JPH07124125A - Medicine prescription analyzing system - Google Patents

Abstract

PURPOSE:To output a report with excellent visibility by predicting and calculat ing concentration in blood by inputting the amount of specific medicine and the concentration in blood after prescription, and calculating and outputting the predicted value of the concentration in blood due to the increment/decrement of a prescribed amount. CONSTITUTION:A certain amount of medicine is specified at a certain interval, and the concentration in blood is measured after the lapse of a fixed period. Patient information and a prescription schedule such as the specific amount, a prescription interval are inputted by a keyboard 10, and they are written on a patient file registered on an auxiliary storage device 20. Hence, each information in the patient file is used as input data by the calculation program 32 of a main storage device 30, and predicted concentration in blood is calculated by calculating a patient estimation parameter by a Bayes least square method. When the obtained predicted concentration of medicine in blood is outside allowable concentration, the increase/decrease simulation of the concentration in blood is performed to perform the re-setting of the prescription schedule. A simulation curve is generated from the calculated data of predicted concentration in blood, and the report including a graph is outputted.

Description

Detailed Description of the Invention

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to a drug administration analysis system for analyzing the optimum dose and administration interval of a drug to be administered to a patient, and more particularly to a drug administration analysis system characterized by an output system of analysis results.

[0002]

2. Description of the Related Art Conventionally, a drug administration planning method based on Bayes' theorem has been used as a method for administering an optimal amount and interval of a drug to a patient. Bayes' theorem is
It is a theory for correcting this inference by adding new information to the inference made in advance based on known information. By using the drug administration planning method based on this Bayes' theorem, the parameter of the patient can be estimated even from the measured value of at least one point, and the optimal drug administration plan can be established. Conventionally, a drug administration planning system in which a drug administration planning method based on the Bayes' theorem is programmed and incorporated into a microcomputer has been put into practical use. Using this system, a doctor or the like can easily calculate a blood concentration predicted value of a drug, create a simulation curve, and the like simply by inputting predetermined data using a keyboard.

An outline of the processing of such a conventional drug administration plan program will be described with reference to the flowchart of FIG. First, data such as patient information such as age, weight, and height, administration schedule (administration dose, administration route, administration interval, etc.), measured values, etc. are input using a keyboard (step 100). Then, the blood concentration predicted value in the current administration schedule is calculated based on the population parameter, and a simulation curve is created (step 101). Furthermore, the Bayesian least squares method (hereinafter referred to as the Bayesian method)
Estimate the patient parameters by the method, and calculate the blood concentration predicted value based on the estimation (Step 1
02). Then, based on the calculated blood concentration predicted value,
Creation of a simulation curve (step 103) and resetting of the administration schedule (step 10)
4). The simulation curve of the blood concentration predicted value created in this way can be output from a printer or the like (step 105).

FIG. 15 shows an output example of a simulation curve.
Shown in. This example output shows a drug administration schedule of 0.25 mg / day for patients who developed side effects 4 days after admission.
It is an example of a simulation curve when it is corrected to 0.125 mg / day.

The details of the above-mentioned conventional examples are described in the document “Pharmaceuticals and Development (Volume 6) Pharmacokinetic Evaluation Method and Computer
Hirokawa Shoten, Hisashi Tanaka, Kiyoshi Yamaoka. "

[0006]

However, in the conventional drug administration planning program, input data, calculation results,
And the graph of the simulation curve shown in FIG.
It was output separately. Therefore, the report of the drug administration plan must be prepared by cutting and pasting these output sheets, which is a practical problem.

Further, since the graph of the simulation curve shown in FIG. 15 is a graph of the blood concentration predicted value, even if the drug is administered according to the administration schedule, the blood concentration will not always be as expected. It was If the blood concentration deviates from the expected value, the reliability of the drug administration plan program itself will be significantly impaired.
It was a problem.

It is an object of the present invention to solve the above problems and provide a drug administration analysis system capable of outputting a report having excellent visibility.

[0009]

In order to solve the above-mentioned problems, the drug administration analysis system of the present invention comprises (a) data on the dose of a drug administered to a patient and data on the blood concentration of the drug measured after the administration. Input means for receiving input, (b)
The storage means for storing the dose data and the blood concentration data input using the input means for each patient, and (c) the dose data and the blood concentration data of a predetermined patient are read from the storage means to read the drug When the dose data and the blood concentration data of a predetermined patient are read from the first calculating means for calculating the predicted value of the blood concentration and (d) the storage means, and the dose of the drug is reduced from these data And / or second calculation means for calculating a predicted value of the blood concentration when increased.
(E) A single sheet of blood concentration data read from the storage means, blood concentration data calculated by the first calculation means, and / or blood concentration data calculated by the second calculation means, together with patient information. Output means for outputting as a written form.

Here, the output means may output each blood concentration data as a graph having a predetermined fluctuation range.

[0011]

According to the drug administration analysis system of the present invention, the blood concentration data read from the storage means and the blood concentration data calculated by at least the first calculation means are reported together with the patient information in one sheet. It is output as a calligraphy.

The output format of these blood concentration data may be a graph having a predetermined fluctuation range.
If the graph has a fluctuation range, even if the actual blood concentration deviates from the expected value, most of the deviation can be absorbed within the fluctuation range, and the report becomes highly reliable.

[0013]

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS An embodiment of the present invention will be described below with reference to the accompanying drawings. First, the system outline of the drug administration analysis system according to the present embodiment will be described using the block diagram of FIG. The drug administration analysis system according to the present embodiment includes a keyboard 10 for inputting drug dose data and measured blood concentration data of the drug, and a patient file containing information such as drug dose data and blood concentration data. Auxiliary storage device 20 registered for each and main program 31
Main storage device 30 in which a calculation program 32 and the like are stored
It has and. Further, an output device including a display device 41 for displaying patient information, blood concentration data, etc. on a screen as one report, and a printer device 42 for printing out patient information, blood concentration data, etc. as one report. 40 and a CPU 50 that controls each of the devices 10 to 40
It has and.

Here, the keyboard 10 is used as the input means, which is a component of the present invention, and the auxiliary storage device 20 is used as the storage means.
However, the arithmetic program 32 and the CPU 50 correspond to the first and second arithmetic means, and the output device 40 corresponds to the output means.

Next, an outline of processing of the drug administration analysis system according to this embodiment will be described. The drug administration analysis system allows the operator to proceed with the process by performing necessary selection input or data input using the keyboard 10 while looking at the menu screen displayed on the display device 41. As a precondition, it is assumed that a certain amount of drug is administered to a patient in advance at certain intervals and the blood concentration of the drug is measured after a certain period of time. The administration schedule, such as drug dose and administration interval, depends on the patient's age, sex,
It should be decided empirically based on weight and other factors.

An outline of the processing of the drug administration analysis system performed under such preconditions is shown in the flowchart of FIG. From the figure, first, when the operator uses the keyboard 10 to input patient information such as name, sex, age, and disease history, and an administration schedule such as dose and administration interval, the system accepts these information. (Step 6
0). Each received information is written in the patient file of the target patient registered in the auxiliary storage device 20. The target patient is usually specified by inputting the ID number of the target patient, but may be input by inputting the name, age, hospital name, reception date, and reception number of the target patient.

Next, the patient file of the target patient is read from the auxiliary storage device 20, and Bayesian estimation processing is performed by using each information of this patient file as input data (step 61). In this process, first, a patient estimation parameter is calculated using the Bayesian method, and a predicted blood concentration is calculated using this patient estimation parameter as a parameter. Specifically, the arithmetic program 32 of the main storage device 30
Done by. It is assumed that the patient estimation parameters obtained by this processing are classified and written for each predetermined layer of the population parameter file stored in the auxiliary storage device 20. Hierarchies are formed by, for example, the administration of valproic acid, classified according to around 18 years old and whether or not other antiepileptic drugs are used in combination.

When the predicted blood concentration of the drug obtained by the Bayesian estimation is out of the allowable concentration (step 62), it is necessary to reset the administration schedule. When resetting, a blood concentration increase / decrease simulation is performed (step 63). The increase / decrease simulation process is the same process as the Bayesian estimation performed in step 61, which is performed by receiving data such as the target value of blood concentration and the calculation mode input by the operator using the keyboard 10.

A simulation curve is created from the data of the predicted blood concentration calculated in this way (step 6).
4) The report including the graph of the simulation curve is output to the display device 41 or the printer device 42 (step 65). When outputting the report,
The operator can use the keyboard 10 to select whether to give a fluctuation range to the graph of the simulation curve and whether to output the deviation value of the data of the target patient.

When the variation of the graph of the simulation curve is selected, any one of the following variation range setting methods is selected.

The first method is a method in which the measurement value has one of the following fluctuation ranges in consideration of the measurement error. The measured value is C.I. V. As a percentage, a uniform variation range of 10% is provided. C. Obtained from quality control for each item
V. It has a fluctuation range depending on%. With each measured value varied in this way, calculation using the Bayesian method,
A graph of each simulation curve is displayed from the obtained parameters. 3A and 3B show examples of simulation curve graphs obtained by the method of FIG. FIG. 3 (a) is a graph showing an example of oral administration of digoxin,
FIG. 3B is a graph showing an example of continuous theophylline infusion. A solid line is a graph of a simulation curve obtained by calculation, and a broken line is a graph of fluctuation range.

In the second method, the parameters are corrected using the Bayesian method from the input information and the measured values. The patient-specific estimated parameters obtained here are measured by measurement item and stored in the population parameter file of the auxiliary storage device 20. The average and variance are obtained from the plurality of estimated parameters written in. The graph of the simulation curve based on each average parameter obtained here is always displayed and used as a comparison. The variance obtained for each parameter is C.I. V. %, Etc., and the average parameter is changed by this variance to give a width to the graph. Naturally, the actual measurement value is not considered at this time. An example of the graph thus obtained is shown in FIG. A solid line is a graph of a simulation curve based on parameters obtained from measured values, and a broken line is a graph having a width due to dispersion.

The patient estimation parameters (correction parameters) written in the population parameter file of the auxiliary storage device 20 include clearance (CL) and distribution volume (V).
d) and the absorption rate constant (Ka). here,
CL is changed by 50%, Vd is changed by 20%, and Ka is changed by 70%. Further, the half-life can be calculated from the above-mentioned modified parameters by the calculation formula t _1/2 = 0.693 / (CL / Vd).

Further, when the selection is made to output the deviation value of the data of the subject patient, the following processing is carried out. As described above, the patient estimation parameters are written in the population parameter file of the auxiliary storage device 20 by classifying them into predetermined layers. In this process, first, all the patient estimation parameters of the hierarchy in which the patient estimation parameters of the target patient are written are read. Then, by calculating the average and the variance from these parameters, the average parameter for each hierarchy can be obtained. further,
By comparing this average parameter with the correction parameter obtained from the measured value after administration using the Bayesian method, by displaying the high or low in standard deviation or percentage, the value estimated this time is compared with the whole, You can know where it is located.

As an example of display, 25 years old, weight 60 k
In the case where valproic acid was administered to a g patient and an antiepileptic drug other than valproic acid was being used in combination, assuming that the clearance obtained from the measured value is 1.00 l / hr, [patient estimated parameter] clearance (CL) 1. 00l / hr average clearance (CL) value 1.14 l / hr [ratio to average] ---> 0.88.

Next, an example of the report output to the display device 41 or the printer device 42 is shown in FIG. In the report shown in the figure, a graph is used so that a doctor or the like can easily understand the predicted blood concentration of the drug in the patient. Furthermore, the patient information of the patient required to determine whether the predicted blood concentration is appropriate is described without omission. The graphs described in this report are the first graph of the simulation curve based on the patient estimation parameters of the current prescription (middle right) and the second graph of the simulation curves based on the changed patient estimation parameters (lower right). The second graph is a graph having a variation range. The fluctuation range is calculated using one of the methods described above. In addition, the deviation values for all treated patient groups are described in this report (middle left column). The deviation value is also calculated using the method described above. It should be noted that the first graph (middle right) may have a predetermined fluctuation range, as in the second graph (lower right).

Next, an operation example of the drug administration analysis system according to this embodiment will be described with reference to the display screens of FIGS. First, when the operator turns on the system, the CP
Under the control of U50, the main program 31 of the main storage device 30 is activated, and the main screen 70 is displayed on the display device 41 (FIG. 6A). When the operator moves the cursor and selects “1. data input”, the display device 41 switches to the display of the input screen 71 (FIG. 6).
(B)). The input screen 71 has an ID input area and a personal information input area. When the cursor is moved to the ID input area and the ID number of the target patient is input, each information of the patient file registered in the auxiliary storage device 20 is read. If no information is registered in the patient file of the target patient, a message indicating that the patient file is not registered is output to a predetermined area of the display device 41. Since the read patient information is displayed in the personal information input area of the display device 41,
The information that needs to be corrected can be corrected by the operator by repeatedly inputting new information.

Next, when the operator operates the keyboard 10 and hits the return key, the display device 41 switches to the display of the input screen 72 (FIG. 7 (a)). The input screen 72 is provided with a drug selection area and a calculation mode selection area. When the operator moves the cursor to the drug selection area and selects a predetermined drug, the display is switched to the display of the disease information input screen 73 related to the selected drug (FIG. 7B). The operator can move the cursor to each selection area of the input screen 73 to input disease information.

When the operator operates the keyboard 10 and hits the return key after inputting all the disease information, the input screen 72 is displayed again. When the operator moves the cursor to the calculation mode selection area and designates a predetermined mode from mode 1 to mode 4, the display is switched to the display of the input screens 74 to 77 in each mode (FIG. 8A).
(B), FIG. 9 (a) (b)).

Mode 1 is a mode in which a drug is administered at a fixed dose and at a constant interval, and the cursor is moved to each input area of the input screen 74 to input data such as a drug dose and an administration interval. You can Mode 2 is a mode in which the drug is administered at different doses and intervals at each time, and the cursor is moved to each input area of the input screen 75 to input data such as the drug dose and the time until the next administration. can do. Mode 3 is an indefinite dose / indefinite interval, but is a mode in which drug administration is performed periodically, and by moving the cursor to each input area of the input screen 76, the drug dose, the time until the next administration, etc. You can enter the data. Mode 4 is a mode when a non-linear drug such as PHT (phenytoin) is used as a drug, and the cursor is moved to each input area of the input screen 77 to display the data of the drug dose, the dosage form, and the measured value. You can enter.

After the data is input in Modes 1 to 3, when the operator operates the keyboard 10 and hits the return key, the display device 41 switches to the display of the input screen 78 (FIG. 10A). Then, the operator enters the input screen 7
When the cursor is moved to the eight measurement point input area and a predetermined number of measurement points is input, the display is switched to the display of an input screen 79 having an input area of measurement values for the number of input measurement points (FIG. 10B). The operator can move the cursor to each input area of the input screen 79 and input the measured value data. When the return key is pressed after inputting all the measured value data, the display device 41 switches to the display of the input screen 80 (FIG. 11A). The input screen 80 has an area for selecting whether the administered drug is a sustained release agent, and when the operator moves the cursor to this area and inputs that the sustained release agent is used, further input of parameter change is performed. A screen (not shown) is switched to, and predetermined parameters can be input. Here, if it is input that the sustained release agent is not used, the process ends.

By the above processing, the input of all the patient information is completed, and all the input information is registered in the auxiliary storage device 20 as a patient file. After that, the display device 41 switches to the display of the main screen 70.

Next, when the operator moves the cursor on the main screen 70 and selects "2. Bayesian estimation", the display device 41 switches to the display of the input screen 81 (FIG. 11 (b)). The input screen 81 has an ID input area. When the cursor is moved to the ID input area and the ID number of the target patient is input, each information of the patient file already registered in the auxiliary storage device 20 is read. Next, when the operator operates the keyboard 10 and hits the return key, the display device 41 switches to the display of the input screen 82 (FIG. 12A). The input screen 82 is provided with an error distribution method selection area, a parameter variation width change area, and a measurement value variation width change area. By moving the cursor to each area and inputting the selection and change data, the operator can set the parameters necessary for the calculation process of Bayesian estimation. When these data are input, the control of the CPU 50 is transferred from the main program 31 to the calculation program 32, the calculation program 32 is executed under the control of the CPU 50, and the Bayesian estimation calculation is performed. By this calculation, the predicted value of the blood concentration of the drug when the drug administration is continued as it is is calculated. After the calculation is completed, the display device 41 switches to the display of the main screen 70.

Next, when the operator moves the cursor on the main screen 70 and selects "3. Graph display", the display device 41 switches to the display of the input screen 83 (FIG. 12 (b)). The input screen 83 is provided with input areas such as a parameter selection area for selecting one of Bayesian estimation parameters and population parameters and an administration schedule selection area for selecting one of a current schedule and a recommended schedule. The operator can move the cursor to each input area of the input screen 83 to make predetermined settings. When the return key is pressed after completing all the settings, a graph of the simulation curve is displayed on the display device 41. When the Bayesian estimation parameter is selected in the highest input area of the input screen 83 and the simultaneous output of the population parameters is selected in the lowest input area, the graph of the simulation curve and the population parameter based on the Bayesian estimation parameter are selected. A graph of a simulation curve based on is simultaneously displayed on the display device 41. After the display is finished, the display device 41 switches to the display of the main screen 70.

Next, when the operator moves the cursor on the main screen 70 and selects "4. Blood concentration prediction",
The display device 41 switches to the display of the input screen 84 (FIG. 13A). On the input screen 84, a parameter selection area for selecting either Bayesian estimation parameters or population parameters, a prediction number specification area for specifying how many times the drug is to be administered to predict blood concentration, and a drug administration area There is provided an elapsed time input area for inputting how many hours after the stop the blood concentration is predicted. Blood concentration prediction refers to the process of predicting the blood concentration at that time by inputting the elapsed time in the schedule,
It is used for weight loss simulation and PHT (phenytoin) prediction. When the operator moves the cursor to the parameter selection area and selects one of the parameters, the schedule is displayed in a predetermined area of the display device 41. When the cursor is moved to the predicted number designation area and the elapsed time input area with reference to this schedule and data is input respectively, the predicted level of blood concentration is displayed in a predetermined area of the display device 41. After that, the prediction level of the blood concentration can be repeatedly displayed by repeating the data input of the prediction count and the elapsed time. After displaying the prediction level,
The display device 41 switches to the display of the main screen 70.

Next, when the operator moves the cursor on the main screen 70 and selects "5. Reset schedule", the display device 41 switches to the display of the input screen 85 (FIG. 13B). The input screen 85 includes a target value input area for inputting a target value of the blood concentration of the drug, a parameter selection area for selecting one of the haze estimation parameter and the population parameter, and a calculation mode selection area used for resetting. Is provided. The operator can move the cursor to each input area of the input screen 85 to make a predetermined setting. When the return key is pressed after completing all the settings, the drug dose and the dose interval for achieving the target blood concentration are calculated, and the calculation result is displayed in a predetermined area of the display device 41. After the display of the calculation result is completed, the display device 41 switches to the display of the main screen 70.

Next, when the operator moves the cursor on the main screen 70 and selects "6. Report output", the report in the format shown in FIG.
1 is displayed on the screen. The columns of this report are automatically populated with the data already entered and the graphs created. Further, it is possible to input in the comment field (lower left), and the operator can input a predetermined comment while looking at the display of the report. After the necessary comment is input, the operator can select the printing process to output the completed report to the printer device 42.

It should be noted that the report format shown in FIG. 5 and the screen layouts shown in FIGS. 6 to 13 are merely examples, and the present invention is not limited to this format and layout, and other formats and layouts may be used. You may use.

Further, instead of the keyboard 10, a mouse,
Other input devices such as a tablet may be used, and the display device 41 may be a liquid crystal display device or another display device other than the cathode ray tube display device.

[0040]

According to the drug administration analysis system of the present invention, the blood concentration data read from the storage means and the blood concentration data calculated by at least the first calculating means are
It is output as one report together with patient information. By using the report with excellent visibility output in this way, it is possible to provide accurate guidance to the patient.

The output format of these blood concentration data may be a graph having a predetermined fluctuation range.
If the graph has a fluctuation range, even if the actual blood concentration deviates from the expected value, most of the deviation can be absorbed within the fluctuation range, and the report becomes highly reliable.

[Brief description of drawings]

FIG. 1 is a block diagram showing a system outline of a drug administration analysis system according to an embodiment.

FIG. 2 is a flowchart showing an outline of processing of a drug administration analysis system.

FIG. 3 is a diagram showing a graph of a simulation curve.

FIG. 4 is a diagram showing a graph of a simulation curve.

FIG. 5 is a diagram showing an example of a report.

FIG. 6 is a diagram showing a display screen for operating the drug administration analysis system.

FIG. 7 is a diagram showing a display screen for operating the drug administration analysis system.

FIG. 8 is a diagram showing a display screen for operating the drug administration analysis system.

FIG. 9 is a diagram showing a display screen for operating the drug administration analysis system.

FIG. 10 is a diagram showing a display screen for operating the drug administration analysis system.

FIG. 11 is a diagram showing a display screen for operating the drug administration analysis system.

FIG. 12 is a diagram showing a display screen for operating the drug administration analysis system.

FIG. 13 is a diagram showing a display screen for operating the drug administration analysis system.

FIG. 14 is a flowchart showing an outline of processing of a conventional drug administration plan program.

FIG. 15 is a diagram showing an output example of a simulation curve.

[Explanation of Codes] 10 ... Keyboard, 20 ... Auxiliary storage device, 30 ... Main storage device, 31 ... Main program, 32 ... Calculation program, 40 ... Output device, 41 ... Display device, 42 ...
Printer device, 50 ... CPU, 70 ... Main screen, 71
~ 85 ... Input screen.

Claims (5)

[Claims] 1. A predetermined amount of a drug is administered to a patient every predetermined time, the blood concentration of the drug is measured after the administration, and the predicted value of the blood concentration of the drug after the measurement is calculated by the Bayesian least square method or the like. In the drug administration analysis system that calculates by using, input means for accepting input of dose data of a drug administered to a patient and blood concentration data of the drug measured after administration, and dose data input using the input means. And a storage unit for storing the blood concentration data for each patient, and a first operation for calculating a predicted blood concentration of the drug by reading the dose data and the blood concentration data of a predetermined patient from the storage unit. Means, and reading the dose data and blood concentration data of a predetermined patient from the storage means, the blood concentration of the drug when the dose of the drug is reduced and / or increased based on these data. Second calculation means for calculating a measured value, blood concentration data read from the storage means, blood concentration data calculated by the first calculation means, and / or calculated by the second calculation means A drug administration analysis system, comprising: output means for outputting blood concentration data together with patient information as a single report. 2. The drug administration analysis system according to claim 1, wherein the output means outputs each blood concentration data as a graph having a predetermined fluctuation range. 3. The drug administration analysis system according to claim 2, wherein the predetermined fluctuation width is a width of a uniform ratio set in advance for all patients. 4. The storage means stores a plurality of drug dose data and blood concentration data at each measurement time, and the predetermined fluctuation range is the drug of all patients stored in the storage means. The range is based on the parameters of all patients obtained by aggregating dose data and blood concentration data and obtaining the mean value or standard deviation calculated from these data at each measurement time. 2. The drug administration analysis system according to 2. 5. The output means collects drug dose data and blood concentration data of all patients stored in the storage means, and specifies based on an average value or standard deviation calculated from these data. The drug administration analysis system according to any one of claims 1 to 4, wherein the position of the patient data in all the patient data is output as a deviation value.