JP4690287B2 - Clinical laboratory analyzer and sample data transmission method - Google Patents

Description

  The present invention relates to an analyzer for clinical testing that can be connected to a management apparatus via a network and a method for transmitting sample data.

  In clinical tests such as blood tests, it is required to analyze various test items using blood and urine as samples. These analysis items are measured by an analyzer that employs a measurement method according to the characteristics. In order to maintain the accuracy of the test results, the analyzer is equipped with an advanced mechanism so that a very low concentration substance can be measured with high sensitivity or more than 10 items can be measured from a small amount of sample. The operation of each mechanism is monitored.

When a trouble occurs in the operation of each mechanism unit, the analyzer issues a warning to that effect and notifies the user of the trouble of the analyzer. In that case, the user solves the trouble according to the instruction manual or by calling the support center and explaining the situation and following the explanation of the engineer. If the user cannot solve the problem by himself, he / she dispatches an engineer from the support center to solve the problem.
However, in clinical examinations, it is not sufficient to monitor the mechanism part in order to accurately manage the test results of such biological components, and the same sample as the biological component or a sample similar thereto is measured as a quality control substance, Quality control is performed to monitor the measurement results.

This quality control includes a method (internal quality control) that monitors whether the same quality control substance is measured every day to obtain a stable measurement result, and results measured with the same analyzer used outside the facility. A method of monitoring whether similar measurement results are obtained (external quality control) is used.
However, in order to perform external quality control, the same quality control materials are sent from the aggregation organization to each facility, the quality control materials are measured at each facility, and the measurement results (hereinafter referred to as sample data) are counted from each facility. The data must be sent to the institution and the sample data collected by the institution. Each facility knows the results of external quality control only after the counting results are returned from the counting organization. From sending this quality control substance to returning the counting results, the counting agency may have to wait until a certain number or more of sample data has been returned, and it usually takes one to two months.

As described above, the external quality control can only be confirmed by waiting for the result of the aggregation by the aggregation organization, and the number of times is usually performed once a year, at most 3 to 4 times a year.
In order to improve the reliability of the measurement data, the accuracy control is inherently performed before daily sample measurement and confirms the result. That is, if the sample data for accuracy control is out of the predetermined range, it can be said that an error has occurred, and the sample should be measured after the analyzer is adjusted to be within the predetermined range. However, in the current external accuracy management, the result of aggregation is returned one to two months after the measurement, and it is only used to confirm the state of the apparatus at the time of the measurement after the fact.

In addition, when analyzing substances that tend to change over time, such as blood, the quality of the quality control material used for measuring sample data must be the same among facilities participating in external quality control. However, when sending quality control materials to each facility and collecting sample data, the measurement date tends to vary. In this case, the freshness of the quality control material that is the basis of the collected sample data varies, and the reliability of the tabulation results is reduced.
An object of this invention is to provide the technique in which the effective external precision management of an analyzer is possible.

A clinical test analyzer according to a first aspect of the present invention is a clinical test analyzer that can be connected to a management device installed outside a facility via a network, for measuring a sample in a container. Analyzing means, transmitting means for transmitting predetermined information to the management device via a network, means for reading a barcode attached to a container having sample identification information, and reading the barcode to control the accuracy of the sample If the sample is a quality control substance, the sample data obtained by the analysis means measuring the quality control substance, the lot number of the quality control substance, the type of the quality control substance, the measurement mode and the device includes the identification information, and control means and create an e-mail written authentication information analyzer in the body, to control the transmission means to transmit the created electronic mail to the management device, Provided, the management device aggregates the received sample data for clinical examination analyzer and per every quality control material, the whole of the analyzer and for each quality control for each material mean and quality control results by performing statistical processing for obtaining the standard deviation It is the management apparatus which produces .

The sample data transmission method according to the second aspect of the present invention is a method for transmitting sample data obtained by measuring a quality control substance from an analyzer via a network to a management device installed outside the facility. A method for transmitting sample data, wherein the reading means reads a barcode having identification information of a sample attached to the container, the analysis means measures the sample in the container, and the control means includes: A step of determining whether or not the sample is a quality control material based on the identification information of the barcode, and sample data obtained by measuring the quality control material when the sample is the quality control material , the quality control material the lot number, the kind of quality control substances including the identification information of the measurement mode and system, and an e-mail written authentication information analyzer in the body, the control means Includes a step of creating, when the sample is the quality control material, the sample data obtained by measuring a quality control substance, the lot number of the quality control material, the kind of quality control substance, the identification information of the measurement mode and system, and an e-mail written authentication information analyzer in the body, comprising the steps of: controlling means creates, transmission means, the created e-mail, and sending to the management apparatus via a network, a management Sample data received by the device is aggregated for each clinical analyzer and quality control substance, and statistical processing is performed to determine the overall average and standard deviation for each analyzer and quality control substance, and a quality control result is created. It is a management device .

  According to the clinical test analyzer and the sample data transmission method of the present invention, the sample data necessary for automatically discriminating the quality control sample and performing external quality control of the analyzer is automatically sent to the management device. Will be able to send to.

Next, the accuracy management method of the present invention will be specifically described with reference to an embodiment.
<First embodiment>
[Overview]
In this embodiment, a remote support system that implements the method of the present invention will be described as an example. The remote support system is configured by connecting an analysis device owned by a facility as a user and a management device on the system providing side through a dedicated network.

The analysis device transmits predetermined history information to the management device via the network at a predetermined timing. The history information includes predetermined operation information indicating the operating status of the analyzer and sample data. The operation information includes error information, the number of operations, an operation program, setting conditions, and the like of each analyzer. Sample data is measurement data of a quality control substance.
The management device collects history information from each analysis device, and performs support processing and QC (Quality Control) processing in which history information is edited and stored according to the content for each analysis device.

A. Support processing The management device edits and accumulates operation information from the collected history information. Further, the management device analyzes the error content based on the operation information, and displays if there is an important error. The engineer can check the history information of the analyzer in which the error occurred on the management device, so that it can fully grasp the device status without requiring detailed explanation from the user, and investigate the cause of the trouble. Can do.
The management device has a function of remotely operating the analysis device. Therefore, the engineer can treat the analyzer directly from the management apparatus without visiting the facility. Further, the management device can analyze the error information to predict a trouble in the analysis device and take measures to prevent the trouble in advance.

B. The QC process management device 1 aggregates the sample data of quality control substances measured by each analysis device 2 for each model of the analysis device 2 and for each type of quality control material. Each time the management apparatus 1 receives sample data, the management apparatus 1 updates the total result of the same type of sample data in the same model, and provides the latest total result on the web page. The analysis device 2 acquires the latest count result by accessing the web page. When accessing the web page, the management device performs an authentication process based on the authentication information input from the analysis device. In this way, immediately after measuring the quality control substance, the user can check the total result of external quality control, and the latest total result in real time.

[Constitution]
(1) Overall Configuration FIG. 1 is an example of an overall configuration diagram of a remote support system according to the first embodiment. In the remote support system according to this embodiment, the management device 1 and the analysis device 2 are connected via a dedicated network 3.
The analysis device 2 is connected to the dedicated network 3 via the network communication device 4. Examples of the analyzer 2 include a blood analyzer and a urine analyzer. As the management apparatus 1, a PC (Personal Computer), a WS (Work Station), or the like is used. As the network communication device 4, a dial-up router or a modem is used.

As the dedicated network 3, for example, a dedicated telephone line that can be used exclusively by a contract of a provider of this system with a company that provides the telephone line can be cited. In addition to the dedicated network, various networks such as the Internet, an intranet, and a LAN can be used.
(2) Management Device FIG. 2 is a block diagram illustrating functional configurations of the management device and the analysis device.
The management device includes a communication interface (I / F) 11, a processing unit 12, a user management DB 14, an e-mail server 15, a WWW server 16, and a remote control unit (host side) 13.

The communication I / F 11 establishes a connection with the analysis apparatus.
The processing unit 12 performs support processing and QC processing using the user management DB 14. By the support process, it is possible to display a predetermined error history on the management apparatus and investigate the cause of the trouble that has occurred in the analysis apparatus. 8 to 11 show display examples of error histories output by the processing unit. Moreover, external quality control can be performed on the analyzer in real time by the QC process. FIGS. 14 and 15 show examples of web pages of the counting results created by the QC process. Details of these display examples will be described later.

In the user management DB 14, error history, number of operations, QC data, log information, and the like are accumulated for each analyzer.
The e-mail server 15 receives the history information and sample data of the analysis apparatus by SMTP (Simple Mail Transfer Protocol). The communication protocol is not limited to SMTP, but since SMTP is not restricted by a firewall or the like, there is an advantage that the system can be easily extended on various networks in the future.
The WWW server 16 provides the web page created by the processing unit 12 to the WWW browser on the analyzer.

The remote control unit (host side) 13 enables remote operation of the analysis device 2 by interlocking with the remote control unit (user side) on the analysis device 2. When the two are linked, the analyzer is logged in remotely, and a window displayed on the analyzer is displayed on the remote control unit (host side) 13 or according to an input operation from the remote control unit (host side) 13. Can be operated.
(3) Analyzing device The user terminal 22 on the analyzing device 2 includes a communication interface (I / F) 23, an e-mail unit 24, a remote control unit (user side) 25, a WWW browser 26, a patient masking unit 27, and a control unit 28. have.

The communication I / F 23 performs a process of establishing a connection, like the communication I / F 11 in the management apparatus 1.
The e-mail unit 24 transmits history information indicating the operation history of the analysis unit 21 and sample data to the management apparatus by SMTP.
The remote control unit (user side) 25 operates together with the remote control unit (host side) 13 to enable operation of the analysis apparatus 2 from the management apparatus 1.

The WWW browser 26 acquires a web page on the management device based on an instruction from the user.
The patient masking unit 27 prevents patient information from being displayed on the management device when the analysis device 2 is operated from the management device 1.
The control unit 28 controls the operation of each component on the analysis unit 21 and the user terminal 22.
<Process flow>
Next, processing performed by the management apparatus and the analysis apparatus in the remote support system will be described.

(1) Process Flow of Entire System First, the process flow of the entire remote support system will be specifically described. FIG. 3 is an explanatory diagram showing an example of a user support flow in the remote support system.
The analyzer 2 performs normal sample measurement (# 1), and transmits the operation information to the management device 1 at a predetermined timing (# 3). The timing of transmission is real-time if there is acute operation information such as error information, and when the operation information is not urgent, such as the number of operations or the sample measurement result, at the time of shutdown. The error information is also displayed on the analyzer 1, and the user finds a trouble with the analyzer 1 (# 8).

The management device 1 divides the operation information sent from the analysis device 2 into the types and accumulates them in the history DB 13 (# 4). The management apparatus 1 predicts the occurrence of a predetermined important error, such as when there is important error information in the accumulated operation information, or when the frequency of the error is small but the error content tends to deteriorate. If so, the trouble of the analyzer is detected based on the setting (# 7).
Further, when measuring the quality control substance, the analyzer 2 transmits the sample data to the management apparatus 1 in real time unlike a normal sample measurement result (# 3). The analyzer 2 reads the barcode attached to the measurement sample container, determines whether the sample is a quality control substance, and transmits sample data based on the determination result. The management device 1 updates the tabulation result based on the new sample data (# 5).

After measuring the sample data, the user acquires the totaling result totaled by the management apparatus 1 (# 6), and confirms the external accuracy. The management device 1 updates the web page according to the update of the total result. When the analysis device 2 accesses the web page and the access is authenticated, the latest aggregated result is provided to the web page together with the sample data.
In this way, the user can immediately check not only the internal quality control result but also the external quality control result, and can find an abnormality in the analyzer in real time (# 8).

The management device 1 analyzes the quality control data, and detects a trouble of the analysis device 2 based on a predetermined setting when the quality control result is out of a predetermined range or when the quality control data is expected to deteriorate. (# 7). For example, the data tends to move away from the median. If the management device 1 detects a problem with the analysis device 2, the user is notified (# 8).
If a trouble with the analyzer is found (# 8), the user takes action to solve the trouble with the analyzer (# 10). The management device 1 analyzes the trouble content from the edited operation information of the analysis device 2 (# 9), and provides the user with optimal information for solving the trouble.

      If it is difficult for the user to solve the problem by himself, the user activates the remote control unit of the analyzer (# 11). The engineer at the support center performs trouble-solving operation by remotely operating the analyzer 2 using the remote control unit on the management device side (# 12). At that time, the screen of the analyzer is linked with the screen of the management device. In this way, troubles that can be solved by operating the analyzer can be solved by remote operation from the support center even if the trouble is complicated (# 14). Any trouble that cannot be dealt with will be repaired by a technician (# 13, 14).

(2) Process Flow in Management Device Next, a process flow performed by the management apparatus 1 in the remote support system will be specifically described.
(2-1) Collection Processing FIG. 4 is a flowchart illustrating an example of the flow of main processing performed by the management apparatus 1. In the main process, the management apparatus 1 collects history information from the analysis apparatus 2, accumulates it if it is an operation history, and performs QC process if it is sample data. The following processing is started by dial-up from the analyzer 2.

In step S1, the communication I / F 11 performs a connection process for establishing a connection with the analysis device 2.
In step S2, the processing unit 12 performs a predetermined authentication process. That is, it is determined whether the authentication information transmitted from the analysis device 2 matches the user information in the user DB.
In step S3, the processing unit 12 performs processing according to the authentication result. If it is determined that the authentication information matches, the process proceeds to step S4. If they do not match, perform processing such as disconnecting the connection.

In step S <b> 4, the e-mail server 15 receives data from the analysis device 2. The processing unit 12 determines whether the received data is predetermined operation information. The operation information is predetermined information other than sample data, and examples thereof include error information, number of operations, program history, and setting information. If it is determined Yes, the process proceeds to step S5. If determined No, the process proceeds to step S6.
In step S5, the process 12 unit temporarily stores the received operation information. This is for use in support processing described later. In the support process, for example, the operation information from each analyzer 2 is accumulated until 0:00 when the date changes, and when 0:00, the operation history is created based on the operation information received on that day.

In step S <b> 6, the communication I / F 11 performs a process of disconnecting the connection with the analyzer 2.
In step S7, the processing unit 12 determines whether or not the received data is sample data obtained by measuring a quality control substance. If YES is determined, the process proceeds to step S8, and the process proceeds to a QC process described later. That is, the sample data including the received data is aggregated, and each analysis device web page is updated. If the determination is No, the process proceeds to step S6, and the connection is disconnected.

(2-2) Support Processing FIG. 5 is a flowchart illustrating an example of the flow of support processing performed by the management apparatus 1 independently of the main processing. Each time the date changes, the management device 1 edits the operation information received on that day and writes it in the history DB.
In step S21, the processing unit 12 waits for a predetermined time, for example, 0:00.
In step S <b> 22, the processing unit 12 determines one of the analysis devices 2 registered in the user management DB 14 as the target user.

In step S <b> 23, the processing unit 12 determines whether or not the operation information indicating the operation status of the day has been received for the target user. If YES is determined, the process proceeds to step S24. If determined No, the process proceeds to step S25 described later.
In step S <b> 24, the processing unit 12 edits the operation information for each analyzer and for each content, and writes it in the history DB. For example, the error information, the number of operations, the operation program, and the setting conditions are each edited in a table format together with the date and time, and written in the history DB.
In step S25, the processing unit 12 writes predetermined error information indicating that the operation information could not be acquired in the user management DB 14. Examples of the error information include an analysis apparatus name, date, time, an error number indicating an error that has occurred, and an error message corresponding to the error number.

In step S26, the processing unit 12 searches for a predetermined error based on the error information of the target user. For example, based on the determination method shown in FIG. 12, the error level as illustrated in FIG. 13 is determined from the error type and the frequency at which the same error occurs.
In step S27, the processing unit 12 determines whether an error is included in the operation information of the target user based on the search result. If the error level is not 0, Yes is determined. If YES is determined, the process proceeds to step S28. If determined No, the process proceeds to step S29 described later.

In step S28, the processing unit 12 writes the determined error level in the user management DB 14.
In step S29, the processing unit 12 determines whether or not the processes of steps S23 to S28 have been performed for all the registered analyzers 2. If YES is determined, the process returns to step S21. That is, it waits until the next date changes. If NO is determined, the process returns to step S22, and another analysis apparatus is determined as the target user.

(2-3) QC Process FIG. 6 is a flowchart showing the flow of the QC process performed by the management apparatus 1. In the main process, when sample data is received from any of the analyzers 2, the management apparatus 1 performs the following QC process. That is, the sample data including the newly received sample data is aggregated, and each analysis apparatus web page is updated based on the new aggregation result.
In step S31, the processing unit 12 aggregates the sample data including the newly received sample data. There are many cases where a plurality of quality control substances are used for the same measurement item, such as high and low values, and normal and abnormal values. Further, when the quality control substance is a biological component, the lot number is usually different for each production lot, that is, for each production time. Furthermore, in order to determine the correction value of the measured data, it is necessary to consider the measurement mode in which the sample data is measured. The type of quality control substance, lot number, measurement mode, etc. are notified from the analyzer to the management device as will be described later.

Aggregation is performed for each type of analyzer and quality control substance. Since this quality control substance may be a substance that tends to change with time, such as blood, it is aggregated every measurement day to increase the reliability of the aggregated result.
In the present invention, since the latest aggregation result is provided in real time, the total number of sample data on the measurement day is not yet sufficient at an early time in the morning, and the reliability of the aggregation result may not be maintained. Therefore, the totaling on the measurement day is performed based on, for example, sample data received within the past 24 hours. As a result, it is possible to use sample data of measurement conditions with the same temporal change, and it is possible to prevent the total number from fluctuating significantly depending on the time zone. At the time when the date changes, the counting results within the past 24 hours are fixed as the counting results for the day.

Similarly, in order to increase the reliability of the tabulation results, it is preferable to use the 3SD iterative cutting method and exclude extreme outliers from the tabulation targets. Further, when the average value of the sample data is used as the totalization result and the sample data within 24 hours is too small, the median value may be used instead of the average value.
In step S <b> 32, the processing unit 12 updates each analyzer web page based on the new tabulation result. Thereafter, the process returns to the main process to disconnect the user terminal.

Note that the timing of updating the aggregation result is not limited to when the sample data is received, and may be any timing that can provide the latest aggregation result to the analyzer. For example, it is also conceivable to update the counting result when an access to the web page occurs from the analysis device. Further, the total result may be updated at a predetermined time interval in consideration of the burden on the management apparatus.
(2-4) Other processes In addition to the main process, the support process, and the QC process, the management apparatus 1 performs other processes.

For example, when a web page is accessed from a WWW browser on the analysis apparatus, the WWW server 16 provides the web page. At this time, it is preferable to perform the authentication processing of the analyzer in the form of an interface program such as a library or CGI.
Further, the processing unit 12 displays the error history accumulated in the user management DB 14 in response to an instruction from the operator of the management apparatus 1.
(3) Flow of processing in analyzer FIG. 7 is a flowchart showing an example of the flow of main processing performed by the analyzer. The analysis apparatus 2 transmits error information and sample data in real time, and operation information other than error information at the end of the operation of the apparatus. FIG. 7 shows only the processing flow according to the present invention. When the analyzer is started, the following processing is started.

In step S41, the control unit 28 monitors the operation status of the analysis unit 21 and determines whether error information has occurred. If YES is determined, the process proceeds to step S42. If determined No, the process proceeds to step S44 described later.
In step S42, the control unit 28 acquires error information from the analysis unit 21 and processes it into e-mail data. For example, an e-mail is created by writing the authentication information and error information of the analyzer into the body of the e-mail.
In step S43, the control unit 28 activates the email unit 24 and transmits the created email. Thereafter, the process returns to step S41.

In step S44, the control unit 28 determines whether measurement of sample data is performed. If YES is determined, the process proceeds to step S45. If determined No, the process proceeds to step S48 described later.
In step S45, the control unit 28 waits for the end of measurement, and when it ends, the process proceeds to step S46.
In step S46, the control unit 28 acquires sample data from the analysis unit 21 and processes it into e-mail data. For example, the authentication information of the analyzer is written in the body of the email and an email is created with sample data attached as an attached file. In the attached file, other data necessary for collecting the sample data is also written. For example, a lot number, a quality control substance type, a measurement mode, and an apparatus ID are listed. The device ID is identification information for specifying an analysis device on this system, and is used to prevent sample data from being counted repeatedly.

In step S47, the control unit 28 activates the email unit 24 and transmits the created email.
In step S <b> 48, the control unit 28 stands by for operation information other than error information indicating the operation status of the analysis unit 21. The operation information other than the error information includes the number of operations, an operation program, setting conditions, and the like. When the operation information is generated, the process proceeds to step S52. In other cases, the process returns to step S41.
In step S49, the control unit 28 stores the generated operation information in a log.

In step S50, the control unit 28 determines whether or not the end of the analyzer 1 is instructed. If the determination is Yes, the control unit 28 proceeds to step S49. If determined No, the process proceeds to step S51 described later.
In step S51, the control unit 28 acquires operation information from the log and processes it into e-mail data. For example, an e-mail is created in which authentication information and operation information of the analysis device are written in the body of the e-mail.
In step S52, the control unit 28 activates the email unit 24 and transmits the created email. Thereafter, the control unit 28 ends the process.

[Specific example of operation information accumulated in history DB by support processing]
Next, the operation information accumulated in the user management DB 14 by the above-described support process will be specifically described. 8 to 11 are examples of operation information displayed on the management device 1 when a blood analyzer is used as the analyzer 2. 8 shows an operation information selection screen, FIG. 9 shows an error history, FIG. 10 shows a program history, and FIG. 11 shows a display example of the number of operations.
The operation information selection screen in FIG. 8 accepts selection of any of operation information of error history, program history, setting, and number of operations. Further, the operator can specify the analyzer and the type of the analyzer on this screen.

      FIG. 9 is an example of a screen displayed when “error history” is selected on the screen of FIG. An error date and time, an error message indicating the content of the error, an error code identifying the error, and detailed codes 1 and 2 are displayed. In this error history, for example, the latest one month of the error history stored in the history DB is displayed. It is preferable that sorting and filtering can be set for each field. In addition, it is preferable to display an abnormal record that is likely to cause trouble in a distinguishable manner by reverse display or the like. An abnormal record is, for example, a record in which the error level described above is a predetermined value or more.

FIG. 10 is an example of a screen displayed when “Program history” is selected on the screen of FIG. In this screen example, the name of the program operating on the designated analyzer, its version, the date and time of operation are displayed.
FIG. 11 is an example of a screen displayed when “number of operations” is selected on the screen of FIG. In this screen example, the number of operations of a predetermined part of the analyzer is displayed together with the date and time of operation.
Although not shown, when “Setting” is selected on the selection screen of FIG. 8, the setting conditions of the analyzer are displayed.

[Specific examples of web pages created by QC processing]
Next, a specific example of a web page created by the management apparatus 1 by the above-described QC process will be described. 14 and 15 are examples of display examples of web pages created by the processing unit 12. These are display examples of the counting results when the quality control substances are tabulated using the blood analyzer as described above.
When the management apparatus 1 is accessed with a WWW browser on the analysis apparatus, a window shown in the upper half of FIG. 14 is displayed. In this window, the display style of the total result can be selected. Here, when the SDI chart is selected as “Reporting style”, the window illustrated in FIG. 15 is displayed.

      In FIG. 15, a predetermined graph is displayed for each component in the blood. This graph is created for each type of analyzer and each quality control substance. This graph can display the sample data and reference device data of the access source user measured every day for the past month. The reference device data is sample data obtained by measuring a predetermined quality control substance with an analyzer on the provider side of the remote support system. Further, the degree of deviation from the average value is shown for each SD in the graph. The daily count results are finalized when the date changes.

      When viewed as internal accuracy management, by displaying these measured values as they are, it is possible to check the fluctuation of the sample data in the analyzer. Further, when viewed as external precision management, as shown in FIG. 15, it is possible to check the fluctuation of the sample data in the analyzer with respect to the overall average value with the overall average value at the time of sample data measurement as the center. By arbitrarily switching the display, the user can visually compare on the web page how much the sample data of the analyzer is deviated from the overall average or the reference data. Moreover, the web pages of FIGS. 14 and 15 are updated immediately after providing sample data. Therefore, the user can perform external accuracy management on the provided sample data in real time without a time lag.

FIG. 16 is another display example of the tabulation results of quality control substances. In this example, the measurement value of the user's analyzer, the overall average value, and the reference device data are directly displayed. Since the user may want to directly compare the measured value of his / her analyzer with the overall average value and the reference data, it is also preferable that each value displayed as a chart in FIG. 15 can be directly displayed. .
<Another embodiment>
(A) FIGS. 17 and 18 are diagrams showing another configuration example of the remote support system. The network connecting the user terminal and the management apparatus is not necessarily a dedicated network, and may be the Internet or a LAN, for example. However, when using the Internet, encryption and a stricter authentication system are required to enhance the security of information transmitted and received.

There is no need for one management device on the system. For example, different dedicated networks may be connected to the Internet and a router or gateway, and a management device may be provided for each dedicated network. Further, the management device is provided with a predetermined value from an analysis device outside the dedicated network, for example, an analysis device on the Internet connected to the dedicated network via a router or an analysis device connected to the LAN from the Internet via a firewall. It is also possible to collect information.
(B) In the first embodiment, the time difference between the management device 1 and the analysis device 2 and the time difference between the analysis devices are not taken into account when performing the QC process. Therefore, as a second embodiment, QC processing in a remote support system in which a management device and an analysis device exist in different time zones will be described.

(B-1) System operation Sample data is aggregated as follows. Similar to the first embodiment, data measured during the past 48 hours are totaled, and the result is used as a real-time totaling result. In addition, the aggregation result for each date is calculated by aggregating data measured on the previous day among the data within the past 48 hours.
In order to make it easy for the operator of the analyzer of each time zone to confirm the total result, the total result is expressed in correspondence with the time (local time) in the time zone.

However, if the reference time for counting is set to the local time, the reference time differs for each time zone, so the counting must be performed for each time zone. For this reason, 24 types of tabulation results for the same date are generated all over the world, which complicates the operation of the system. This is especially true when there are multiple time zones in one country, or when there are group hospitals across multiple time zones.
On the other hand, regardless of the local time, if the reference time for aggregation is determined based on the time in any time zone, the difference between the local time and the reference time becomes a problem. For example, the date of the QC process changes during measurement of the analyzer, causing confusion.

Therefore, based on the same measurement date (local time) of sample data in each time zone, that is, sample data having the same measurement date so that the total result of one day becomes the same result in any time zone Based on the result, the total result of the day is calculated.
(B-2) Basic In consideration of the above points, in the present embodiment, the reference time of the management apparatus 1 is set to the most advanced time on the earth, that is, GMT (Greenwich Mean Time) +12: 00. In the following description, the time reference is the time of the time zone in which the management apparatus 1 is located, in this case GMT + 12: 00. Each analysis device 2 transmits the measurement date and time in the time zone in which it is located to the management device 1 together with the sample data. The management apparatus 1 aggregates sample data based on sample data having measurement dates and times within the past 48 hours. The reason why the sample data is aggregated within 48 hours instead of within the past 24 hours is to secure a certain total number N of sample data as a basis of aggregation.

      FIG. 19 is a conceptual configuration diagram of data transmitted from the analysis device 2 to the management device 1. This data includes lot number, quality control substance type, measurement mode, device ID, time zone, time, and sample data. Of these, data other than the time zone and time are the same as in the first embodiment. In the time zone, the time zone where the analyzer 2 is located is described. The time describes the measurement date and time in the time zone where each analyzer is located. The management device 1 performs QC processing, which will be described later, based on sample data having a measurement date and time within 48 hours from the time in the time zone where the management device is located.

FIG. 20A is an explanatory diagram showing that the total number N of data cannot be sufficiently secured with the sample data within the past 24 hours. For ease of explanation, it is assumed that analyzers A, B, C, D, and E located in different time zones send sample data to the management device at 0:00 every day. The analyzer A is at the position GMT + 12: 00, the analyzer E is at the position GMT-12: 00, and the other analyzers B, C, D are in the middle. The management device is at GMT + 12: 00.
In FIG. 20, sample data of date _x is represented as A _x and B _x . For example, A ₁ , A _2, and A ₃ are sample data of the analyzer A for 1 day, 2 days, and 3 days, respectively. Black circles are sample data that has already been measured, and white circles are sample data that has not yet been measured.

Now, when the time of the management device is 3:00 on the third day (time T1), the sample data within the past 24 hours includes A ₂ , B ₂ , C ₂ , D ₂ , E ₂ . However, when it becomes time T2 has elapsed some time, is that in a sample data within the last 24 hours, data in the area of a triangle shown by oblique lines in the figure, i.e. becomes only A _3. In this case, the possibility that the sample data is not aggregated increases as the time zone moves away from GMT + 12: 00, and the total number N cannot be sufficiently secured, and it is difficult to always provide reliable aggregation results.

FIG. 20B is an explanatory diagram showing that the total number N is sufficiently secured based on the sample data within the past 48 hours. At the time when the time of the management device becomes 3:00 (time T1) on the 3rd, sample data within the past 48 hours includes sample data (A ₁ , B) of the _1st and 2nd dates of the analysis devices A to E. ₁ , C ₁ , D ₁ , E ₁ ; A ₂ , B ₂ , C ₂ , D ₂ , E ₂ ). Then, when a little time has passed and the time T2 is reached, the data in the trapezoidal area indicated by the diagonal lines in the figure, that is, A ₂ , B ₂ , C ₂ , D ₂ , E ₂ , A ₃ are populations for aggregation. It becomes. Actually, although the measurement time differs for each analyzer, the sample data within the last 48 hours is used as the aggregate population, so that the number of sample data close to the number of all analyzers in the system is always secured. It becomes possible to do. If there are a plurality of sample data of the same analyzer in the population, the sample data other than the latest sample data may be excluded.

Note that the reference time of the management device is not limited to GMT + 12: 00. It is possible to make the totaling time longer than 48 hours instead of 48 hours, or a little shorter, but 48 hours is convenient for system operation.
(B-3) Process Flow The process performed by the management apparatus 1 according to the present embodiment is the same as the first embodiment except for the QC process subroutine (step S8 in FIG. 4) performed after receiving sample data. It is. Therefore, the QC process in the present embodiment will be described in detail below. The QC process of the present embodiment is roughly divided into (1) today's total process and (2) previous day's total process.

(B-3-1) Conceptual Explanation of Today Aggregation Processing FIG. 21A is a conceptual explanatory diagram of today aggregation processing. In today's totalization process, a first temporary population composed of sample data having dates within the past 48 hours is sequentially created based on the time of the management apparatus 1. Further, sample data is aggregated based on the first provisional population to be created, and today's aggregation result is updated. In this embodiment, the first temporary population is updated and counted every 10 minutes.
In FIG. 21 (a-1), a trapezoidal area S0 indicated by hatching indicates the first temporary population at the current time T1 (2nd, 18:00). As time passes, the trapezoidal region S0 moves to the right side in the figure. That is, the first temporary population is updated. As the first temporary population is updated, the totaling results for today (2nd) are also updated.

At the time T2 (3rd 00:00:00) when the date has changed from the 2nd to the 3rd after a lapse of time, the previous day aggregation process for determining the aggregation result of the 2nd date is started. In the diagram (a-2), the trapezoidal area indicated by hatching, that is, the sum of the area S1 and the area S2 ′ represents the first temporary population at time T2. A region S1 represents a set of sample data for one date, and a region S2 ′ represents a set of sample data for two dates obtained at this time.
Even if the previous day aggregation process is activated, today's aggregation process is continued as described above. In today's totaling process, the totaling result for today (3rd) is updated at a predetermined timing.

(B-3-2) Conceptual description of the previous day totaling process FIG. 21B is a conceptual explanatory diagram of the previous day totaling process. When this process is started at 3:00 on 3rd, the management device 1 creates a second temporary population. The management device 1 updates the second temporary population every 10 minutes, and updates the aggregation result of the previous day (2 days) based on the updated second temporary population.
The creation and update of the second temporary population is performed as follows. The management device 1 creates a second temporary population consisting of sample data within the last 48 hours every 10 minutes. As the time elapses from T2 (3rd 00:00), the sample data of today's date (3rd date) measured in the area with the earlier time zone is deleted from the created second temporary population.

      FIG. 21 (b-1) shows the second temporary population at time T3 (3rd 10:00) after 10 hours have elapsed from time T2. The area S1 ′ is a set of data having a measurement time within 48 hours from the time T3 in the set of one-day sample data. The region S2 ′ is a set of data that has already been measured and is sample data with a measurement date of 2 days. Region S3 ′ is sample data of the 3rd date deleted from the second temporary population among the sample data within the past 48 hours from time T3. At time T3, the management apparatus calculates the aggregation result of the previous day (2 days) based on the sample data of the area S1 ′ and the area S2 ′.

FIG. 21B-2 shows the second temporary population at time T4 (4th 00:00:00) after 24 hours have elapsed from time T2. A hatched region S2 represents the second temporary population at this time. The second temporary population at this point is a set of 2-date sample data from all analyzers participating in the remote support system. At this time, the management apparatus 1 determines a population for aggregation of the previous day (2 days). And let the total result obtained from this population be the final total result of the previous day (2 days).
(B-4) Flowchart In the present embodiment, the management device 1 independently performs three of the collection process, the today count process, and the previous day count process as the QC process.

(B-4-1) Collection Processing FIG. 22 shows sample data collection processing performed by the management apparatus 1. This process is started by moving to step S8 (QC process subroutine) in the main process (FIG. 4) performed by the management apparatus 1. That is, in this embodiment, the management device 1 accumulates data in a base DB (not shown) every time sample data is received. In this base DB, sample data received by the management apparatus 1 is accumulated without being deleted.

(B-4-2) Today Aggregation Processing FIG. 23 is a flowchart showing the flow of today aggregation processing performed by the management device 1. In the following description, the work area for forming the first temporary population that is the basis of the today aggregation process is defined as buffer 1.
Steps S101 and S102: The management apparatus 1 determines whether or not the date has changed (S101), and if it has changed, activates the previous day aggregation process (S102) (see FIG. 21A-2).

Steps S103, S104, S105, S106: The management apparatus 1 determines whether or not a predetermined time, that is, 10 minutes has elapsed since the previous aggregation (S103). If not, the process returns to step S101 again without performing aggregation. If it has elapsed, the first temporary population is updated, and today's aggregation is updated.
Specifically, first, sample data having a date and time within the past 48 hours is acquired from the base DB and stored in the buffer 1 (S104). Next, it is determined whether or not data from the same analyzer is duplicated in the data stored in the buffer 1 (S105). If there is any data other than the latest data, it is excluded from the buffer 1 (S106). (See FIG. 21 (a-1)).

Step S107: The management apparatus 1 performs aggregation based on the updated first temporary population. This total result is the current total result at this point.
The above processing is performed independently of the sample data collection processing, and the current totaling result is updated every 10 minutes based on the sample data having the date and time within the past 48 hours.
(B-4-2) Previous Day Aggregation Process FIG. 24 is a flowchart showing the flow of the previous day aggregation process performed by the management apparatus 1. In the following description, the work area for forming the second temporary population that is the basis of the previous day aggregation processing is referred to as buffer 2. By shifting to the step S102 of the today counting process, the following process is started. Now, as in FIG. 21, it is assumed that this processing is started at time T2 (3rd 00:00).

Step S111: The management apparatus 1 determines whether or not the date has been changed again. If the date has not changed, the management apparatus 1 performs the processing from step S112 onward. That is, the second temporary population is updated and the total is updated until the time changes from 3:00:00 to 4:00:00 (S112 to S117 described later). When the time is 4:00 on the 4th, the aggregation result is confirmed two days before, that is, two days (steps S118 to S120 described later).
Step S112: The management apparatus 1 determines whether or not 10 minutes have elapsed since the previous aggregation. If it determines Yes, it will transfer to step S113 and will update the 2nd temporary population. If determined No, the process returns to step S111 again without updating the temporary population.

      Steps S113, S114, S115, S116: The management apparatus 1 acquires sample data having a time within the past 48 hours from the base DB and stores it in the buffer 2 (S113). Next, the management device 1 deletes the data dated today (date 3) from the acquired sample data (S114). Next, it is determined whether or not data from the same analyzer is duplicated in the data stored in the buffer 2 (S115). If there is any data other than the latest data, it is excluded from the buffer 1 (S116). As a result, the second temporary population is updated (see FIG. 21B-1).

Step S117: The management device 1 newly calculates the aggregation result of the previous day, that is, two days, based on the updated second temporary population. As described above, the count result for 2 days (the previous day) is updated every 10 minutes (S112 to S117).
Step S118: When it is determined that the date has changed in Step S111, that is, when the time is 4th, 0:00, the management device 1 determines the population that is the basis of the total result of 2 days. In other words, the second temporary population at this point is set as the population for the tabulation result of the previous day (2 days). The confirmed population includes only sample data for two dates (see FIG. 21 (b-2)).

Step S119: The management device 1 calculates the total result of the previous day (2 days) based on the confirmed population (S119).
The display of the web page on which the counting result is posted is executed based on the authentication information input from the analysis apparatus. Furthermore, when displaying a web page, the management apparatus 1 recognizes the time zone of the analysis apparatus. This is because the date in which the local time in the time zone is different from GMT + 12: 00, that is, the local time is not yet the date. In this case, the management apparatus 1 does not display today's aggregation results at GMT + 12: 00, but displays only the aggregation results of the previous day aggregation processing.

      Through the above processing, based on sample data collected from analyzers existing in various parts of the world, today's tabulation results are updated sequentially in today's tabulation processing, and the previous day's tabulation results are updated in the previous day tabulation processing. In addition, the totaling result for each day is finally determined by the totaling process on the previous day. Aggregation is performed based on a certain number of sample data or more, so the reliability of the aggregation results can be improved. In addition, since the sample data measured in each time zone is reflected in the total result of the day, the user can use this system without feeling a time difference.

(C) The recording medium on which the program of the present invention as described above is recorded is included in the present invention. Here, as the recording medium, a computer readable / writable flexible disk, hard disk, semiconductor memory, CD-ROM, DVD, magneto-optical disk (MO), and the like can be assumed.
(D) The transmission medium for transmitting the program of the present invention as described above is also included in the present invention. Here, the transmission medium includes a communication medium (optical fiber, wireless line, etc.) in a computer network (LAN, Internet, wireless communication network) system for propagating and supplying program information as a carrier wave.

1 is an example of an overall configuration diagram of a remote support system according to a first embodiment. The block diagram which shows a function structure. An example of the flow of processing in a remote support system. The flowchart which shows an example of the flow of the main process which a management apparatus performs. The flowchart which shows an example of the flow of the support process which a management apparatus performs. The flowchart which shows an example of the flow of QC process which a management apparatus performs. The flowchart which shows an example of the flow of the main process which an analyzer performs. An example of an error information selection screen. Error history display example. Example of program history display. Display example of the number of operations. An example of an error judgment pattern. An example of an error determination table. A display example (menu screen) of a web page created by QC processing. The example of a web page created by QC processing (aggregation result). Another display example (total result) of a web page created by QC processing. The example of whole structure of the remote support system which concerns on other example embodiments. The example of whole structure of the remote support system which concerns on other example embodiments. The conceptual block diagram of the data sent to a management apparatus from an analyzer. (A) When the past 24 hours are to be counted. (B) When the past 48 hours are to be counted. (A) The concept explanatory drawing of today totaling processing. (B) Conceptual explanatory diagram of the previous day aggregation process. The flowchart which shows an example of the flow of a collection process. The flowchart which shows an example of the flow of today total process. The flowchart which shows an example of the flow of an aggregation process on the previous day.

Explanation of symbols

1; management device 2; analysis device 3; network

Claims (5)

An analyzer for clinical testing that can be connected to a management device installed outside the facility via a network,
Analytical means for measuring the sample in the container;
Transmitting means for transmitting predetermined information to the management apparatus via a network;
Means for reading a barcode having identification information of a sample attached to the container;
Read the barcode to determine whether the sample is a quality control material. If the sample is a quality control material, the sample data obtained by the analysis means measuring the quality control material, the lot number of the quality control material, and the accuracy Control that controls the transmission means to create an e-mail that includes the type of controlled substance, measurement mode, and device identification information, and in which the authentication information of the analyzer is written in the text, and to send the created e-mail to the management device and means, the,
The sample data received by the control device is aggregated for each clinical laboratory analyzer and each quality control substance, and statistical processing is performed to obtain the overall average and standard deviation for each analyzer and quality control substance, and a quality control result is created. An analytical device for clinical testing that is a management device . 2. The clinical analyzer according to claim 1, wherein the e-mail is attached with sample data, quality control substance lot number, quality control substance type, measurement mode and apparatus identification information as an attached file. Email history information including showing the operation history analysis section, a clinical test analyzer according to claim 1 or claim 2. E-mail, authentication information and history information of the analyzer in the body is the write Mareta email, clinical test analyzer according to claim 3. A sample data transmission method for transmitting sample data obtained by measuring quality control substances from an analysis device via a network to a management device installed outside a facility,
A reading means reading a barcode having identification information of the sample attached to the container;
An analyzing means measuring a sample in the container;
A step of determining whether or not the sample is a quality control substance based on the identification information of the barcode;
If the sample is a quality control substance, including sample data analyzing means is obtained by measuring the quality control substance, the lot number of the quality control material, the kind of quality control substance, the identification information of the measurement mode and system, and Text A step of creating an e-mail in which authentication information of the analyzer is written in the control means;
When the sample is a quality control substance, the sample data obtained by measuring the quality control substance, the lot number of the quality control substance, the type of the quality control substance, the measurement mode, and the identification information of the apparatus are included in the main text. A step for the control means to create an e-mail in which the authentication information is written ;
A transmission means comprising transmitting the created e-mail to a management device via a network ; and
The sample data received by the control device is aggregated for each clinical laboratory analyzer and each quality control substance, and statistical processing is performed to obtain the overall average and standard deviation for each analyzer and quality control substance, and a quality control result is created. A sample data transmission method , which is a management device .

Images