CN110993050A - Method for calculating predicted report time of medical examination based on artificial intelligence - Google Patents
Method for calculating predicted report time of medical examination based on artificial intelligence Download PDFInfo
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Abstract
The invention discloses a method for calculating the predicted report time of medical examination based on artificial intelligence, which comprises the following steps: s1: signing for a sample; s2: processing sample information; s3: determining the initial detection date of the sample; s4: calculating the completion date of the experimental project, and adding the time required by the detection project in the experimental project table and the initial detection date of the sample by the sample date calculating component to determine the completion date of the experimental project; s5: judging a report date, searching report time aiming at the detection item in an experiment report configuration table by a sample date calculation component, and judging the report date according to the completion date and the report time of the experiment item; s6: and feeding back sample detection information. According to the invention, by configuring the detection mechanism aiming at the information of the starting time, the experiment date length, the rest day and the like of the detection project, the time for predicting the report of the current detection project can be quickly determined, so that the aim of rapidness is fulfilled, and a doctor can be helped to better perform medical service on a patient.
Description
Technical Field
The invention relates to the technical field of computer information processing, in particular to a method for calculating predicted report time of medical inspection based on artificial intelligence.
Background
With the rapid development of data-based and information-based systems, how to rapidly improve the medical quality of the basic medical unit through an information-based means will be a core appeal for basic medical institutions and patients in the future. The system estimates the time of the test report by matching the relevant configuration data of the laboratory through the sample information of the patient blood drawing test, so that the clinic doctor can determine the viewing time of the report, the patient condition is determined by analyzing the report, and the pain of the patient is relieved. Currently, judgment is carried out by adopting an estimation mode aiming at a detection result, but not an intelligent automatic calculation mode.
Disclosure of Invention
The invention aims to overcome the defects of the prior art and provides a method for calculating the predicted report time of a medical test based on artificial intelligence.
The purpose of the invention is realized by the following technical scheme: a method for calculating a predicted reporting time for a medical examination based on artificial intelligence, comprising the steps of:
s1: signing a sample, signing the sample by a laboratory, and sending a signing command, wherein the command contains a sample information data transmission object;
s2: processing sample information, wherein the sample date calculation component receives a sample information data transmission object in the signing command, and searches an experiment time period of an experiment project through the sample information data transmission object;
s3: determining the initial detection date of the sample, wherein the sample date calculation component determines the initial detection date of the sample according to the sample detection date of the sample information data transmission object;
s4: calculating the completion date of the experimental project, and adding the time required by the detection project in the experimental project table and the initial detection date of the sample by the sample date calculating component to determine the completion date of the experimental project;
s5: judging a report date, searching report time aiming at the detection item in an experiment report configuration table by a sample date calculation component, and judging the report date according to the completion date and the report time of the experiment item;
s6: feeding back sample detection information; the sample date calculation component feeds back the detected sample information data transmission object to the doctor again, and the doctor can know the experimental data of the sample through the sample information data transmission object.
Preferably, the information data in S1 includes a laboratory code, a sample bar code number, a sample detection date, and a detection item.
Preferably, the sample information data transmission object according to the step of S2 is a laboratory code and a test item.
Preferably, in S3, the sample detection date needs to be determined, when the sample detection date is in the experiment time period of the experiment item, the sample detection date is the sample initial detection date, and when the sample detection date is not in the experiment time period of the experiment item, the sample initial detection date is continued backward on the basis of the sample detection date until the sample initial detection date is in the experiment time period of the experiment item.
Preferably, in S4, the time required for the test items in the test item table is set as an initial date, the date of completion of the test item is estimated by adding the initial date to the initial date, and when the date of completion of the test item is estimated to fall within the legal holiday date, the date of completion of the test item is continued based on the estimated date of completion of the test item until the date of completion of the test item does not fall within the legal holiday date, and when the date of completion of the test item is not estimated to fall within the legal holiday date, the date of completion of the test item is the date of completion of the estimated test item.
Preferably, the experiment report configuration table in S5 further includes a report date, a date on which the experiment item is completed and a report time are added to form a report date, the report date is determined as a report date if the report date does not fall within the report date, and the report date is continued based on the report date until the report date does not fall within the report date if the report date falls within the report date.
Preferably, the sample information data transmission object in S6 includes a sample barcode number, detection item data, and a report date.
The invention has the following advantages: according to the invention, by configuring the detection mechanism aiming at the information of the starting time, the experiment date length, the rest day and the like of the detection project, the time for predicting the report of the current detection project can be quickly determined, so that the aim of rapidness is fulfilled, and a doctor can be helped to better perform medical service on a patient.
Detailed Description
In addition, the embodiments of the present invention and the features of the embodiments may be combined with each other without conflict.
In the description of the present invention, it should also be noted that, unless otherwise explicitly specified or limited, the terms "disposed," "mounted," "connected," and "connected" are to be construed broadly and may, for example, be fixedly connected, detachably connected, or integrally connected; can be mechanically or electrically connected; they may be connected directly or indirectly through intervening media, or they may be interconnected between two elements. The specific meanings of the above terms in the present invention can be understood in specific cases to those skilled in the art.
A method for calculating a predicted reporting time for a medical examination based on artificial intelligence, comprising the steps of:
s1: the method comprises the steps of sample signing, wherein a laboratory signs a sample and sends a signing command, the command contains a sample information data transmission object, in the actual application process, the sample information data transmission object is SampleInfoDTO, the following sample signal data transmission object is replaced by the SampleInfoDTO, and the SampleInfoDTO comprises LabCode, SampleNo, SampleCheckDate and CheckItem, namely the sample information data transmission object comprises a laboratory code, a sample bar code number, a sample detection date and a detection item;
s2: sample information processing, wherein sampleDateComputeMsg receives sampleInfoDTO in the sign-in command, the sampleDateComputeMsg is a sample date calculation component, an experiment time period of an experiment item is searched through the sampleInfoDTO, specifically, a Week field of a LabItem is searched according to Labcode and CheckItem information in the sampleInfoDTO, the Labcode is the experiment item, the CheckItem is a detection item, the Week field mainly refers to that a laboratory aims at the detection item, and a start-up can be performed on the day of the Week, so the Week field can be set to be any day or several days of the Week;
s3: determining the initial detection date of the sample, wherein the sampleDateComputeMsg determines the initial detection date of the sample according to the sampleCheckDate of the sampleInfoDTO, in the practical application process, the judgment of the sampleCheckDate is needed, namely when the sampleCheckDate is in the Week field, the detection date of the sample is in the experimental period of the experimental item, namely the detection date of the sample can be used for carrying out the experimental item of the sample, so the sampleCheckDate is the initial detection date of the sample, when the sampleCheckDate is not in the Week field, the initial detection date of the sample is continued backwards on the basis of the sampleCheckDate until the initial detection date of the sample is in the experimental period of the Week field, namely, a date variable X is declared, the initial value of the date variable is the date of the sampleCheckDate, and then the date variable is assigned, and the cyclic comparison is carried out by adopting X = X +1 until the initial detection date of the sample is in the experimental period of the Week field.
S4: calculating the completion date of the experimental project, and judging the completion date of the experimental project by adding the time required by the detection project in the experimental project table and the initial detection date of the sample by the SampleDateComputeMSg; setting the time required by CheckItem in the LabItem table as an initial date, adding the initial date to the initial detection date of the sample to form a date of the completion of the predicted experimental item, when the date of the completion of the predicted experimental item is within the legal holiday date, continuing the date of the completion of the experimental item on the basis of the date of the completion of the predicted experimental item until the date of the completion of the experimental item is not within the legal holiday date, setting the variable of the date of the completion of the predicted experimental item as Y, performing cycle evaluation according to the formula Y = Y +1 to determine the date of the completion of the experimental item, and when the date of the completion of the predicted experimental item is not within the legal holiday date, determining the date of the completion of the experimental item as the date of the completion of the predicted experimental item
S5: judging a report date, searching report output time aiming at CheckItem in LabReportConfig by SampleDateComputeMsg, and judging the report date according to the completion date and the report output time of the experimental item; here, the LabReportConfig is an experiment report configuration table, and further, a non report is included in the LabReportConfig, and the non report is a report output rest date, that is, a report is not output on the same day, and a date when an experiment item is completed and a report output time are added to form a report output date, and in general, the report output can be immediately output when the experiment item is completed, so that the report output time is usually 0, if the report output date does not fall within the non report interval, the report output date is determined as a report output date, and if the report output date falls within the non report interval, the report output date is advanced based on the report output date until the report output date does not fall within the report output rest date, that is, the report output date is set as Z, and then the report output date is evaluated with the non report interval in a manner of Z = Z +1, so as to determine the report output date.
S6: feeding back sample detection information; the sample date calculation component feeds back the detected sampleInfoDTO to the doctor, and the doctor can know the experimental data of the sample through the sampleInfoDTO, and further, the sampleInfoDTO comprises sampleNo, CheckItem and report date.
Two laboratories are further described below as examples:
example one: signing a sample including a blood routine test item in Sichuan laboratory;
the Sichuan laboratory signs the sample to obtain LabCode, SampleNo, SampleCheckDate (2019, 9 and 17 days) sample detection date and CheckItem of the sample, wherein the time for signing the sample is 2019, 9 and 17 days, namely SampleCheckDate is 2019, 9 and 17 days, and CheckItem mainly adopts blood routine item detection;
SampleDateComputeMsg receives SampleInfoDTO, searches Week fields in LabItem registration items through Labcode and CheckItem information of the SampleInfoDTO, and the field values are Monday to Sunday, which indicates that the computer is started for the detection item every day.
SampleDateComputeMsg determines whether the SampleCheckDate of SampleInfoDTO falls within the Week field interval, whereas days 9 and 17 of 2019 are tuesdays, falls within the start-up day of the Week field, declares a variable X and assigns X = SampleCheckDate, when the sample initial test date is 2019, day 9 and 17.
The SampleDateComputeMsg searches for the Holiday field of the LabItem table for the blood routine test item, namely the legal Holiday date, and since the initial test date of the sample is 2019, month 9 and day 17, but not the Holiday date of the holidaty, the initial test date of the sample required for the LabItem to check the test item for the blood routine is 1 day, which represents that a working day is required for the blood routine test, the date of completion of the experimental item is predicted to be 2019, month 18, and the date of completion of the experimental item is not the legal Holiday date of 2019, month 18, so the date of completion of the experimental item is 2019, month 18.
SampleDateComputeMsg searches for a NonReport for the blood routine test item in LabReportConfig, the NonReport value is Sunday, and 9/18 th in 2019 is Wednesday, and the NonReport does not fall in a NonReport interval, so that the report date is 9/18 th in 2019.
SampleDate ComputeMsg finally returns the DTO object of ComputeReportDate to the doctor, the ComputeReportDate is the report date, and the SampleInfo DTO received by the doctor comprises SampleNo, CheckItem and ComputeReportDate.
Example two: the south of Henan laboratory signed for a sample containing 7 measures of liver function:
the sample is checked in by Henan laboratory to obtain SampleInfoDTO, wherein the SampleInfoDTO comprises LabCode, SampleNo, SampleCheckDate and CheckItem, and the SampleCheckDate is 2019, 9 and 14 days, and the CheckItem is liver function 7;
SampleDateComputeMsg receives SampleInfoDTO: the Week field value of LabCode and CheckItem information lookup table LabItem of the SampleInfoDTO is from Monday to Saturday, indicating that every Week except the Sunday is powered on for this item.
sampleDateComputeMsg determines whether the day of Week corresponding to the sampleCheckDate date of the sampleInfoDTO object falls within the Week field interval, and if so, the Week 14 in 2019 is Saturday, and the day of Week is fallen into the start date of Week, declares a variable X, and assigns X = sampleCheckDate, and then the initial detection date of the sample is 2019, 9 and 14 days.
SampleDateComputeMsg searches the Holiday field of the LabItem table for the CheckItem detection item, the set date variable value Y is 2019, month 9 and day 14, is the Holiday date of the Holiday, the value is Y = Y +1, 2019-09-15, the value after the value is still in the Holiday of the Holiday, the value is further assigned Y = Y +1, 2019, month 9 and day 16, and finally the date does not fall in the Holiday of the Holiday, and then the detection date of the LabItem for the liver function 7 detection item is checked, the detection date is 3, which represents that three working days need to be detected, so the experiment item completion date is added to 2019, month 16, namely 2019, month 9 and day 19.
SampleDateComputeMsg searches a NonReport of a LabReportConfig table for the CheckItem detection item, wherein the NonReport value is Sunday, the week corresponding to the 9/19/2019 th Date of Date does not fall in the interval, and the ComputeReportDate is the 19/9/2019 th Date.
SampleDateComputeMsg feeds back the detected SampleInfoDTO to the doctor, and the doctor can know the experimental data of the sample through the SampleInfoDTO, and further, the SampleInfoDTO comprises SampleNo, CheckItem and ComputeReportDate.
Although the present invention has been described in detail with reference to the foregoing embodiments, it will be apparent to those skilled in the art that various changes in the embodiments and/or modifications of the invention can be made, and equivalents and modifications of some features of the invention can be made without departing from the spirit and scope of the invention.
Claims (7)
1. A method for calculating a predicted reporting time for a medical examination based on artificial intelligence, comprising: the method comprises the following steps:
s1: signing a sample, signing the sample by a laboratory, and sending a signing command, wherein the command contains a sample information data transmission object;
s2: processing sample information, wherein the sample date calculation component receives a sample information data transmission object in the signing command, and searches an experiment time period of an experiment project through the sample information data transmission object;
s3: determining the initial detection date of the sample, wherein the sample date calculation component determines the initial detection date of the sample according to the sample detection date of the sample information data transmission object;
s4: calculating the completion date of the experimental project, and adding the time required by the detection project in the experimental project table and the initial detection date of the sample by the sample date calculating component to determine the completion date of the experimental project;
s5: judging a report date, searching report time aiming at the detection item in an experiment report configuration table by a sample date calculation component, and judging the report date according to the completion date and the report time of the experiment item;
s6: feeding back sample detection information; the sample date calculation component feeds back the detected sample information data transmission object to the doctor again, and the doctor can know the experimental data of the sample through the sample information data transmission object.
2. The method for calculating the predicted report time of medical examination based on artificial intelligence of claim 1, wherein: the information data in S1 includes laboratory code, sample bar code number, sample detection date, and detection item.
3. The method for calculating the predicted report time of medical examination based on artificial intelligence as claimed in claim 2, wherein: the sample information data transmission object according to the step of S2 is a laboratory code and a test item.
4. The method for calculating the predicted report time of medical examination based on artificial intelligence as claimed in claim 3, wherein: in S3, the sample detection date needs to be determined, when the sample detection date is in the experiment time period of the experiment item, the sample detection date is the sample initial detection date, and when the sample detection date is not in the experiment time period of the experiment item, the sample initial detection date is continued backward on the basis of the sample detection date until the sample initial detection date is in the experiment time period of the experiment item.
5. The method for calculating the predicted report time of medical examination based on artificial intelligence of claim 4, wherein: in S4, the time required for the test items in the test item table is set as the inception date, the expected completion date of the test items is formed by adding the inception date to the sample inception date, and when the expected completion date of the test items falls within the legal holiday date, the completion date of the test items is continued based on the expected completion date of the test items until the completion date of the test items does not fall within the legal holiday date, and when the expected completion date of the test items does not fall within the legal holiday date, the completion date of the test items is the expected completion date of the test items.
6. The method for calculating the predicted report time of medical examination based on artificial intelligence of claim 5, wherein: the experiment report configuration table in S5 further includes a report date, and the date when the experiment item is completed and the report time are added to form a report date to be output, and if the report date to be output does not fall within the report date to be output, the report date to be output is determined as the report date to be output, and if the report date to be output falls within the report date to be output, the report date to be output is delayed backward on the basis of the report date to be output until the report date to be output does not fall within the report date to be output.
7. The method for calculating the predicted report time of medical examination based on artificial intelligence of claim 6, wherein: the sample information data transmission object in S6 includes a sample barcode number, detection item data, and a report date.
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