CN109545370B - Disease type determining method and device based on sample processing and terminal - Google Patents
Disease type determining method and device based on sample processing and terminal Download PDFInfo
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Abstract
The embodiment of the invention discloses a disease type determining method, a device and a terminal based on sample processing, wherein the method comprises the following steps: obtaining at least one treatment scheme of at least one sample patient in a preset area, detecting whether each treatment item in the treatment scheme exists in a clinical path corresponding to the target disease, if so, further detecting the use rate of each treatment item of the sample patient, adding the treatment item with the use rate being greater than a first preset threshold value into a target standard treatment scheme, and determining the disease type of the patient to be detected according to the similarity of the target standard treatment scheme and the treatment scheme of the patient to be detected in the preset area. By executing the method, the accuracy of the determination result of the diseased species of the patient can be improved.
Description
Technical Field
The present invention relates to the field of big data technologies, and in particular, to a method, an apparatus, and a terminal for determining a disease type based on sample processing.
Background
Clinical pathway (Clinical pathway) refers to the establishment of a standardized set of treatment patterns and treatment procedures for a disease, and is a comprehensive pattern of Clinical treatment. After the clinical path is adopted as a standard treatment scheme for a certain disease, not only can unnecessary treatment projects of a patient be avoided, but also the disease suffered by the patient can be determined by finding the clinical path closest to the actual treatment scheme for treating the patient.
However, because of the large differences in medical levels in different areas, the usual treatment regimens for a disease in different areas may differ significantly from the clinical pathway corresponding to the disease. Such that the result of determining the type of disease a patient suffers from based on the clinical path pairs is less accurate.
Disclosure of Invention
The embodiment of the invention provides a disease type determining method based on sample processing, which can improve the accuracy of the result of determining the disease type of a patient.
In a first aspect, an embodiment of the present invention provides a method for determining a disease type based on sample processing, the method including:
obtaining at least one treatment regimen for at least one patient within a predetermined area, said at least one patient having the same target disease species, one of said treatment regimens comprising at least one treatment item;
detecting whether a first treatment item exists in a clinical path corresponding to the target disease, wherein the first treatment item is any treatment item in the at least one treatment scheme;
if the first treatment item exists in the clinical path corresponding to the target disease, detecting whether the use rate of the first treatment item is larger than a first preset threshold value, wherein the use rate of the first treatment item is determined according to the number of sample patients treated by the first treatment item;
If the usage rate of the first treatment item is greater than the first preset threshold value, adding the first treatment item to a target standard treatment scheme, wherein the target standard treatment scheme is a standard treatment scheme corresponding to the preset area and the target disease, and the target standard treatment scheme comprises at least one standard treatment item for treating the target disease in the preset area;
and determining the disease type of the patient to be detected according to the similarity of the target standard treatment scheme and the treatment scheme aiming at the patient to be detected in the preset area.
In a second aspect, an embodiment of the present invention provides a disease type determining apparatus based on sample processing, the apparatus including:
an acquisition module for acquiring at least one treatment plan of at least one sample patient in a preset area, wherein the at least one sample patient has the same target disease species, and one treatment plan comprises at least one treatment item;
the detection module is used for detecting whether a first treatment item exists in a clinical path corresponding to the target disease, wherein the first treatment item is any treatment item in the at least one treatment scheme;
The detection module is further configured to detect whether a usage rate of the first treatment item is greater than a first preset threshold if the first treatment item exists in a clinical path corresponding to the target disease, where the usage rate of the first treatment item is determined according to a number of sample patients treated with the first treatment item;
the adding module is used for adding the first treatment item to a target standard treatment scheme if the utilization rate of the first treatment item is greater than the first preset threshold value, wherein the target standard treatment scheme is a standard treatment scheme corresponding to the preset area and the target disease, and the target standard treatment scheme comprises at least one standard treatment item for treating the target disease in the preset area;
and the determining module is used for determining the disease type of the patient to be detected according to the similarity of the target standard treatment scheme and the treatment scheme of the patient to be detected in the preset area.
In a third aspect, an embodiment of the present invention provides a terminal, including a processor, an input device, an output device, and a memory, where the processor, the input device, the output device, and the memory are connected to each other, and the memory is configured to store a computer program, where the computer program includes program instructions, and where the processor is configured to invoke the program instructions to perform the method according to the first aspect.
In a fourth aspect, an embodiment of the present invention provides a computer readable storage medium, wherein the computer storage medium stores a computer program comprising program instructions that, when executed by a processor, cause the processor to perform the method according to the first aspect.
In the embodiment of the invention, at least one treatment scheme of at least one sample patient in a preset area is acquired by a terminal, the sample patient in the preset area has the same target disease, whether each treatment item in the treatment scheme exists in a clinical path corresponding to the target disease is detected, if so, the use rate of the sample patient for each treatment item is further detected, the treatment item with the use rate larger than a first preset threshold value is added into a target standard treatment scheme, and the disease of the patient to be detected is determined according to the similarity of the target standard treatment scheme and the treatment scheme of the patient to be detected in the preset area. By executing the method, the accuracy of the determination result of the diseased species of the patient can be improved.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings required for the description of the embodiments will be briefly described below, and it is obvious that the drawings in the following description are some embodiments of the present invention, and other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 is a schematic flow chart of a method for determining a disease type based on sample processing according to an embodiment of the present invention;
FIG. 2 is a flow chart of another method for determining a disease type based on sample processing according to an embodiment of the present invention;
fig. 3 is a schematic structural diagram of a disease type determining device based on sample processing according to an embodiment of the present invention;
fig. 4 is a schematic structural diagram of a terminal according to an embodiment of the present invention.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and fully with reference to the accompanying drawings, in which it is evident that the embodiments described are some, but not all embodiments of the invention. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
The image retrieval method provided by the embodiment of the invention is realized in a terminal, wherein the terminal comprises electronic equipment such as a smart phone, a tablet personal computer, a digital audio/video player, an electronic reader, a handheld game machine or vehicle-mounted electronic equipment and the like.
Fig. 1 is a flow chart of a method for determining a disease type based on sample processing according to an embodiment of the present invention. The flow of the disease type determining method based on sample processing in this embodiment as shown in the drawings may include:
S101, the terminal acquires at least one treatment scheme of at least one sample patient in a preset area.
In the embodiment of the present invention, at least one patient in a preset area has the same target disease, and one treatment scheme includes at least one medical item, that is, the treatment scheme is a set of treatment items received by the patient, where the treatment items may include blood drawing, CT, medicine taking, hospitalization, and the like, and the preset area may be an area formed by one or more cities, regions, counties, such as a north-clear region, a northwest region, a city-mouth county, and the like. The sample patient has the same target disease, and the target disease can be single disease such as appendicitis, cholecystitis, gall-stone and the like. Because the treatment schemes adopted by different doctors for the target disease types in the preset area can be different, the terminal can acquire different treatment schemes aiming at the same target disease type.
In a specific implementation, before at least one treatment plan of at least one patient in the preset area is acquired, the terminal may further screen the patient suffering from the target disease in the preset area according to a preset screening condition, where the screening condition includes the same gender, age group or medical history. In one implementation, the screening conditions are the same gender, and the terminal may determine a male patient having the target disease within the preset area as a sample patient, or determine a female patient having the target disease within the preset area as a sample patient. In one implementation, the screening conditions are the same age group, the terminal may divide the age group of the patient into 4 age groups including infants (0-3 years), children (3-12 years), young and middle-aged (13-60 years), elderly (60 years or more), and the terminal determines the patient in any one age group as a sample patient. In one implementation, the screening conditions are the same historical conditions, the terminal can classify the patient's historical conditions as diabetes, hypertension, heart disease, hepatitis b, etc., and the terminal identifies the patient with any one of the historical conditions as a sample patient. In one implementation, the terminal may also set a combined screening condition, e.g., the screening condition is the same gender and age group, the same medical history and gender, etc. By screening out the sample patients under each category, the treatment scheme difference of the sample patients is smaller, and the treatment scheme difference of the sample patients caused by unnecessary factors such as age, gender, medical history and the like is avoided.
S102, the terminal detects whether a first treatment item exists in a clinical path corresponding to a target disease type, wherein the first treatment item is any treatment item in at least one treatment scheme.
In the embodiment of the invention, after the terminal acquires at least one treatment plan of at least one sample patient in the preset area, whether a first treatment item exists in a clinical path corresponding to the target disease type is detected, wherein the first treatment item is any treatment item in the at least one treatment plan, namely, whether each treatment item in the treatment plan exists in the clinical path corresponding to the target disease type is detected by the terminal.
For example, at least one treatment regimen within the predetermined area includes treatment regimen 1, treatment regimen 2, and treatment regimen 3, each treatment regimen including treatment items as shown in table 1:
TABLE 1
Wherein, the treatment items can include blood drawing, CT, medicine taking, hospitalization and the like, and different letters are used for representing different treatment items, and then the first treatment item can be any one of treatment item A, treatment item B, treatment item C, treatment item D, treatment item E, treatment item F and treatment item H, and as can be seen from the above table, the treatment item A, the treatment item B and the treatment item C exist in the clinical path corresponding to the target disease.
S103, if the first treatment item exists in the clinical path corresponding to the target disease, the terminal detects whether the use rate of the first treatment item is larger than a first preset threshold.
In the embodiment of the invention, after detecting that the first treatment item exists in the clinical path corresponding to the target disease, the terminal acquires the utilization rate of the first treatment item.
In one implementation manner, the usage rate of the first treatment item is determined according to the number of sample patients treated with the first treatment item, and the usage rate of the first treatment item may specifically be calculated by the terminal acquiring the number of sample patients treated with the first treatment item in the preset area, calculating a ratio of the number of sample patients treated with the first treatment item to the total number of sample patients in the preset area, and determining the ratio as the usage rate of the first treatment item. For example, if the number of sample patients receiving the first treatment item in the preset area is 100 and the total number of sample patients in the preset area is 200, the usage rate of the first treatment item is determined to be 50%.
In one implementation manner, the specific calculation manner of the usage rate of the first treatment item may further be that the terminal obtains a history visit record of at least one sample patient in the preset area, obtains the number of times of average usage of the sample patient on the first treatment item from the history visit record, and uses the number of times of average usage as the usage rate of the first treatment item. For example, if the total number of visits by the terminal for 10 sample patients is 20 and the number of uses of the first treatment item is 15, it may be determined that the usage rate of the first treatment item is 75%.
After the terminal obtains the usage rate of the first treatment item, it will be detected whether the usage rate of the first treatment item is greater than a first preset threshold, where the first preset threshold may be 20%, 30%, and the like, and specifically may be preset by a developer.
S104, if the usage rate of the first treatment item is greater than a first preset threshold, the terminal adds the first treatment item to the target standard treatment scheme.
In the embodiment of the invention, the target standard treatment scheme is a standard treatment scheme corresponding to a preset area and a target disease type, the target standard treatment scheme comprises at least one standard treatment item for treating the target disease type in the preset area, after the terminal determines the use rate of the first treatment item, whether the use rate of the first treatment item is larger than a first preset threshold value is detected, and if the use rate of the first treatment item is larger than the first preset threshold value, the terminal adds the first treatment item into the target standard treatment scheme.
For example, if the preset threshold is 30%, and the first treatment item is treatment item a in table 1, and the usage rate corresponding to treatment item a is 100%, the terminal adds treatment item a to the target standard treatment scheme. If the first treatment item is treatment item C in table 1 and the usage rate corresponding to treatment item C is 1%, the terminal may not add treatment item C to the target standard treatment scheme.
And after the terminal determines that the utilization rate is larger than a first preset threshold value and each first treatment item existing in the clinical path corresponding to the target disease type, determining a set formed by each first treatment item as a target standard treatment scheme.
S105, the terminal determines the disease type of the patient to be detected according to the similarity between the target standard treatment scheme and the treatment scheme of the patient to be detected in the preset area.
In the embodiment of the present invention, the patient to be detected may be a patient who is receiving treatment in a preset area, and after the terminal determines the target standard treatment scheme, the disease type of the patient to be detected in the preset area is determined according to the target standard treatment scheme. Specifically, the terminal acquires a treatment scheme aiming at the patient to be detected, detects the similarity between the treatment scheme aiming at the patient to be detected and the target standard treatment scheme, and determines the target disease corresponding to the target standard treatment scheme as the disease of the patient to be detected if the similarity is greater than the preset similarity. For example, a treatment regimen for a patient to be tested includes: treatment item A, treatment item B, treatment item C, treatment item D, the standard treatment regimen of interest for appendicitis includes: and (3) determining that the similarity between the treatment scheme for the patient to be detected and the target standard treatment scheme is greater than a preset threshold value and determining that the disease species of the patient to be detected is appendicitis if the preset similarity is 90% in the treatment item A, the treatment item B, the treatment item C and the treatment item D. Or the terminal determines a target standard treatment scheme with highest similarity to the treatment scheme aiming at the patient to be detected from at least one target standard treatment scheme, and determines the target disease type corresponding to the target standard treatment scheme with highest similarity to the patient to be detected as the disease type of the patient to be detected.
It should be noted that, the specific calculation manner of the similarity between the treatment plan of the patient to be detected and the target standard treatment plan may be that the terminal obtains a first number of treatment items of the same treatment plan for the patient to be detected and the target standard treatment plan, calculates a ratio of the first number to the total number of treatment items in the treatment plan for the patient to be detected, and determines the calculated ratio as the similarity between the treatment plan for the patient to be detected and the target standard treatment plan.
In the embodiment of the invention, a terminal acquires at least one treatment scheme of at least one sample patient in a preset area, the sample patient in the preset area suffers from the same target disease, whether each treatment item in the treatment scheme exists in a clinical path corresponding to the target disease is detected, if so, the use rate of the sample patient for each treatment item is further detected, the treatment item with the use rate larger than a first preset threshold value is added into a target standard treatment scheme, and the disease of the patient to be detected in the preset area is determined according to the target standard treatment scheme. By executing the method, the accuracy of the determination result of the diseased species of the patient can be improved.
Fig. 2 is a schematic flow chart of another method for determining a disease seed based on sample processing according to an embodiment of the present invention, as shown in the drawing, the flow chart of the method for determining a disease seed based on sample processing according to the present embodiment may include:
s201, the terminal acquires at least one treatment scheme of at least one sample patient in a preset area.
In the embodiment of the present invention, at least one patient in a preset area has the same target disease, and one treatment scheme includes at least one medical item, that is, the treatment scheme is a set of treatment items received by the patient, where the treatment items may include blood drawing, CT, medicine taking, hospitalization, and the like, and the preset area may be an area formed by one or more cities, regions, counties, such as a north-clear region, a northwest region, a city-mouth county, and the like. The sample patient has the same target disease, and the target disease can be single disease such as appendicitis, cholecystitis, gall-stone and the like. Because the treatment schemes adopted by different doctors for the target disease types in the preset area can be different, the terminal can acquire different treatment schemes aiming at the same target disease type.
Specifically, before at least one treatment plan of at least one sample patient in the preset area is acquired, the terminal may further screen sample patients from patients with target disease in the preset area according to preset screening conditions, where the preset screening conditions may be that patients with a conventional hospitalization period of time are screened out, for example, the conventional hospitalization period of time of patients with target disease is 5 to 10 days, then the terminal determines, when sample screening is performed, the patient with a hospitalization period of time of 5 to 10 days as a sample patient, and further, the terminal may also randomly select a preset number of patients from the patients with a hospitalization period of 5 to 10 days as sample patients.
In one implementation manner, the terminal may further screen the sample by combining variances of the hospitalization durations of at least one patient in the preset area, specifically, the terminal obtains the hospitalization durations of at least one patient with the target disease in the preset area, detects whether the variances of the hospitalization durations of at least one patient with the target disease in the preset area are smaller than the preset variances, and if the variances are smaller than the preset variances, the terminal determines the at least one patient with the target disease in the preset area as the sample patient. For example, the hospitalization duration of each patient with the target disease in the preset area is 5, 6 and 7 (days), the preset variance is 2, the variance of the hospitalization duration of each patient is calculated to be 0.4, the variance is determined to be smaller than the preset variance, and each patient with the target disease in the preset area is determined to be a sample patient by the terminal. Optionally, if the variance of the hospitalization duration of at least one patient with the target disease in the preset area is greater than or equal to the preset variance, screening the patient corresponding to the hospitalization duration causing the excessive variance is needed, and the specific screening method may be to calculate the difference between each hospitalization duration and the average hospitalization duration, and screen the patient corresponding to the hospitalization duration with the largest difference one by one until the variance of the hospitalization duration of the rest patients is less than the preset variance. For example, the hospitalization duration of each patient with the target disease in the preset area is 1, 5, 6, 7 and 11 (days), the preset variance is 2, the variance is calculated to be 8.7, the hospitalization duration of each patient obtained by screening out the patient corresponding to the hospitalization duration causing the excessive variance by the terminal is 5, 6 and 7 (days), and the terminal determines the patient corresponding to each hospitalization duration remaining after screening out as the sample patient.
After the terminal acquires at least one sample patient with the target disease species in the preset area, at least one treatment scheme of the at least one sample patient in the preset area is acquired, wherein the sample patients have the same target disease species.
S202, the terminal detects whether a first treatment item exists in a clinical path corresponding to a target disease type, wherein the first treatment item is any treatment item in at least one treatment scheme.
In the embodiment of the invention, after the terminal acquires at least one treatment plan of at least one sample patient in the preset area, whether a first treatment item exists in a clinical path corresponding to the target disease type is detected, wherein the first treatment item is any treatment item in the at least one treatment plan, namely, whether each treatment item in the treatment plan exists in the clinical path corresponding to the target disease type is detected by the terminal.
S203, if the first treatment item does not exist in the clinical path corresponding to the target disease, the terminal detects whether the usage rate of the first treatment item is greater than a second preset threshold.
In the embodiment of the invention, after detecting that the first treatment item does not exist in the clinical path corresponding to the target disease, the terminal detects whether the usage rate of the first treatment item is greater than a second preset threshold. The second preset threshold is greater than the first preset threshold, and the second preset threshold may be 70%, 80%, etc., which may be specifically preset by a developer. For example, 5 patients with the target disease are selected as sample patients, and the correspondence between the sample patients and the treatment scheme is shown in table 2:
The treatment items may include blood drawing, CT, medicine taking, hospitalization, and the like, different letters are used to indicate different treatment items, if the first treatment item does not exist in the clinical path corresponding to the target disease, the first treatment item may be treatment item D, treatment item E, treatment item F, or treatment item H, as can be seen from table 2, the usage rate of treatment item D is 20% when only sample patient 1 of the 5 sample patients uses treatment item D, and similarly, the usage rate of treatment item E is 40%, the usage rate of treatment item F is 80%, the usage rate of treatment item H is 40%, and if the second preset threshold is 70%, the terminal determines that the usage rate of treatment item F is greater than the second preset threshold.
S204, if the usage rate of the first treatment item is greater than a second preset threshold, the terminal acquires the acceptance of at least one sample patient for the first treatment item.
In the embodiment of the invention, after detecting that the usage rate of the first treatment item is greater than the second preset threshold, the terminal acquires the approval of at least one sample patient in the preset area for the first treatment item.
In one implementation, the approval degree is determined by the number of sample patients approved for the first treatment item, and the specific calculation method of the approval degree of the at least one sample patient for the first treatment item in the preset area may be that the terminal acquires the number of the first sample patients approved for the first treatment item, calculates a ratio of the number of the first sample patients to the total number of the sample patients in the preset area, and determines the calculated ratio as the approval degree of the first treatment item.
In one implementation, the specific calculation of the acceptance of the first treatment item by the at least one sample patient in the preset area may be that the terminal obtains the score of the first treatment item by the at least one sample patient, and determines the average value of the scores as the acceptance of the first treatment item by the at least one sample patient. For example, sample patient 1 scored 0.9 for the first treatment item, sample patient 2 scored 0.8 for the first treatment item, and sample patient 3 scored 0.7 for the first treatment item, then the acceptance of the first treatment item by the sample patient is determined to be 0.8.
S205, if the approval is greater than the preset approval, the terminal adds the first treatment item to the target standard treatment scheme.
In the embodiment of the invention, the target standard treatment scheme is a standard treatment scheme corresponding to a preset area and a target disease, the target standard treatment scheme comprises at least one standard treatment item for treating the target disease in the preset area, the terminal detects that the first treatment item does not exist in a clinical path corresponding to the target disease, and after the usage rate of the first treatment item is greater than a second preset threshold and the acceptance of the first treatment item by a sample patient is greater than a preset acceptance, the first treatment item is added into the target standard treatment scheme. For example, the first treatment item is treatment item F, the usage rate of treatment item F is greater than a second preset threshold, the approval of the sample patient for treatment item F is 0.9, and the preset approval is 0.8, and the terminal adds treatment item F to the target standard treatment regimen.
In one implementation, before the first treatment item is added to the target standard treatment scheme, the terminal may further detect whether the first treatment item is matched with a second treatment item according to a detection index, where the second treatment item is any treatment item in a clinical path corresponding to the target disease, and the detection index includes a function of the treatment item, a number of times of average use of the treatment item, and a cost of the treatment item. Specifically, the terminal detects whether the function of the first treatment item is the same as that of the second treatment item, if so, it detects whether the number of times of the first treatment item used is the same as that of the second treatment item used, and if so, it calculates the difference between the cost of the first treatment item and the cost of the second treatment item; if the calculated difference is smaller than the preset difference, the first treatment item is determined to be matched with the second treatment item. The corresponding preset differences may be different for different first treatment projects, and specifically preset by a developer. For example, the target disease is appendicitis, the first treatment is epidural anesthesia and the second treatment is combined anesthesia. The first treatment item and the second treatment item are used for anaesthetizing a patient when the appendix is resected, the functions of the first treatment item and the second treatment item are the same, the times of use of the epidural anesthesia or the combined anesthesia are all one, the treatment cost of the epidural anesthesia is 500 yuan, the treatment cost of the combined anesthesia is 490 yuan, the preset difference is 100 yuan, and then the terminal determines that the first treatment item is matched with the second treatment item. And adding the first treatment item to the target standard treatment regimen, the terminal may refuse to add the first treatment item to the target standard treatment regimen if the first treatment item does not match the second treatment item. By the mode, treatment items which are not related to the target disease can be prevented from being added into the target standard treatment scheme, and the practicability of the target standard treatment scheme is improved.
S206, the terminal determines the disease type of the patient to be detected according to the similarity between the target standard treatment scheme and the treatment scheme of the patient to be detected in the preset area.
In the embodiment of the invention, the patient to be detected can be the patient receiving the treatment in the preset area, and after the terminal determines the target standard treatment scheme, the disease type of the patient to be detected is determined according to the similarity between the target standard treatment scheme and the treatment scheme of the patient to be detected in the preset area. Specifically, the terminal acquires a treatment scheme aiming at the patient to be detected, detects the similarity between the treatment scheme aiming at the patient to be detected and the target standard treatment scheme, and determines the target disease corresponding to the target standard treatment scheme as the disease of the patient to be detected if the similarity is greater than the preset similarity. Or the terminal determines a target standard treatment scheme with highest similarity to the treatment scheme aiming at the patient to be detected from at least one target standard treatment scheme, and determines the target disease type corresponding to the target standard treatment scheme with highest similarity to the patient to be detected as the disease type of the patient to be detected. For example, if the appendicitis corresponds to the target standard treatment plan 1, the cholecystitis corresponds to the target standard treatment plan 2, the cholelithiasis corresponds to the target standard treatment plan 3, and the terminal detects that the treatment plan for the patient to be detected is the highest in similarity with the target standard treatment plan 1, the terminal determines the diseased species of the patient to be detected as appendicitis. In an implementation scenario, the terminal can detect treatment items accepted by a patient to be detected in real time in the patient treatment process, each time the patient to be detected completes a new treatment item, the terminal calculates the similarity between a treatment scheme formed by each item and each target standard treatment scheme, and displays disease types possibly suffered by the patient to the patient according to the similarity ranking order, so that the patient can know own disease condition change in real time, and when the patient completes treatment, the terminal determines the target disease type corresponding to the target standard treatment scheme with the highest similarity of the treatment scheme of the patient to be detected in each target standard treatment scheme as the disease type of the patient to be detected. Furthermore, after the terminal determines the disease type of the patient, a corresponding basis can be provided for medical reimbursement of the patient.
It should be noted that, the specific calculation manner of the similarity between the treatment plan of the patient to be detected and the target standard treatment plan may be that the terminal obtains a first number of treatment items of the same treatment plan for the patient to be detected and the target standard treatment plan, calculates a ratio of the first number to the total number of treatment items in the treatment plan for the patient to be detected, and determines the calculated ratio as the similarity between the treatment plan for the patient to be detected and the target standard treatment plan.
In the embodiment of the invention, the terminal acquires at least one treatment scheme of at least one sample patient in a preset area, the sample patient in the preset area has the same target disease, whether each treatment item in the treatment scheme exists in a clinical path corresponding to the target disease is detected, if not, the use rate of the sample patient for each treatment item is further detected, the treatment item with the use rate larger than a second preset threshold and the patient acceptance degree larger than the preset acceptance degree is selected from the treatment items, the selected treatment item is added into the target standard treatment scheme, the terminal determines the disease of the patient to be detected in the preset area according to the target standard treatment scheme, and determines the disease of the patient by establishing different target standard treatment schemes aiming at different areas and then searching the target standard treatment scheme matched with the actual treatment scheme of the patient, so that the accuracy of the determination result of the disease of the patient can be improved.
The following describes in detail a sample processing-based disease type determining apparatus according to an embodiment of the present invention with reference to fig. 3. It should be noted that, the sample processing-based disease type determining apparatus shown in fig. 3 is used to perform the method of the embodiment shown in fig. 1-2 of the present invention, and for convenience of explanation, only the portion relevant to the embodiment of the present invention is shown, and specific technical details are not disclosed, and reference is made to the embodiment shown in fig. 1-2 of the present invention.
Referring to fig. 3, a schematic structural diagram of a sample processing-based disease type determining apparatus according to the present invention is provided, and the sample processing-based disease type determining apparatus 30 may include: an acquisition module 301, a detection module 302, an addition module 303 and a determination module 304.
An acquisition module 301 for acquiring at least one treatment plan of at least one sample patient within a preset area, wherein the at least one sample patient has the same target disease species, and one treatment plan comprises at least one treatment item;
a detection module 302, configured to detect whether a first treatment item exists in a clinical path corresponding to the target disease, where the first treatment item is any one treatment item in the at least one treatment scheme;
The detection module 302 is further configured to detect whether a usage rate of a first treatment item is greater than a first preset threshold if the first treatment item exists in a clinical path corresponding to the target disease, where the usage rate of the first treatment item is determined according to the number of sample patients treated with the first treatment item;
an adding module 303, configured to add the first treatment item to a target standard treatment plan if the usage rate of the first treatment item is greater than the first preset threshold, where the target standard treatment plan is a standard treatment plan corresponding to the preset area and the target disease, and the target standard treatment plan includes at least one standard treatment item for treating the target disease in the preset area;
and the determining module 304 is configured to determine a disease type of the patient to be detected according to a similarity between the target standard treatment plan and a treatment plan for the patient to be detected in the preset area.
In one implementation, the detection module 302 is further configured to detect whether the usage rate of the first treatment item is greater than a second preset threshold if the first treatment item does not exist in the clinical path corresponding to the target disease, where the second preset threshold is greater than the first preset threshold;
The obtaining module 301 is further configured to obtain an acceptance of the first treatment item by the at least one sample patient if the usage rate of the first treatment item is greater than the second preset threshold, where the acceptance is determined by the number of sample patients approved for the first treatment item;
the adding module 303 is further configured to add the first treatment item to the target standard treatment regimen if the approval is greater than a preset approval.
In one implementation, the first treatment item is not present in a clinical pathway corresponding to the target disease species,
the detection module 302 is further configured to detect, according to a detection indicator, whether the first treatment item is matched with a second treatment item, where the second treatment item is any treatment item in a clinical path corresponding to the target disease, and the detection indicator includes a function of the treatment item, a number of times of average use of the treatment item, and a cost of the treatment item;
the adding module 303 is further configured to trigger the operation of adding the first treatment item to the target standard treatment plan if the first treatment item matches the second treatment item.
In one implementation, the detection module is specifically configured to:
detecting whether the function of the first treatment item is the same as the function of the second treatment item;
if so, detecting whether the times of the first treatment item for the average use are the same as the times of the second treatment item for the average use;
if the first treatment item and the second treatment item are the same, calculating a difference value between the cost of the first treatment item and the cost of the second treatment item;
and if the difference is smaller than a preset difference, determining that the first treatment item is matched with the second treatment item.
In one implementation, the apparatus further includes a screening module 305,
the screening module 305 is configured to screen patients with the target disease in the preset area according to preset screening conditions, where the screening conditions include the same gender, age group or medical history;
the determining module 304 is further configured to determine, as a sample patient, a patient with the target disease species that satisfies the screening condition in the preset area.
In one implementation, the determining module 304 is specifically configured to:
acquiring a treatment scheme for a patient to be detected in the preset area;
detecting a similarity of a treatment regimen for the patient to be detected to the target standard treatment regimen;
And if the similarity is greater than the preset similarity, determining the target disease type corresponding to the target standard treatment scheme as the disease type of the patient to be detected.
In one implementation, the determining module 304 is specifically configured to:
obtaining a first number of identical treatment items in the treatment regimen for the patient to be tested and the target standard treatment regimen;
calculating a ratio of the first number to a total number of treatment items in the treatment regimen for the patient to be tested;
and determining the ratio as the similarity of the treatment plan for the patient to be detected and the target standard treatment plan.
In this embodiment of the present invention, the obtaining module 301 obtains at least one treatment plan of at least one patient in a preset area, the detecting module 302 detects whether a first treatment item exists in a clinical path corresponding to a target disease, if the first treatment item exists in the clinical path corresponding to the target disease, the detecting module 302 detects whether the usage rate of the first treatment item is greater than a first preset threshold, and if the usage rate of the first treatment item is greater than the first preset threshold, the adding module 303 adds the first treatment item to a target standard treatment plan, where the target standard treatment plan is a standard treatment plan corresponding to the preset area and the target disease, and the determining module 304 determines, according to the target standard treatment plan, the disease of the patient to be detected in the preset area. By establishing different target standard treatment schemes for different areas and then searching for a target standard treatment scheme matching the actual treatment scheme of the patient to determine the patient's disease, the accuracy of the determination of the patient's disease can be improved.
Referring to fig. 4, a schematic structural diagram of a terminal is provided in an embodiment of the present invention. As shown in fig. 4, the terminal includes: at least one processor 401, an input device 403, an output device 404, a memory 405, and at least one communication bus 402. Wherein communication bus 402 is used to enable connected communications between these components. The input device 403 may be a control panel, a microphone, or the like, and the output device 404 may be a display screen or the like. The memory 405 may be a high-speed RAM memory or a non-volatile memory (non-volatile memory), such as at least one disk memory. The memory 405 may also optionally be at least one storage device located remotely from the aforementioned processor 401. Wherein the processor 401 may be described in connection with fig. 3, a set of program codes is stored in the memory 405, and the processor 401, the input device 403, the output device 404 call the program codes stored in the memory 405 for performing the following operations:
an input device 403 for acquiring at least one treatment regimen of at least one sample patient within a preset area, said at least one sample patient suffering from the same target disease species, one of said treatment regimens comprising at least one treatment item;
A processor 401, configured to detect whether a first treatment item exists in a clinical path corresponding to the target disease, where the first treatment item is any one treatment item in the at least one treatment scheme;
a processor 401, configured to detect whether a usage rate of a first treatment item is greater than a first preset threshold if the first treatment item exists in a clinical path corresponding to the target disease, where the usage rate of the first treatment item is determined according to the number of sample patients treated with the first treatment item;
a processor 401, configured to add the first treatment item to a target standard treatment plan if the usage rate of the first treatment item is greater than the first preset threshold, where the target standard treatment plan is a standard treatment plan corresponding to the preset area and the target disease, and the target standard treatment plan includes at least one standard treatment item for treating the target disease in the preset area; and the processor 401 is configured to determine a disease type of the patient to be detected according to a similarity between the target standard treatment plan and a treatment plan for the patient to be detected in the preset area.
In one implementation, the processor 401 is specifically configured to:
if the first treatment item does not exist in the clinical path corresponding to the target disease, detecting whether the use rate of the first treatment item is greater than a second preset threshold value, wherein the second preset threshold value is greater than the first preset threshold value;
if the usage rate of the first treatment item is greater than the second preset threshold, obtaining acceptance of the first treatment item by the at least one sample patient, the acceptance being determined by the number of sample patients approved for the first treatment item;
if the acceptance is greater than a preset acceptance, the first treatment item is added to the target standard treatment regimen.
In one implementation, the first treatment item is not in the clinical path corresponding to the target disease, and the processor 401 is specifically configured to:
detecting whether the first treatment item is matched with a second treatment item according to a detection index, wherein the second treatment item is any treatment item in a clinical path corresponding to the target disease, and the detection index comprises the function of the treatment item, the number of times of average use of the treatment item and the cost of the treatment item;
If the first treatment item matches the second treatment item, triggering the operation of adding the first treatment item to the target standard treatment regimen.
In one implementation, the processor 401 is specifically configured to:
detecting whether the function of the first treatment item is the same as the function of the second treatment item;
if so, detecting whether the times of the first treatment item for the average use are the same as the times of the second treatment item for the average use;
if the first treatment item and the second treatment item are the same, calculating a difference value between the cost of the first treatment item and the cost of the second treatment item;
and if the difference is smaller than a preset difference, determining that the first treatment item is matched with the second treatment item.
In one implementation, the processor 401 is specifically configured to:
screening patients suffering from target disease seeds in the preset area according to preset screening conditions, wherein the screening conditions comprise the same gender, age group or medical history;
and determining the patient with the target disease species meeting the screening conditions in the preset area as a sample patient.
In one implementation, the processor 401 is specifically configured to:
Acquiring a treatment scheme for a patient to be detected in the preset area;
detecting a similarity of a treatment regimen for the patient to be detected to the target standard treatment regimen;
and if the similarity is greater than the preset similarity, determining the target disease type corresponding to the target standard treatment scheme as the disease type of the patient to be detected.
In one implementation, the processor 401 is specifically configured to:
obtaining a first number of identical treatment items in the treatment regimen for the patient to be tested and the target standard treatment regimen;
calculating a ratio of the first number to a total number of treatment items in the treatment regimen for the patient to be tested;
and determining the ratio as the similarity of the treatment plan for the patient to be detected and the target standard treatment plan.
In this embodiment of the present invention, the input device 403 obtains at least one treatment plan of at least one patient in a preset area, the processor 401 detects whether a first treatment item exists in a clinical path corresponding to a target disease, if the first treatment item exists in the clinical path corresponding to the target disease, the processor 401 detects whether the usage rate of the first treatment item is greater than a first preset threshold, if the usage rate of the first treatment item is greater than the first preset threshold, the processor 401 adds the first treatment item to a target standard treatment plan, where the target standard treatment plan is a standard treatment plan corresponding to the preset area and the target disease, and the processor 401 determines the disease of the patient to be detected in the preset area according to the target standard treatment plan. By establishing different target standard treatment schemes for different areas and then searching for a target standard treatment scheme matching the actual treatment scheme of the patient to determine the patient's disease, the accuracy of the determination of the patient's disease can be improved.
The modules described in the embodiments of the present invention may be implemented by general-purpose integrated circuits such as a CPU (Central Processing Unit ) or by ASIC (Application Specific Integrated Circuit, application specific integrated circuit).
It should be appreciated that in embodiments of the present invention, the processor 401 may be a central processing unit (Central Processing Unit, CPU), which may also be other general purpose processors, digital signal processors (Digital Signal Processor, DSPs), application specific integrated circuits (Application Specific Integrated Circuit, ASICs), off-the-shelf programmable gate arrays (Field-Programmable Gate Array, FPGAs) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, or the like. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like.
Bus 402 can be an industry standard architecture (Industry Standard Architecture, ISA) bus, an external device interconnect (Peripheral Component, PCI) bus, or an extended industry standard architecture (Extended Industry Standard Architecture, EISA) bus, etc., and bus 402 can be divided into an address bus, a data bus, a control bus, etc., with fig. 4 shown with only one bold line for ease of illustration, but not with only one bus or one type of bus.
Those skilled in the art will appreciate that implementing all or part of the above-described methods in the embodiments may be accomplished by way of a computer program stored in a computer storage medium, which when executed may comprise the steps of the embodiments of the methods described above. The computer storage medium may be a magnetic disk, an optical disk, a Read-Only Memory (ROM), a random access Memory (Random Access Memory, RAM), or the like.
The foregoing disclosure is illustrative of the present invention and is not to be construed as limiting the scope of the invention, which is defined by the appended claims.
Claims (9)
1. A method of determining a disease type based on sample processing, the method comprising:
obtaining at least one treatment regimen for at least one patient within a predetermined area, said at least one patient having the same target disease species, one of said treatment regimens comprising at least one treatment item;
detecting whether a first treatment item exists in a clinical path corresponding to the target disease, wherein the first treatment item is any treatment item in the at least one treatment scheme;
If the first treatment item exists in the clinical path corresponding to the target disease, detecting whether the use rate of the first treatment item is larger than a first preset threshold value, wherein the use rate of the first treatment item is determined according to the number of sample patients treated by the first treatment item;
if the usage rate of the first treatment item is greater than the first preset threshold value, adding the first treatment item to a target standard treatment scheme, wherein the target standard treatment scheme is a standard treatment scheme corresponding to the preset area and the target disease, and the target standard treatment scheme comprises at least one standard treatment item for treating the target disease in the preset area;
if the first treatment item does not exist in the clinical path corresponding to the target disease, detecting whether the use rate of the first treatment item is larger than a second preset threshold value, wherein the second preset threshold value is larger than the first preset threshold value;
if the usage rate of the first treatment item is greater than the second preset threshold, obtaining acceptance of the first treatment item by the at least one sample patient, the acceptance being determined by the number of sample patients approved for the first treatment item; if the acceptance is greater than a preset acceptance, adding the first treatment item to the target standard treatment regimen;
And determining the disease type of the patient to be detected according to the similarity of the target standard treatment scheme and the treatment scheme aiming at the patient to be detected in the preset area.
2. The method of claim 1, wherein if the first treatment item is not present in the clinical pathway corresponding to the target disease, the method further comprises, prior to adding the first treatment item to the target standard treatment regimen:
detecting whether the first treatment item is matched with a second treatment item according to a detection index, wherein the second treatment item is any treatment item in a clinical path corresponding to the target disease, and the detection index comprises the function of the treatment item, the number of times of average use of the treatment item and the cost of the treatment item;
if the first treatment item matches the second treatment item, triggering the operation of adding the first treatment item to the target standard treatment regimen.
3. The method of claim 2, wherein detecting whether the first treatment item matches a second treatment item based on a detection indicator comprises:
Detecting whether the function of the first treatment item is the same as the function of the second treatment item;
if so, detecting whether the times of the first treatment item for the average use are the same as the times of the second treatment item for the average use;
if the first treatment item and the second treatment item are the same, calculating a difference value between the cost of the first treatment item and the cost of the second treatment item;
and if the difference is smaller than a preset difference, determining that the first treatment item is matched with the second treatment item.
4. The method of claim 1, wherein prior to the acquiring at least one treatment regimen for at least one sample patient within the predetermined area, the method further comprises:
screening patients suffering from target disease species in a preset area according to preset screening conditions, wherein the screening conditions comprise the same gender, age group or medical history;
and determining the patient with the target disease species meeting the screening conditions in the preset area as a sample patient.
5. The method of claim 1, wherein the determining the disease type of the patient to be tested according to the similarity of the target standard treatment regimen to the treatment regimen for the patient to be tested in the preset area comprises:
Acquiring a treatment scheme for a patient to be detected in the preset area;
detecting a similarity of a treatment regimen for the patient to be detected to the target standard treatment regimen;
and if the similarity is greater than the preset similarity, determining the target disease type corresponding to the target standard treatment scheme as the disease type of the patient to be detected.
6. The method of claim 5, wherein the detecting similarity of the treatment regimen for the patient to be detected to the target standard treatment regimen comprises:
obtaining a first number of identical treatment items in the treatment regimen for the patient to be tested and the target standard treatment regimen;
calculating a ratio of the first number to a total number of treatment items in the treatment regimen for the patient to be tested;
and determining the ratio as the similarity of the treatment plan for the patient to be detected and the target standard treatment plan.
7. A sample processing-based disease type determining apparatus, the apparatus comprising:
an acquisition module for acquiring at least one treatment plan of at least one sample patient in a preset area, wherein the at least one sample patient has the same target disease species, and one treatment plan comprises at least one treatment item;
The detection module is used for detecting whether a first treatment item exists in a clinical path corresponding to the target disease, wherein the first treatment item is any treatment item in the at least one treatment scheme;
the detection module is further configured to detect whether a usage rate of the first treatment item is greater than a first preset threshold if the first treatment item exists in a clinical path corresponding to the target disease, where the usage rate of the first treatment item is determined according to a number of sample patients treated with the first treatment item;
the adding module is used for adding the first treatment item to a target standard treatment scheme if the utilization rate of the first treatment item is greater than the first preset threshold value, wherein the target standard treatment scheme is a standard treatment scheme corresponding to the preset area and the target disease, and the target standard treatment scheme comprises at least one standard treatment item for treating the target disease in the preset area;
the detection module is further configured to detect whether a usage rate of a first treatment item is greater than a second preset threshold if the first treatment item does not exist in a clinical path corresponding to the target disease, where the second preset threshold is greater than the first preset threshold;
The obtaining module is further configured to obtain an acceptance of the at least one sample patient for the first treatment item if the usage rate of the first treatment item is greater than the second preset threshold, where the acceptance is determined by a number of sample patients approved for the first treatment item;
the adding module is further configured to add the first treatment item to the target standard treatment plan if the acceptance is greater than a preset acceptance;
and the determining module is used for determining the disease type of the patient to be detected according to the similarity of the target standard treatment scheme and the treatment scheme of the patient to be detected in the preset area.
8. A terminal comprising a processor, an input device, an output device and a memory, the processor, the input device, the output device and the memory being interconnected, wherein the memory is adapted to store a computer program comprising program instructions, the processor being configured to invoke the program instructions to perform the method of any of claims 1-6.
9. A computer readable storage medium, characterized in that the computer storage medium stores a computer program comprising program instructions which, when executed by a processor, cause the processor to perform the method of any of claims 1-6.
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| CN110060786A (en) * | 2019-04-17 | 2019-07-26 | 深圳安泰创新科技股份有限公司 | Internet interrogation reminding method, device, terminal and storage medium |
| CN112397171A (en) * | 2020-12-04 | 2021-02-23 | 上海蓬海涞讯数据技术有限公司 | DRG-based method, device, processor and storage medium for realizing monitoring of critical path for diagnosis and treatment items and materials |
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