WO2020029009A1 - 一种样本检测信息管理方法以及样本检测设备 - Google Patents

一种样本检测信息管理方法以及样本检测设备 Download PDF

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Publication number
WO2020029009A1
WO2020029009A1 PCT/CN2018/098955 CN2018098955W WO2020029009A1 WO 2020029009 A1 WO2020029009 A1 WO 2020029009A1 CN 2018098955 W CN2018098955 W CN 2018098955W WO 2020029009 A1 WO2020029009 A1 WO 2020029009A1
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Prior art keywords
sample
abnormal
information
test tube
category
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PCT/CN2018/098955
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English (en)
French (fr)
Inventor
刘建超
王生
詹应键
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深圳迈瑞生物医疗电子股份有限公司
深圳迈瑞科技有限公司
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Application filed by 深圳迈瑞生物医疗电子股份有限公司, 深圳迈瑞科技有限公司 filed Critical 深圳迈瑞生物医疗电子股份有限公司
Priority to CN201880094613.2A priority Critical patent/CN112334930A/zh
Priority to PCT/CN2018/098955 priority patent/WO2020029009A1/zh
Publication of WO2020029009A1 publication Critical patent/WO2020029009A1/zh

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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00—Administration; Management
    • G06Q10/10—Office automation; Time management

Definitions

  • the invention relates to the field of in vitro diagnostics, and in particular, to a method for managing sample detection information and a sample detection device.
  • IVD In vitro diagnostic equipment
  • Human samples detected by IVD mainly include blood, body fluids or tissues.
  • the process of IVD testing of human samples mainly includes: collecting human samples, detecting human samples, and publishing the test results.
  • the unique barcode corresponding to the human sample is attached to the container.
  • the IVD performs the human sample detection, the IVD first scans and obtains the unique barcode, and after the sample detection is completed, the barcode number of the unique barcode corresponds to the detection result.
  • the embodiment of the present application provides a sample detection information management method and a sample detection device, and an inspector can directly obtain an abnormal category and statistical information of abnormal samples belonging to the abnormal category from a sample detection result according to a sample abnormal category, without the need for Finding information about each abnormal sample from a large number of test results reduces the workload and improves the efficiency of in vitro testing.
  • a first aspect of the embodiments of the present application provides a sample detection information management method, including:
  • sample detection result includes abnormal sample detection information
  • a second aspect of the embodiments of the present application provides a sample detection device, including:
  • the processor performs the following steps:
  • sample detection result includes abnormal sample detection information
  • the display displays the at least one classification statistical result.
  • a third aspect of the present application provides a computer-readable storage medium including a program or an instruction.
  • the program or the instruction is run on a computer, the methods in the foregoing aspects are executed.
  • the abnormal sample detection information is confirmed in the sample result, and the abnormal sample detection information is classified and statistic based on the sample abnormal category.
  • the inspector can directly obtain the abnormal category from the sample detection result according to the sample abnormal category. And statistical information of abnormal samples belonging to the abnormal category, without the need to find each piece of abnormal sample detection information from a large number of detection results, reducing the workload and improving the efficiency of in vitro detection.
  • FIG. 1 is a schematic block diagram of a sample detection device according to an embodiment of the present application.
  • FIG. 2 is a schematic diagram of an embodiment of a sample detection information management method according to an embodiment of the present application
  • 3a is a schematic diagram of a sample detection result in an embodiment of the present application.
  • 3b is a schematic diagram of abnormal sample detection information in an embodiment of the present application.
  • FIG. 4 is a schematic diagram of a display interface of a classification and statistics result in an embodiment of the present application.
  • FIG. 5a is a schematic diagram of a main display interface of a classification and statistics result in an embodiment of the present application.
  • FIG. 5b is a schematic diagram of a sub-display interface of a classification and statistics result in an embodiment of the present application.
  • FIG. 6 is a schematic diagram of a sub-display interface of a classification and statistics result in an embodiment of the present application.
  • FIG. 7a is a schematic diagram of a first sub-display interface of a classification and statistics result in an embodiment of the present application
  • 7b is a schematic diagram of a second sub-display interface of a classification and statistics result in an embodiment of the present application.
  • FIG. 8a is a schematic diagram of a third sub-display interface of a classification and statistics result in an embodiment of the present application.
  • FIG. 8b is a schematic diagram of a fourth sub-display interface of a classification and statistics result in an embodiment of the present application.
  • FIG. 9 is a schematic flowchart of a mode of “level one abnormal sample information display” in an application scenario of this application.
  • FIG. 10 is a schematic flowchart of a “secondary abnormal sample information display” mode in an application scenario of this application.
  • FIG. 11 is a schematic flowchart of a "three-level abnormal sample information display" mode in an application scenario of this application;
  • FIG. 12 is another schematic flowchart of the "three-level abnormal sample information display" mode in the application scenario of this application.
  • FIG. 1 is a schematic structural block diagram of a sample detection device 10 in an embodiment of the present invention.
  • the sample detection device 10 may include a processor 101, a scanner 102, a sensor 103, a display 104, and a memory 105.
  • the scanner 102 may scan a bar code, a two-dimensional code or other identification attached to the outer wall of a sample container (such as a test tube) for holding a sample to obtain sample identification information, and send the sample identification information to the processor 101.
  • the sensor 103 recognizes whether there is a sample container at each position where the sample container is placed on the test tube rack, and sends the recognition result to the processor 101.
  • the component analysis result is sent to the processor 10.
  • the processor 101 performs anomaly analysis and classification statistics processing on the component analysis result and the identification information to obtain classification statistics results.
  • the classification and statistical results obtained by the processor 101 may be stored in the memory 105.
  • the classification statistics results can be displayed on the display 104.
  • the display 104 of the aforementioned sample detection device 10 may be a touch display screen, a liquid crystal display, or the like, or may be an independent display device such as a liquid crystal display, a television, etc., which is independent of the sample detection device 10.
  • the memory 105 of the aforementioned sample detection device 10 may be a flash memory card, a solid state memory, a hard disk, or the like.
  • An embodiment of the present invention further provides a computer-readable storage medium.
  • the computer-readable storage medium stores a plurality of program instructions. After the plurality of program instructions are called and executed by the processor 101, the program instructions in the foregoing embodiments can be executed. Some or all steps or any combination of steps in the method for managing sample detection information.
  • the computer-readable storage medium may be the memory 105, which may be a non-volatile storage medium such as a flash memory card, a solid state memory, or a hard disk.
  • the processor 101 of the aforementioned sample detection device 10 may be implemented by software, hardware, firmware, or a combination thereof, and may use a circuit, a single or multiple application-specific integrated circuits (ASIC), a single Or multiple general-purpose integrated circuits, single or multiple microprocessors, single or multiple programmable logic devices, or a combination of the foregoing circuits or devices, or other suitable circuits or devices, so that the processor 101 can perform various implementations The corresponding steps of the sample detection information management method in the example.
  • ASIC application-specific integrated circuits
  • microprocessors single or multiple programmable logic devices
  • sample detection information management method in the present invention is described in detail below. Please refer to FIG. 2.
  • a sample detection information management method provided by an embodiment of the present invention is applied to the sample detection device 10.
  • the embodiment of the sample detection information management method includes :
  • the sample needs to be detected. It can be understood that, before the sample is detected, the sample needs to be placed in the sample suction position in the detection port of the sample detection device 10 so that the sample detection device 10 can pass the probe. The sample is sucked with a needle. The sample can be placed automatically or manually. Taking automatic sample as an example, the detection port of the sample detection device 10 can be provided with a conveyor belt. The inspectors place each sample on the conveyor belt in turn. The conveyor belt drives the sample to be transferred to the sample suction position in the detection port of the sample detection device 10 for the sample detection device 10 to perform sample suction and subsequent detection through the probe. Each time the sample detection device 10 completes the detection process, the conveyor can be controlled to perform the next step.
  • a sample is transmitted to realize automatic sample delivery. It can be understood that the sample needs to be contained in a sample container.
  • the sample container can be a test tube, a centrifuge tube (eppendorf, EP tube) or other detection vessels, which is not limited here. Further Can be placed in the test port of the sample detection device 10 Inside the sample aspiration position, specifically, the tester places each sample on a conveyor belt in turn, and the conveyor belt drives the sample to be transferred to the sample aspiration location in the detection port of the sample detection device 10 for the sample detection device 10 to suck the sample through the probe and Subsequent testing.
  • the sample detection device 10 After the sample detection device 10 completes the automatic or manual sample delivery and sucks the sample, it is equivalent to completing the preparation for obtaining the sample. After that, the sample detection device 10 can detect the sample.
  • the sample may include but not It is limited to human blood, human body fluids, or human tissues. It can be understood that different samples are detected, and the corresponding sample detection device 10 is also different. Accordingly, the sample detection device 10 may be a blood analyzer, a body fluid detector, and a tissue detector.
  • the process of detecting the sample by the sample detection device 10 may include the following steps: Step 1. Obtain the position of the sample container where the sample is located; Step 2. The sample detection device 10 scans the sample identification of the sample to obtain the sample identification information. Step 3: Perform a component analysis on the sample obtained by aspiration to obtain a component analysis result.
  • the sample detection device 10 can scan a sample rack (such as a test tube rack) by a scanner to obtain a sample rack number, and then use a sensor to sense the position of the sample container on the test tube rack to obtain the position of each sample. Information, for example, a sample is in position 2 of No.
  • the position information of the sample can be obtained by this method is 1-2; if a sample container is out of specification (such as smaller size) or placed If it is improper, the existence of the sample container cannot be detected, a detection abnormality will occur, and the abnormal sample can be classified as an empty seat.
  • the sample identification information of step 2 carries a unique identification identifier corresponding to the sample. Taking a blood analyzer as an example, the sample identification information is a unique identification identifier that uniquely corresponds to the source of the blood sample.
  • the sample identification information may be, but is not limited to, On the bar code or two-dimensional code, the bar code or two-dimensional code carrying the sample identification information can be pasted on the outer wall of the sample container containing the sample.
  • steps 1, 2, and 3 are only examples of the detection process, and the actual detection process is not limited to the above three types, and there is no necessary timing relationship between steps 1, 2, and 3, that is, steps 1 can be performed before step 2, step 1 can be performed after step 2, or step 1 and step 2 are performed simultaneously.
  • the timing relationship between the specific steps of the detection process can be selected according to actual requirements, which is not limited in this embodiment.
  • sample detection result includes abnormal sample detection information
  • the processor 101 can obtain a sample detection result.
  • the sample detection result may include abnormal sample detection information and normal sample detection information, among which abnormal sample detection
  • the information includes abnormal sample detection information due to abnormalities in the detection process (such as analyzer plugging, sample aspiration failure, sample barcode scanning failure, or vacancy).
  • the processor 101 needs to perform abnormality identification on the sample detection result to determine which of the sample detection results belong to the abnormal sample detection information.
  • the abnormality identification first needs to determine whether the detection result is complete.
  • the above detection process including steps 1 to 3 is taken as an example.
  • the abnormality identification Specifically, whether the sample detection result includes both the component analysis result and the sample identification information.
  • the normal sample detection information rule in the sample detection result can be determined, and further, the normal condition is not satisfied.
  • the sample detection result of the sample detection information rule can be determined as abnormal sample detection information, and the normal sample detection information rule that determines the sample detection result is:
  • the sample detection result includes both the sample identification information and the component analysis result.
  • the sample identification information is included but not Include ingredients Analysis of results (sample identification information), but does not include the identification information of the sample analysis results comprising component (component analysis), the identification information includes neither the sample nor a component analysis (vacancies) test results for three samples abnormality detection information.
  • FIG. 3a and FIG. 3b FIG. 3a is a schematic diagram of a sample detection result in the embodiment of the present application
  • FIG. 3b is a schematic diagram of abnormal sample detection information in the embodiment of the present application.
  • the results include sample identification information "A”, “B”, “C”, “E”, “G”, and “H”, and also include two "?”, Where "?” Indicates the sample identification of the sample test result. Information is missing.
  • the sample test results shown in Figure 3a also include the results of component analysis. Taking a blood analyzer to test blood samples as an example, white blood cells (WBC) and red blood cells (RBC) are specific. The results of the two component analysis of normal, the normal component analysis results should be specific values, such as “6.3”, “5.0”, etc., Figure 3a also includes “***", at this time "***” means the corresponding " WBC "or” RBC "component analysis results are missing. Please refer to FIG. 3b. FIG.
  • FIG. 3b is a schematic diagram of the abnormal sample detection information corresponding to the sample detection result shown in FIG. 3a.
  • FIG. 3b includes all the abnormal sample detection information in FIG. Sample detection information, the second line is abnormal sample detection information due to missing sample identification information, and the third line is abnormal sample detection information due to both missing component analysis results and sample identification information.
  • the processor 101 needs to perform classification statistics on the abnormal sample detection information to obtain at least one classification statistical result.
  • Each classification statistical result includes an abnormal category and belongs to the abnormality. Anomaly sample statistics for the category.
  • the processor 101 needs to perform classification statistics on the abnormal sample detection information, and the classification basis is specifically classified according to different types of abnormalities.
  • the quantity statistics of the abnormal sample detection information belonging to each classification category can be obtained to obtain the quantity statistical information. Further, in order to improve the classification statistics As a result, it is possible to further obtain abnormal sample position information, where the abnormal sample position information may be a test tube rack number of a test tube rack corresponding to the test tube where the abnormal sample is located, and position information of the test tube on the test tube rack. It is understandable that the abnormal The position information of the sample can be equivalent to the physical position information of the sample container that holds the abnormal sample. Generally, the sample container needs a holder to fix it. Taking the sample container as an example, the holder for fixing the test tube can be a test tube.
  • the physical position information of the sample container containing the abnormal sample can be determined by the label (test tube rack number) of the test tube rack and the position information of the test tube on the test tube rack. It can be seen that only the test tube rack number of the test tube rack corresponding to the test tube where the abnormal sample is located; and the position information of the test tube on the test tube rack can determine the position information of the abnormal sample. Further, in order to improve the classification statistics As a result, the abnormal sample detection time can be further obtained. It should be noted that the above-mentioned statistical information of the number of abnormal categories, the abnormal sample detection information belonging to the abnormal category, the location information, and the abnormal sample detection time can all be included in the embodiments of the present application. Statistics of anomaly samples belonging to this anomaly category.
  • the processor 101 obtains at least one classification statistical result after completing the classification statistics of the abnormal samples, wherein each classification statistical result includes an abnormal category and statistical information of the abnormal samples belonging to the abnormal category, which needs to be explained
  • the abnormal sample statistical information in this embodiment may include at least one of statistical information of the number of abnormal categories, detection information of abnormal samples belonging to the abnormal category, location information, and detection time of abnormal samples.
  • the obtained at least one classification statistical result may be stored in the memory 103.
  • At least one classification statistical result may be displayed on the display 102.
  • Each classification statistical result includes an abnormal category and statistical information of abnormal samples belonging to the abnormal category.
  • the display 102 of the aforementioned sample detection device 10 may be touched. The display screen, the liquid crystal display screen, etc.
  • FIG. 4 is a schematic diagram of a display interface for classification and statistical results in the embodiment of the present application.
  • Figure 4 shows the results of four classification statistics, corresponding to the four types of anomalies: “analyzer plugging”, “sample aspiration failure”, “invalid barcode”, and “vacancy”. Contains abnormal sample detection information-"sample identification information", location information-"sample location”, and abnormal sample detection time-"detection time” that belong to this abnormal category.
  • the sample detection device 10 can confirm abnormal sample detection information in a sample result, and perform classification statistics on the abnormal sample detection information at the same time.
  • the abnormal category and the abnormal sample statistical information belonging to the abnormal category can be directly obtained from the sample detection results according to the sample abnormal category, without the need to find each piece of abnormal sample detection information from a large number of detection results, reducing the workload , Which improves the efficiency of in vitro detection.
  • classifying statistics on an abnormal sample includes: identifying whether the abnormal sample is Due to the plugging of gemstone holes in the red blood cell / platelet impedance channel of the detection instrument, if so, the abnormal sample is classified as a plugging hole; identifying whether the abnormal sample is due to a clot in the sample, or the amount of specimen does not meet the minimum test amount, Or it is caused by air bubbles in the aspiration process.
  • the abnormal sample is classified as an abnormal sample; identify whether the abnormal sample is caused by the failure of the barcode scanning of the sample; if so, the abnormal sample is classified as an un-barcoded invalid; Or identify whether the abnormal sample has a test tube because the location of the abnormal sample is not identified, and if so, classify the abnormal sample as a vacancy.
  • the processor 101 before the processor 101 classifies and collects the abnormal sample detection information according to the difference of the abnormal category, it is necessary to confirm the abnormal category of each abnormal sample detection information.
  • perform the abnormal category confirmation on the abnormal sample detection information can include:
  • the sample detection device 10 identifies whether the abnormal sample is caused by a gem hole plugging in the RBC / PLT impedance channel of the detection instrument, and if so, the abnormality Samples are classified as analyzer plugging holes;
  • the abnormal sample is caused by a clot in the sample, or the sample amount does not meet the minimum test amount, or caused by air bubbles during the aspiration process; if so, the abnormal sample is classified as a suction failure;
  • sample identification information such as the barcode or two-dimensional code corresponding to the missing barcode number or number
  • identify whether the abnormal sample was caused by the failure of the sample barcode scanning and if so, classify the abnormal sample as Invalid barcode
  • the abnormal sample When neither the sample identification information nor the component analysis result is included, it is further identified whether the abnormal sample has a test tube because the location where the abnormal sample is located is not identified, and if so, the abnormal sample is classified as a vacancy.
  • the classification statistics of the abnormal samples are completed. Further, in order to improve the classification statistical results, anomalies belonging to each classification category can be further performed. The number of sample detection information is counted to obtain the number of statistical information. Further, in order to improve the classification statistical results, the abnormal sample position information can be further obtained, where the abnormal sample position information can be a test tube rack of a test tube rack corresponding to the test tube where the abnormal sample is located. No .; and the position information of the test tube on the test tube rack. It can be understood that the position information of the abnormal sample can be equivalent to the physical position information of the sample container holding the abnormal sample. Generally, the sample container needs a fixed rack to carry it out.
  • the fixing rack for fixing the test tube may specifically be a test tube rack, and at least one test tube is arranged on the test tube rack. Therefore, the physical position information of the sample container holding the abnormal sample can be identified by the test tube rack's label. (Test tube rack number) and test Determination of the position information of the test tube rack. It can be seen that only the test tube rack number of the test tube rack corresponding to the test tube where the abnormal sample is located; and the position information of the test tube on the test tube rack can determine the position information of the abnormal sample. Further, in order to improve the classification statistics As a result, the target abnormal sample detection time and target abnormal sample identification information can be further obtained.
  • classifying and statistic of the abnormal sample includes: identifying whether the abnormal sample is caused by a gem hole blocking in the RBC / PLT impedance channel of the detection instrument, and if so, classifying the abnormal sample as Plugging holes; identify whether the abnormal sample is caused by clots in the sample, or the sample amount does not meet the minimum test amount, or air bubbles are generated during the aspiration process; if so, the abnormal sample is classified as an abnormal aspiration sample; identify the abnormal sample Whether it is caused by the failure of the barcode scanning of the sample, and if so, classify the abnormal sample as an invalid barcode; or identify whether the abnormal sample has a test tube because the location of the abnormal sample is not identified, and if so, classify the abnormal sample The class is vacant.
  • the abnormal sample detection information can be classified and classified into four types of classification statistical results, which improves the accuracy of classification statistics.
  • the method further includes:
  • each abnormal sample information of the target abnormal category is displayed, and each abnormal sample information includes abnormal sample position information.
  • FIG. 5a is a schematic diagram of a main display interface of a classification statistical result in the embodiment of the present application
  • FIG. 5b is a schematic diagram of a sub-display interface of the classification statistical result in the embodiment of the present application.
  • the main display interface contains the abnormal category (analyzer plugging, sample aspiration failure, invalid bar code, and vacancy) and the statistical information (3, 2, 2, 1) belonging to the abnormal category. It can be understood
  • the type and arrangement of the abnormality category in FIG. 5a is only an example, and other abnormality types may be displayed and arranged in practice, which is not limited here.
  • the interface in order to provide the inspector with a specific abnormal sample information that belongs to a certain abnormal category, the interface also includes a "Detailed Information” module: when the button is clicked, a query instruction is received, and the query instruction is received. It is used to view the abnormal sample information of the target anomaly category.
  • a "Detailed Information” module in Fig. 5a can also be named “Specific Information” or “View More”, etc., and the "Detailed Information” module in Fig. 5a It is only an example, and other named modules are displayed in practice, which is not limited here;
  • each The abnormal sample information includes abnormal sample position information.
  • the specific display mechanism of classification and statistics results is explained, that is, receiving a query instruction, and the query instruction is used to view the abnormal sample information of the target abnormal category; in response to the query instruction, all abnormal sample information of the target abnormal category is displayed.
  • Each abnormal sample information includes abnormal sample position information.
  • the sample detection device 10 displays the classification statistical result and the abnormal sample information including the abnormal category and the abnormal sample statistical information on the basis of displaying at least one classification statistical result, so that the inspector may The abnormal category is selected, and then the abnormal sample information is displayed. On the basis of not needing to find each piece of abnormal sample detection information from a large number of detection results, the workload is further reduced, and the readability of classification statistics is improved.
  • the method further includes: obtaining abnormal sample position information,
  • the position information of the abnormal sample includes the test tube rack number of the test tube rack corresponding to the test tube in which the abnormal sample is located; and the position information of the test tube on the test tube rack.
  • the abnormal sample position information included in the sub-display interface is shown in FIG. 5b. The specific steps of obtaining the abnormal sample position information are described in detail below.
  • the sample detection device 10 can detect the sample, or the sample detection device 10 can detect the sample, or the sample detection device 10 can detect the sample. While detecting the abnormal sample position information, the abnormal sample position information identifies the specific physical location of the abnormal sample, so that the inspector can directly obtain the physical location of the abnormal sample through the abnormal sample position information corresponding to the abnormal sample.
  • the position information of the abnormal sample may correspond to the test tube in which the abnormal sample is located.
  • the sample container needs a The holder is used to fix the sample container as an example.
  • the holder for fixing the test tube can be a test tube holder. At least one test tube is placed on the test tube holder.
  • the physical position information of the sample container holding the abnormal sample can be It is determined by the label of the test tube rack (test tube rack number) and the position information of the test tube on the test tube rack. It can be seen that only the test tube rack number of the test tube rack corresponding to the test tube where the abnormal sample is located; and the position information of the test tube on the test tube rack can be used to determine the position information indicating the abnormal sample, for example, as shown in FIG. 5b 1-2, 2-9, and 9-6, taking 1-2 as an example, 1 is the test tube rack number of the test tube rack corresponding to the test tube where the abnormal sample is located, and 2 is the position information of the test tube on the test tube rack. 2 can be understood as the position of the No.
  • the position information on the test tube rack can be expressed by No. 1, 2, and 3, and can also be expressed by A, B, and C positions. There is no limitation here.
  • the inspector can directly find the test tube rack where the abnormal sample is located according to the test tube rack number in the position information of the abnormal sample, and according to the position information of the abnormal sample, the test tube The position information on the test tube rack finds the test tube where the corresponding abnormal sample is located.
  • the position information of the abnormal sample is refined into the test tube rack number and the position information of the test tube on the test tube rack.
  • the containers to be a physical location such further detected in the art knowing the position information of the abnormal samples, and faster to find abnormal samples.
  • how to obtain the position of the abnormal sample includes two questions: where to obtain the position of the abnormal sample and how to obtain the position of the abnormal sample from this position. The following describes where to obtain the position of the abnormal sample.
  • the identification of the location of the abnormal sample can be attached to the test tube rack and test tube as follows:
  • test tube rack number of the corresponding test tube rack and the identification of the position information of the test tube on the test tube rack are affixed to the outer wall of the test tube;
  • test tube rack number is affixed to one side of the test tube rack, and the position information on the test tube rack is affixed near the test tube placement holes of the test tube rack.
  • test tube rack number is affixed to one side of the test tube rack, and the outer wall of the test tube is affixed with the position information of the test tube on the test tube rack.
  • the above three methods are only three examples of acquiring positions of abnormal sample positions.
  • the acquisition positions can be set in more ways, which is not limited here.
  • the sample detection device 10 can scan the positions of the abnormal samples by using a recognizer or a scanner. To obtain the position of the abnormal sample. Specifically, the sample detection device 10 may scan the identifier carrying the position of the abnormal sample through a recognizer or a scanner to obtain the test tube rack number of the test tube rack corresponding to the test tube in which the sample is located, and Location information on the tube rack.
  • the position information of the abnormal sample is obtained, and the position information of the abnormal sample includes the test tube rack number of the test tube rack corresponding to the test tube where the abnormal sample is located; and the position information of the test tube on the test tube rack.
  • the position information of the abnormal sample in the above manner, refine the position information of the abnormal sample into the test tube rack number and the position information of the test tube on the test tube rack, and map the sample position to the physical position of the container, further making the inspector know the abnormal sample. In the case of location information, find abnormal samples faster.
  • each abnormal sample information further includes sample identification information At least one of the detection time information.
  • FIG. 6 is a schematic diagram of a sub-display interface of classification and statistical results in the embodiment of the present application. It can be understood that FIG. The display interface that appears after the button of the "Information" module can be seen that the figure contains sample identification information, detection time information, and sample location. It should be noted that the sample identification information can be the same as the barcode and two-dimensional code above. The unique identification information corresponding to the sample source.
  • each abnormal sample information further includes at least one of sample identification information and detection time information.
  • the inspector further shows the sample identification information when the location information of the abnormal sample is known, and can determine the abnormal sample to be found more accurately by judging the detection time, and provide the inspector with For more information guidelines.
  • the fifth optional embodiment of the sample detection information management method provided by the embodiment of the present invention further includes: receiving a second query instruction, and querying The instruction is used to view the second abnormal sample information of the second target abnormal category included in the abnormal sample information.
  • the second target abnormal category includes a detection time period.
  • all second abnormalities of the second target abnormal category are displayed.
  • Each second abnormal sample information includes abnormal sample position information.
  • FIG. 7a is a schematic diagram of a first sub-display interface of a classification statistics result in the embodiment of the present application
  • FIG. 7b is a second sub-display interface of a classification statistics result in the embodiment of the present application
  • FIG. 7a can be a display interface that appears after clicking a button of the “Detailed Information” module in FIG. 5a.
  • the first sub-display interface includes a target anomaly category (analyzer plugging hole) and a second target anomaly category module (detection time) that belongs to the anomaly category.
  • the target anomaly category is only an example, and other target anomaly types can also be displayed and arranged in practice, which is not limited here.
  • the second target anomaly category module in FIG. 7a includes modules corresponding to multiple detection time periods. It can be understood that clicking on any second target anomaly category module is equivalent to the second query instruction to view the second target anomaly.
  • the second abnormal sample information corresponding to the detection period corresponding to the category for example, FIG. 7a shows the second query instruction to view the second abnormal sample corresponding to the time period of "2018-04-0318: 20-18: 25" Information, optionally, each second abnormal sample information includes abnormal sample position information.
  • each second abnormal sample information includes abnormal sample position information.
  • a specific display mechanism of classification and statistics results is explained, that is, a second query instruction is received, and the query instruction is used to view the second abnormal sample information of the second target abnormal category included in the abnormal sample information; in response to the second The query instruction displays all second abnormal sample information of the second target abnormal category, and each second abnormal sample information includes abnormal sample position information.
  • the sample detection device 10 performs the secondary display of the classification statistical result and the abnormal sample information including the abnormal category and the abnormal sample statistical information, so that the detection personnel can further perform the second abnormal category that they want to view. After selecting and displaying the abnormal sample information, on the basis of not needing to search for each piece of abnormal sample detection information from a large number of detection results, the workload is further reduced, and the readability of classification statistics is improved.
  • the method further includes: receiving a third query instruction, and querying The instruction is used to view the third abnormal sample information of the third target abnormal category included in the abnormal sample information.
  • the third target abnormal category includes the second abnormal sample position information.
  • all of the third target abnormal category are displayed.
  • Third abnormal sample information each third abnormal sample information includes third abnormal sample position information.
  • FIG. 8a is a schematic diagram of a third sub-display interface of a classification statistics result in the embodiment of the present application
  • FIG. 8b is a fourth sub-display interface of a classification statistics result in the embodiment of the present application
  • FIG. 8a can be a display interface that appears after clicking a button of the “Detailed Information” module in FIG. 5a.
  • the second sub-display interface includes a target anomaly category (analyzer plugging hole) and a third target anomaly category module (second anomaly sample position information) belonging to the anomaly category.
  • the target abnormality category in FIG. 8a is only an example, and other target abnormality types can also be displayed and arranged in practice, which is not limited here.
  • the third target abnormality category module in FIG. 8a includes modules corresponding to multiple different test tube rack numbers. It can be understood that clicking on any third target abnormality category module is equivalent to the third query instruction to view the third target.
  • the third abnormal sample information corresponding to the test tube rack number corresponding to the abnormal category For example, FIG.
  • each The third abnormal sample information includes the second abnormal sample position information.
  • the second abnormal sample position information and the first abnormal sample position information are more specific position information, for example, as shown in FIG. 7a.
  • An abnormal sample position information is a test tube rack number (for example, test tube rack No. 2)
  • the second abnormal sample position information in FIG. 7b is a specific position on the test tube rack (for example, 2-9, which is the 9th position of test tube rack 2) .
  • each third abnormal sample information includes third abnormal sample position information.
  • the specific display mechanism of the classification and statistics results is explained. That is, a third query instruction is received, and the query instruction is used to view the third target sample information of the third target abnormal category contained in the abnormal sample information, and the third target abnormality.
  • the category includes second abnormal sample position information; in response to the third query instruction, all third abnormal sample information of the third target abnormal category is displayed, and each third abnormal sample information includes third abnormal sample position information.
  • the sample detection device 10 performs the secondary display of the classification statistical result and the abnormal sample information including the abnormal category and the abnormal sample statistical information, so that the detection personnel can further perform the second abnormal category that they want to view. After selecting and displaying the abnormal sample information, on the basis of not needing to search for each piece of abnormal sample detection information from a large number of detection results, the workload is further reduced, and the readability of classification statistics is improved.
  • the embodiments of the present application mainly include three display modes, which are a "first-level abnormal sample information display” mode, a “second-level abnormal sample information display” mode, and a “three-level abnormal sample information display” mode.
  • FIG. 9 is a schematic flowchart of the “level one abnormal sample information display” mode in the application scenario of the present application. As shown in the figure, specifically:
  • Obtain position information of a blood sample where the position information of the blood sample includes a test tube rack number of a test tube rack corresponding to the test tube in which the blood sample is located; and position information of the test tube on the test tube rack;
  • sample identification information When the sample identification information is missing, identify whether the blood sample is caused by the failure of the sample barcode scanning. If yes, classify the abnormal sample as a barcode invalid.
  • sample identification information is missing and the WBC, RBC, HGB, or PLT in the component analysis result is missing or blocked, identify whether the blood sample has a test tube because the abnormal sample location is not identified, and if so, the abnormality
  • the samples are classified as vacant;
  • the first main abnormal sample display interface displays the four types of abnormalities of the analyzer, such as plugging of the analyzer, sample aspiration failure, invalid barcode, and vacancy, and the location information, blood sample detection time, and sample of each abnormal sample belonging to the four abnormal categories. Identification information.
  • FIG. 10 is a schematic flowchart of the “secondary abnormal sample information display” mode in the application scenario of the application, as shown in the figure, specifically:
  • position information of a blood sample where the position information of the blood sample includes a test tube rack number of a test tube rack corresponding to the test tube in which the blood sample is located; and position information of the test tube on the test tube rack;
  • sample identification information When the sample identification information is missing, identify whether the blood sample is caused by the failure of the sample barcode scanning. If yes, classify the abnormal sample as a barcode invalid.
  • sample identification information is missing and the WBC, RBC, HGB, or PLT in the component analysis result is missing or blocked, identify whether the blood sample has a test tube because the location of the abnormal sample is not identified, and if so, the abnormality
  • the samples are classified as vacant;
  • the second main abnormal sample display interface displays four types of abnormality of the analyzer, such as plugging of the analyzer, failure of aspiration, invalid barcode, and vacancy.
  • the first sub-abnormal sample display interface displays blood sample position information, blood sample detection time, and sample identification information of each abnormal sample belonging to the target abnormal category.
  • FIG. 11 is a schematic flowchart of the "three-level abnormal sample information display" mode in the application scenario of the present application. As shown in the figure, specifically:
  • position information of the blood sample includes a test tube rack number of a test tube rack corresponding to the test tube in which the blood sample is located; and position information of the test tube on the test tube rack;
  • sample identification information When the sample identification information is missing, identify whether the blood sample is caused by the failure of the sample barcode scanning. If yes, classify the abnormal sample as a barcode invalid.
  • sample identification information is missing and the WBC, RBC, HGB, or PLT in the component analysis result is missing or blocked, identify whether the blood sample has a test tube because the location of the abnormal sample is not identified, and if so, the abnormality
  • the samples are classified as vacant;
  • the second main abnormal sample display interface displays the four types of abnormality of the analyzer, such as plugging of the analyzer, failure of aspiration, invalid bar code, and vacancy, as well as quantitative statistical information belonging to each abnormal category.
  • each detection time period of the blood sample belonging to the target abnormality category is displayed on the second sub-anomalous sample display interface
  • the third sub-abnormal sample display interface In response to the second query instruction corresponding to the detection time period, the third sub-abnormal sample display interface displays the blood sample position information, the blood sample detection time, and the sample identification information belonging to the target detection time period.
  • FIG. 12 is another schematic flowchart of the “three-level abnormal sample information display” mode in the application scenario of the application, as shown in the figure, specifically:
  • position information of the blood sample includes a test tube rack number of a test tube rack corresponding to the test tube where the blood sample is located; and position information of the test tube on the test tube rack;
  • sample identification information When the sample identification information is missing, identify whether the blood sample is caused by a failed barcode scan of the sample, and if so, classify the abnormal sample as a barcode invalid.
  • sample identification information is missing and the WBC, RBC, HGB, or PLT in the component analysis result is missing or blocked, identify whether the blood sample has a test tube because the abnormal sample location is not identified, and if so, the abnormality
  • the samples are classified as vacant;
  • the second main abnormal sample display interface displays four types of abnormality of the analyzer, such as plugging of the analyzer, failure of suction, invalid bar codes, and vacancies, as well as quantitative statistical information belonging to each abnormal category;
  • the fourth sub-abnormal sample display interface displays blood sample position information, blood sample detection time, and sample identification information belonging to each test tube rack number.
  • the computer program product includes one or more computer instructions.
  • the computer may be a general-purpose computer, a special-purpose computer, a computer network, or other programmable devices.
  • the computer instructions may be stored in a computer-readable storage medium, or transmitted from one computer-readable storage medium to another computer-readable storage medium, for example, the computer instructions may be from a website site, computer, server, or data center Transmission by wire (such as coaxial cable, optical fiber, digital subscriber line (DSL)) or wireless (such as infrared, wireless, microwave, etc.) to another website site, computer, server, or data center.
  • wire such as coaxial cable, optical fiber, digital subscriber line (DSL)
  • wireless such as infrared, wireless, microwave, etc.
  • the computer-readable storage medium may be any available medium that can be stored by a computer or a data storage device such as a server, a data center, and the like that includes one or more available medium integration.
  • the available medium may be a magnetic medium (for example, a floppy disk, a hard disk, a magnetic tape), an optical medium (for example, a DVD), or a semiconductor medium (for example, a solid state disk (SSD)).
  • the disclosed systems, devices, and methods may be implemented in other ways.
  • the device embodiments described above are only schematic.
  • the division of the unit is only a logical function division.
  • multiple units or components may be combined or Can be integrated into another system, or some features can be ignored or not implemented.
  • the displayed or discussed mutual coupling or direct coupling or communication connection may be indirect coupling or communication connection through some interfaces, devices or units, which may be electrical, mechanical or other forms.
  • the units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, may be located in one place, or may be distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the objective of the solution of this embodiment.
  • each functional unit in each embodiment of the present application may be integrated into one processing unit, or each of the units may exist separately physically, or two or more units may be integrated into one unit.
  • the above integrated unit may be implemented in the form of hardware or in the form of software functional unit.
  • the integrated unit When the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it may be stored in a computer-readable storage medium.
  • the technical solution of the present application is essentially a part that contributes to the existing technology or all or part of the technical solution can be embodied in the form of a software product, which is stored in a storage medium. , Including a number of instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method described in the embodiments of the present application.
  • the aforementioned storage media include: U disks, mobile hard disks, read-only memories (ROMs), random access memories (RAMs), magnetic disks or compact discs and other media that can store program codes .

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Abstract

本申请实施例提供了一种样本检测信息管理方法,包括：对样本进行检测；如果样本检测结果包括异常样本检测信息，对所述异常样本检测信息进行分类统计，以得到至少一个分类统计结果，每个所述分类统计结果包括异常类别及属于该所述异常类别的异常样本统计信息；显示所述至少一个分类统计结果。本申请实施例还提供了一种样本检测设备。本申请实施例可以根据样本异常类别直接从样本检测结果中获取异常类别及属于该异常类别的异常样本统计信息，而不需要从大量的检测结果中寻找各条异常样本检测信息，减少了工作量，提高了体外检测的效率。

Description

一种样本检测信息管理方法以及样本检测设备 技术领域
本发明涉及体外诊断领域，尤其涉及一种样本检测信息管理方法以及样本检测设备。
背景技术
体外诊断仪器(in vitro diagnostic products，IVD)其作为医疗器械的一个独立分支，是指在人体之外，通过对人体样本进行检测而获取临床诊断信息，进而判断疾病或机体功能的仪器，其中，IVD检测的人体样本主要包括血液、体液或组织。
目前，IVD在对人体样本进行检测的过程主要包括：收集人体样本、人体样本检测以及检测结果的发布，为了将人体样本与使用该人体样本得到的检测结果进行对应，一般通过在人体样本的盛取容器外贴附与人体样本对应的唯一条形码，在IVD进行人体样本检测时，IVD首先对唯一条形码进行扫描和获取，并在样本检测完成后将该唯一条形码的条码号与检测结果进行对应。
然而，IVD进行人体样本检测时，人体样本本身会存在一些异常情况，例如样本量不够等，此时检测结果中会记录对应的异常记录，检测人员需要在大量的检测结果中寻找该异常记录以及对应的条码号，并根据条码号从唯一条形码中找到相应的人体样本进行状态的确认，由于现有条码号为8位甚至更多的全数字且检测结果的数量过大，对于检测人员而言，找到异常记录并根据条码号找到相应的人体样本工作量过大。
发明内容
本申请实施例提供了一种样本检测信息管理方法以及样本检测设备，检测人员可以根据样本异常类别直接从样本检测结果中获取异常类别及属于该所述异常类别的异常样本统计信息，而不需要从大量的检测结果中寻找各条异常样本检测信息，减少了工作量，提高了体外检测的效率。
本申请实施例的第一方面提供一种样本检测信息管理方法，包括：
对样本进行检测；
如果样本检测结果包括异常样本检测信息，对所述异常样本检测信息进行分类统计，以得到至少一个分类统计结果，每个所述分类统计结果包括异常类别及属于该所述异常类别的异常样本统计信息；
显示所述至少一个分类统计结果。
本申请实施例第二方面提供了一种样本检测设备，包括：
处理器和显示器；
所述处理器执行如下步骤：
对样本进行检测；
如果样本检测结果包括异常样本检测信息，对所述异常样本检测信息进行分类统计，以得到至少一个分类统计结果，每个所述分类统计结果包括异常类别及属于该所述异常类别的异常样本统计信息；
所述显示器显示所述至少一个分类统计结果。
本申请的第三方面提供了一种计算机可读存储介质，包括程序或指令，当所述程序或指令在计算机上运行时，上述各方面的方法被执行。
本申请实施例提供的技术方案中，在样本结果中确认异常样本检测信息，同时根据样本异常类别对异常样本检测信息进行分类统计，检测人员可以根据样本异常类别直接从样本检测结果中获取异常类别及属于该所述异常类别的异常样本统计信息，而不需要从大量的检测结果中寻找各条异常样本检测信息，减少了工作量，提高了体外检测的效率。
附图说明
图1为本申请实施例中样本检测设备的结构框图示意图；
图2为本申请实施例中样本检测信息管理方法一个实施例的示意图；
图3a为本申请实施例中一个样本检测结果的示意图；
图3b为本申请实施例中异常样本检测信息的示意图；
图4为本申请实施例中一个分类统计结果的显示界面示意图；
图5a为本申请实施例中一个分类统计结果的主显示界面示意图；
图5b为本申请实施例中一个分类统计结果的子显示界面示意图；
图6为本申请实施例中一个分类统计结果的子显示界面示意图；
图7a为本申请实施例中一个分类统计结果的第一子显示界面示意图；
图7b为本申请实施例中一个分类统计结果的第二子显示界面示意图；
图8a为本申请实施例中一个分类统计结果的第三子显示界面示意图；
图8b为本申请实施例中一个分类统计结果的第四子显示界面示意图；
图9为本申请应用场景中“一级异常样本信息显示”模式的一个流程示意图；
图10为本申请应用场景中“二级异常样本信息显示”模式的一个流程示意图；
图11为本申请应用场景中“三级异常样本信息显示”模式的一个流程示意图；
图12为本申请应用场景中“三级异常样本信息显示”模式的另一个流程示意图。
具体实施方式
下面将结合本申请实施例中的附图，对本申请实施例中的技术方案进行清楚、完整地描述，显然，所描述的实施例仅仅是本申请一部分实施例，而不是全部的实施例。
本申请的说明书和权利要求书及上述附图中的术语“第一”、“第二”、“第三”、“第四”等(如果存在)是用于区别类似的对象，而不必用于描述特定的顺序或先后次序。应该理解这样使用的数据在适当情况下可以互换，以便这里描述的实施例能够以除了在这里图示或描述的内容以外的顺序实施。此外，术语“包括”和“具有”以及他们的任何变形，意图在于覆盖不排他的包含，例如，包含了一系列步骤或单元的过程、方法、系统、产品或设备不必限于清楚地列出的那些步骤或单元，而是可包括没有清楚地列出的或对于这些过程、方法、产品或设备固有的其它步骤或单元。
图1为本发明实施例中的样本检测设备10的结构框图示意图。该样本检测设备10可以包括处理器101、扫描器102、传感器103、显示器104和存储器105。扫描器102可以扫描贴在盛装样本的样本容器(如试管)外壁的条码、 二维码或其他标识从而获得样本标识信息，并将样本标识信息发送到处理器101。传感器103识别试管架上各个放置样本容器的位置是否有样本容器，并将识别结果送到处理器101。样本检测设备10上的检测设备对样本进行成分分析后，将将成分分析结果送入处理器10。处理器101对该成分分析结果和标识信息进行异常分析和分类统计处理，以获得分类统计结果。处理器101获得的分类统计结果可以存储于存储器105中。分类统计结果可以在显示器104上显示。
本发明的实施例中，前述的样本检测设备10的显示器104可为触摸显示屏、液晶显示屏等，也可以是独立于样本检测设备10之外的液晶显示器、电视机等独立显示设备，也可为手机、平板电脑等电子设备上的显示屏，等等。
本发明的实施例中，前述的样本检测设备10的存储器105可为闪存卡、固态存储器、硬盘等。
本发明的实施例中还提供一种计算机可读存储介质，该计算机可读存储介质存储有多条程序指令，该多条程序指令被处理器101调用执行后，可执行前述各个实施例中的样本检测信息管理方法中的部分步骤或全部步骤或其中步骤的任意组合。
一些实施例中，该计算机可读存储介质可为存储器105，其可以是闪存卡、固态存储器、硬盘等非易失性存储介质。
本发明的实施例中，前述的样本检测设备10的处理器101可以通过软件、硬件、固件或者其组合实现，可以使用电路、单个或多个专用集成电路(application specific integrated circuits，ASIC)、单个或多个通用集成电路、单个或多个微处理器、单个或多个可编程逻辑器件、或者前述电路或器件的组合、或者其他适合的电路或器件，从而使得该处理器101可以执行各个实施例中的样本检测信息管理方法的相应步骤。
下面对本发明中的样本检测信息管理方法进行详细描述，请参阅图2，本发明实施例提供的一种样本检测信息管理方法，该方法应用于样本检测设备10，样本检测信息管理方法实施例包括：
201、对样本进行检测。
在本申请实施例中，需要对样本进行检测，可以理解的是，在对样本进行 检测之前，需要将样本放置在样本检测装置10检测口内的吸样位置上，使得样本检测装置10可以通过探针进行吸样，其中，样本的放置方式可以为自动送样或手动送样，以自动送样为例，样本检测装置10的检测口可以设置有传送带，检测人员将各样本依次放置在传送带上，传送带带动样本传送到样本检测装置10检测口内的吸样位置上，供样本检测装置10通过探针进行吸样以及后续的检测，样本检测装置10每完成一次检测过程，就可以控制传送带进行下一个样本的传送，以此实现自动送样，可以理解的是，样本需要盛装在样本容器中，样本容器可以为试管、离心管(eppendorf，EP管)或其他检测器皿，这里不做限定，进一步的，可以是将盛装有样本的样本容器放置在样本检测装置10检测口内的吸样位置上，具体的，检测人员将各样本依次放置在传送带上，传送带带动样本传送到样本检测装置10检测口内的吸样位置上，供样本检测装置10通过探针进行吸样以及后续的检测。
在样本检测装置10完成自动送样或手动送样，并对样本进行吸样，相当于完成了获取样本的准备工作，之后样本检测装置10就可以对样本进行检测，其中，样本可以包括但不限于人体血液、人体体液或人体组织，可以理解的是，检测的样本不同，对应的样本检测装置10也不同，相应的，样本检测装置10可以为血液分析仪、体液检测仪和组织检测仪。
在本申请实施例中，样本检测装置10对样本进行检测的过程可以包括如下步骤：步骤1、获取样本所在的样本容器的位置；步骤2、样本检测装置10扫描样本的样本标识得到样本标识信息；步骤3、对吸样得到的样本进行成分分析得到成分分析结果。其中，步骤1中，样本检测装置10可以通过扫描仪扫描样本架(例如试管架)从而获得样本架号，再通过传感器感测该试管架上的样本容器的位置，从而获得每个样本的位置信息，例如某一样本在1号试管架的2号位置，则通过该种方式就能获取该样本的位置信息为1-2；如果某个样本容器由于规格异常(例如尺寸较小)或放置不当，导致不能检测到该样本容器的存在，则会出现检测异常，该异常样本可归类为空位。其中，步骤2的样本标识信息携带有与样本对应的唯一身份标识，以血液分析仪为例，样本标识信息为唯一对应于该血液样本的来源人的唯一身份标识，样本标识信息可以但不限于在条形码或二维码上，携带有样本标识信息的条形码或二维码可以 粘贴在盛装样本的样本容器的外壁上，当条形码或二维码污损或翻起会导致样本检测装置10扫描不到样本标识。需要说明的是，上述步骤1、2和3仅为检测过程的示例，实际检测过程并不限于上述3种，且，步骤1、步骤2和步骤3之间没有必然的时序关系，即，步骤1可以在步骤2之前，步骤1也可以在步骤2之后，或者步骤1和步骤2同时进行，检测过程的具体步骤之间的时序关系可以按照实际需求进行选择，本实施例并不对此限定。
202、如果样本检测结果包括异常样本检测信息，对异常样本检测信息进行分类统计，以得到至少一个分类统计结果，每个分类统计结果包括异常类别及属于该异常类别的异常样本统计信息。
本申请实施例中，样本检测装置10对样本进行检测后，处理器101可以得到样本检测结果，可以理解的是，样本检测结果中可以包含异常样本检测信息和正常样本检测信息，其中异常样本检测信息包括由于检测过程的异常(例如分析仪堵孔、吸样失败、样本条码扫描失败或空位)而导致的异常样本检测信息。
本申请实施例中，处理器101在得到样本检测结果后，需要对样本检测结果进行异常性鉴别，来确定样本检测结果中哪些属于异常样本检测信息，通常情况下，样本检测结果中若出现检测信息的缺失，则需要检测人员重新返回寻找样本并重新测试或其它处理，即异常性鉴别首先需要判断检测结果是否完整，具体的，以上述包括步骤1至3的检测过程为例，异常性鉴别具体为样本检测结果是否既包含成分分析结果又包含样本标识信息，可选地，对样本检测结果进行异常性鉴别时，可以通过确定样本检测结果中的正常样本检测信息规则，进而，不满足正常样本检测信息规则的样本检测结果可确定为异常样本检测信息，确定样本检测结果的正常样本检测信息规则为：样本检测结果既包括样本标识信息又包括成分分析结果，则，包括样本标识信息但不包括成分分析结果(样本标识信息)、不包括样本标识信息但包括成分分析结果(成分分析结果)、既不包括样本标识信息又不包括成分分析结果(空缺)的三种检测结果为异常样本检测信息。为了便于理解，请参阅图3a和图3b，图3a为本申请实施例中一个样本检测结果的示意图，图3b为本申请实施例中异常样本检 测信息的示意图，如图3a所示，样本检测结果包括样本标识信息“A”、“B”、“C”、“E”、“G”和“H”，此外，还包括两个“？”，“？”表示该样本检测结果的样本标识信息缺失，如图3a所示的样本检测结果还包括成分分析结果，以血液分析仪对血液样本进行的检测为例，白血球(white blood cell,WBC)和红血球(Red Blood Cell，RBC)为具体的两个成分分析结果，正常的成分分析结果应为具体的数值，如“6.3”、“5.0”等，图3a中还包括“***”，此时“***”表示对应的“WBC”或“RBC”的成分分析结果缺失。请参阅图3b，图3b为相应于图3a所示样本检测结果的异常样本检测信息的示意图，图3b包括了图3a中全部的异常样本检测信息，例如第一行为由于成分分析结果缺失的异常样本检测信息，第二行为由于样本标识信息缺失的异常样本检测信息，第三行为由于成分分析结果和样本标识信息同时缺失的异常样本检测信息。
本申请实施例中，如果样本检测结果包括异常样本检测信息，则处理器101需要对异常样本检测信息进行分类统计，以得到至少一个分类统计结果，每个分类统计结果包括异常类别及属于该异常类别的异常样本统计信息。
本申请实施例中，处理器101需要对异常样本检测信息进行分类统计，其中，分类的依据具体为根据异常类别的不同进行分类。
处理器101在完成了对异常样本的分类统计后，进一步的，为了完善分类统计结果，可以进行属于各分类类别的异常样本检测信息的数量统计，得到数量统计信息，进一步的，为了完善分类统计结果，可以进一步进行获取异常样本位置信息，其中异常样本位置信息可以为该异常样本所在的试管对应的试管架的试管架号、以及试管在该试管架上的位置信息，可以理解的是，异常样本的位置信息可以等同于盛装该异常样本的样本容器的物理位置信息，通常情况下样本容器需要一个固定架对其进行固定，以样本容器为试管为例，固定试管的固定架具体可以为试管架，而试管架上安置有至少一个试管，因此，盛装该异常样本的样本容器的物理位置信息可以由试管架的标号(试管架号)以及试管在该试管架上的位置信息进行确定。可见，只需获取该异常样本所在的试管对应的试管架的试管架号；以及试管在该试管架上的位置信息，就 可以确定表示出该异常样本的位置信息，进一步的，为了完善分类统计结果，可以进一步获取到异常样本检测时间，需要说明的是，上述异常类别的数量统计信息、属于该异常类别的异常样本检测信息、位置信息和异常样本检测时间都可以包括在本申请实施例中的属于该异常类别的异常样本统计信息。
本申请实施例中，处理器101在完成了对异常样本的分类统计后，得到至少一个分类统计结果，其中，每个分类统计结果包括异常类别及属于该异常类别的异常样本统计信息，需要说明的是，本实施例中异常样本统计信息可以包括属于该异常类别的数量统计信息、属于该异常类别的异常样本检测信息、位置信息和异常样本检测时间中的至少一种。
203、显示至少一个分类统计结果。
本申请实施例中，在得到至少一个分类统计结果后，需要显示至少一个分类统计结果，需要说明的是，获得的至少一个分类统计结果可以存储于存储器103中。至少一个分类统计结果可以在显示器102上显示，每个分类统计结果包括异常类别及属于该异常类别的异常样本统计信息，本发明的实施例中，前述的样本检测装置10的显示器102可为触摸显示屏、液晶显示屏等，也可以是独立于样本检测装置10之外的液晶显示器、电视机等独立显示设备，也可以是其他信息管理系统的显示器，例如实验室信息管理系统(Laboratory Information System，LIS系统)，也可为手机、平板电脑等电子设备上的显示屏，等等，为了便于理解，请参阅图4，图4为本申请实施例中一个分类统计结果的显示界面示意图。
图4示出了四个分类统计结果，对应了四种异常类别“分析仪堵孔”、“吸样失败”、“条码无效”和“空位”，属于每个异常类别的异常样本统计信息又包含属于该异常类别的异常样本检测信息—“样本标识信息”、位置信息—“样本位置”和异常样本检测时间—“检测时间”。
本申请实施例提供的技术方案中，样本检测装置10能够在样本结果中确认异常样本检测信息，同时对异常样本检测信息进行分类统计。通过上述方式，可以根据样本异常类别直接从样本检测结果中获取异常类别及属于该异常类别的异常样本统计信息，而不需要从大量的检测结果中寻找各条异常样本检测信息，减少了工作量，提高了体外检测的效率。
可选地，在上述图2对应的实施例的基础上，本发明实施例提供的样本检测信息管理方法的第一个可选实施例中，对异常样本进行分类统计包括：识别该异常样本是否由于检测仪器的红血球/血小板阻抗通道发生宝石孔堵孔造成的，若是，则将该异常样本归类为堵孔；识别该异常样本是否由于样本有凝块，或者标本量不满足最低测试用量，或者吸样过程产生气泡造成的，若是，则将该异常样本归类为异常吸样；识别该异常样本是否由于样本条码扫描失败造成的，若是，则将该异常样本归类为未条码无效；或识别该异常样本是否由于未识别到该异常样本所在的位置有试管，若是，则将该异常样本归类为空位。
本申请实施例中，处理器101在根据异常类别的不同对异常样本检测信息进行分类统计前，需要对各异常样本检测信息进行异常类别确认，可选的，对异常样本检测信息进行异常类别确认可以包括如下方式：
以上述包括步骤1至3的检测过程为例，当“成分分析结果”缺失或被屏蔽时(如白血球(white blood cell,WBC)、红血球(Red Blood Cell，RBC)、血红蛋白(Hemoglobin，HGB)、血小板(platelet,PLT)等信息缺失或被屏蔽)，进一步的，样本检测装置10识别该异常样本是否由于检测仪器的RBC/PLT阻抗通道发生宝石孔堵孔造成的，若是，则将该异常样本归类为分析仪堵孔；
或者识别该异常样本是否由于样本有凝块，或者标本量不满足最低测试用量，或者吸样过程产生气泡造成的，若是，则将该异常样本归类为吸样失败；
当“样本标识信息”缺失时(如条形码或二维码对应的条码号或编号缺失)，进一步的，识别该异常样本是否由于样本条码扫描失败造成的，若是，则将该异常样本归类为条码无效；
当既不包括样本标识信息也不包括成分分析结果时，进一步的，识别该异常样本是否由于未识别到该异常样本所在的位置有试管，若是，则将该异常样本归类为空位。
当完成了对各异常样本检测信息进行异常类别确认并将该异常样本的归类后，即完成了异常样本的分类统计，进一步的，为了完善分类统计结果，可以进一步进行属于各分类类别的异常样本检测信息的数量统计，得到数量统计信息，进一步的，为了完善分类统计结果，可以进一步进行获取异常样本位置信息，其中异常样本位置信息可以为该异常样本所在的试管对应的试管架的试 管架号；以及试管在该试管架上的位置信息，可以理解的是，异常样本的位置信息可以等同于盛装该异常样本的样本容器的物理位置信息，通常情况下样本容器需要一个固定架对其进行固定，以样本容器为试管为例，固定试管的固定架具体可以为试管架，而试管架上安置有至少一个试管，因此，盛装该异常样本的样本容器的物理位置信息可以由试管架的标号(试管架号)以及试管在该试管架上的位置信息进行确定。可见，只需获取该异常样本所在的试管对应的试管架的试管架号；以及试管在该试管架上的位置信息，就可以确定表示出该异常样本的位置信息，进一步的，为了完善分类统计结果，可以进一步获取到目标异常样本检测时间和目标异常样本标识信息。
本申请实施例提供的技术方案中，对异常样本进行分类统计包括：识别该异常样本是否由于检测仪器的RBC/PLT阻抗通道发生宝石孔堵孔造成的，若是，则将该异常样本归类为堵孔；识别该异常样本是否由于样本有凝块，或者标本量不满足最低测试用量，或者吸样过程产生气泡造成的，若是，则将该异常样本归类为异常吸样；识别该异常样本是否由于样本条码扫描失败造成的，若是，则将该异常样本归类为未条码无效；或识别该异常样本是否由于未识别到该异常样本所在的位置有试管，若是，则将该异常样本归类为空位，通过上述方式，通过更精确的分类方式，可以将异常样本检测信息进行分类统计为四类分类统计结果，提高了分类统计的精确度。
可选地，在上述图2对应的实施例的基础上，本发明实施例提供的样本检测信息管理方法的第二个可选实施例中，方法还包括：
接收查询指令，查询指令用于查看目标异常类别的异常样本信息；
响应于查询指令，显示目标异常类别的所有异常样本信息，每个异常样本信息包括异常样本位置信息。
本申请的实施例中，说明了分类统计结果的具体显示机制。为了便于理解，请参阅图5a和图5b，图5a为本申请实施例中一个分类统计结果的主显示界面示意图，图5b为本申请实施例中一个分类统计结果的子显示界面示意图。
如图5a所示，主显示界面中包含了异常类别(分析仪堵孔、吸样失败、条码无效和空位)和属于该异常类别的数量统计信息(3、2、2、1)，可以理解的是，图5a中的异常类别种类和排布仅为一种示例，实际中还可针对其他 异常类型进行显示和排布，这里不做限定。
本申请实施例中，为了给检测人员提供一个可查看属于某一异常类别的具体异常样本信息，在该界面中还包含了“详细信息”模块：当点击该按键时，接收查询指令，查询指令用于查看目标异常类别的异常样本信息，可以理解的是，图5a中的“详细信息”模块还可以命名为“具体信息”或“查看更多”等，图5a中的“详细信息”模块仅为一种示例，实际中还进行其他的命名模块的显示，这里不做限定；
当点击该“详细信息”模块的按键时，响应于该查询指令，显示目标异常类别的所有异常样本信息，异常样本信息可以展示在以图5b为示例的子显示界面上，参照图5b，每个异常样本信息包括异常样本位置信息。
其次，本发明实施例中，说明了分类统计结果的具体显示机制，即接收查询指令，查询指令用于查看目标异常类别的异常样本信息；响应于查询指令，显示目标异常类别的所有异常样本信息，每个异常样本信息包括异常样本位置信息。通过上述方式，样本检测装置10在显示至少一个分类统计结果的基础上，将包括有异常类别和异常样本统计信息的分类统计结果和异常样本信息进行分级显示，使得检测人员可以对想要查看的异常类别进行选择，之后再显示异常样本信息，在不需要从大量的检测结果中寻找各条异常样本检测信息的基础上，进一步减少了工作量，提高了分类统计结果的可读性。
可选地，在上述图2对应的第二个实施例的基础上，本发明实施例提供的样本检测信息管理方法的第三个可选实施例中，方法还包括：获取异常样本位置信息，异常样本的位置信息包括该异常样本所在的试管对应的试管架的试管架号；以及试管在该试管架上的位置信息。图5b中示出了子显示界面中包含的异常样本位置信息，以下对获取异常样本位置信息的具体步骤进行详细说明。
本申请实施例中，在如何获取异常样本位置信息之前，首先说明为何要要获取异常样本位置信息，在样本检测设备检测的样本的结果中出现异常样本检测信息时，检测人员需要去查找异常样本的条码号，并根据条码号从全部样本中查找对应的样本，之后对该异常样本进行状态的确认，并重新检测，由于现有条码号为8位甚至更多的全数字，对于检测人员而言，根据条码号找到相应 的样本工作量过大，因此，可以在样本检测装置10对样本进行检测之前，或在样本检测装置10对样本进行检测之后，或与样本检测装置10对样本进行检测的同时检测异常样本位置信息，该异常样本位置信息标识了异常样本的具体物理位置，使得检测人员可以直接通过与异常样本对应的异常样本位置信息得到异常样本的物理位置。
本申请实施例中，在说明了为何要要获取异常样本位置信息之后，首先对异常样本位置信息的含义进行阐述，在本实施例中，异常样本位置信息可以为该异常样本所在的试管对应的试管架的试管架号；以及试管在该试管架上的位置信息，可以理解的是，异常样本的位置信息可以等同于盛装该异常样本的样本容器的物理位置信息，通常情况下样本容器需要一个固定架对其进行固定，以样本容器为试管为例，固定试管的固定架具体可以为试管架，而试管架上安置有至少一个试管，因此，盛装该异常样本的样本容器的物理位置信息可以由试管架的标号(试管架号)以及试管在该试管架上的位置信息进行确定。可见，只需获取该异常样本所在的试管对应的试管架的试管架号；以及试管在该试管架上的位置信息，就可以确定表示出该异常样本的位置信息，例如图5b中示出的1-2、2-9和9-6，以1-2为例，1具体为该异常样本所在的试管对应的试管架的试管架号，2具体为试管在该试管架上的位置信息，2可以理解为试管在该试管架上的2号孔位置，需要说明的是，试管架上的位置信息可以用1、2、3号来表示，也可以用A、B、C位来表示，这里不做限定，进一步的，检测人员在获取到异常样本的位置信息后，就可以直接根据异常样本位置信息中的试管架号找到异常样本所在的试管架，并根据异常样本位置信息中试管在该试管架上的位置信息找到对应的异常样本所在的试管，本申请实施例中，将异常样本位置信息细化为试管架号和试管在该试管架上的位置信息，将样本位置对应到盛装容器的物理位置，进一步使得检测人员在知道异常样本位置信息的情况下，更快的找到异常样本。
可以理解的是，如何获取异常样本位置包括从哪里获取异常样本位置以及从该位置用何种方式获取异常样本位置两个问题，接下来说明从哪里获取异常样本位置，本申请实施例中，携带有异常样本位置的标识可以按照如下方式贴附在试管架和试管上：
1、在试管外壁贴有对应的试管架的试管架号和试管在该试管架上的位置信息的标识；
2、在试管架上的一侧贴有试管架号的标识，在试管架各试管放置孔附近贴有试管架上位置信息的标识；
3、在试管架上的一侧贴有试管架号的标识，在试管外壁贴有试管在该试管架上的位置信息的标识。
以上三种方式仅为异常样本位置的获取位置的三个示例，实际中可以通过更多方式设置获取位置，这里不做限定，样本检测装置10可通过识别器或扫描器扫描携带有异常样本位置的标识来获取异常样本位置，具体来说，样本检测装置10可通过识别器或扫描器扫描携带有异常样本位置的标识来获取该样本所在的试管对应的试管架的试管架号，以及试管在该试管架上的位置信息。
进一步地，本发明实施例中，获取异常样本位置信息，异常样本的位置信息包括该异常样本所在的试管对应的试管架的试管架号；以及试管在该试管架上的位置信息。通过上述方式获取异常样本位置信息，将异常样本位置信息细化为试管架号和试管在该试管架上的位置信息，将样本位置对应到盛装容器的物理位置，进一步使得检测人员在知道异常样本位置信息的情况下，更快的找到异常样本。
可选地，在上述图2对应的第二个实施例的基础上，本发明实施例提供的样本检测信息管理方法的第四个可选实施例中，每个异常样本信息还包括样本标识信息、检测时间信息至少其中之一，为了便于理解，请参阅图6，图6为本申请实施例中一个分类统计结果的子显示界面示意图，可以理解的是图6可以为点击图5a中“详细信息”模块的按键后出现的显示界面，可以看出，图中包含有样本标识信息、检测时间信息和样本位置，需要说明的是，样本标识信息可以为上述的条形码和二维码对应的与样本来源唯一对应的身份标识信息。
进一步地，本发明实施例中，每个异常样本信息还包括样本标识信息、检测时间信息至少其中之一。通过上述异常样本信息的扩充，进一步使得检测人员在知道异常样本位置信息的情况下，进一步示出了样本标识信息，并可以通过判断检测时间更精确的确定需要找到的异常样本，为检测人员提供了更多的 信息指引。
可选地，在上述图2对应的第三个实施例的基础上，本发明实施例提供的样本检测信息管理方法的第五个可选实施例中，还包括：接收第二查询指令，查询指令用于查看异常样本信息中包含的第二目标异常类别的第二异常样本信息，第二目标异常类别包括检测时间段；响应于第二查询指令，显示第二目标异常类别的所有第二异常样本信息，每个第二异常样本信息包括异常样本位置信息。
本申请的实施例中，说明了分类统计结果的具体显示机制。为了便于理解，请参阅图7a和图7b，图7a为本申请实施例中一个分类统计结果的第一子显示界面示意图，图7b为本申请实施例中一个分类统计结果的第二子显示界面示意图，可以理解的是，图7a可以为点击图5a中“详细信息”模块的按键后出现的显示界面。
如图7a所示，第一子显示界面中包含了与目标异常类别(分析仪堵孔)和属于该异常类别的第二目标异常类别模块(检测时间)，可以理解的是，图7a中的目标异常类别仅为一种示例，实际中还可针对其他目标异常类型进行显示和排布，这里不做限定。图7a中的第二目标异常类别模块包含有与多个检测时间段对应的模块，可以理解的是，点击任一第二目标异常类别模块，相当于第二查询指令要查看与第二目标异常类别相应的检测时间段对应的第二异常样本信息，例如图7a中示出了第二查询指令要查看在“2018-04-0318:20-18:25”的时间段对应的第二异常样本信息，可选地，每个第二异常样本信息包括异常样本位置信息。
当点击该“2018-04-03 18:20-18:25”模块的按键时，响应于该第二查询指令，显示第二目标异常类别的所有第二异常样本信息，第二异常样本信息可以展示在以图7b为示例的子显示界面上，可选地，每个第二异常样本信息包括异常样本位置信息。
本发明实施例中，说明了分类统计结果的具体显示机制，即接收第二查询指令，查询指令用于查看异常样本信息中包含的第二目标异常类别的第二异常样本信息；响应于第二查询指令，显示第二目标异常类别的所有第二异常样本信息，每个第二异常样本信息包括异常样本位置信息。通过上述方式，样本检 测装置10将包括有异常类别和异常样本统计信息的分类统计结果和异常样本信息进行二级显示的基础上，使得检测人员可以对想要查看的第二异常类别进行进一步的选择，之后再显示异常样本信息，在不需要从大量的检测结果中寻找各条异常样本检测信息的基础上，进一步减少了工作量，提高了分类统计结果的可读性。
可选地，在上述图2对应的第三个实施例的基础上，本发明实施例提供的样本检测信息管理方法的第六个可选实施例中，还包括：接收第三查询指令，查询指令用于查看异常样本信息中包含的第三目标异常类别的第三异常样本信息，第三目标异常类别包括第二异常样本位置信息；响应于第三查询指令，显示第三目标异常类别的所有第三异常样本信息，每个第三异常样本信息包括第三异常样本位置信息。
本申请的实施例中，说明了分类统计结果的具体显示机制。为了便于理解，请参阅图8a和图8b，图8a为本申请实施例中一个分类统计结果的第三子显示界面示意图，图8b为本申请实施例中一个分类统计结果的第四子显示界面示意图，可以理解的是，图8a可以为点击图5a中“详细信息”模块的按键后出现的显示界面。
如图8a所示，第二子显示界面中包含了与目标异常类别(分析仪堵孔)和属于该异常类别的第三目标异常类别模块(第二异常样本位置信息)，可以理解的是，图8a中的目标异常类别仅为一种示例，实际中还可针对其他目标异常类型进行显示和排布，这里不做限定。图8a中的第三目标异常类别模块包含有与多个不同试管架号对应的模块，可以理解的是，点击任一第三目标异常类别模块，相当于第三查询指令要查看与第三目标异常类别相应的试管架号对应的的第三异常样本信息，例如图8a中示出了第三查询指令要查看在“2号试管架”对应的第三异常样本信息，可选地，每个第三异常样本信息包括第二异常样本位置信息，需要说明的是，在本申请实施例中，第二异常样本位置信息和第一异常样本位置信息为更具体的位置信息，例如图7a中第一异常样本位置信息为试管架号(例如2号试管架)，图7b中第二异常样本位置信息为该试管架上的具体位置(例如2-9，即2号试管架的9号位置)。
当点击该“2号试管架”模块的按键时，响应于该第三查询指令，显示第 三目标异常类别的所有第三异常样本信息，第三异常样本信息可以展示在以图8b为示例的子显示界面上，可选地，每个第三异常样本信息包括第三异常样本位置信息。
本发明实施例中，说明了分类统计结果的具体显示机制，即接收第三查询指令，查询指令用于查看异常样本信息中包含的第三目标异常类别的第三异常样本信息，第三目标异常类别包括第二异常样本位置信息；响应于第三查询指令，显示第三目标异常类别的所有第三异常样本信息，每个第三异常样本信息包括第三异常样本位置信息。通过上述方式，样本检测装置10将包括有异常类别和异常样本统计信息的分类统计结果和异常样本信息进行二级显示的基础上，使得检测人员可以对想要查看的第二异常类别进行进一步的选择，之后再显示异常样本信息，在不需要从大量的检测结果中寻找各条异常样本检测信息的基础上，进一步减少了工作量，提高了分类统计结果的可读性。
应理解，本申请实施例主要包括三种显示方式，分别为“一级异常样本信息显示”模式、“二级异常样本信息显示”模式以及“三级异常样本信息显示”模式，下面将结合附图进行说明。
以样本检测装置10具体为血液分析仪为例对样本检测信息管理方法的过程进行说明，请参阅图9，图9为本申请应用场景中“一级异常样本信息显示”模式的一个流程示意图，如图所示，具体地：
301、对至少一个人体血液样本进行自动进样并吸样；
302、扫描盛装有血液样本的试管上的标识信息，得到样本标识信息；
303、获取血液样本位置信息，血液样本的位置信息包括该血液样本所在的试管对应的试管架的试管架号；以及试管在该试管架上的位置信息；
304、对吸样得到的样本进行成分分析得到至少一个成分分析结果，成分分析结果包括WBC、RBC、HGB、PLT；
305、获取血液样本检测时间；
3061、当一个成分分析结果中的WBC、RBC、HGB或PLT缺失或被屏蔽，识别该血液样本是否由于检测仪器的RBC/PLT阻抗通道发生宝石孔堵孔造成的，若是，则将该异常样本归类为分析仪堵孔；
3062、当一个成分分析结果中的WBC、RBC、HGB或PLT缺失或被屏蔽，识 别该血液样本是否由于样本有凝块，或者标本量不满足最低测试用量，或者吸样过程产生气泡造成的，若是，则将该异常样本归类为吸样失败；
3063、当样本标识信息缺失，识别该血液样本是否由于样本条码扫描失败造成的，若是，则将该异常样本归类为条码无效；
3064、当样本标识信息缺失且成分分析结果中的WBC、RBC、HGB或PLT缺失或被屏蔽时，识别该血液样本是否由于未识别到该异常样本所在的位置有试管，若是，则将该异常样本归类为空位；
307、在第一主异常样本显示界面显示分析仪堵孔、吸样失败、条码无效和空位四种异常类别及属于四种异常类别的各异常样本的血液样本位置信息、血液样本检测时间和样本标识信息。
请参阅图10，图10为本申请应用场景中“二级异常样本信息显示”模式的一个流程示意图，如图所示，具体地：
401、对至少一个人体血液样本进行自动进样并吸样；
402、扫描盛装有血液样本的试管上的标识信息，得到样本标识信息；
403、获取血液样本位置信息，血液样本的位置信息包括该血液样本所在的试管对应的试管架的试管架号；以及试管在该试管架上的位置信息；
404、对吸样得到的样本进行成分分析得到至少一个成分分析结果，成分分析结果包括WBC、RBC、HGB、PLT；
405、获取血液样本检测时间；
4061、当一个成分分析结果中的WBC、RBC、HGB或PLT缺失或被屏蔽，识别该血液样本是否由于检测仪器的RBC/PLT阻抗通道发生宝石孔堵孔造成的，若是，则将该异常样本归类为分析仪堵孔；
4062、当一个成分分析结果中的WBC、RBC、HGB或PLT缺失或被屏蔽，识别该血液样本是否由于样本有凝块，或者标本量不满足最低测试用量，或者吸样过程产生气泡造成的，若是，则将该异常样本归类为吸样失败；
4063、当样本标识信息缺失，识别该血液样本是否由于样本条码扫描失败造成的，若是，则将该异常样本归类为条码无效；
4064、当样本标识信息缺失且成分分析结果中的WBC、RBC、HGB或PLT缺失或被屏蔽时，识别该血液样本是否由于未识别到该异常样本所在的位置 有试管，若是，则将该异常样本归类为空位；
407、进行属于各分类类别的异常样本检测信息的数量统计，得到数量统计信息；
408、在第二主异常样本显示界面显示分析仪堵孔、吸样失败、条码无效和空位四种异常类别及属于各异常类别的数量统计信息；
409、响应对应于目标异常类别的查询指令，在第一子异常样本显示界面显示属于目标异常类别的各异常样本的血液样本位置信息、血液样本检测时间和样本标识信息。
请参阅图11，图11为本申请应用场景中“三级异常样本信息显示”模式的一个流程示意图，如图所示，具体地：
501、对至少一个人体血液样本进行自动进样并吸样；
502、扫描盛装有血液样本的试管上的标识信息，得到样本标识信息；
503、获取血液样本位置信息，血液样本的位置信息包括该血液样本所在的试管对应的试管架的试管架号；以及试管在该试管架上的位置信息；
504、对吸样得到的样本进行成分分析得到至少一个成分分析结果，成分分析结果包括WBC、RBC、HGB、PLT；
505、获取血液样本检测时间；
5061、当一个成分分析结果中的WBC、RBC、HGB或PLT缺失或被屏蔽，识别该血液样本是否由于检测仪器的RBC/PLT阻抗通道发生宝石孔堵孔造成的，若是，则将该异常样本归类为分析仪堵孔；
5062、当一个成分分析结果中的WBC、RBC、HGB或PLT缺失或被屏蔽，识别该血液样本是否由于样本有凝块，或者标本量不满足最低测试用量，或者吸样过程产生气泡造成的，若是，则将该异常样本归类为吸样失败；
5063、当样本标识信息缺失，识别该血液样本是否由于样本条码扫描失败造成的，若是，则将该异常样本归类为条码无效；
5064、当样本标识信息缺失且成分分析结果中的WBC、RBC、HGB或PLT缺失或被屏蔽时，识别该血液样本是否由于未识别到该异常样本所在的位置有试管，若是，则将该异常样本归类为空位；
507、进行属于各分类类别的异常样本检测信息的数量统计，得到数量统 计信息；
508、在第二主异常样本显示界面显示分析仪堵孔、吸样失败、条码无效和空位四种异常类别及属于各异常类别的数量统计信息；
509、响应对应于目标异常类别的查询指令，在第二子异常样本显示界面显示属于目标异常类别的血液样本各检测时间段；
510、响应对应于检测时间段的第二查询指令，在第三子异常样本显示界面显示属于目标检测时间段的血液样本位置信息、血液样本检测时间和样本标识信息。
请参阅图12，图12为本申请应用场景中“三级异常样本信息显示”模式的另一个流程示意图，如图所示，具体地：
601、对至少一个人体血液样本进行自动进样并吸样；
602、扫描盛装有血液样本的试管上的标识信息，得到样本标识信息；
603、获取血液样本位置信息，血液样本的位置信息包括该血液样本所在的试管对应的试管架的试管架号；以及试管在该试管架上的位置信息；
604、对吸样得到的样本进行成分分析得到至少一个成分分析结果，成分分析结果包括WBC、RBC、HGB、PLT；
605、获取血液样本检测时间；
6061、当一个成分分析结果中的WBC、RBC、HGB或PLT缺失或被屏蔽，识别该血液样本是否由于检测仪器的RBC/PLT阻抗通道发生宝石孔堵孔造成的，若是，则将该异常样本归类为分析仪堵孔；
6062、当一个成分分析结果中的WBC、RBC、HGB或PLT缺失或被屏蔽，识别该血液样本是否由于样本有凝块，或者标本量不满足最低测试用量，或者吸样过程产生气泡造成的，若是，则将该异常样本归类为吸样失败；
6063、当样本标识信息缺失，识别该血液样本是否由于样本条码扫描失败造成的，若是，则将该异常样本归类为条码无效；
6064、当样本标识信息缺失且成分分析结果中的WBC、RBC、HGB或PLT缺失或被屏蔽时，识别该血液样本是否由于未识别到该异常样本所在的位置有试管，若是，则将该异常样本归类为空位；
607、进行属于各分类类别的异常样本检测信息的数量统计，得到数量统 计信息；
608、在第二主异常样本显示界面显示分析仪堵孔、吸样失败、条码无效和空位四种异常类别及属于各异常类别的数量统计信息；
609、响应对应于目标异常类别的查询指令，在第三子异常样本显示界面显示属于目标异常类别的各试管架号；
610、响应对应于各试管架号的第三查询指令，在第四子异常样本显示界面显示属于各试管架号的血液样本位置信息、血液样本检测时间和样本标识信息。
在上述实施例中，可以全部或部分地通过软件、硬件、固件或者其任意组合来实现。当使用软件实现时，可以全部或部分地以计算机程序产品的形式实现。
所述计算机程序产品包括一个或多个计算机指令。在计算机上加载和执行所述计算机程序指令时，全部或部分地产生按照本发明实施例所述的流程或功能。所述计算机可以是通用计算机、专用计算机、计算机网络、或者其他可编程装置。所述计算机指令可以存储在计算机可读存储介质中，或者从一个计算机可读存储介质向另一计算机可读存储介质传输，例如，所述计算机指令可以从一个网站站点、计算机、服务器或数据中心通过有线(例如同轴电缆、光纤、数字用户线(digital subscriber line，DSL))或无线(例如红外、无线、微波等)方式向另一个网站站点、计算机、服务器或数据中心进行传输。所述计算机可读存储介质可以是计算机能够存储的任何可用介质或者是包含一个或多个可用介质集成的服务器、数据中心等数据存储设备。所述可用介质可以是磁性介质，(例如，软盘、硬盘、磁带)、光介质(例如，DVD)、或者半导体介质(例如固态硬盘solid state disk(SSD))等。
所属领域的技术人员可以清楚地了解到，为描述的方便和简洁，上述描述的系统，装置和单元的具体工作过程，可以参考前述方法实施例中的对应过程，在此不再赘述。
在本申请所提供的几个实施例中，应该理解到，所揭露的系统，装置和方法，可以通过其它的方式实现。例如，以上所描述的装置实施例仅仅是示意性的，例如，所述单元的划分，仅仅为一种逻辑功能划分，实际实现时可以有另 外的划分方式，例如多个单元或组件可以结合或者可以集成到另一个系统，或一些特征可以忽略，或不执行。另一点，所显示或讨论的相互之间的耦合或直接耦合或通信连接可以是通过一些接口，装置或单元的间接耦合或通信连接，可以是电性，机械或其它的形式。
所述作为分离部件说明的单元可以是或者也可以不是物理上分开的，作为单元显示的部件可以是或者也可以不是物理单元，即可以位于一个地方，或者也可以分布到多个网络单元上。可以根据实际的需要选择其中的部分或者全部单元来实现本实施例方案的目的。
另外，在本申请各个实施例中的各功能单元可以集成在一个处理单元中，也可以是各个单元单独物理存在，也可以两个或两个以上单元集成在一个单元中。上述集成的单元既可以采用硬件的形式实现，也可以采用软件功能单元的形式实现。
所述集成的单元如果以软件功能单元的形式实现并作为独立的产品销售或使用时，可以存储在一个计算机可读取存储介质中。基于这样的理解，本申请的技术方案本质上或者说对现有技术做出贡献的部分或者该技术方案的全部或部分可以以软件产品的形式体现出来，该计算机软件产品存储在一个存储介质中，包括若干指令用以使得一台计算机设备(可以是个人计算机，服务器，或者网络设备等)执行本申请各个实施例所述方法的全部或部分步骤。而前述的存储介质包括：U盘、移动硬盘、只读存储器(read-only memory，ROM)、随机存取存储器(random access memory，RAM)、磁碟或者光盘等各种可以存储程序代码的介质。
以上所述，以上实施例仅用以说明本申请的技术方案，而非对其限制；尽管参照前述实施例对本申请进行了详细的说明，本领域的普通技术人员应当理解：其依然可以对前述各实施例所记载的技术方案进行修改，或者对其中部分技术特征进行等同替换；而这些修改或者替换，并不使相应技术方案的本质脱离本申请各实施例技术方案的精神和范围。

Claims (15)

  1. 一种样本检测信息管理方法，其特征在于，所述方法包括：
    对样本进行检测；
    如果样本检测结果包括异常样本检测信息，对所述异常样本检测信息进行分类统计，以得到至少一个分类统计结果，每个所述分类统计结果包括异常类别及属于该所述异常类别的异常样本统计信息；
    显示所述至少一个分类统计结果。
  2. 根据权利要求1所述的样本检测信息管理方法，其特征在于，所述方法还包括：
    接收查询指令，所述查询指令用于查看目标异常类别的异常样本信息；
    响应于所述查询指令，显示目标异常类别的所有异常样本信息，每个所述异常样本信息包括异常样本位置信息。
  3. 根据权利要求2所述的样本检测信息管理方法，其特征在于，每个异常样本信息还包括样本标识信息、检测时间信息至少其中之一。
  4. 根据权利要求1至3任一所述的样本检测信息管理方法，其特征在于，
    每种异常类别的异常样本统计信息包括属于该异常类别的异常样本数量。
  5. 根据权利要求1至3任一所述的样本检测信息管理方法，其特征在于，所述样本异常类别包括如下至少一种：
    分析仪堵孔、吸样失败、条码无效和空位。
  6. 根据权利要求1至5所述的方法，其特征在于，所述对异常样本进行分类统计包括：
    识别该异常样本是否由于检测仪器的红血球/血小板阻抗通道发生宝石孔堵孔造成的，若是，则将该异常样本归类为分析仪堵孔；或
    识别该异常样本是否由于样本有凝块，或者标本量不满足最低测试用量，或者吸样过程产生气泡造成的，若是，则将该异常样本归类为吸样失败；或
    识别该异常样本是否由于样本条码扫描失败造成的，若是，则将该异常样本归类为条码无效；或
    识别该异常样本是否由于未识别到该异常样本所在的位置有试管，若是，则将该异常样本归类为空位。
  7. 根据权利要求2至6中任一所述的样本检测信息管理方法，其特征在于，所述方法还包括：
    获取异常样本位置信息，所述异常样本的位置信息包括该异常样本所在的试管对应的试管架的试管架号；
    以及试管在该试管架上的位置信息。
  8. 一种样本检测设备，其特征在于，包括：处理器和显示器；
    所述处理器执行如下步骤：
    对样本进行检测；
    如果样本检测结果包括异常样本检测信息，对所述异常样本检测信息进行分类统计，以得到至少一个分类统计结果，每个所述分类统计结果包括异常类别及属于该所述异常类别的异常样本统计信息；
    所述显示器显示所述至少一个分类统计结果。
  9. 根据权利要求8所述的样本检测设备，其特征在于，所述处理器还用于执行如下步骤：
    接收查询指令，所述查询指令用于查看目标异常类别的异常样本信息；
    响应于所述查询指令，显示目标异常类别的所有异常样本信息，每个所述异常样本信息包括异常样本位置信息。
  10. 根据权利要求9所述的样本检测设备，其特征在于，每个异常样本信息还包括样本标识信息、检测时间信息至少其中之一。
  11. 根据权利要求8至10任一所述的样本检测设备，其特征在于，每种异常类别的异常样本统计信息包括属于该异常类别的异常样本数量。
  12. 根据权利要求8至10任一所述的样本检测设备，其特征在于，所述样本异常类别包括如下至少一种：
    分析仪堵孔、吸样失败、条码无效和空位。
  13. 根据权利要求8至12任一所述的样本检测设备，其特征在于，所述处理器还用于执行如下步骤：
    识别该异常样本是否由于检测仪器的红血球/血小板阻抗通道发生宝石孔堵孔造成的，若是，则将该异常样本归类为分析仪堵孔；或
    识别该异常样本是否由于样本有凝块，或者标本量不满足最低测试用量， 或者吸样过程产生气泡造成的，若是，则将该异常样本归类为吸样失败；或
    识别该异常样本是否由于样本条码扫描失败造成的，若是，则将该异常样本归类为条码无效；或
    识别该异常样本是否由于未识别到该异常样本所在的位置有试管，若是，则将该异常样本归类为空位。
  14. 根据权利要求9至12中任一所述的样本检测设备，其特征在于，所述处理器还用于执行如下步骤：
    获取异常样本位置信息，所述异常样本的位置信息包括该异常样本所在的试管对应的试管架的试管架号；
    以及试管在该试管架上的位置信息。
  15. 一种可读存储介质，包括程序或指令，当所述程序或指令在计算机上运行时，如权利要求1-7中任意一项所述的方法被执行。
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