CN112334930A

CN112334930A - Sample detection information management method and sample detection equipment

Info

Publication number: CN112334930A
Application number: CN201880094613.2A
Authority: CN
Inventors: 刘建超; 王生; 詹应键
Original assignee: Shenzhen Mindray Bio Medical Electronics Co Ltd; Shenzhen Mindray Scientific Co Ltd
Current assignee: Shenzhen Mindray Bio Medical Electronics Co Ltd; Shenzhen Mindray Scientific Co Ltd
Priority date: 2018-08-06
Filing date: 2018-08-06
Publication date: 2021-02-05
Also published as: WO2020029009A1

Abstract

The embodiment of the application provides a sample detection information management method, which comprises the following steps: detecting the sample; if the sample detection result comprises abnormal sample detection information, performing classified statistics on the abnormal sample detection information to obtain at least one classified statistical result, wherein each classified statistical result comprises an abnormal category and abnormal sample statistical information belonging to the abnormal category; displaying the at least one classification statistic. The embodiment of the application also provides sample detection equipment. According to the embodiment of the application, the abnormal type and the abnormal sample statistical information belonging to the abnormal type can be directly obtained from the sample detection result according to the abnormal type of the sample, and the detection information of each abnormal sample does not need to be searched from a large number of detection results, so that the workload is reduced, and the efficiency of in-vitro detection is improved.

Description

Sample detection information management method and sample detection equipment

Technical Field

The invention relates to the field of in-vitro diagnosis, in particular to a sample detection information management method and sample detection equipment.

Background

An in vitro diagnostic device (IVD) is an independent branch of medical devices, which is an instrument for obtaining clinical diagnostic information by detecting human body samples outside human bodies to determine diseases or body functions, wherein the human body samples detected by the IVD mainly include blood, body fluid or tissues.

Currently, the process of IVD in detecting human body samples mainly includes: in order to collect a human body sample, detect the human body sample and release a detection result, generally, a unique bar code corresponding to the human body sample is attached to the outside of a containing container of the human body sample, when the human body sample is detected by the IVD, the IVD firstly scans and acquires the unique bar code, and after the sample is detected, the bar code number of the unique bar code is corresponding to the detection result.

However, when the IVD detects a human body sample, the human body sample itself may have some abnormal situations, for example, the sample amount is insufficient, and at this time, a corresponding abnormal record may be recorded in the detection result, and the detecting person needs to search for the abnormal record and the corresponding barcode number in a large number of detection results, and find the corresponding human body sample from the unique barcode according to the barcode number to confirm the state.

Invention of the inventionContent providing method and apparatus

The embodiment of the application provides a sample detection information management method and sample detection equipment, so that detection personnel can directly obtain abnormal types and abnormal sample statistical information belonging to the abnormal types from sample detection results according to the abnormal types of the samples, the detection personnel do not need to search for all pieces of abnormal sample detection information from a large number of detection results, the workload is reduced, and the efficiency of in-vitro detection is improved.

A first aspect of an embodiment of the present application provides a sample detection information management method, including:

detecting the sample;

if the sample detection result comprises abnormal sample detection information, performing classified statistics on the abnormal sample detection information to obtain at least one classified statistical result, wherein each classified statistical result comprises an abnormal category and abnormal sample statistical information belonging to the abnormal category;

displaying the at least one classification statistic.

A second aspect of the embodiments of the present application provides a sample detection apparatus, including:

a processor and a display;

the processor performs the steps of:

detecting the sample;

the display displays the at least one classification statistic.

A third aspect of the application provides a computer-readable storage medium comprising a program or instructions which, when run on a computer, performs the method of the above-described aspects.

According to the technical scheme, the abnormal sample detection information is confirmed in the sample result, the abnormal sample detection information is classified and counted according to the abnormal sample types, detection personnel can directly obtain the abnormal types and the abnormal sample statistical information belonging to the abnormal types from the sample detection result according to the abnormal sample types, and the abnormal sample detection information does not need to be searched from a large number of detection results, so that the workload is reduced, and the efficiency of in-vitro detection is improved.

Drawings

FIG. 1 is a block diagram of a sample testing device according to an embodiment of the present disclosure;

FIG. 2 is a diagram illustrating an embodiment of a sample detection information management method according to an embodiment of the present disclosure;

FIG. 3a is a schematic diagram of a sample detection result in an embodiment of the present application;

FIG. 3b is a diagram illustrating abnormal sample detection information according to an embodiment of the present application;

FIG. 4 is a schematic diagram of a display interface of a classification statistical result according to an embodiment of the present application;

FIG. 5a is a schematic diagram of a main display interface of a classification statistical result according to an embodiment of the present application;

FIG. 5b is a schematic diagram of a sub-display interface of a classification statistical result according to an embodiment of the present application;

FIG. 6 is a schematic diagram of a sub-display interface of a classification statistical result according to an embodiment of the present application;

FIG. 7a is a schematic diagram of a first sub-display interface of a classification statistical result according to an embodiment of the present application;

FIG. 7b is a diagram of a second sub-display interface of a classification statistic result according to an embodiment of the present application;

FIG. 8a is a diagram of a third sub-display interface of a statistical classification result according to an embodiment of the present application;

FIG. 8b is a diagram of a fourth sub-display interface of a statistical classification result according to an embodiment of the present application;

FIG. 9 is a schematic flow chart of a "primary abnormal sample information display" mode in an application scenario of the present application;

FIG. 10 is a schematic flow chart of a "secondary abnormal sample information display" mode in an application scenario of the present application;

FIG. 11 is a schematic flow chart of a "three-level abnormal sample information display" mode in an application scenario of the present application;

fig. 12 is another schematic flow chart of the "three-level abnormal sample information display" mode in the application scenario of the present application.

Detailed Description

The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are only a part of the embodiments of the present application, and not all of the embodiments.

The terms "first," "second," "third," "fourth," and the like in the description and in the claims of the present application and in the drawings described above, if any, are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order. It will be appreciated that the data so used may be interchanged under appropriate circumstances such that the embodiments described herein may be practiced otherwise than as specifically illustrated or described herein. Furthermore, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed, but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.

Fig. 1 is a block diagram illustrating a structure of a sample testing device 10 according to 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 barcode, two-dimensional code, or other identifier affixed to the outer wall of a sample container (e.g., a test tube) containing the sample to obtain sample identification information, and send the sample identification information to the processor 101. The sensor 103 recognizes whether or not there is a sample container at each position where a sample container is placed on the test tube rack, and sends the recognition result to the processor 101. After the sample is subjected to a component analysis by the detection device on the sample detection device 10, the component analysis result is sent to the processor 10. The processor 101 performs anomaly analysis and classification statistical processing on the component analysis result and the identification information to obtain a classification statistical result. The classification statistics obtained by the processor 101 may be stored in the memory 105. The classification statistics may be displayed on the display 104.

In an embodiment of the present invention, the display 104 of the sample testing device 10 may be a touch screen, a liquid crystal display, or the like, or may be an independent display device such as a liquid crystal display, a television, or the like, which is independent of the sample testing device 10, or may be a display screen on an electronic device such as a mobile phone, a tablet computer, or the like.

In an embodiment of the present invention, the memory 105 of the sample detection device 10 can be a flash memory card, a solid state memory, a hard disk, or the like.

The embodiment of the present invention further provides a computer-readable storage medium, where multiple program instructions are stored, and after the multiple program instructions are called and executed by the processor 101, some or all of the steps of the sample detection information management method in the foregoing embodiments, or any combination of the steps may be performed.

In some embodiments, the computer readable storage medium may be memory 105, which may be a non-volatile storage medium such as a flash memory card, solid state memory, hard disk, or the like.

In the embodiments of the present invention, the processor 101 of the sample detection apparatus 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 (ASICs), a single or multiple general purpose integrated circuits, a single or multiple microprocessors, a 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 may execute the corresponding steps of the sample detection information management methods in the various embodiments.

Referring to fig. 2, the sample detection information management method according to an embodiment of the present invention is described in detail below, and the method is applied to a sample detection device 10, and the sample detection information management method includes:

201. and detecting the sample.

In the embodiment of the present application, a sample needs to be detected, it can be understood that, before the sample is detected, the sample needs to be placed on a sample suction position in a detection port of the sample detection device 10, so that the sample detection device 10 can suck the sample through a probe, where the sample can be placed in an automatic sample feeding manner or a manual sample feeding manner, taking the automatic sample feeding manner as an example, a detection port of the sample detection device 10 can be provided with a conveyor belt, a detection person sequentially places each sample on the conveyor belt, the conveyor belt drives the sample to be conveyed to the sample suction position in the detection port of the sample detection device 10, so that the sample detection device 10 can suck the sample through the probe and perform subsequent detection, and the conveyor belt can be controlled to convey the next sample every time the sample detection device 10 completes a detection process, so as to realize automatic sample feeding, it can be understood that, the sample needs the splendid attire in sample container, sample container can be the test tube, centrifuging tube (eppendorf, EP pipe) or other detection wares, do not do the injecing here, it is further, can place the sample container that contains the sample on the intraoral appearance position of inhaling of sample detection device 10 detection, and is concrete, the measurement personnel place each sample on the conveyer belt in proper order, the conveyer belt drives the sample and conveys on the intraoral appearance position of inhaling of sample detection device 10 detection, supply sample detection device 10 to inhale appearance and subsequent detection through the probe.

After the sample testing device 10 completes automatic sample feeding or manual sample feeding and sample suction, which is equivalent to completing preparation for obtaining a sample, the sample testing device 10 can test the sample, wherein the sample may include but is not limited to human blood, human body fluid or human tissue, it is understood that different samples are tested and corresponding sample testing devices 10 are different, and accordingly, the sample testing device 10 may be a blood analyzer, a body fluid testing instrument or a tissue testing instrument.

In the embodiment of the present application, the process of detecting the sample by the sample detection apparatus 10 may include the following steps: step 1, obtaining the position of a sample container where a sample is located; step 2, the sample detection device 10 scans the sample identification of the sample to obtain sample identification information; and 3, carrying out component analysis on the sample obtained by sample adsorption to obtain a component analysis result. In step 1, the sample detection apparatus 10 may scan a sample rack (e.g., a test tube rack) through a scanner to obtain a sample rack number, and then sense a position of a sample container on the test tube rack through a sensor to obtain position information of each sample, for example, a position 2 of a certain sample on the test tube rack 1 is obtained, and the position information of the sample is 1-2 through this way; if a sample container fails to detect the presence of the sample container due to an abnormal size (e.g., a small size) or improper placement, a detection anomaly occurs and the abnormal sample can be classified as empty. The sample identification information in step 2 carries a unique identification corresponding to the sample, taking a blood analyzer as an example, the sample identification information is a unique identification uniquely corresponding to a source of the blood sample, the sample identification information may be but is not limited to a barcode or a two-dimensional code, the barcode or the two-dimensional code carrying the sample identification information may be pasted on an outer wall of a sample container holding the sample, and when the barcode or the two-dimensional code is stained or turned up, the sample detection device 10 may not scan the sample identification. It should be noted that, the

above steps

1, 2, and 3 are only examples of the detection process, the actual detection process is not limited to the above 3 kinds, and there is no necessary timing relationship among the

steps

1, 2, and 3, that is, the step 1 may be before the step 2, the step 1 may also be after the step 2, or the step 1 and the step 2 are performed simultaneously, the timing relationship among the specific steps of the detection process may be selected according to actual requirements, and this embodiment is not limited thereto.

202. And if the sample detection result comprises abnormal sample detection information, performing classified statistics on the abnormal sample detection information to obtain at least one classified statistical result, wherein each classified statistical result comprises an abnormal category and abnormal sample statistical information belonging to the abnormal category.

In the embodiment of the present application, after the sample is detected by the sample detection device 10, the processor 101 may obtain a sample detection result, and it is understood that the sample detection result may include abnormal sample detection information and normal sample detection information, where the abnormal sample detection information includes abnormal sample detection information caused by an abnormality in the detection process (for example, a hole is blocked by an analyzer, a sample sucking failure, a sample barcode scanning failure, or a blank position).

In this embodiment, after obtaining the sample detection result, the processor 101 needs to perform abnormality identification on the sample detection result to determine which of the sample detection results belongs to the abnormal sample detection information, and in a normal case, if the sample detection result has a missing of the detection information, the inspector needs to return to search the sample again and perform retesting or other processing, that is, the abnormality identification needs to determine whether the detection result is complete, specifically, taking the detection process including steps 1 to 3 as an example, the abnormality identification specifically is whether the sample detection result includes both the component analysis result and the sample identification information, optionally, when performing the abnormality identification on the sample detection result, the processor can determine the normal sample detection information rule in the sample detection result, and further, the sample detection result that does not satisfy the normal sample detection information rule can be determined as the abnormal sample detection information, the normal sample detection information rule for determining the sample detection result is as follows: the sample detection result includes both the sample identification information and the component analysis result, and then, three kinds of detection results including the sample identification information but not including the component analysis result (sample identification information), not including the sample identification information but including the component analysis result (component analysis result), and not including both the sample identification information and the component analysis result (vacancy) are abnormal sample detection information. For convenience of understanding, please refer to fig. 3a and fig. 3B, where fig. 3a is a schematic diagram of a sample detection result in the embodiment of the present application, and fig. 3B is a schematic diagram of abnormal sample detection information in the embodiment of the present application, and as shown in fig. 3a, the sample detection result includes sample identification information "a", "B", "C", "E", "G", and "H", and in addition, includes two? ","? "sample identification information indicating the sample detection result is missing, the sample detection result shown in fig. 3a further includes a component analysis result, taking the detection of the Blood sample by the Blood analyzer as an example, White Blood Cells (WBCs) and Red Blood Cells (RBCs) are specific two component analysis results, and a normal component analysis result should be a specific numerical value, such as" 6.3 "," 5.0 ", and the like, and further includes" × ", in fig. 3a, at this time" × "indicates that the component analysis result of the corresponding" WBC "or" RBC "is missing. Referring to fig. 3b, fig. 3b is a schematic diagram of abnormal sample detection information corresponding to the sample detection result shown in fig. 3a, where fig. 3b includes all the abnormal sample detection information in fig. 3a, such as the abnormal sample detection information with the first behavior due to the missing component analysis result, the abnormal sample detection information with the second behavior due to the missing sample identification information, and the abnormal sample detection information with the third behavior due to the missing component analysis result and the missing sample identification information.

In this embodiment of the application, if the sample detection result includes abnormal sample detection information, the processor 101 needs to perform classification statistics on the abnormal sample detection information to obtain at least one classification statistical result, where each classification statistical result includes an abnormal category and abnormal sample statistical information belonging to the abnormal category.

In the embodiment of the present application, the processor 101 needs to perform classification statistics on the abnormal sample detection information, where the classification is specifically based on the different abnormal classes.

After completing the classification statistics of the abnormal samples, the processor 101 may further perform, in order to complete the classification statistics result, the quantity statistics of the abnormal sample detection information belonging to each classification category to obtain quantity statistics information, and further may further perform, in order to complete the classification statistics result, the abnormal sample position information, which may be 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, may be understood as that the position information of the abnormal sample may be equal to the physical position information of the sample container containing the abnormal sample, and the sample container needs a fixing rack to be fixed under normal conditions, taking the sample container as the test tube as an example, the fixing rack for fixing the test tube rack may specifically be the test tube, and the test tube rack is provided with at least one test tube, therefore, the physical position information of the specimen 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. Therefore, only the test tube rack number of the test tube rack corresponding to the test tube in which the abnormal sample is located needs to be obtained; and the position information of the test tube on the test tube rack, the position information indicating the abnormal sample can be determined, and further, in order to perfect the classification statistical result, the abnormal sample detection time can be further obtained, it should be noted that the statistical information of the number of the abnormal categories, the abnormal sample detection information belonging to the abnormal category, the position information, and the abnormal sample detection time can all include the statistical information of the abnormal sample belonging to the abnormal category in the embodiment of the present application.

In this embodiment, after completing the classification statistics on the abnormal samples, the processor 101 obtains at least one classification statistical result, where each classification statistical result includes an abnormal category and abnormal sample statistical information belonging to the abnormal category, and it should be noted that in this embodiment, the abnormal sample statistical information may include at least one of quantity statistical information belonging to the abnormal category, abnormal sample detection information belonging to the abnormal category, position information, and abnormal sample detection time.

203. Displaying at least one classification statistic.

In this embodiment of the application, after obtaining the at least one classification statistical result, the at least one classification statistical result needs to be displayed, and it should be noted that the obtained at least one classification statistical result may be stored in the memory 103. In an embodiment of the present invention, the display 102 of the sample detection device 10 may be a touch display screen, a liquid crystal display screen, or an independent display device such as a liquid crystal display and a television that is independent of the sample detection device 10, or a display of other Information management systems, such as a Laboratory Information management System (LIS System), or a display screen on an electronic device such as a mobile phone and a tablet computer, and so on, and for convenience of understanding, please refer to fig. 4, where fig. 4 is a schematic display interface diagram of a classification statistical result in the embodiment of the present application.

Fig. 4 shows four classification statistical results corresponding to four abnormality categories "analyzer hole blocking", "sample suction failure", "barcode invalid", and "empty position", and the statistical information of the abnormal sample belonging to each abnormality category includes the detection information of the abnormal sample belonging to the abnormality category, "sample identification information", position information, "sample position", and detection time of the abnormal sample, "detection time".

In the technical solution provided in the embodiment of the present application, the sample detection apparatus 10 can confirm the abnormal sample detection information in the sample result, and perform classification statistics on the abnormal sample detection information at the same time. By the mode, the abnormal type and the abnormal sample statistical information belonging to the abnormal type can be directly obtained from the sample detection result according to the sample abnormal type, and the detection information of each abnormal sample does not need to be searched from a large number of detection results, so that the workload is reduced, and the efficiency of in vitro detection is improved.

Optionally, on the basis of the embodiment corresponding to fig. 2, in a first optional embodiment of the sample detection information management method according to the embodiment of the present invention, performing classification statistics on the abnormal samples includes: identifying whether the abnormal sample is caused by the fact that a jewel hole is blocked in a red blood cell/platelet impedance channel of the detection instrument, and if so, classifying the abnormal sample as a blocked hole; identifying whether the abnormal sample is caused by clot in the sample, or the sample amount does not meet the minimum test dosage, or bubbles generated in the sample suction process, and if so, classifying the abnormal sample as abnormal sample suction; identifying whether the abnormal sample is caused by the failure of sample bar code scanning, if so, classifying the abnormal sample as invalid without bar codes; or whether the abnormal sample has a test tube at the position where the abnormal sample is not identified is identified, and if so, the abnormal sample is classified as a vacant position.

In this embodiment of the application, before performing classification statistics on the abnormal sample detection information according to different abnormal categories, the processor 101 needs to perform abnormal category confirmation on each abnormal sample detection information, and optionally, the performing abnormal category confirmation on the abnormal sample detection information may include the following steps:

taking the above detection process including steps 1 to 3 as an example, when the "component analysis result" is missing or shielded (for example, information such as White Blood Cells (WBC), Red Blood Cells (RBC), Hemoglobin (HGB), Platelets (PLT) and the like is missing or shielded), further, the sample detection apparatus 10 identifies whether the abnormal sample is caused by the jewel hole blockage occurring in the RBC/PLT impedance channel of the detection instrument, and if so, classifies the abnormal sample as the analyzer hole blockage;

or identifying whether the abnormal sample is caused by the fact that the sample has a clot, or the sample amount does not meet the minimum test dosage, or bubbles are generated in the sample suction process, and if so, classifying the abnormal sample as sample suction failure;

when the 'sample identification information' is missing (such as the bar code number or the serial number corresponding to the bar code or the two-dimensional code is missing), further identifying whether the abnormal sample is caused by the failure of scanning the bar code of the sample, and if so, classifying the abnormal sample as invalid bar code;

when neither the sample identification information nor the component analysis result is included, further, whether the abnormal sample has a test tube because the position of the abnormal sample is not identified is identified, and if so, the abnormal sample is classified as a blank.

After the abnormal sample detection information is confirmed in abnormal type and classified, the classified statistics of the abnormal samples is completed, further, in order to perfect the classified statistics result, the quantity statistics of the abnormal sample detection information belonging to each classified type can be further performed to obtain the quantity statistics information, further, in order to perfect the classified statistics result, the position information of the abnormal sample can be further obtained, wherein the position information of the abnormal sample can be 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, it can be understood that the position information of the abnormal sample can be equal to the physical position information of the sample container for holding the abnormal sample, the sample container needs a fixing frame to fix the sample container under normal conditions, taking the sample container as the test tube as an example, the fixing frame for fixing the test tube can be specifically the test tube rack, and the test tube rack is provided with at least one test tube, so the physical position information of the sample container for holding 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. Therefore, only the test tube rack number of the test tube rack corresponding to the test tube in which the abnormal sample is located needs to be obtained; and the position information of the test tube on the test tube rack can be determined to show the position information of the abnormal sample, and further, in order to perfect the classification statistical result, the detection time of the target abnormal sample and the identification information of the target abnormal sample can be further obtained.

In the technical scheme provided by the embodiment of the application, the classified statistics of the abnormal samples comprises the following steps: identifying whether the abnormal sample is caused by the diamond hole blockage of the RBC/PLT impedance channel of the detection instrument, if so, classifying the abnormal sample as the hole blockage; identifying whether the abnormal sample is caused by clot in the sample, or the sample amount does not meet the minimum test dosage, or bubbles generated in the sample suction process, and if so, classifying the abnormal sample as abnormal sample suction; identifying whether the abnormal sample is caused by the failure of sample bar code scanning, if so, classifying the abnormal sample as invalid without bar codes; or whether the abnormal sample is identified because the test tube is not identified at the position where the abnormal sample is located is identified, if so, the abnormal sample is classified into the vacancy, and through the mode and the more accurate classification mode, the detection information of the abnormal sample can be classified and counted into four types of classification statistical results, so that the accuracy of classification statistics is improved.

Optionally, on the basis of the embodiment corresponding to fig. 2, in a second optional embodiment of the sample detection information management method provided in the embodiment of the present invention, the method further includes:

receiving a query instruction, wherein the query instruction is used for checking the abnormal sample information of the target abnormal category;

and responding to the query instruction, and displaying all abnormal sample information of the target abnormal category, wherein each abnormal sample information comprises abnormal sample position information.

In the embodiment of the present application, a specific display mechanism of the classification statistical result is described. For easy understanding, please refer to fig. 5a and 5b, in which fig. 5a is a schematic diagram of a main display interface of a classification statistical result in the embodiment of the present application, and fig. 5b is a schematic diagram of a sub-display interface of a classification statistical result in the embodiment of the present application.

As shown in fig. 5a, the main display interface includes the abnormality category (analyzer hole blocking, sample failure, barcode invalid and empty) and the statistical information (3, 2, 1) of the number belonging to the abnormality category, it is understood that the abnormality category and arrangement in fig. 5a are only an example, and in practice, other abnormality types may be displayed and arranged, and this is not limited here.

In the embodiment of the application, in order to provide a specific abnormal sample information which can be viewed and belongs to a certain abnormal category for a detection person, the interface further comprises a detailed information module: when the key is clicked, a query instruction is received, and the query instruction is used for checking the abnormal sample information of the target abnormal category, it can be understood that the "detailed information" module in fig. 5a may also be named as "specific information" or "check more" and the like, the "detailed information" module in fig. 5a is only an example, and other named modules are actually displayed, which is not limited herein;

when the key of the "detailed information" module is clicked, all the abnormal sample information of the target abnormal category is displayed in response to the query instruction, and the abnormal sample information may be displayed on the sub-display interface exemplified by fig. 5b, referring to fig. 5b, where each abnormal sample information includes abnormal sample position information.

Secondly, in the embodiment of the invention, a specific display mechanism of the classified statistical result is explained, namely, a query instruction is received, and the query instruction is used for checking the abnormal sample information of the target abnormal category; and responding to the query instruction, and displaying all abnormal sample information of the target abnormal category, wherein each abnormal sample information comprises abnormal sample position information. Through the manner, the sample detection device 10 displays the classification statistical result including the abnormal category and the abnormal sample statistical information and the abnormal sample information in a grading manner on the basis of displaying at least one classification statistical result, so that a detection person can select the abnormal category to be checked, then the abnormal sample information is displayed, the workload is further reduced on the basis of not searching each abnormal sample detection information from a large number of detection results, and the readability of the classification statistical result is improved.

Optionally, on the basis of the second embodiment corresponding to fig. 2, in a third optional embodiment of the sample detection information management method provided in the embodiment of the present invention, the method further includes: acquiring position information of an abnormal sample, wherein the position information of the abnormal sample comprises a test tube rack number of a test tube rack corresponding to a test tube in which the abnormal sample is positioned; and the position information of the test tube on the test tube rack. Fig. 5b shows the abnormal sample position information included in the sub-display interface, and the specific steps for acquiring the abnormal sample position information will be described in detail below.

In the embodiment of the present application, before how to obtain the position information of the abnormal sample, first, it is described how to obtain the position information of the abnormal sample, when the abnormal sample detection information appears in the result of the sample detected by the sample detection device, the detecting person needs to search the barcode number of the abnormal sample, search the corresponding sample from all samples according to the barcode number, then confirm the state of the abnormal sample, and detect again, because the existing barcode number is 8 bits or more, for the detecting person, the workload of finding the corresponding sample according to the barcode number is too large, therefore, the position information of the abnormal sample can be detected before the sample is detected by the sample detection device 10, or after the sample is detected by the sample detection device 10, or while the sample is detected by the sample detection device 10, the position information of the abnormal sample identifies the specific physical position of the abnormal sample, therefore, the detection personnel can directly obtain the physical position of the abnormal sample through the abnormal sample position information corresponding to the abnormal sample.

In the embodiment of the present application, after explaining how to obtain the position information of the abnormal sample, the meaning of the position information of the abnormal sample is explained first, and in this embodiment, the position information of the abnormal sample may be a test tube rack number of a test tube rack corresponding to a test tube in which the abnormal sample is located; 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 equal to the physical position information of the sample container for holding the abnormal sample, the sample container needs a fixing frame to fix the sample container under normal conditions, taking the sample container as the test tube as an example, the fixing frame for fixing the test tube can be specifically the test tube rack, and the test tube rack is provided with at least one test tube, so the physical position information of the sample container for holding 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. Therefore, only the test tube rack number of the test tube rack corresponding to the test tube in which the abnormal sample is located needs to be obtained; and the position information of the test tube on the test tube rack, the position information indicating the abnormal sample can be determined, for example, 1-2, 2-9 and 9-6 shown in fig. 5b, taking 1-2 as an example, 1 specifically being the test tube rack number corresponding to the test tube in which the abnormal sample is located, 2 specifically being the position information of the test tube on the test tube rack, and 2 being understood as the position of the test tube at hole No. 2 on the test tube rack, it should be noted that the position information on the test tube rack can be represented by 1, 2, 3, or A, B, C bits, which is not limited herein, further, after the detecting person obtains the position information of the abnormal sample, the test tube rack in which the abnormal sample is located can be directly found according to the test tube rack number in the position information of the abnormal sample, and the test tube at which the corresponding abnormal sample is located according to the position information on the test tube rack in the position information of the abnormal sample, in the embodiment of the application, refine unusual sample positional information into test tube rack number and the positional information of test tube on this test-tube rack, correspond the physical position to the splendid attire container with the sample position, further make testing personnel know under the condition of unusual sample positional information, faster find unusual sample.

It can be understood that how to obtain the abnormal sample position includes two problems of where to obtain the abnormal sample position and from the position in what manner, and it is next described where to obtain the abnormal sample position, in this embodiment of the present application, the identifier carrying the abnormal sample position may be attached to the test tube rack and the test tube as follows:

1. the outer wall of the test tube is pasted with the corresponding test tube rack number of the test tube rack and the mark of the position information of the test tube on the test tube rack;

2. the method comprises the following steps that a mark of a test tube rack number is pasted on one side of a test tube rack, and a mark of position information on the test tube rack is pasted near each test tube placing hole of the test tube rack;

3. one side subsides on the test-tube rack has the sign of test tube rack number, pastes the sign that has the test tube position information on this test-tube rack at the test tube outer wall.

The above three modes are only three examples of the obtaining position of the abnormal sample position, and in practice, the obtaining position may be set in more modes, and here, the sample detection apparatus 10 may obtain the abnormal sample position by scanning the identifier carrying the abnormal sample position through the identifier or the scanner, and specifically, the sample detection apparatus 10 may obtain the test tube rack number of the test tube rack corresponding to the test tube where the sample is located and the position information of the test tube on the test tube rack by scanning the identifier carrying the abnormal sample position through the identifier or the scanner.

Further, in the embodiment of the present invention, position information of the abnormal sample is obtained, where the position information of the abnormal sample includes a test tube rack number of a test tube rack corresponding to a test tube in which the abnormal sample is located; and the position information of the test tube on the test tube rack. Obtain abnormal sample positional information through above-mentioned mode, refine abnormal sample positional information into test tube frame number and test tube positional information on this test-tube rack, correspond the physical position to the splendid attire container with the sample position, further make the testing personnel know under the condition of abnormal sample positional information, faster find abnormal sample.

Optionally, on the basis of the second embodiment corresponding to fig. 2, in a fourth optional embodiment of the sample detection information management method provided in the embodiment of the present invention, each abnormal sample information further includes at least one of sample identification information and detection time information, for convenience of understanding, please refer to fig. 6, fig. 6 is a schematic view of a sub-display interface of a classification statistical result in the embodiment of the present application, it can be understood that fig. 6 may be a display interface appearing after a key of the "detailed information" module in fig. 5a is clicked, it can be seen that the display interface includes the sample identification information, the detection time information and a sample position, and it is to be noted that the sample identification information may be identification information corresponding to the barcode and the two-dimensional code and uniquely corresponding to a sample source.

Further, in this embodiment of the present invention, each abnormal sample information further includes at least one of sample identification information and detection time information. Through the expansion of the abnormal sample information, the sample identification information is further shown under the condition that the detection personnel know the position information of the abnormal sample, and the abnormal sample needing to be found can be determined more accurately by judging the detection time, so that more information guide is provided for the detection personnel.

Optionally, on the basis of the third embodiment corresponding to fig. 2, in a fifth optional embodiment of the sample detection information management method according to the embodiment of the present invention, the method further includes: receiving a second query instruction, wherein the query instruction is used for checking second abnormal sample information of a second target abnormal category contained in the abnormal sample information, and the second target abnormal category comprises a detection time period; and responding to the second query instruction, and displaying all second abnormal sample information of the second target abnormal category, wherein each second abnormal sample information comprises abnormal sample position information.

In the embodiment of the present application, a specific display mechanism of the classification statistical result is described. For easy understanding, please refer to fig. 7a and 7b, where fig. 7a is a schematic diagram of a first sub-display interface of a classification statistical result in the embodiment of the present application, and fig. 7b is a schematic diagram of a second sub-display interface of a classification statistical result in the embodiment of the present application, and it is understood that fig. 7a may be a display interface appearing after a key of the "detailed information" module in fig. 5a is clicked.

As shown in fig. 7a, the first sub-display interface includes a target anomaly category (analyzer plugging hole) and a second target anomaly category module (detection time) belonging to the anomaly category, and it is understood that the target anomaly category in fig. 7a is only an example, and may be actually displayed and arranged for other target anomaly types, which is not limited herein. The second target abnormality category module in fig. 7a includes modules corresponding to a plurality of detection time periods, and it can be understood that, when any one of the second target abnormality category modules is clicked, it is equivalent to the second query instruction to view the second abnormality sample information corresponding to the detection time period corresponding to the second target abnormality category, for example, fig. 7a shows that the second query instruction is to view the second abnormality sample information corresponding to the time period of "2018-04-0318: 20-18: 25", and optionally, each piece of the second abnormality sample information includes abnormality sample position information.

When the key of the "2018-04-0318: 20-18: 25" module is clicked, all second abnormality sample information of the second target abnormality category is displayed in response to the second query instruction, and the second abnormality sample information may be displayed on the sub-display interface exemplified by fig. 7b, and optionally, each piece of the second abnormality sample information includes abnormality sample position information.

In the embodiment of the invention, a specific display mechanism of the classified statistical result is described, namely, a second query instruction is received, and the query instruction is used for checking second abnormal sample information of a second target abnormal category contained in the abnormal sample information; and responding to the second query instruction, and displaying all second abnormal sample information of the second target abnormal category, wherein each second abnormal sample information comprises abnormal sample position information. Through the manner, on the basis that the sample detection device 10 carries out secondary display on the classification statistical result including the abnormal category and the abnormal sample statistical information and the abnormal sample information, a detection person can further select the second abnormal category to be checked, then the abnormal sample information is displayed, on the basis that the abnormal sample detection information does not need to be searched from a large number of detection results, the workload is further reduced, and the readability of the classification statistical result is improved.

Optionally, on the basis of the third embodiment corresponding to fig. 2, in a sixth optional embodiment of the sample detection information management method provided in the embodiment of the present invention, the method further includes: receiving a third query instruction, wherein the query instruction is used for checking third abnormal sample information of a third target abnormal category contained in the abnormal sample information, and the third target abnormal category comprises second abnormal sample position information; and displaying all the third abnormal sample information of the third target abnormal category in response to the third query instruction, wherein each third abnormal sample information comprises third abnormal sample position information.

In the embodiment of the present application, a specific display mechanism of the classification statistical result is described. For convenience of understanding, please refer to fig. 8a and 8b, where fig. 8a is a schematic diagram of a third sub-display interface of a classification statistical result in the embodiment of the present application, and fig. 8b is a schematic diagram of a fourth sub-display interface of a classification statistical result in the embodiment of the present application, and it is understood that fig. 8a may be a display interface appearing after a key of the "detailed information" module in fig. 5a is clicked.

As shown in fig. 8a, the second sub-display interface includes a target abnormality category (analyzer plugging hole) and a third target abnormality category module (second abnormality sample position information) belonging to the abnormality category, and it can be understood that the target abnormality category in fig. 8a is only an example, and may also be displayed and arranged for other target abnormality types in practice, which is not limited herein. The third target abnormal category module in fig. 8a contains modules corresponding to a plurality of different test tube rack numbers, and it can be understood that, by clicking any third target abnormal category module, it is equivalent to the third query command to check the third abnormal sample information corresponding to the test tube rack number corresponding to the third target abnormal category, for example, fig. 8a shows that the third query command checks the third abnormal sample information corresponding to the "test tube rack No. 2", optionally, each third abnormal sample information includes the second abnormal sample position information, it should be noted that, in the embodiment of the present application, the second abnormal sample position information and the first abnormal sample position information are more specific position information, for example, the first abnormal sample position information in fig. 7a is the 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, i.e. position No. 9 of test tube rack No. 2).

When the key of the "test tube rack No. 2" module is clicked, all the third abnormal sample information of the third target abnormal category is displayed in response to the third query instruction, and the third abnormal sample information may be displayed on the sub-display interface exemplified by fig. 8b, and optionally, each piece of the third abnormal sample information includes third abnormal sample position information.

In the embodiment of the present invention, a specific display mechanism of the classification statistical result is described, that is, a third query instruction is received, where the query instruction is used to view third abnormal sample information of a third target abnormal category included in the abnormal sample information, and the third target abnormal category includes second abnormal sample position information; and displaying all the third abnormal sample information of the third target abnormal category in response to the third query instruction, wherein each third abnormal sample information comprises third abnormal sample position information. Through the manner, on the basis that the sample detection device 10 carries out secondary display on the classification statistical result including the abnormal category and the abnormal sample statistical information and the abnormal sample information, a detection person can further select the second abnormal category to be checked, then the abnormal sample information is displayed, on the basis that the abnormal sample detection information does not need to be searched from a large number of detection results, the workload is further reduced, and the readability of the classification statistical result is improved.

It should be understood that the embodiment of the present application mainly includes three display modes, namely, a "first-level abnormal sample information display" mode, a "second-level abnormal sample information display" mode, and a "third-level abnormal sample information display" mode, which will be described below with reference to the accompanying drawings.

Taking the sample detection device 10, specifically a blood analyzer, as an example to explain the process of the sample detection information management method, please refer to fig. 9, fig. 9 is a schematic flow chart of a "primary abnormal sample information display" mode in the application scenario of the present application, as shown in the figure, specifically:

301. automatically sampling at least one human blood sample and sucking the sample;

302. scanning identification information on a test tube containing a blood sample to obtain sample identification information;

303. obtaining the position information of the blood sample, wherein the position information of the blood sample comprises the test tube rack number of the test tube rack corresponding to the test tube in which the blood sample is positioned; and position information of the test tube on the test tube rack;

304. performing component analysis on the sample obtained by sample suction to obtain at least one component analysis result, wherein the component analysis result comprises WBC, RBC, HGB and PLT;

305. obtaining the detection time of the blood sample;

3061. when WBC, RBC, HGB or PLT in one component analysis result is missing or shielded, identifying whether the blood sample is caused by the fact that the RBC/PLT impedance channel of the detection instrument is plugged by a gem hole, if so, classifying the abnormal sample as the analyzer plugged hole;

3062. when WBC, RBC, HGB or PLT in one component analysis result is missing or shielded, identifying whether the blood sample is caused by clotting of the sample, or the sample amount does not meet the minimum test dosage, or bubbles generated in the sample suction process, and if so, classifying the abnormal sample as sample suction failure;

3063. when the sample identification information is lost, identifying whether the blood sample is caused by sample bar code scanning failure, if so, classifying the abnormal sample as invalid bar code;

3064. when the sample identification information is missing and WBC, RBC, HGB or PLT in the component analysis result is missing or shielded, identifying whether the blood sample has a test tube at the position where the abnormal sample is not identified, if so, classifying the abnormal sample as a vacant position;

307. and displaying four abnormal categories of the analyzer, namely hole blocking, sample sucking failure, invalid bar codes and vacant positions, blood sample position information, blood sample detection time and sample identification information of each abnormal sample belonging to the four abnormal categories on a first main abnormal sample display interface.

Referring to fig. 10, fig. 10 is a schematic flow chart of a "secondary abnormal sample information display" mode in an application scenario of the present application, as shown in the figure, specifically:

401. automatically sampling at least one human blood sample and sucking the sample;

402. scanning identification information on a test tube containing a blood sample to obtain sample identification information;

403. obtaining the position information of the blood sample, wherein the position information of the blood sample comprises the test tube rack number of the test tube rack corresponding to the test tube in which the blood sample is positioned; and position information of the test tube on the test tube rack;

404. performing component analysis on the sample obtained by sample suction to obtain at least one component analysis result, wherein the component analysis result comprises WBC, RBC, HGB and PLT;

405. obtaining the detection time of the blood sample;

4061. when WBC, RBC, HGB or PLT in one component analysis result is missing or shielded, identifying whether the blood sample is caused by the fact that the RBC/PLT impedance channel of the detection instrument is plugged by a gem hole, if so, classifying the abnormal sample as the analyzer plugged hole;

4062. when WBC, RBC, HGB or PLT in one component analysis result is missing or shielded, identifying whether the blood sample is caused by clotting of the sample, or the sample amount does not meet the minimum test dosage, or air bubbles generated in the sample suction process, and if so, classifying the abnormal sample as sample suction failure;

4063. when the sample identification information is lost, identifying whether the blood sample is caused by sample bar code scanning failure, if so, classifying the abnormal sample as invalid bar code;

4064. when the sample identification information is missing and WBC, RBC, HGB or PLT in the component analysis result is missing or shielded, identifying whether the blood sample has a test tube at the position where the abnormal sample is not identified, if so, classifying the abnormal sample as a vacant position;

407. counting the quantity of the abnormal sample detection information belonging to each classification category to obtain quantity statistical information;

408. displaying four abnormal categories of analyzer hole blocking, sample sucking failure, bar code invalidation and vacancy and number statistical information belonging to each abnormal category on a second main abnormal sample display interface;

409. and responding to the query instruction corresponding to the target exception category, and displaying the blood sample position information, the blood sample detection time and the sample identification information of each exception sample belonging to the target exception category on the first sub exception sample display interface.

Referring to fig. 11, fig. 11 is a schematic flow chart of a "three-level abnormal sample information display" mode in an application scenario of the present application, as shown in the figure, specifically:

501. automatically sampling at least one human blood sample and sucking the sample;

502. scanning identification information on a test tube containing a blood sample to obtain sample identification information;

503. obtaining the position information of the blood sample, wherein the position information of the blood sample comprises the test tube rack number of the test tube rack corresponding to the test tube in which the blood sample is positioned; and position information of the test tube on the test tube rack;

504. performing component analysis on the sample obtained by sample suction to obtain at least one component analysis result, wherein the component analysis result comprises WBC, RBC, HGB and PLT;

505. obtaining the detection time of the blood sample;

5061. when WBC, RBC, HGB or PLT in one component analysis result is missing or shielded, identifying whether the blood sample is caused by the fact that the RBC/PLT impedance channel of the detection instrument is plugged by a gem hole, if so, classifying the abnormal sample as the analyzer plugged hole;

5062. when WBC, RBC, HGB or PLT in one component analysis result is missing or shielded, identifying whether the blood sample is caused by clotting of the sample, or the sample amount does not meet the minimum test dosage, or air bubbles generated in the sample suction process, and if so, classifying the abnormal sample as sample suction failure;

5063. when the sample identification information is lost, identifying whether the blood sample is caused by sample bar code scanning failure, if so, classifying the abnormal sample as invalid bar code;

5064. when the sample identification information is missing and WBC, RBC, HGB or PLT in the component analysis result is missing or shielded, identifying whether the blood sample has a test tube at the position where the abnormal sample is not identified, if so, classifying the abnormal sample as a vacant position;

507. counting the quantity of the abnormal sample detection information belonging to each classification category to obtain quantity counting information;

508. displaying four abnormal categories of analyzer hole blocking, sample sucking failure, bar code invalidation and vacancy and number statistical information belonging to each abnormal category on a second main abnormal sample display interface;

509. responding to a query instruction corresponding to the target abnormal category, and displaying each detection time period of the blood sample belonging to the target abnormal category on a second sub-abnormal sample display interface;

510. and responding to a second query instruction corresponding to the detection time period, and displaying the blood sample position information, the blood sample detection time and the sample identification information belonging to the target detection time period on a third sub abnormal sample display interface.

Referring to fig. 12, fig. 12 is another schematic flow chart of a "three-level abnormal sample information display" mode in the application scenario of the present application, as shown in the figure, specifically:

601. automatically sampling at least one human blood sample and sucking the sample;

602. scanning identification information on a test tube containing a blood sample to obtain sample identification information;

603. obtaining the position information of the blood sample, wherein the position information of the blood sample comprises the test tube rack number of the test tube rack corresponding to the test tube in which the blood sample is positioned; and position information of the test tube on the test tube rack;

604. performing component analysis on the sample obtained by sample suction to obtain at least one component analysis result, wherein the component analysis result comprises WBC, RBC, HGB and PLT;

605. obtaining the detection time of the blood sample;

6061. when WBC, RBC, HGB or PLT in one component analysis result is missing or shielded, identifying whether the blood sample is caused by the fact that the RBC/PLT impedance channel of the detection instrument is plugged by a gem hole, if so, classifying the abnormal sample as the analyzer plugged hole;

6062. when WBC, RBC, HGB or PLT in one component analysis result is missing or shielded, identifying whether the blood sample is caused by clotting of the sample, or the sample amount does not meet the minimum test dosage, or air bubbles generated in the sample suction process, and if so, classifying the abnormal sample as sample suction failure;

6063. when the sample identification information is lost, identifying whether the blood sample is caused by sample bar code scanning failure, if so, classifying the abnormal sample as invalid bar code;

6064. when the sample identification information is missing and WBC, RBC, HGB or PLT in the component analysis result is missing or shielded, identifying whether the blood sample has a test tube at the position where the abnormal sample is not identified, if so, classifying the abnormal sample as a vacant position;

607. counting the quantity of the abnormal sample detection information belonging to each classification category to obtain quantity counting information;

608. displaying four abnormal categories of analyzer hole blocking, sample sucking failure, bar code invalidation and vacancy and number statistical information belonging to each abnormal category on a second main abnormal sample display interface;

609. responding to a query instruction corresponding to the target exception category, and displaying each test tube frame number belonging to the target exception category on a third sub exception sample display interface;

610. and displaying the blood sample position information, the blood sample detection time and the sample identification information belonging to each test tube rack number on a fourth sub abnormal sample display interface in response to a third query instruction corresponding to each test tube rack number.

In the above embodiments, the implementation may be wholly or partially realized by software, hardware, firmware, or any combination thereof. When implemented in software, may be implemented in whole or in part in the form of a computer program product.

The computer program product includes one or more computer instructions. When loaded and executed on a computer, cause the processes or functions described in accordance with the embodiments of the invention to occur, in whole or in part. The computer may be a general purpose computer, a special purpose computer, a network of computers, or other programmable device. The computer instructions may be stored on a computer readable storage medium or transmitted from one computer readable storage medium to another, for example, from one website, computer, server, or data center to another website, computer, server, or data center via wire (e.g., coaxial cable, fiber optic, Digital Subscriber Line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.). The computer-readable storage medium can be any available medium that a computer can store or a data storage device, such as a server, a data center, etc., that is integrated with one or more available media. The usable medium may be a magnetic medium (e.g., floppy disk, hard disk, magnetic tape), an optical medium (e.g., DVD), or a semiconductor medium (e.g., Solid State Disk (SSD)), among others.

It is clear to those skilled in the art that, for convenience and brevity of description, the specific working processes of the above-described systems, apparatuses and units may refer to the corresponding processes in the foregoing method embodiments, and are not described herein again.

In the several embodiments provided in the present application, it should be understood that the disclosed system, apparatus and method may be implemented in other manners. For example, the above-described apparatus embodiments are merely illustrative, and for example, the division of the units is only one type of logical functional division, and other divisions may be realized in practice, for example, a plurality of units or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, devices or units, and may be in an electrical, mechanical or other form.

The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.

In addition, functional units in the embodiments of the present application may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit can be realized in a form of hardware, and can also be realized in a form of a software functional unit.

The integrated unit, if implemented in the form of a software functional unit and sold or used as a stand-alone product, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present application may be substantially implemented or contributed to by the prior art, or all or part of the technical solution may be embodied in a software product, which is stored in a storage medium and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method according to the embodiments of the present application. And the aforementioned storage medium includes: various media capable of storing program codes, such as a usb disk, a removable hard disk, a read-only memory (ROM), a Random Access Memory (RAM), a magnetic disk, or an optical disk.

The above embodiments are only used for illustrating the technical solutions of the present application, and not for limiting the same; although the present application has been described in detail with reference to the foregoing embodiments, it should be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; and such modifications or substitutions do not depart from the spirit and scope of the corresponding technical solutions in the embodiments of the present application.

Claims

A method for managing sample testing information, the method comprising:

detecting the sample;

if the sample detection result comprises abnormal sample detection information, performing classified statistics on the abnormal sample detection information to obtain at least one classified statistical result, wherein each classified statistical result comprises an abnormal category and abnormal sample statistical information belonging to the abnormal category;

displaying the at least one classification statistic.
The sample detection information management method according to claim 1, further comprising:

receiving a query instruction, wherein the query instruction is used for checking the abnormal sample information of the target abnormal category;

and responding to the query instruction, displaying all abnormal sample information of a target abnormal category, wherein each abnormal sample information comprises abnormal sample position information.
The sample detection information management method according to claim 2, wherein each abnormal sample information further includes at least one of sample identification information and detection time information.
The sample detection information management method according to any one of claims 1 to 3,

the anomaly sample statistics for each anomaly class include the number of anomaly samples belonging to that anomaly class.
The sample detection information management method according to any one of claims 1 to 3, wherein the sample abnormality category includes at least one of:

analyzer plugging, sample failure, barcode invalidity, and empty positions.
The method of claims 1 to 5, wherein the performing classification statistics on abnormal samples comprises:

identifying whether the abnormal sample is caused by the plugging of a jewel hole in a red blood cell/platelet impedance channel of the detection instrument, if so, classifying the abnormal sample as the plugging of the analyzer; or

Identifying whether the abnormal sample is caused by clotting of the sample, or the quantity of the sample does not meet the minimum test dosage, or bubbles generated in the sample suction process, and if so, classifying the abnormal sample as sample suction failure; or

Identifying whether the abnormal sample is caused by the failure of sample bar code scanning, if so, classifying the abnormal sample as invalid bar code; or

And identifying whether the abnormal sample has a test tube because the position of the abnormal sample is not identified, and if so, classifying the abnormal sample as a vacant position.
The sample detection information management method according to any one of claims 2 to 6, characterized by further comprising:

acquiring position information of an abnormal sample, wherein the position information of the abnormal sample comprises a test tube rack number of a test tube rack corresponding to a test tube in which the abnormal sample is positioned;

and the position information of the test tube on the test tube rack.
A sample testing device, comprising: a processor and a display;

the processor performs the steps of:

detecting the sample;

if the sample detection result comprises abnormal sample detection information, performing classified statistics on the abnormal sample detection information to obtain at least one classified statistical result, wherein each classified statistical result comprises an abnormal category and abnormal sample statistical information belonging to the abnormal category;

the display displays the at least one classification statistic.
The sample testing device of claim 8, wherein said processor is further configured to perform the steps of:

receiving a query instruction, wherein the query instruction is used for checking the abnormal sample information of the target abnormal category;

and responding to the query instruction, displaying all abnormal sample information of a target abnormal category, wherein each abnormal sample information comprises abnormal sample position information.
The specimen-testing device according to claim 9, wherein each abnormal specimen information further includes at least one of specimen identification information, test time information.
The apparatus according to any one of claims 8 to 10, wherein the statistical information on the abnormal samples for each abnormal class includes the number of abnormal samples belonging to the abnormal class.
The sample testing device of any of claims 8 to 10, wherein said sample abnormality category comprises at least one of:

analyzer plugging, sample failure, barcode invalidity, and empty positions.
The sample testing device of any of claims 8 to 12, wherein said processor is further configured to perform the steps of:

identifying whether the abnormal sample is caused by the plugging of a jewel hole in a red blood cell/platelet impedance channel of the detection instrument, if so, classifying the abnormal sample as the plugging of the analyzer; or

Identifying whether the abnormal sample is caused by clotting of the sample, or the quantity of the sample does not meet the minimum test dosage, or bubbles generated in the sample suction process, and if so, classifying the abnormal sample as sample suction failure; or

Identifying whether the abnormal sample is caused by the failure of sample bar code scanning, if so, classifying the abnormal sample as invalid bar code; or

And identifying whether the abnormal sample has a test tube because the position of the abnormal sample is not identified, and if so, classifying the abnormal sample as a vacant position.
The sample testing device of any of claims 9 to 12, wherein said processor is further configured to perform the steps of:

acquiring position information of an abnormal sample, wherein the position information of the abnormal sample comprises a test tube rack number of a test tube rack corresponding to a test tube in which the abnormal sample is positioned;

and the position information of the test tube on the test tube rack.
A readable storage medium comprising a program or instructions which, when run on a computer, performs the method of any of claims 1-7.