocal of the average value of the time characteristics of all visits of the elderly patient is taken as the second change characteristic of the elderly patient's time interval between visits; based on the first change characteristic and the second change characteristic, the frequency of illness of the elderly patient is obtained.

[0015] Furthermore, the method of obtaining the frequency of onset of disease in elderly patients according to the first change characteristic and the second change characteristic comprises the following specific steps:

[0016] The inverse proportional value of the first change characteristic and the second change characteristic are multiplied to obtain the frequency of onset of the disease in elderly patients.

[0017] Furthermore, the method of obtaining the drug resistance of each elderly patient according to the characteristics of the change of medication time, the frequency of onset, and the duration of medication of the elderly patient includes the following specific steps:

[0018] For any elderly patient, the characteristics of changes in medication time, the frequency of onset, and the duration of medication are multiplied and normalized to obtain the degree of drug resistance of the elderly patient.

[0019] Furthermore, the contact density of each cross-path node is obtained according to the length of stay of all elderly patients at the cross-path node in the past six months and the number of elderly patients, including the following specific steps:

[0020] For any cross-path node, the average length of stay of all elderly patients at the cross-path node in the past six months and the number of all elderly patients at the cross-path node in the past six months are multiplied to obtain the contact density of the cross-path node.

[0021] Furthermore, clustering all elderly patients according to the differences in drug resistance among elderly patients to obtain two clusters includes the following specific steps:

[0022] K-means clustering was performed on all elderly patients, and the absolute value of the difference in drug resistance between elderly patients was used as the distance metric to obtain two clusters.

[0023] Furthermore, the risk level of each cross-path node is obtained according to the proportion of elderly patients in the cluster with high drug resistance, drug resistance and close contact in the cross-path node, and the specific steps include the following:

[0024] For any cross-path node, obtain the proportion of the number of elderly patients who belong to the high-resistance cluster among all elderly patients at the cross-path node in the past six months, obtain the average drug resistance level of the elderly patients who belong to the high-resistance cluster among all elderly patients at the cross-path node in the past six months, multiply and normalize the proportion of the number of people, the average drug resistance level, and the contact density of the cross-path node to obtain the risk level of the cross-path node.

[0025] Furthermore, the method of correcting the drug resistance level according to the risk level of the elderly patient at multiple cross-path nodes to obtain the final drug resistance level of each elderly patient includes the following specific steps:

[0026] Acquire all cross-path nodes in the target patient's driving path; use the target patient's drug resistance level as the drug resistance level of the first cross-path node in the target patient's driving path; multiply the drug resistance level of the first cross-path node in the target patient's driving path and the risk level of the first cross-path node to obtain the drug resistance level of the second cross-path node in the target patient's driving path; multiply the drug resistance level of the second cross-path node in the target patient's driving path and the risk level of the second cross-path node to obtain the drug resistance level of the third cross-path node in the target patient's driving path, and so on, to obtain the drug resistance level of the last cross-path node in the target patient's driving path, which is used as the final drug resistance level of the target patient.

[0027] Furthermore, the method of screening out a number of elderly patients with high drug resistance according to the final drug resistance level includes the following specific steps:

[0028] A first threshold is preset, and elderly patients whose final drug resistance level is greater than the first threshold are regarded as elderly patients with high drug resistance.

[0029] The beneficial effect of the technical solution of the present invention is as follows: after obtaining the relevant information of the elderly patients, the present invention obtains the drug resistance of each elderly patient by analyzing the changes in the duration of taking the prescription drugs purchased by the elderly patients each time they see a doctor and the changes in the time interval between each visit and the last visit of the elderly patients, so that the initial drug resistance quantification is more reasonable and accurate, avoiding the large error caused by evaluating the drug resistance of the elderly patients only by a single medication duration; then, by analyzing the stay time of all elderly patients in the cross-path nodes in the elderly patients' driving paths in the past six months, the number of elderly patients, the proportion of elderly patients in the clusters with high drug resistance in the cross-path nodes, the drug resistance and the closeness of contact, the risk degree of the cross-path nodes is obtained, and the risk degree evaluates the impact of the spread of drug-resistant bacteria in contact between different elderly patients; finally, the drug resistance is corrected by the risk degree of the elderly patients at multiple cross-path nodes to obtain the final drug resistance of each elderly patient; and according to the size of the final drug resistance, a number of elderly patients with high drug resistance are screened out, thereby improving the accuracy of determining the drug resistance of the elderly patients, thereby better determining the elderly patients with high drug resistance. BRIEF DESCRIPTION OF THE DRAWINGS

[0030] 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 some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0031] Figure 1 A flowchart of the steps of a method for integrated auxiliary prevention and control of infectious diseases in elderly patients provided by one embodiment of the present invention;

[0032] Figure 2 A flow chart for obtaining elderly patients with high drug resistance provided by one embodiment of the present invention. DETAILED DESCRIPTION

[0033] In order to further illustrate the technical means and effects adopted by the present invention to achieve the predetermined invention purpose, the following is a detailed description of the specific implementation method, structure, characteristics and effects of an integrated auxiliary prevention and control method for accurate diagnosis and treatment of infectious diseases in elderly patients proposed by the present invention in combination with the accompanying drawings and preferred embodiments. In the following description, different "one embodiment" or "another embodiment" does not necessarily refer to the same embodiment. In addition, specific features, structures or characteristics in one or more embodiments may be combined in any suitable form.

[0034] Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs.

[0035] The specific scheme of the method for integrated auxiliary prevention and control of infectious diseases in elderly patients provided by the present invention is described in detail below with reference to the accompanying drawings.

[0036] See also Figure 1 and Figure 2 , which shows a flowchart of the steps of a method for integrated auxiliary prevention and control of infectious diseases in elderly patients provided by an embodiment of the present invention and a flowchart for obtaining elderly patients with high drug resistance, the method comprising the following steps:

[0037] Step S001: among a number of elderly patients, obtain the duration of time that each elderly patient can take the prescription drugs purchased each time when seeing a doctor in the past six months, the time of each visit, and the daily driving route.

[0038] It should be noted that the main purpose of this embodiment is to determine the more accurate drug resistance of elderly patients, and then screen out elderly patients with drug resistance problems, so that subsequent medical staff can re-evaluate the types of drug-resistant bacteria and their overall health status, and further enhance the prevention and control of accurate diagnosis and treatment of infectious diseases in elderly patients. Before starting the analysis, first collect the required data.

[0039] Specifically, among a number of elderly patients, the time that each elderly patient can take the prescription medicine purchased during each visit to the doctor in the past six months, the time of each visit, and the daily driving route are obtained. It should be noted that obtaining the time that each elderly patient can take the prescription medicine purchased during each visit to the doctor in the past six months, the time of each visit, and the daily driving route is an existing method and will not be repeated in this embodiment.

[0040] At this point, we have obtained the length of time that each elderly patient can take the prescription drugs purchased each time they see a doctor in the past six months, the time of each visit, and the daily driving route.

[0041] Step S002: based on the changes in the length of time that the elderly patients can take the prescription drugs they purchase each time they see a doctor, obtain the changing characteristics of the medication time for each elderly patient; based on the changes in the time interval between each visit and the last visit of the elderly patient, obtain the frequency of illness for each elderly patient; based on the changing characteristics of the medication time, the frequency of illness, and the length of time that the elderly patients take the drugs, obtain the degree of drug resistance for each elderly patient.

[0042] It should be noted that as elderly patients age, their immune systems will gradually weaken and will be affected by various infectious diseases, so elderly patients usually take a lot of antibiotics to resist bacterial infections. Since drug-resistant bacteria can spread between elderly patients through contact between them, other elderly patients also have drug resistance, which will affect the health of other elderly patients. Therefore, it is necessary to analyze the degree of drug resistance of each elderly patient in order to better assist in prevention and control. Since the degree of drug resistance of elderly patients is related to the time they take medicine, if the time of taking medicine is getting longer and longer, the drug resistance of the elderly patient is stronger, that is, the greater the degree of drug resistance, so here it is necessary to first analyze the changes in the time of taking prescription drugs purchased by elderly patients during all visits to the doctor.

[0043] Preferably, in one embodiment of the present invention, according to the change in the duration of taking prescription drugs purchased by the elderly patients each time they see a doctor, the change characteristics of the medication time of each elderly patient are obtained, as follows:

[0044] For any elderly patient, the difference between the length of time the elderly patient can take the prescription drugs purchased each time he sees a doctor and the length of time the elderly patient can take the prescription drugs purchased during the last visit to the doctor is used as the elderly patient's medication time change parameter, and the average value of all the elderly patient's medication time change parameters is used as the elderly patient's medication time change feature.

[0045] As a specific example, the specific method for obtaining the characteristics of the change in medication time is as follows;

[0046] Any elderly patient is recorded as the target patient.

[0047]

[0048] Where n is the number of times the target patient visits the doctor; t i The duration that the target patient can take the prescription drugs purchased during the i-th visit to the doctor; t i-1 is the length of time that the target patient can take the prescription drugs purchased during the i-1th visit to the doctor; y is the change characteristic of the target patient's medication taking time.

[0049] It should be noted that since the drug resistance of elderly patients is related to the duration of medication, if the duration of medication is longer and longer, the drug resistance of the elderly patients is stronger. Since the duration of medication for elderly patients is generally longer, this embodiment analyzes the duration of medication between two consecutive times, t i -t i-1 The larger it is, the longer the elderly patients take their medications, and the greater the variation in medication time.

[0050] It should be noted that the above analysis of the changes in the time of taking prescription drugs purchased by elderly patients during all visits to the doctor, that is, the characteristics of the change in medication time, is related not only to the time of taking the drugs, but also to the frequency of the elderly patients' illnesses. In order to obtain a more accurate degree of drug resistance for more elderly patients, it is also necessary to analyze the frequency of illness of each elderly patient. The greater the frequency of illness, the stronger the elderly patient's drug resistance. Since the frequency of illness of elderly patients is mainly related to the frequency of their visits to the doctor, if the time interval between each visit of the elderly patient is getting shorter and shorter, it means that the illness is more frequent. Therefore, this embodiment obtains the frequency of illness of elderly patients by analyzing the time changes between each visit of the elderly patient and the last visit.

[0051] Preferably, in one embodiment of the present invention, the frequency of illness of each elderly patient is obtained according to the change in the time interval between each visit to the doctor and the last visit to the doctor, as follows:

[0052] For any elderly patient, the time interval between each visit and the last visit is recorded as the time characteristic of each visit of the elderly patient, the difference between the time characteristic of each visit and the time characteristic of the last visit is taken as the initial time interval characteristic of the elderly patient, the average value of all initial time interval characteristics of the elderly patient's visits is taken as the first change characteristic of the elderly patient's time interval between visits; the reciprocal of the average value of the time characteristics of all visits of the elderly patient is taken as the second change characteristic of the elderly patient's time interval between visits; the inverse proportional value of the first change characteristic and the second change characteristic are multiplied to obtain the frequency of illness of the elderly patient.

[0053] As a specific example, the specific method for obtaining the frequency of the disease is as follows:

[0054]

[0055] Where n is the number of times the target patient visits the doctor; g a is the time interval between the target patient's first visit to the doctor and the last visit to the doctor; g a-1 is the time interval between the target patient's a-1th visit and the last visit; g is the mean time interval between all visits and the last visit of the target patient; exp[] is an exponential function with a natural constant as the base. This embodiment uses the exp[-U] model to present an inverse proportional relationship, and U is the input of the model; w is the frequency of the target patient's illness.

[0056] It should be noted that the frequency of onset of elderly patients is mainly related to the frequency of their visits to the doctor. If the time interval between each visit is getting shorter, it means that the onset is more frequent. Therefore, the above formula obtains the frequency of onset of elderly patients by analyzing the time change between each visit and the last visit. g a -g a-1 The smaller g is, the shorter the time interval between elderly patients' medical treatment and the more frequent the disease attacks. At the same time, if the time interval between each medical treatment and the last one is also short as a whole, that is, the smaller g is, the more frequent the disease attacks are.

[0057] It should be noted that since drug-resistant bacteria can spread among elderly patients through contact between them, other elderly patients may also have drug resistance, which will affect the health of other elderly patients. Therefore, it is necessary to analyze the degree of drug resistance of each elderly patient in order to better assist in prevention and control. The above analysis respectively analyzes the characteristics of changes in medication time for elderly patients and the frequency of onset of elderly patients. The degree of drug resistance of each elderly patient is determined by combining these two characteristics and the duration of medication for the elderly patients themselves.

[0058] Preferably, in one embodiment of the present invention, the drug resistance of each elderly patient is obtained according to the characteristics of the change of medication time, the frequency of onset, and the duration of medication taken by the elderly patient, as follows:

[0059] For any elderly patient, the characteristics of changes in medication time, the frequency of onset, and the duration of medication are multiplied and normalized to obtain the degree of drug resistance of the elderly patient.

[0060] As a specific example, the specific method for obtaining the drug resistance level is as follows:

[0061] p = softmax(y×w×G)

[0062] Where y is the change characteristic of the target patient's medication time; w is the frequency of the target patient's onset; G is the duration of the target patient's medication; softmax() is the softmax function used for normalization; and p is the drug resistance of the target patient.

[0063] It should be noted that the larger y is, the longer the elderly patients take medication, and the longer the medication, the higher the drug resistance of the elderly patients will be, and the greater the degree of drug resistance will be; the larger w is, the more frequent the onset of the disease in the elderly patients, and the greater the corresponding degree of drug resistance; the larger G is, the longer the total medication time of the elderly patients, and the greater the corresponding degree of drug resistance.

[0064] At this point, the degree of drug resistance of each elderly patient was obtained.

[0065] Step S003, according to the driving paths of all elderly patients, obtain several cross-path nodes; according to the length of stay of all elderly patients at the cross-path nodes in the past six months and the number of elderly patients, obtain the contact density of each cross-path node; according to the differences in drug resistance among the elderly patients, cluster all elderly patients to obtain two clusters; according to the proportion of elderly patients in the cluster with high drug resistance in the cross-path nodes, the drug resistance level and the contact density, obtain the risk level of each cross-path node.

[0066] It should be noted that since drug-resistant bacteria can be spread among elderly patients through contact between them, it will affect the degree of drug resistance of elderly patients. In order to facilitate subsequent analysis, it is necessary to determine the cross-path nodes in the elderly patients' travel paths, that is, the places where they come into contact with other elderly patients.

[0067] Specifically, several cross-path nodes are obtained according to the driving paths of all elderly patients. It should be noted that obtaining several cross-path nodes according to the driving paths of all elderly patients is an existing method and will not be repeated in this embodiment, wherein the driving paths consider all driving paths of all elderly patients in the past six months.

[0068] It should be noted that the length of time each elderly patient stays at each cross-path node and the density of people at the cross-path node are different, which will affect the final degree of drug resistance of the elderly patients. Therefore, it is necessary to quantify the contact intensity of each cross-path node.

[0069] Preferably, in one embodiment of the present invention, the contact closeness of each cross-path node is obtained according to the length of stay of all elderly patients at the cross-path node in the last six months and the number of elderly patients, as follows:

[0070] For any cross-path node, the average length of stay of all elderly patients at the cross-path node in the past six months and the number of all elderly patients at the cross-path node in the past six months are multiplied to obtain the contact density of the cross-path node.

[0071] As a specific example, the specific method for obtaining the contact tightness is as follows:

[0072] s v =t v ×N v

[0073] Where, t v is the average length of stay of all elderly patients at the vth cross-path node in the past six months; N v is the number of all elderly patients at the vth cross-path node in the last six months; s v is the contact density of the vth cross-path node.

[0074] It should be noted that the length of time each elderly patient stays at each cross-path node and the population density of the cross-path node are different, which will affect the final degree of drug resistance of the elderly patients. Therefore, it is necessary to quantify the contact density of each cross-path node. Since the contact density is mainly related to the length of time all elderly patients stay at the cross-path node in the past six months and the number of elderly patients at the cross-path node, the longer the stay time and the more elderly patients there are, the greater the contact density of the cross-path node.

[0075] It should be noted that since the drug resistance levels of other elderly patients contacted in each cross-path node are different, in order to better obtain the risk situation of each cross-path node, it is necessary to cluster all elderly patients according to the differences in drug resistance levels among elderly patients for subsequent analysis.

[0076] Specifically, all elderly patients were clustered according to the differences in drug resistance among them, and two clusters were obtained, as follows:

[0077] K-means clustering was performed on all elderly patients, and the absolute value of the difference in drug resistance between elderly patients was used as the distance metric to obtain two clusters.

[0078] It should be noted that in order to better obtain the final drug resistance level of each elderly patient, it is necessary to analyze the risk level of each cross-path node. Since elderly patients will come into contact and cause the spread of drug-resistant bacteria, which will in turn affect the drug resistance level of elderly patients, it is necessary to analyze the risk level of each cross-path node. Since the drug resistance levels of other elderly patients contacted in each cross-path node are different, the elderly patients with high drug resistance levels are more affected. At the same time, the closer the contact level of the cross-path node is, the higher the risk level of the cross-path node will be, which will cause other elderly patients to also develop drug resistance.

[0079] Preferably, in one embodiment of the present invention, the risk level of each cross-path node is obtained according to the proportion of elderly patients in the cluster with high drug resistance, drug resistance and close contact in the cross-path node, as follows:

[0080] For any cross-path node, obtain the proportion of the number of elderly patients who belong to the high-resistance cluster among all elderly patients at the cross-path node in the past six months, obtain the average drug resistance level of the elderly patients who belong to the high-resistance cluster among all elderly patients at the cross-path node in the past six months, multiply and normalize the proportion of the number of people, the average drug resistance level, and the contact density of the cross-path node to obtain the risk level of the cross-path node.

[0081] As a specific example, the specific method for obtaining the risk level is as follows:

[0082] The average drug resistance of elderly patients in each cluster is obtained, and the cluster corresponding to the maximum average drug resistance is recorded as the cluster with high drug resistance.

[0083]

[0084] In the formula, m v N is the number of the vth cross-path node in the high-drug resistance cluster among all elderly patients in the past six months; v is the number of all elderly patients at the vth cross-path node in the last six months; is the average drug resistance of the elderly patients belonging to the high drug resistance cluster in the vth cross-path node in the past six months; s v is the contact density of the vth cross-path node; softmax() is the softmax function used for normalization; r v is the risk level of the vth cross-path node.

[0085] It should be noted that in order to better obtain the final drug resistance level of each elderly patient, it is necessary to analyze the risk level of each cross-path node. Since elderly patients may come into contact and cause the spread of drug-resistant bacteria, which in turn affects the drug resistance level of elderly patients, it is necessary to analyze the risk level of each cross-path node. It indicates the proportion of elderly patients in the cross-path node who belong to the high-drug resistance cluster in the past six months. The larger it is, the more elderly patients with high drug resistance there are in the cross-path node, and the higher the risk level of the cross-path node, the greater the impact on other elderly patients. The larger the value is, the higher the overall drug resistance of the elderly patients in the cross-path node is, and the higher the risk level of the cross-path node is. v The larger it is, the closer the contact between people in the cross-path node is, and the higher the risk level of the cross-path node is.

[0086] At this point, the risk level of each cross-path node is obtained.

[0087] Step S004: correct the drug resistance level according to the risk level of the elderly patients at multiple cross-path nodes to obtain the final drug resistance level of each elderly patient; and screen out a number of elderly patients with high drug resistance levels according to the size of the final drug resistance level.

[0088] It should be noted that the risk level of each cross-path node is obtained above. The drug resistance level of each elderly patient is corrected by combining the risk level of the cross-path node to obtain the final drug resistance level of each patient. The final drug resistance level takes into account the elderly patient's contact with multiple cross-path nodes, making the quantification of drug resistance more accurate.

[0089] Specifically, the drug resistance level is corrected according to the risk level of the elderly patients at multiple cross-path nodes to obtain the final drug resistance level of each elderly patient, as follows:

[0090] Acquire all cross-path nodes in the target patient's driving path; use the target patient's drug resistance level as the drug resistance level of the first cross-path node in the target patient's driving path; multiply the drug resistance level of the first cross-path node in the target patient's driving path and the risk level of the first cross-path node to obtain the drug resistance level of the second cross-path node in the target patient's driving path; multiply the drug resistance level of the second cross-path node in the target patient's driving path and the risk level of the second cross-path node to obtain the drug resistance level of the third cross-path node in the target patient's driving path, and so on, to obtain the drug resistance level of the last cross-path node in the target patient's driving path, which is used as the final drug resistance level of the target patient.

[0091] It should be noted that the above-mentioned final drug resistance level of each elderly patient is obtained. By setting a suitable threshold, elderly patients with high drug resistance levels can be screened out.

[0092] Specifically, according to the final degree of drug resistance, several elderly patients with high drug resistance were screened out, as follows:

[0093] A first threshold is preset. This embodiment is described with the first threshold being 0.7, and elderly patients whose final drug resistance level is greater than the first threshold are regarded as elderly patients with high drug resistance.

[0094] It should be noted that elderly patients with high levels of drug resistance are elderly patients with drug resistance problems. Subsequent medical staff need to re-evaluate the types of their drug-resistant bacteria and overall health status to further strengthen the prevention and control of these elderly patients.

[0095] Through the above steps, an integrated auxiliary prevention and control method for precise diagnosis and treatment of infectious diseases in elderly patients is completed.

[0096] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the principles of the present invention should be included in the protection scope of the present invention.

Claims

1. A method for integrated auxiliary prevention and control of infectious diseases in elderly patients, characterized in that: The method comprises the following steps: Among a number of elderly patients, obtain the duration of each elderly patient's use of prescription drugs purchased during each visit to the doctor in the past six months, the time of each visit, and the daily driving route; According to the changes in the duration of taking prescription drugs purchased by elderly patients each time they see a doctor, the characteristics of the changes in medication time for each elderly patient are obtained; according to the changes in the time interval between each visit and the last visit of an elderly patient, the frequency of illness for each elderly patient is obtained; according to the characteristics of the changes in medication time, the frequency of illness, and the duration of medication taken by elderly patients, the degree of drug resistance of each elderly patient is obtained; According to the driving paths of all elderly patients, several cross-path nodes are obtained; according to the length of stay of all elderly patients at the cross-path nodes in the past six months and the number of elderly patients, the contact density of each cross-path node is obtained; according to the differences in drug resistance among the elderly patients, all elderly patients are clustered to obtain two clusters; according to the proportion of elderly patients in the cluster with high drug resistance in the cross-path nodes, the drug resistance level and the contact density, the risk level of each cross-path node is obtained; The drug resistance level is corrected according to the risk level of elderly patients at multiple cross-path nodes to obtain the final drug resistance level of each elderly patient; based on the size of the final drug resistance level, a number of elderly patients with high drug resistance levels are screened out.

2. According to claim 1, a method for integrated auxiliary prevention and control of infectious diseases in elderly patients, characterized in that: The method of obtaining the change characteristics of medication time for each elderly patient according to the change of the duration of taking the prescription drugs purchased by the elderly patient each time when seeing a doctor includes the following specific steps: For any elderly patient, the difference between the length of time the elderly patient can take the prescription drugs purchased each time he sees a doctor and the length of time the elderly patient can take the prescription drugs purchased during the last visit to the doctor is used as the elderly patient's medication time change parameter, and the average value of all the elderly patient's medication time change parameters is used as the elderly patient's medication time change feature.

3. According to claim 1, a method for integrated auxiliary prevention and control of infectious diseases in elderly patients, characterized in that: The specific steps of obtaining the frequency of illness of each elderly patient according to the change of the time interval between each visit to the doctor and the last visit to the doctor include the following: For any elderly patient, the time interval between each visit and the last visit is recorded as the time characteristic of each visit, the difference between the time characteristic of each visit and the time characteristic of the last visit is taken as the initial time interval characteristic of the elderly patient, the average value of all initial time interval characteristics of the elderly patient's visits is taken as the first change characteristic of the elderly patient's time interval between visits; the reciprocal of the average value of the time characteristics of all visits of the elderly patient is taken as the second change characteristic of the elderly patient's time interval between visits; based on the first change characteristic and the second change characteristic, the frequency of illness of the elderly patient is obtained.

4. According to claim 3, a method for integrated auxiliary prevention and control of infectious diseases in elderly patients, characterized in that: The method of obtaining the frequency of onset of disease in elderly patients according to the first change characteristic and the second change characteristic comprises the following specific steps: The inverse proportional value of the first change characteristic and the second change characteristic are multiplied to obtain the frequency of onset of the disease in elderly patients.

5. According to claim 1, a method for integrated auxiliary prevention and control of infectious diseases in elderly patients with precise diagnosis and treatment, characterized in that: The method of obtaining the drug resistance of each elderly patient according to the characteristics of the change of medication time, the frequency of onset, and the duration of medication of the elderly patient includes the following specific steps: For any elderly patient, the characteristics of changes in medication time, the frequency of onset, and the duration of medication are multiplied and normalized to obtain the elderly patient's drug resistance.

6. According to claim 1, a method for integrated auxiliary prevention and control of infectious diseases in elderly patients with precise diagnosis and treatment, characterized in that: The contact density of each cross-path node is obtained according to the length of stay of all elderly patients at the cross-path node in the past six months and the number of elderly patients, and the specific steps include the following: For any cross-path node, the average length of stay of all elderly patients at the cross-path node in the past six months and the number of all elderly patients at the cross-path node in the past six months are multiplied to obtain the contact density of the cross-path node.

7. According to claim 1, a method for integrated auxiliary prevention and control of infectious diseases in elderly patients, characterized in that: The method of clustering all elderly patients according to the differences in drug resistance among elderly patients to obtain two clusters includes the following specific steps: K-means clustering was performed on all elderly patients, and the absolute value of the difference in drug resistance between elderly patients was used as the distance metric to obtain two clusters.

8. According to claim 1, a method for integrated auxiliary prevention and control of infectious diseases in elderly patients with precise diagnosis and treatment, characterized in that: The risk level of each cross-path node is obtained according to the proportion of elderly patients in the cluster with high drug resistance, drug resistance and close contact in the cross-path node, including the following specific steps: For any cross-path node, obtain the proportion of the number of elderly patients who belong to the high-resistance cluster among all elderly patients at the cross-path node in the past six months, obtain the average drug resistance level of the elderly patients who belong to the high-resistance cluster among all elderly patients at the cross-path node in the past six months, multiply and normalize the proportion of the number of people, the average drug resistance level, and the contact density of the cross-path node to obtain the risk level of the cross-path node.

9. According to claim 8, a method for integrated auxiliary prevention and control of infectious diseases in elderly patients, characterized in that: The specific steps of correcting the drug resistance level according to the risk level of the elderly patient at multiple cross-path nodes to obtain the final drug resistance level of each elderly patient are as follows: Acquire all cross-path nodes in the target patient's driving path; use the target patient's drug resistance level as the drug resistance level of the first cross-path node in the target patient's driving path; multiply the drug resistance level of the first cross-path node in the target patient's driving path and the risk level of the first cross-path node to obtain the drug resistance level of the second cross-path node in the target patient's driving path; multiply the drug resistance level of the second cross-path node in the target patient's driving path and the risk level of the second cross-path node to obtain the drug resistance level of the third cross-path node in the target patient's driving path, and so on, to obtain the drug resistance level of the last cross-path node in the target patient's driving path, which is used as the final drug resistance level of the target patient.

10. According to claim 1, a method for integrated auxiliary prevention and control of infectious diseases in elderly patients with precise diagnosis and treatment, characterized in that: The specific steps of screening out a number of elderly patients with high drug resistance according to the final drug resistance level are as follows: A first threshold is preset, and elderly patients whose final drug resistance level is greater than the first threshold are regarded as elderly patients with high drug resistance.

Images