JP2012022374A - Clinical test data processing system - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide a highly-accurate clinical test data processing system capable of determining the presence or absence of an abnormal value from test result data based on a stable reference range.SOLUTION: A clinical test data processing system that includes a server which comprises: data collection means for collecting test result data of multiple test subjects tested in multiple medical institutions, and reference range data adopted in the medical institutions and used for determining the presence or absence of an abnormal value in the test result data; reference range setting means for setting a new reference range based on the whole of the collected test result data; and determination means for generating determination data obtained by newly determining the presence or absence of an abnormal value for the test subjects based on the newly set reference range.

Description

  The present invention relates to a clinical test data processing system that determines the presence or absence of abnormal values based on a predetermined reference range for a plurality of test items from test result data obtained by a clinical test.

  A clinical examination of a sample collected or acquired in a health examination or the like that is regularly performed is performed by a medical institution or a contractor (examination institution) of the medical institution. The term “clinical test” as used herein includes a sample test for performing a test for the presence or absence of a component analysis or a microbial analysis on a test object obtained from a human body.

Usually, in clinical examinations, in order to determine whether the test result data is normal or abnormal for a plurality of test items, a numerical range called a reference range is preset, and the doctor in charge of the clinical test Judgment is made for each inspection item using the reference range as a rule.

The setting of the reference range is statistically defined as a range that conventionally includes about 95% excluding the upper and lower 2.5% of the healthy population. Ideally, this standard range should be common to all medical institutions and inspection institutions (hereinafter referred to as “medical institutions, etc.”), but technical factors (new inspection items and inspection methods are not available). It is being developed one after another, accuracy adjustment values differ depending on the testing equipment and reagents used, etc., and environmental / physiological factors (populations and specimens used in the above statistical definitions are determined by each medical institution, etc.) Because of differences, differences in the attributes of patients to be examined, and time-series changes in health status, etc., it is important not only for medical institutions etc. but also for external external quality control. In particular, in external accuracy management, it is difficult to set a uniform reference range, and therefore many methods have been proposed to replace the unified standard.

For example, the distribution type for each inspection item is specified in advance, and for each inspection item, the average value and standard deviation of the inspection value (target inspection value) to be compared are obtained, and the inspection value to be converted (the inspection value before conversion) By obtaining the deviation value and obtaining the value of the target inspection value that is the same deviation value as this deviation value from the distribution type, the inspection value before conversion can be compared within the reference range of the target inspection value. An inspection value conversion program has been proposed (see, for example, Patent Document 1).

JP 2009-176023 A

  In the above prior art, the distribution type of test values is focused on the fact that it is not affected by differences in test equipment, reagents used, etc., but the target to be compared is a specific test value (target test value). In other words, there is a problem that it cannot be said that it can realize external precision management with a plurality of, in other words, a unified standard range at the national level. For example, when the distribution type of the target inspection value is formed by a certain biased population, conversion by comparison of distribution types may cause a large error when viewed at the national level. Therefore, in the case of the above prior art, the selection of the target inspection value is very important, but no conditions are described regarding the selection of the target inspection value, and as a result, it may not be possible to provide a stable reference range. There was sex.

On the other hand, as one of the reliable methods to unify the reference range, it is conceivable that all medical institutions conducting clinical examinations use the same testing equipment and the same reagents. I can't say that.

Therefore, in the present invention, it is determined whether there is an abnormal value from the test result data based on a highly accurate and stable reference range without changing the existing test equipment of each medical institution and the reagent used. It is an object of the present invention to provide a clinical test data processing system that can be used.

  The present invention relates to a clinical test data processing system for determining the presence or absence of abnormal values based on a predetermined reference range for a plurality of test items from test result data obtained by a sample obtained and collected from a medical examination subject by a medical institution The test result data of a plurality of examination subjects examined at a plurality of the medical institutions, and each reference range adopted by each of the medical institutions and used to determine the presence or absence of an abnormal value of each test result data Data collection means for collecting data, reference range setting means for setting a new reference range from the entire collected test result data, and a plurality of examination subjects based on the newly set reference range On the other hand, the main feature is to have a server including a determination unit that generates determination data for newly determining the presence or absence of an abnormal value.

According to this configuration, it is possible to set a new uniform reference range from a plurality of test result data based on different test devices and reagents used, and determine the presence or absence of an abnormal value based on this reference range. .

The data collection means is configured so that the server receives each test result data and reference range data adopted by each medical institution from a communication terminal of each medical institution via a communication network such as the Internet. What is necessary is just to comprise.

  The server includes, in advance, medical institution data in which identification data of each medical institution, location data, schedule data indicating date and time of examination, and the reference range data are associated with each other, identification data of a person to be examined, and the communication network Storage means for storing contact data that can be communicated via the network and the attribute data of the subject of examination, and a communication terminal of the subject of examination via the communication network When reservation data for requesting a clinical examination is received, medical institution data that matches the conditions described in the reservation data is read from the medical institution data to identify the medical institution, and the communication of this medical institution The terminal is notified that the clinical examination of the examination subject has been reserved, and the communication terminal of the examination subject is sent to the identified medical institution. It may have a transmission means for notifying that the reservation is complete.

  In addition, the server transmits, to the communication terminal of the examination subject, reference range data adopted by the medical institution, test result data, and individual determination data in which the presence or absence of an abnormal value is determined by the medical institution, The determination data generated by the determination unit may be transmitted. According to this configuration, the screening subject can receive the determination by the medical institution that has undergone the screening, the determination based on the unified reference range, and two determination results.

The reference range setting means has a plurality of reference range calculation means, and automatically selects a calculation means for setting a new reference range according to the total number of inspection result data collected for each inspection item. May be. For example, as the calculation method of the reference range, when the number of data of the inspection result data is 300 or more, the non-parametric percentile method is selected, and when the number of data is 150 or more and less than 300, the probability paper method is selected. When the number of data is 80 or more and less than 150, an iterative cutting method may be selected.

  The determination means uses the inspection result data collected by the data collection means and the upper limit data and lower limit data of each reference range data corresponding to each inspection result data as explanatory variables, the individual determination data as an objective variable, The presence / absence of an abnormal value may be determined from the explanatory variable and the objective variable by discriminant analysis.

  According to this configuration, since the upper limit data and the lower limit data of the reference range are included as explanatory variables, it is possible to determine the presence or absence of an abnormal value from the entire collected data in consideration of variations in each reference range. .

  The data collection means may collect examination result data and reference range data for each attribute based on attribute data registered as examination subject data from the communication terminal of the examination subject. According to this configuration, it is possible to set a new reference range for each attribute.

  The storage means stores history data composed of test result data and determination data of each examination subject who has undergone a plurality of examinations, and there is a request for browsing progress data from the communication terminal of the examination subject. The history data generated by the configuration that can compare the history data by age or age of the examination subject with the average data by age or age of all test result data stored in the storage means You may make it provide to the communication terminal of a medical checkup subject. According to this configuration, it is possible to observe the progress data of the examination subject on a new unified reference range basis.

  The clinical test data processing system according to the present invention is based on a highly accurate and stable reference range without changing the existing test equipment such as each medical institution and the reagent used. There is an effect that it is possible to determine the presence or absence of a value.

FIG. 1 is a block diagram of a server constituting a clinical test data processing system according to the present invention. FIG. 2 is a diagram showing a reservation process sequence in the clinical test data processing system according to the present invention. FIG. 3A is a diagram showing an example of a medical institution data table, and FIG. 3B is a diagram showing an example of a screening subject person data table. FIG. 4 is a diagram showing a determination processing flow in the clinical test data processing system according to the present invention. FIG. 5 is a diagram showing an example of a test result table output by the clinical test data processing system according to the present invention. FIG. 6 is a diagram showing a progress result table output from the clinical test data processing system according to the present invention. FIG. 7 (a) is a diagram showing discriminant analysis data, (b) is a diagram showing regression statistics, (c) is a diagram showing an analysis of variance table, and (d) is a linear discriminant. It is a figure which shows a formula calculation table | surface, (e) is a figure which shows a discrimination | determination result table | surface.

  Referring to FIG. 1, reference numeral 1 denotes a server constituting the clinical test data processing system according to the present invention. The server 1 can transmit and receive data to and from a communication terminal M of a medical examination subject and a communication terminal H of a medical institution such as a hospital via a communication network such as the Internet (hereinafter referred to as “communication network”). The server 1 mainly performs a reservation processing unit 11 that performs a reservation process for a clinical examination consultation request to a medical institution that performs a clinical examination from the communication terminal M of the examination subject and a data process that performs a determination based on the examination result data. It consists of two parts 12.

The reservation processing unit 11 is for promoting the collection of data required for performing statistical processing in the clinical test data processing according to the present invention. That is, in the present invention, as described later, it is necessary to collect test result data and corresponding reference range data from all over the country. Current clinical examinations are carried out within each medical institution or at an institution outsourced by a medical institution. In clinical tests, the normal range of test values is generally the range that includes statistically 95% of the healthy population (excluding extremely high values of 2.5% and low values of 2.5%). However, since this healthy population is calculated from a sample with the number of specimens handled by the medical institution (or laboratory) as a population, each test value of this population is a predetermined value. If it is unevenly distributed in the range, the reference range also varies. As a result, even if the test result data (that is, the numerical data obtained as a result of the test) is the same, the determination of the presence or absence of an abnormal value may differ depending on the reference range adopted by the medical institution performing the test. Therefore, in the system according to the present invention, in order to collect test value data from all over the country as much as possible, the server 1 is configured to perform clinical test reservation processing in an integrated manner. In this specification, “clinical test” includes “specimen test”.

The reservation processing unit 11 includes a storage unit 111 that stores medical institution data and examination subject data. FIG. 3 exemplarily shows a table of data registered in the storage unit 111. 3A is a table D1 of medical institution data, and FIG. 3B is a table D2 of examination subject data. The table D1 includes hospital ID number data D11, hospital name data D12, location data D13, schedule data D14, and reference range data D15 to D17 of each examination item adopted by the medical institution. The location data D13 displays the address in the table D1, but may be linked to the location map data together with the address. This is because this map data is also transmitted at the time of notifying that a reservation is made to the communication terminal M of the examinee who will be described later. The reservation schedule data D14 is schedule data indicating the date and time at which a medical institution can check up, and is linked to a list or the like set separately. In the present embodiment, the reference range data D15 to D17 indicate three items, that is, WBC (white blood cell count), RBC (red blood cell count), and Hb (hemoglobin amount) because of space limitations. There are many other inspection items.

The table D2 is composed of ID number data D21, name data D22, contact data D23, gender data D24 and date of birth data D25 of the person to be examined. In the present embodiment, the contact data D23 is a mail address. However, the contact data D23 is not limited to a mail address as long as data can be transmitted / received to / from the server 1 via a communication network. Absent. In addition to the above data, the table D2 may add attribute data of the examination subject. In particular, it is desirable that there are a lot of attribute data (historical history, family medical history, race, etc.) that affect the test value as long as the subject of the examination agrees. This is because, by performing various processing performed by the data processing unit 12 for each attribute data, highly accurate clinical test data processing becomes possible.

Hereinafter, the sequence processing of the reservation processing unit 11 will be described with reference to FIGS. 1 and 2. The server 1 will memorize | store in the memory | storage part 111, if there exists registration of the said screening subject person data from the communication terminal M of a screening subject beforehand (S1). Similarly, when the medical institution data is registered from the communication terminal H of the medical institution, it is stored in the storage unit 111 (S2). When the appointment data for examination is transmitted from the communication terminal M to the server 1 (S3), the appointment data is accepted by the appointment data accepting unit 112 of the appointment processing unit 11. In addition, the reservation data is configured to be able to describe the area, date and time, and other desired items (conditions) to be examined (not shown), and the reservation data receiving unit 112 selects a medical institution that meets these conditions. It is read out from the medical institution data stored in the storage unit 111 and specified. The reservation data reception unit 112 notifies the communication terminal H of the specified medical institution that the appointment of the examination subject has been made (S4), and the notification data generation unit 113 generates notification data (date and time) This notification data is transmitted to the communication terminal M of the person to be examined to notify that the reservation has been completed (S5). After undergoing a clinical test at the medical institution that has been reserved for the subject to be examined and obtaining test result data for each test item, the server 1 performs based on the reference range adopted by this medical institution. Individual determination data about the presence or absence of abnormal values is received from the communication terminal H of the medical institution (S6). At this time, together with the individual determination data, examination result data, ID data of the person to be examined may be received together. Furthermore, in the present embodiment, the reference range adopted by each medical institution (or the contracting laboratory) is collected in advance as the registration data of the medical institution data. The reference range data may be received at the time of transmission. When the server 1 receives the individual determination data (and the reference range data of each medical institution), data can be collected by the data processing unit 12 described later. When the server 1 receives the individual determination data, the data processing unit 12 generates determination data based on a new reference range (to be described later), and the determination data generated including the individual determination data is transmitted to the examination subject. It transmits to the terminal M (S7). The determination data may be transmitted by transmitting the generated determination data and the individual determination data together in one form, or separately transmitting the determination data and the individual determination data.

By the way, in the present embodiment, data is collected for clinical examinations at the medical institution where the medical institution data is registered. However, the data collection is not limited to this form. When a medical examination is received at a medical institution where the medical institution data is not registered, at least the test value (test result data) for each item and the relevant information are obtained from the judgment results obtained from the medical institution. After the reference range data adopted by the medical institution and the individual determination data by the medical institution are transmitted from the communication terminal M of the examinee to the server 1 and the data processing unit 12 performs predetermined data processing, The determination data obtained by the data processing may be transmitted to the communication terminal M of the examination subject.

The server 1 transmits / receives data to / from the communication terminal M of the person to be examined and transmits / receives data to / from the communication terminal H of the medical institution via the transmission / reception unit 13.

Hereinafter, the processing flow of the data processing unit 12 of the server 1 will be described with reference to FIGS. 1 and 4. As described above, the examination result data of a plurality of examination subjects and the reference range data adopted by each medical institution used for determining the presence or absence of abnormal values in each examination result data are acquired from the reservation processing unit 11. The data is collected by the data collection unit 121 of the data processing unit 12 (S101). The inspection result data collected by the data collection unit 121 is subjected to processing for setting a new reference range for each inspection item by the reference range setting unit 122. The reference range is set by statistical processing as described above, but the optimum calculation method differs depending on the total number of collected inspection result data. Therefore, the reference range setting unit 122 is configured to automatically select an optimal calculation method according to the total number of collected inspection result data. In the present embodiment, when the total number of collected inspection result data for each inspection item is less than 150 (S102, Yes), the repetitive cutting method is selected (S103), and each collected inspection item is selected. When the total number of other inspection result data is 150 or more and less than 300 (S102, No, and S104, Yes), the probability paper method is selected (S105), and each collected inspection item is classified. When the total number of the inspection result data is 300 or more (S104, No), the non-parametric percentile method is selected (S106). The iterative cutting method is a method for determining statistical outliers, and is a method for determining data outside the range of the mean value ± 2SD as outliers. Even when the data is not a normal distribution, the reference range can be calculated by normalizing by a power transformation, processing the data by an iterative cutting method, and restoring the data. The probability paper method is a method for converting the distribution function F (x) into a linear function by setting the scales on the horizontal axis and the vertical axis to predetermined function scales according to the distribution type. In other words, test result data are arranged in order from the smallest numerical value, and when the far lower or upper limit is 1 or 2, this is removed, and the substantially continuous numerical range is classified into about 10 levels. When the frequency of each stage is counted, the ratio (%) to the total number is calculated, and this is plotted as a percentage on the normal probability paper. When each plot is linear between 10% and 90% (almost straight line) If it is located above), it is calculated as a normal type. When the distribution type is a lognormal type, the measurement value may be calculated after logarithmic conversion. The non-parametric percentile method is a statistical method for summary values that does not depend on the data distribution type (no assumptions are made about the distribution of the population) and does not change in any distribution type. . Note that the method of dividing the total number and the calculation method to be selected are not limited to the above three calculation methods. In addition, the reference range setting unit 122 is configured to select a calculation method based on the total number of collected inspection result data. However, the calculation method may be selected according to other criteria (for example, distribution type for each inspection item). May be selected.

When the optimum calculation method is selected by the reference range setting unit 122, a new reference range is calculated by the calculation unit 123 by the selected calculation method (S107). Based on this new reference range, the determination unit 124 determines whether or not there is an abnormal value of the inspection result data for each inspection item for each person to be examined. Here, as described above, the reference range data of each medical institution collected by the data collection unit 121 varies depending on the number of samples handled by the medical institution. Also affected by. As a result, the test result data (that is, the test value) of each person to be screened may also vary depending on the test equipment and reagents used, as well as attributes and physiological factors (such as health conditions). The examination result data of each examination subject collected by the data collection unit 121 is not determined as it is based on the calculated new reference range, but is finalized in consideration of variations in the reference range of each medical institution. It is desirable to make a judgment. Therefore, the data processing unit 12 uses the discriminant analysis unit 125 as the explanatory variables the inspection result data collected by the data collection unit 121 and the upper limit data and lower limit data of each reference range data corresponding to each inspection result data. The individual determination data is used as an objective variable, the presence / absence of an abnormal value is determined from the explanatory variable and the objective variable (S108), and determination processing is performed based on the determination result (S109). The determination unit 124 generates determination data based on the above determination process (S110), passes the generated determination data to the notification data generation unit 113 of the reservation processing unit 11, and passes through the transmission / reception unit 13 to be examined. The determination data is transmitted to the communication terminal M.

  Hereinafter, an example of determination data transmitted to the communication terminal M of the person to be examined will be described with reference to FIG. In the present embodiment, the individual determination data of the medical institution where the examination subject has undergone the clinical examination and the determination data determined based on the new reference range generated by the server 1 are stored in the same form L1. Although what was output was shown, it is not the meaning limited to this form. Further, as described above, the determination data generated by the new reference range and the individual determination data may be output in separate forms.

  The form L1 is composed of a bibliographic item column L11 in which the attributes and the like of the person to be examined are described and a display column for determination data including items L12 to L18. In the present embodiment, the bibliographic item column L11 includes items of patient ID, patient name, sex, age, sample collection date, medical institution name, and material. Of these, the patient ID, patient designation, sex, and age may be read by the data collection unit 121 from the examination subject data table D2 of the storage unit 111 of the server 1, and the medical institution name, sample collection date, and materials The data collection unit 121 may read the data included in the test result data transmitted from the communication terminal H of the medical institution to the server 1.

The display column of the judgment data includes a number field L12 indicating an item number, an examination item field L13, a display field L14 of a reference range adopted by a medical institution, an examination value field L15 of the subject of examination, and each examination value. In contrast, a medical institution determination field L16 determined individually by the medical institution based on a reference range adopted by the medical institution, a display field L17 of a new reference range (overall reference range) calculated by the server 1, It is comprised from the determination column L18 which displays the determination result based on this whole reference | standard range. Here, “L” displayed in the medical institution determination column L16 and the determination column L18 indicates that the value of the test value is lower than the reference range, and “H” is higher than the reference range of the test value. Indicates. In the present embodiment, Hb (hemoglobin amount) and Ht (hematocrit value) are determined to be “normal” in the medical institution determination column L16, but both are determined to be “L” in the determination column L18. Yes. On the other hand, K (potassium) is determined as “normal” in the medical institution determination column L16, but is determined as “H” in the determination column L18. As described above, according to the present invention, it is possible to separately indicate the same test value based on the national standard reference range in addition to the individual determination of the medical institution.

  FIG. 6 shows that when the same examination target person regularly conducts clinical examinations (for example, once a year), the server 1 stores each year's examination result data as history data, and 6 shows an example of a form of progress data that is generated based on the history data and transmitted to the communication terminal M when a request for browsing progress data is received from the communication terminal M to the server 1.

  In general, it is considered to be important for prevention to detect a change in health status from a change in test result data (test value) over time even when it is not determined as an abnormal value in a health check. However, it is not always possible to conduct clinical tests at the same medical institution every year. Also, even if the medical institutions are the same, when a medical institution outsources the inspection to an external inspection institution, it does not always outsource the same inspection institution every year. In many cases, it is difficult to have a clinical examination. Therefore, even if progress data is generated based on test result data obtained under different conditions, the change in the health condition cannot be accurately detected.

  Since the determination data generated in the present invention is determined based on a new reference range, that is, a reference range calculated by statistically processing data of examination subjects nationwide, It can provide useful data in detecting changes. The progress data Y1 in FIG. 6 shows an example of displaying the progress every year. However, the history is not intended to be limited to one year but may be displayed in less than one year or by age. The progress data Y1 is displayed in the same format so that it can be compared with each year. Taking the 2008 column as an example, it is composed of a year display column Y11, an inspection item column Y12, an inspection value column Y13, a national average column Y14, and a new reference range column Y15 calculated by the server 1. .

  The progress data Y1 stores history data composed of the examination result data and determination data of each examination subject registered in the storage unit 111 of the server 1, and the server 1 transmits the examination data from the communication terminal M of the examination subject. When there is a request for browsing the progress data Y1, the history data is read out, generated by a progress data generation unit (not shown in FIG. 1), and transmitted to the communication terminal M via the transmission / reception unit 13. .

  In the present embodiment, three years of data from 2008 to 2010 are displayed for TP (total protein), Alb (albumin), and A / G as test items. Any test value is within the reference range and is considered to be a normal value. For example, when compared with the national average value of Alb, the test subject has a test value of 0. While it has risen by 7, the national average has risen only by 0.2. Therefore, although it is within the reference range, it will be understood that it is necessary to pay attention to Alb in the future. In general, even for the same inspection item, the normal value may differ for each age. Therefore, it is desirable that the average inspection value of the average 襴 Y14 is to display a value for each age or age. Furthermore, if progress data is generated for each attribute of the person to be examined (for example, for each gender), more accurate determination is possible.

FIG. 7 illustrates an example of a process of discriminant analysis performed by the discriminant analysis unit 125 of the server 1. In discriminant analysis, when a group (group) is divided into two values (in a specific example according to the present invention, when divided into a normal value group and an abnormal value group), the correlation ratio value of both groups is calculated. The analysis is performed by determining the coefficient of a predetermined linear equation so as to maximize it. Since the position where the values (inspection values) are scattered differs depending on the group, the discriminant is specified by obtaining the coefficient so that the correlation ratio becomes maximum, and the newly input value is substituted into the discriminant. Thus, based on the sign of the calculated value, it is determined to which group the newly assigned value belongs.

FIG. 7A shows sample data of 10 test subjects for the test item γ-GTP. The test values of the test subjects are those tested at different medical institutions, and the reference ranges of the medical institutions are also different. Here, in this discriminant analysis, each test result data (test value) and the upper limit value and lower limit value of each reference range are used as explanatory variables, and individual determination data of each medical institution is used as an objective variable. In order to make it easy to refer to the analysis result, the individual determination data is converted to “0.5” when it is a normal value, and is converted to “−0.5” when it is an abnormal value. The “z” column and “discrimination result” column of the table indicate how the discrimination result differs from individual discrimination data by substituting the value of sample data into a linear discriminant described later. . P0004 and P0006 have different determination results from the individual determination data.

FIGS. 7B to 7D summarize the calculation process for obtaining the coefficients of the linear discriminant in a table. (B) shows the result of regression statistics, (c) shows the result of analysis of variance, and (d) shows the result of linear discriminant calculation. Based on the coefficient obtained in (d), the linear discriminant in the present embodiment is z = −0.018 × lower limit + 0.034 × upper limit−0.013 × inspection value−1.12 (Equation 1). (E) shows the result of discriminating the presence / absence of an abnormal value using Equation 1 from the newly collected screening result data of the screening subject. According to this table, P0012 and P0013 are different from the individual determination data in the examination subject ID.

In this embodiment, the example in which the discriminant analysis is performed using the linear discriminant as described above is shown, but the present invention is not limited to this. Therefore, for example, the discriminant analysis may be performed based on the Mahalanobis distance.

1 server
11 Reservation processing unit 12 Data processing unit 13 Transmission / reception unit 111 Storage unit 112 Reservation data reception unit 113 Notification data generation unit 121 Data collection unit 122 Reference range setting unit 123 Calculation unit 124 Determination unit 125 Discriminant analysis unit

Claims (8)

A clinical test data processing system for determining the presence or absence of an abnormal value based on a predetermined reference range for a plurality of test items from test result data obtained by a sample acquired and collected from a medical examination target by a medical institution,
Collect test result data of a plurality of examination subjects examined at a plurality of medical institutions and each reference range data adopted by each medical institution and used to determine the presence or absence of abnormal values in each test result data Based on the data collection means, the reference range setting means for setting a new reference range from the entire collected examination result data, and the newly set reference range, a new abnormality is detected for the plurality of examination subjects. A clinical test data processing system comprising a server including determination means for generating determination data for determining the presence or absence of a value.   The data collection means is performed by the server receiving each test result data and reference range data adopted by each medical institution from a communication terminal of each medical institution via a communication network. The clinical test data processing system according to claim 1, wherein:   The server includes, in advance, medical institution data in which identification data of each medical institution, location data, schedule data indicating date and time of examination, and the reference range data are associated with each other, identification data of a person to be examined, and the communication network Storage means for storing contact data that can be communicated via the network and attribute data of each examination subject, and storage means for storing the data from the communication terminal of the examination subject via the communication network When receiving reservation data for requesting a clinical examination, the medical institution data that matches the conditions described in the reservation data is read out from the medical institution data, and the medical institution is specified. The communication terminal is notified that the clinical examination of the examination subject has been reserved, and the specified medical institution is provided to the communication terminal of the examination subject. Claim 1 or claim 2 clinical test data processing system according to a sending means for notifying that the reservation is complete.   The server transmits reference range data adopted by the medical institution, test result data, and individual determination data in which the presence or absence of an abnormal value is determined by the medical institution to the communication terminal of the examination subject, and the determination The clinical test data processing system according to any one of claims 1 to 3, wherein determination data generated by the means is transmitted. The reference range setting means includes a plurality of reference range calculation means, and automatically selects a calculation means for setting a new reference range according to the total number of inspection result data collected for each inspection item. The clinical test data processing system according to any one of claims 1 to 4, wherein the system is a clinical test data processing system.   The determination means uses the inspection result data collected by the data collection means and the upper limit data and lower limit data of each reference range data corresponding to each inspection result data as explanatory variables, the individual determination data as an objective variable, The clinical test data processing system according to any one of claims 1 to 5, wherein the presence or absence of an abnormal value is determined from the explanatory variable and the objective variable by discriminant analysis.   The data collection means collects test result data and reference range data for each attribute based on attribute data registered as test subject data from the communication terminal of the subject to be examined. . The storage means stores history data composed of test result data and determination data of each examination subject who has undergone a plurality of examinations, and there is a request for browsing progress data from the communication terminal of the examination subject. The history data generated by the configuration that can compare the history data by age or age of the examination subject with the average data by age or age of all test result data stored in the storage means The clinical test data processing system according to claim 1, wherein the clinical test data processing system is provided to a communication terminal of a person to be examined.

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