Risk Calculator

Abstract

A processor (11) acquires the body temperature of a patient (100) and patient state information through a communication device (14). The processor (11) compares the body temperature acquired through the communication device (14) with a reference temperature to calculate a comparison result, and outputs a risk concerning the health state of the patient (100) from the comparison result. The processor (11) executes at least one of: a process in which the body temperature is corrected on the basis of the patient state information when the body temperature and the reference temperature are compared; a process in which the reference temperature is set on the basis of the patient state information when the body temperature and the reference temperature are compared; and a process in which the comparison result is increased or decreased on the basis of the patient state information.

Description

[Technical Field]

[0001] The present invention relates to a risk calculation device, a risk calculation system, and a program for calculating risks related to a patient's health condition. [Background technology]

[0002] 2. Description of the Related Art In order to detect the onset or worsening of a patient's disease at an early stage, it is known to calculate a risk related to a patient's health condition based on measurements of some parameter indicating the patient's condition.

[0003] For example, US Pat. No. 6,299,649 discloses a patient monitoring system that determines a patient status value based on measurements of one or more physiological parameters. [Prior art documents] [Patent documents]

[0004] [Patent Document 1] Special Publication No. 2018-506759 Summary of the Invention [Problem to be solved by the invention]

[0005] The parameters measured to calculate the risk of a patient's health condition may fluctuate due to factors not directly related to the patient's disease, which may result in an inaccurate calculation of the patient's risk of the health condition. Furthermore, even if the measured values ​​of the parameters are the same, the magnitude of the risk varies depending on the type of disease the patient has or is suspected of having. Therefore, it is necessary to accurately calculate the risk of a patient's health condition regardless of the patient's condition, which depends on factors related to and / or unrelated to the patient's disease.

[0006] An object of the present invention is to provide a risk calculation device that can calculate the risk related to a patient's health condition more accurately than conventional devices, regardless of the patient's condition. [Means for solving the problem]

[0007] According to one aspect of the present invention, A risk calculation device for calculating a risk related to a patient's health condition, an input unit for acquiring the patient's body temperature and patient condition information; a calculation unit that compares the body temperature acquired by the input unit with a reference temperature to calculate a comparison result, and outputs a risk related to the health condition of the patient from the comparison result; The calculation unit performs at least one of the following processes: correcting the body temperature based on the patient condition information when comparing the body temperature with the reference temperature; setting the reference temperature based on the patient condition information when comparing the body temperature with the reference temperature; and increasing or decreasing the comparison result based on the patient condition information.

[0008] According to one aspect of the present invention, the patient condition information includes a circadian rhythm variation in the patient's body temperature; The calculation unit performs at least one of the following processes based on fluctuations due to the circadian rhythm: correcting the body temperature; setting the reference temperature; and increasing or decreasing the comparison result.

[0009] According to one aspect of the present invention, The calculation unit performs at least one of the following processes: correcting the body temperature to offset fluctuations due to the circadian rhythm; setting the reference temperature; and increasing or decreasing the comparison result.

[0010] According to one aspect of the present invention, The calculation unit performs at least one of the following processes: correcting the body temperature to follow fluctuations due to the circadian rhythm; setting the reference temperature; and increasing or decreasing the comparison result.

[0011] According to one aspect of the present invention, The input unit continuously acquires the patient condition information; The calculation unit performs at least one of the following processes based on the time when the input unit acquires the patient's body temperature: correcting the body temperature; setting the reference temperature; and increasing or decreasing the comparison result.

[0012] According to one aspect of the present invention, the patient status information includes behavioral information indicating whether the patient is currently asleep or awake; The calculation unit performs at least one of a process of correcting the body temperature, a process of setting the reference temperature, and a process of increasing or decreasing the comparison result based on the behavior information.

[0013] According to one aspect of the present invention, the patient condition information includes a basal metabolic rate of the patient or includes information for calculating a basal metabolic rate of the patient; The calculation unit performs at least one of the following processes based on the patient's basal metabolic rate and a reference basal metabolic rate: correcting the body temperature; setting the reference temperature; and increasing or decreasing the comparison result.

[0014] According to one aspect of the present invention, The calculation unit performs at least one of the following processes: correcting the body temperature so as to offset an increase or decrease in the patient's basal metabolic rate relative to the reference basal metabolic rate; setting the reference temperature; and increasing or decreasing the comparison result.

[0015] According to one aspect of the present invention, The calculation unit performs at least one of the following processes: correcting the body temperature to follow increases or decreases in the patient's basal metabolic rate relative to the standard basal metabolic rate; setting the standard temperature; and increasing or decreasing the comparison result.

[0016] According to one aspect of the present invention, the patient condition information includes medication information for medications administered to the patient; The calculation unit performs at least one of a process of correcting the body temperature, a process of setting the reference temperature, and a process of increasing or decreasing the comparison result based on the medication information.

[0017] According to one aspect of the present invention, The calculation unit performs at least one of the following processes: correcting the body temperature to offset an increase or decrease in the patient's body temperature caused by the drug; setting the reference temperature; and increasing or decreasing the comparison result.

[0018] According to one aspect of the present invention, The calculation unit performs at least one of the following processes: correcting the body temperature to follow an increase or decrease in the patient's body temperature caused by the drug; setting the reference temperature; and increasing or decreasing the comparison result.

[0019] According to one aspect of the present invention, The medication information includes at least one of the type of the medication, the time elapsed since the medication was administered, and the administration method of the medication.

[0020] According to one aspect of the present invention, the patient status information includes a diagnosis of a disease of the patient; The calculation unit performs at least one of a process of correcting the body temperature, a process of setting the reference temperature, and a process of increasing or decreasing the comparison result based on the diagnosis result.

[0021] According to one aspect of the present invention, the patient condition information includes the patient's pulse; The calculation unit calculating a relatively bradycardia based on said pulse rate; Based on the relatively bradycardia, at least one of the following processes is performed: correcting the body temperature; setting the reference temperature; and increasing or decreasing the comparison result.

[0022] According to one aspect of the present invention, The calculation unit performs at least one of the following processes: correcting the body temperature to follow the magnitude of the difference between the actually measured first body temperature rise value and the second body temperature rise value estimated from the pulse rate; setting the reference temperature; and increasing or decreasing the comparison result.

[0023] According to one aspect of the present invention, The calculation unit performs at least one of the following processes: correcting the body temperature so as to offset the magnitude of the difference between the actually measured first body temperature rise value and the second body temperature rise value estimated from the pulse rate; setting the reference temperature; and increasing or decreasing the comparison result.

[0024] According to one aspect of the present invention, a risk calculation system comprises: a temperature sensor for measuring the patient's body temperature; and the risk calculation device.

[0025] According to one aspect of the present invention, 1. A program comprising instructions executable by a processor of a computer for calculating a risk associated with a health condition in a patient, the instructions causing the processor to: a first step of acquiring the patient's temperature and patient condition information; a second step of comparing the patient's body temperature with a reference temperature to calculate a comparison result, and calculating a risk related to the patient's health condition from the comparison result; The second step includes at least one of the following processes: correcting the body temperature based on the patient condition information when comparing the body temperature with the reference temperature; setting the reference temperature based on the patient condition information when comparing the body temperature with the reference temperature; and increasing or decreasing the comparison result based on the patient condition information. [Effects of the Invention]

[0026] According to one aspect of the present invention, a patient's risk associated with a health condition can be calculated more accurately than previously possible, regardless of the patient's condition. [Brief explanation of the drawings]

[0027] [Figure 1] 1 is a block diagram showing a configuration of a risk calculation system according to a first embodiment. [Figure 2] 10 is a flowchart showing a first embodiment of the risk calculation process executed by the processor 11 of FIG. 1, the risk calculation process including a body temperature correction process. [Figure 3] 10 is a flowchart showing a subroutine of a body temperature correction process based on a circadian rhythm, which is a first embodiment of step S102 in FIG. 2. [Figure 4] FIG. 1 is a schematic diagram illustrating the fitting of circadian rhythms to body temperature measured over a 24-hour period. [Figure 5] FIG. 4 is a schematic diagram for explaining the body temperature correction process based on the circadian rhythm of FIG. 3. [Figure 6] 10 is a flowchart showing a subroutine of a body temperature correction process based on a basal metabolic rate, as a second embodiment of step S102 in FIG. 2. [Figure 7] 10 is a flowchart showing a subroutine of a body temperature correction process based on medication, which is a third embodiment of step S102 in FIG. 2. [Figure 8] 1 is a schematic diagram showing the concentration of a drug in the blood over time when the drug is administered to a patient. [Figure 9] FIG. 8 is a schematic diagram for explaining the medication-based body temperature correction process of FIG. 7. [Figure 10] 10 is a flowchart showing a subroutine of a body temperature correction process based on a diagnosis result, as a fourth embodiment of step S102 in FIG. 2. [Figure 11] FIG. 10 is a block diagram showing the configuration of a risk calculation system according to a modified example of the first embodiment. [Figure 12]10 is a flowchart showing a subroutine of a body temperature correction process based on a pulse rate, as a fifth embodiment of step S102 in FIG. 2. [Figure 13] 10 is a graph illustrating the occurrence of relatively bradycardia. [Figure 14] 10 is a flowchart showing a second embodiment of the risk calculation process executed by the processor 11 of FIG. 1, the risk calculation process including a setting value correction process. [Figure 15] 15 is a flowchart showing a subroutine of a setting value correction process based on a circadian rhythm, which is a first embodiment of step S202 in FIG. 14. [Figure 16] 15 is a flowchart showing a subroutine of a setting value correction process based on a basal metabolic rate, which is a second embodiment of step S202 in FIG. 14. [Figure 17] 15 is a flowchart showing a subroutine of a setting value correction process based on medication, which is a third example of step S202 in FIG. 14. [Figure 18] 15 is a flowchart showing a subroutine of a setting value correction process based on a diagnosis result, which is a fourth embodiment of step S202 in FIG. 14. [Figure 19] 15 is a flowchart showing a subroutine of a setting value correction process based on the pulse rate, which is a fifth embodiment of step S202 in FIG. 14. [Figure 20] 10 is a flowchart showing a third embodiment of the risk calculation process executed by the processor 11 of FIG. 1, the risk calculation process including a risk value correction process. [Figure 21] 21 is a flowchart showing a subroutine of a risk value correction process based on a circadian rhythm, which is a first embodiment of step S303 in FIG. 20. [Figure 22] 21 is a flowchart showing a subroutine of a risk value correction process based on a basal metabolic rate, as a second example of step S303 in FIG. 20. [Figure 23] 21 is a flowchart showing a subroutine of a risk value correction process based on medication, as a third example of step S303 in FIG. 20. [Figure 24] 21 is a flowchart showing a subroutine of a risk value correction process based on a diagnosis result, as a fourth embodiment of step S303 in FIG. 20. [Figure 25] 21 is a flowchart showing a subroutine of a risk value correction process based on a pulse rate, which is a fifth example of step S303 in FIG. 20. [Figure 26] FIG. 10 is a block diagram showing the configuration of a risk calculation system according to a second embodiment. DETAILED DESCRIPTION OF THE INVENTION

[0028] A risk calculation system according to an embodiment of the present invention will now be described with reference to the drawings. In the drawings, the same reference numerals denote similar components.

[0029] [First embodiment] 1 is a block diagram showing the configuration of a risk calculation system according to the first embodiment. A risk calculation device 1 acquires the body temperature of a patient 100 from a thermometer 2 attached to the body of the patient 100, and calculates the risk related to the health condition of the patient 100 based on the body temperature of the patient 100. The "risk" here includes a prediction of the possibility that the patient 100 will become seriously ill after a predetermined time has passed (for example, after half a day).

[0030] The risk calculation device 1 comprises a bus 10, a processor 11, a memory 12, a storage device 13, a communication device 14, an input device 15, a display device 16, and a clock RTC1. The processor 11 executes a risk calculation process, which will be described later with reference to FIG. 2 etc., to calculate the risk related to the health condition of the patient 100, and also controls the operation of the entire risk calculation device 1. The memory 12 temporarily stores programs and data necessary for the operation of the risk calculation device 1. The storage device 13 is a non-volatile storage medium that stores programs and data necessary for the operation of the risk calculation device 1. The communication device 14 is communicatively connected to the thermometer 2 and acquires the body temperature of the patient 100 from the thermometer 2. The input device 15 receives user input to control the operation of the risk calculation device 1. The input device 15 includes, for example, a keyboard and a pointing device. The display device 16 displays the calculated risk related to the health condition of the patient 100. The clock RTC1 provides time information indicating the current time. The processor 11 , memory 12 , storage device 13 , communication device 14 , input device 15 , and display device 16 are connected to one another via a bus 10 .

[0031] The risk calculation device 1 may be a general-purpose personal computer of tablet, notebook, or desktop type, or may be a dedicated calculation device such as a wearable calculation device. The risk calculation device 1 may also be an all-in-one device, or may be a combination of multiple components, such as a desktop computer including a main body, a display (display device), and a keyboard (input device).

[0032] The thermometer 2 includes a temperature sensor 21, a signal processing circuit 22, and a communication device 23. The temperature sensor 21 acquires the body temperature of the patient 100. The signal processing circuit 22 converts the body temperature of the patient 100 acquired by the temperature sensor 21 into a format (e.g., a digital value) that can be transmitted to the risk calculation device 1. The communication device 23 is communicatively connected to the risk calculation device 1, and transmits the body temperature of the patient 100 to the risk calculation device 1.

[0033] The thermometer 2 may be, for example, a deep body thermometer that measures the deep body temperature of the patient 100 by detecting the temperature of the trunk, eardrum, rectum, or esophagus. The thermometer 2 may be wirelessly connected to the risk calculation device 1 via Bluetooth (registered trademark) or WiFi (registered trademark), or may be wired connected to the risk calculation device 1.

[0034] The processor 11 acquires the current body temperature of the patient 100 from the thermometer 2 via the communication device 14 .

[0035] The processor 11 acquires patient condition information other than the current body temperature regarding the condition of the patient 100 via the input device 15, and stores the acquired patient condition information in the storage device 13. The processor 11 may also acquire, via the communication device 14, patient condition information stored in advance in an external server device (not shown) communicatively connected via the communication device 14. The patient condition information includes, for example, at least one of the circadian rhythm of the body temperature of the patient 100, the basal metabolic rate of the patient 100 or information associated therewith, medication information on a drug administered to the patient 100, a diagnosis of a disease of the patient 100, and the pulse rate of the patient 100. The patient condition information also includes the current body temperature of the patient 100 acquired from the thermometer 2, as described above.

[0036] The processor 11 compares the current body temperature of the patient 100 with the set value, calculates the comparison result, and determines and outputs the risk related to the health condition of the patient 100 based on the comparison result.

[0037] The set point is a certain reference temperature. For example, the set point may be set to a temperature threshold that is significantly higher than the patient's 100 normal body temperature, such as 38.5°C, or may be set to the patient's 100 normal body temperature of 36.5°C. The set point may include not only one reference temperature, but also a pair of reference temperatures that respectively indicate the upper and lower limits of a temperature range. The set point may also include multiple pairs of reference temperatures that indicate multiple different temperature ranges.

[0038] The comparison result between the patient's 100 current body temperature and the set value may be expressed, for example, in the form of a numerical value. In this specification, the numerical value indicating the comparison result will be referred to as a "risk value." The risk value may have a discrete value or a continuous value. For example, if the set value is set to a temperature threshold significantly higher than the patient's 100 normal body temperature, and if the patient's 100 body temperature exceeds the temperature threshold, the patient 100 may be determined to be in a high-risk state and the risk value may be set to 1; otherwise, the risk value may be set to 0. Alternatively, multiple temperature thresholds may be set so that the risk value increases as the body temperature rises. Alternatively, if the set value is set to the patient's 100 normal body temperature, the risk value may be calculated to indicate the difference between the patient's 100 current body temperature and the normal body temperature. In this case, the risk value may be calculated to increase as the patient's 100 current body temperature becomes higher than the normal body temperature.

[0039] The processor 11 performs at least one of correcting the current body temperature, setting or resetting a set value, and increasing or decreasing a risk value (comparison result) based on the patient condition information. In this specification, changing (correcting, setting, or increasing or decreasing) these parameters is collectively referred to as "correcting the risk." In other words, in this embodiment, "correcting the risk" not only refers to directly correcting the risk related to the health condition of the patient 100, which is the information ultimately presented to the user, but also includes indirectly correcting the risk, i.e., correcting the parameters used to calculate the risk. "Correcting the risk" includes correcting the body temperature and calculating a risk value based on the corrected body temperature, setting or resetting a set value and calculating a risk value using the set or reset set value, and increasing or decreasing the calculated risk value.

[0040] The processor 11 determines and outputs a risk related to the health condition of the patient 100 based on the calculated risk value. The processor 11 outputs the determined risk to the display device 16. The processor 11 may output the determined risk to an external device communicatively connected via the communication device 14. The processor 11 may output the determined risk via a speaker (not shown).

[0041] The processor 11 may output the calculated risk value as it is as the risk related to the health condition of the patient 100, or may convert the risk value into another numerical value (such as a percentage) and output it. The processor 11 may also output the determined risk not only in the form of a numerical value but also in other forms, for example, visual or auditory. For example, the processor 11 may output the determined risk in text such as "high," "medium," and "low." The processor 11 may also display the determined risk using a gradation including a color that changes as the measured body temperature deviates from a reference value such as normal body temperature. If the determined risk indicates that the patient 100 is in a high-risk state, the processor 11 may output an alarm via a speaker (not shown).

[0042] For simplicity of explanation, the following describes the case where processor 11 outputs the calculated risk value as is as the risk related to the health condition of patient 100, but as described above, processor 11 may also output the determined risk in other forms.

[0043] The communication device 14 is an example of an input unit that acquires the current body temperature of the patient 100. The input device 15 or the communication device 14 is an example of an input unit that acquires patient condition information. The processor 11 is an example of a calculation unit that determines the risk related to the health condition of the patient 100. The display device 16, the communication device 14, or a speaker (not shown) is an example of an output unit that outputs the determined risk.

[0044] As described above, the processor 11 corrects the current body temperature, the set value, or the risk value based on the patient condition information. Below, the risk calculation process including the body temperature correction process, the risk calculation process including the set value correction process, and the risk calculation process including the risk value correction process will be described.

[0045] [Risk calculation process including body temperature correction process] Fig. 2 is a flowchart showing a first example of a risk calculation process executed by the processor 11 of Fig. 1, which includes a body temperature correction process. According to the process of Fig. 2, the processor 11 corrects the measured current body temperature of the patient 100 before calculating the risk value.

[0046] In step S101, the processor 11 acquires the current measured body temperature of the patient 100 from the thermometer 2 via the communication device 14.

[0047] In step S102, the processor 11 executes a body temperature correction process to correct the current body temperature of the patient 100 based on the patient condition information.

[0048] In step S103, the processor 11 calculates a risk value based on the corrected body temperature and the set value.

[0049] In step S104, the processor 11 outputs the calculated risk value to the display device 16.

[0050] The processor 11 periodically repeats the risk calculation process of FIG.

[0051] As described above, the patient condition information includes, for example, at least one of the circadian rhythm of the body temperature of the patient 100, the basal metabolic rate of the patient 100 or information associated therewith, medication information on the medicine administered to the patient 100, the diagnosis result of the disease of the patient 100, and the pulse rate of the patient 100. Below, the body temperature correction process based on the circadian rhythm, the body temperature correction process based on the basal metabolic rate, the body temperature correction process based on the medication, the body temperature correction process based on the diagnosis result, and the body temperature correction process based on the pulse rate will be described.

[0052] [Body temperature correction processing based on circadian rhythm] Circadian rhythm is a diurnal variation of a parameter indicating a human condition, which exists regardless of the disease and its severity. A patient's body temperature may increase or decrease due to the circadian rhythm, regardless of the disease and its severity, which may result in an incorrect calculation of the patient's health risk. Below, a method for correcting a patient's body temperature to reduce the influence of the circadian rhythm is described.

[0053] Figure 3 is a flowchart showing a subroutine of a body temperature correction process based on a circadian rhythm, which is a first example of step S102 in Figure 2. To distinguish the body temperature correction process based on a circadian rhythm from body temperature correction processes based on other patient condition information, the step of the body temperature correction process in Figure 3 is indicated by the reference symbol S102A.

[0054] In step S111, the processor 11 reads the circadian rhythm of the body temperature of the patient 100 from the storage device 13. The circadian rhythm of the body temperature of the patient 100 may be generated in advance by the processor 11 based on a log of the body temperature of the patient 100 acquired over a time period of 24 hours or more using the thermometer 2, and stored in the storage device 13. Alternatively, the circadian rhythm of the body temperature of the patient 100 may be acquired in advance from an external server device (not shown) via the communication device 14 and stored in the storage device 13.

[0055] FIG. 4 is a schematic diagram illustrating fitting a circadian rhythm to body temperature measured over 24 hours. Human body temperature generally reaches its maximum value during wakefulness and its minimum value during sleep. The times at which body temperature reaches its maximum and minimum values ​​depend on the subject's wake-up time and bedtime. However, the subject's wake-up time and bedtime are generally unknown, and the mean value, amplitude, and initial phase of the body temperature are also unknown. According to the example of FIG. 4, a circadian rhythm function x(t) of the subject's body temperature is estimated by fitting a cosine wave (or sine wave) to the measured body temperature (actual value) as follows:

[0056] x(t)=ab×cos(2π(t-t0) / 24)

[0057] Here, a indicates the average body temperature, b indicates the amplitude of the change in body temperature, and t0 indicates the initial phase, that is, the time (unit: time) when the body temperature reaches its minimum value.

[0058] The circadian rhythm is not limited to a cosine wave (or a sine wave) and may be represented by, for example, a triangular wave or a square wave. Furthermore, the circadian rhythm is not limited to being generated based on a log of the body temperature of the patient 100, and may be determined based on, for example, the wake-up time and bedtime of the patient 100 obtained by a doctor's interview.

[0059] In step S112, the processor 11 acquires time information indicating the current time from the clock RTC1. If the circadian rhythm of the body temperature of the patient 100 is represented by a square wave that is at a low level during sleep and at a high level during wakefulness, the processor 11 may acquire, instead of the time information, behavioral information indicating whether the patient 100 is currently asleep or wakeful via the input device 15.

[0060] In step S113, the processor 11 corrects the current body temperature of the patient 100 based on the circadian rhythm and the current time (i.e., the time when the body temperature of the patient 100 is obtained) to offset fluctuations in the body temperature of the patient 100 due to the circadian rhythm. The corrected body temperature Ta(t) is calculated from the current body temperature T(t) and the above-mentioned circadian rhythm function x(t) as follows:

[0061] Ta(t)=T(t)-(x(t)-a) =T(t)+b×cos(2π(t-t0) / 24)

[0062] FIG. 5 is a schematic diagram illustrating the circadian rhythm-based body temperature correction process of FIG. 3. Generally, the processor 11 corrects the measured body temperature T(t) so that it approaches the average body temperature a due to the circadian rhythm. At time t1, the body temperature due to the circadian rhythm is lower than the average body temperature a by a temperature d1. Therefore, the processor 11 calculates the corrected body temperature Ta(t1) by adding the temperature d1 to the body temperature T(t1) measured at time t1. At time t2, the body temperature due to the circadian rhythm is higher than the average body temperature a by a temperature d1. Therefore, the processor 11 calculates the corrected body temperature Ta(t2) by subtracting the temperature d1 from the body temperature T(t2) measured at time t2.

[0063] Here, "offsetting body temperature fluctuations" means at least partially offsetting increases or decreases in body temperature due to circadian rhythms. Referring to the example of Figure 5, the body temperature T(t1) measured at time t1 is on the circadian rhythm plot, but the body temperature T(t2) measured at time t2 is off the circadian rhythm plot. In the former case, the corrected body temperature Ta(t1) matches the average body temperature a due to circadian rhythms, but in the latter case, the corrected body temperature Ta(t2) does not match the average body temperature a due to circadian rhythms.

[0064] As described above, if the circadian rhythm of the patient's 100 body temperature is represented by a square wave, in step S113, the processor 11 may correct the patient's 100's current body temperature based on the circadian rhythm and behavioral information to offset fluctuations in the patient's 100 body temperature due to the circadian rhythm.

[0065] By performing body temperature correction processing based on circadian rhythms, the effects of circadian fluctuations in the body temperature of the patient 100 can be reduced, and the risk related to the health condition of the patient 100 can be calculated more accurately than before, regardless of the time of day.

[0066] [Body temperature correction processing based on basal metabolic rate] A person's body temperature is highly correlated with their basal metabolic rate, which varies depending on their weight, height, age, and gender. This information can be used to calculate their basal metabolic rate. In other words, a patient's body temperature may rise or fall due to individual differences in basal metabolic rate, regardless of the illness or its severity. As a result, the patient's health risk may be calculated incorrectly. Below, we will explain a method for correcting a patient's body temperature to reduce the impact of individual differences in basal metabolic rate.

[0067] Fig. 6 is a flowchart showing a subroutine of body temperature correction processing based on basal metabolic rate, which is a second embodiment of step S102 in Fig. 2. In order to distinguish the body temperature correction processing based on basal metabolic rate from body temperature correction processing based on other patient condition information, the step of the body temperature correction processing in Fig. 6 is indicated by the symbol S102B.

[0068] In step S121, the processor 11 acquires physical characteristic information of the patient 100. The physical characteristic information of the patient 100 includes, for example, at least one of weight, height, age, and sex. The processor 11 may read out pre-stored physical characteristic information from the storage device 13, may acquire the physical characteristic information via the input device 15, or may acquire the physical characteristic information from an external server device (not shown) via the communication device 14.

[0069] In step S122, the processor 11 calculates the basal metabolic rate of the patient 100 based on the physical characteristic information of the patient 100. The following formula for calculating the basal metabolic rate, obtained by the National Institute of Health and Nutrition in Japan, is known.

[0070] Jm=(0.481×W+0.0234×H-0.0138×A-0.4235)×1000 / 4.186 Jf=(0.481×W+0.0234×H-0.0138×A-0.9708)×1000 / 4.186

[0071] Here, Jm represents the basal metabolic rate for men, Jf represents the basal metabolic rate for women, W represents weight, H represents height, and A represents age. According to the above formula, the basal metabolic rates Jm and Jf increase as weight W and height H increase, and decrease as age A increases.

[0072] In step S123, the processor 11 corrects the current body temperature of the patient 100 based on the basal metabolic rate so as to offset the increase or decrease in the basal metabolic rate of the patient 100 relative to the reference basal metabolic rate. The corrected body temperature Tb is calculated from the current body temperature T and the above-mentioned basal metabolic rates Jm and Jf as follows:

[0073] Tb=T×Mm / Jm (for men) Tb=T×Mf / Jf (for women)

[0074] Here, Mm indicates the average basal metabolic rate for men (i.e., the standard basal metabolic rate for men), and Mf indicates the average basal metabolic rate for women (i.e., the standard basal metabolic rate for women).

[0075] According to the above formula, the corrected body temperature Tb decreases as the weight W and height H increase, and increases as the age A increases.

[0076] Here, "offsetting the increase or decrease in basal metabolic rate" means at least partially offsetting the increase or decrease in body temperature caused by individual differences in basal metabolic rate.

[0077] If any of weight, height, and age is unknown, the processor 11 may use the average value in a predetermined population.

[0078] As described above, the processor 11 may acquire physical characteristic information for calculating the basal metabolic rate (i.e., information associated with the basal metabolic rate of the patient 100), or alternatively, may acquire a pre-calculated basal metabolic rate itself. In this case, the processor 11 may read out the pre-stored basal metabolic rate from the storage device 13, may acquire the basal metabolic rate via the input device 15, or may acquire the basal metabolic rate from an external server device (not shown) via the communication device 14.

[0079] By performing a body temperature correction process based on the basal metabolic rate, the influence of individual differences in basal metabolic rate can be reduced, and the risk related to the health condition of the patient 100 can be calculated more accurately than before.

[0080] [Temperature correction processing based on medication] Administering a drug to a patient artificially lowers or raises the patient's body temperature. For example, when an antipyretic is administered to a patient with a fever caused by an infectious disease or other illness, the fever is suppressed and the patient's body temperature drops for a certain period of time after administration due to the antipyretic's effect. However, because the antipyretic does not treat the illness itself, there is a risk that the patient's health risk may be incorrectly calculated based on the patient's body temperature. Below, we will explain a method for correcting a patient's body temperature to reduce the effects of the drug administered to the patient.

[0081] Fig. 7 is a flowchart showing a subroutine of body temperature correction processing based on medication, which is a third embodiment of step S102 in Fig. 2. In order to distinguish body temperature correction processing based on medication from body temperature correction processing based on other patient condition information, the step of body temperature correction processing in Fig. 7 is indicated by the symbol S102C.

[0082] In step S131, the processor 11 acquires medication information about a drug administered to the patient 100. The medication information includes at least one of the type of drug, the time elapsed since administration of the drug, and the administration method of the drug. The effect on body temperature (decreasing or increasing) and the duration of the effect vary depending on the type of drug. The drug administration method also varies in the speed at which the effect appears and the duration of the effect. Administration methods include, for example, oral administration, injection, and suppository. In the case of oral administration, the speed at which the effect appears and the duration of the effect also vary depending on the dosage form (tablet, granule, powder, etc.). The processor 11 may read out pre-stored medication information from the storage device 13, acquire the medication information via the input device 15, or acquire the medication information from an external server device (not shown) via the communication device 14. When acquiring medication information via the input device 15, the processor 11 may display a user interface on the display device 16 that makes it easy to input medication information, such as a pull-down menu including multiple options.

[0083] Figure 8 is a schematic diagram showing the concentration of a drug in the blood over time when a drug is administered to a patient. The concentration of the drug in the blood over time increases rapidly after administration, reaches a peak value, and then gradually decreases. The concentration of the drug in the blood over time can be represented, for example, by a Weibull distribution.

[0084] The amount of change in body temperature resulting from administering a drug to patient 100 depends on the concentration of the drug in the blood. Therefore, the profile of the change in body temperature of patient 100 has a shape similar to the profile of the change in concentration over time, as shown in Figure 8.

[0085] Antipyretics include, for example, ibuprofen, naproxen, ketoprofen, nimesulide, Acetylsalicylic acid and acetaminophen.

[0086] On the other hand, when a drug that is not intended to reduce fever is administered to the patient 100, the side effects of the drug may increase the body temperature of the patient 100. Drugs that increase the body temperature of the patient 100 include, for example, the following.

[0087] (1) Drugs that cause hyperthermia through increased muscle activity: Amphetamines, monoamine oxidase inhibitors, cocaine, lithium, antipsychotics (butyrophenones, phenothiazines), tricyclic or tetracyclic antidepressants, halothane, succinylcholine, MDMA, lysergic acid diethylamide (LSD), phencyclidine (phenylcyclohexyl piperidine: PCP), strychnine, isoniazid, sympathomimetics (theophylline, ephedrine, etc.) (2) Drugs that cause hyperthermia due to hypermetabolism: Salicylates, thyroid hormones, sympathomimetics, alcohol withdrawal, sedative or hypnotic withdrawal (3) Drugs that cause hyperthermia by disturbing the body temperature center: Alcohol, antipsychotics (phenothiazines), inhaled or intravenous anesthetics (4) Drugs that cause hyperthermia by impairing heat dissipation: Anticholinergics, muscle relaxants, antipsychotics, sympathomimetics

[0088] The medication information includes, for each medication, a profile of temperature change over time, that is, the rise and fall of body temperature and the rate thereof.

[0089] In step S132, the processor 11 obtains time information indicating the current time from the clock RTC1.

[0090] In step S133, the processor 11 corrects the current body temperature of the patient 100 based on the medication information so as to offset the increase or decrease in the body temperature of the patient 100 caused by the medication. As described above, when the concentration of the medication in the blood with respect to elapsed time is represented by a Weibull distribution, the corrected body temperature Tc(t) is calculated from the current body temperature T(t) as follows:

[0091] Tc(t) =T(t)×(1+κ×(α / β α )×T(t) α-1 ×exp(-(T(t) / β) α ))

[0092] Here, α denotes a shape factor, β denotes a scale factor, and κ denotes a correction factor.

[0093] Here, "offsetting the increase or decrease in body temperature of the patient 100 caused by the drug" means at least partially offsetting the increase or decrease in body temperature caused by the drug.

[0094] FIG. 9 is a schematic diagram for explaining the medication-based body temperature correction process of FIG. 7. In FIG. 9, the thick solid line indicates the measured body temperature T(t), and the thick dashed line indicates the corrected body temperature Tc(t). The body temperature of the patient 100 began to rise at time 0, and when an antipyretic was administered to the patient 100 at time t10, the body temperature gradually decreased. Ten hours after the body temperature of the patient 100 began to rise, the effect of the antipyretic disappeared, and the body temperature of the patient 100 began to rise again. Thereafter, when an antipyretic was administered to the patient 100 at time t12, the body temperature gradually decreased. The processor 11 calculates the corrected body temperature Tc(t) by adding a temperature d11 to the body temperature T(t11) measured at time t11. Tc The processor 11 calculates the body temperature T(t13) measured at time t13. to temperature d13 By adding Tc Calculate (t13).

[0095] When administering an antipyretic to the patient 100, the processor 11 corrects the measured body temperature by increasing it, as shown in Fig. 9. On the other hand, when administering a drug that increases body temperature to the patient 100, the processor 11 corrects the measured body temperature by decreasing it.

[0096] By performing a body temperature correction process based on medication, the effects of the medication administered to the patient 100 can be reduced, and the risk related to the health condition of the patient 100 can be calculated more accurately than before.

[0097] [Body temperature correction processing based on diagnosis results] Even if the measured body temperature is the same, the magnitude of the risk may differ depending on the type of disease the patient has or is suspected of having. Below, we will explain a method for correcting the patient's body temperature to reduce the impact of the type of disease.

[0098] Fig. 10 is a flowchart showing a subroutine of body temperature correction processing based on diagnosis results, which is a fourth embodiment of step S102 in Fig. 2. In order to distinguish the body temperature correction processing based on diagnosis results from body temperature correction processing based on other patient condition information, the step of body temperature correction processing in Fig. 10 is indicated by the symbol S102D.

[0099] In step S141, the processor 11 acquires a diagnosis result by a doctor regarding a disease of the patient 100. The processor 11 may read out the pre-stored diagnosis result from the storage device 13, may acquire the diagnosis result via the input device 15, or may acquire the diagnosis result from an external server device (not shown) via the communication device 14.

[0100] In step S142, the processor 11 corrects the current body temperature of the patient 100 based on the diagnosis result. The corrected body temperature Td may be calculated from the current body temperature T and a coefficient k1 predetermined for each disease, for example, Td = T × k1. The coefficient k1 is set, for example, as follows:

[0101] Covid-19 (new coronavirus) 1 SARS 1 Norovirus infection 1.05 Cold (other than those mentioned above) 0.98 ·Hepatitis A, hepatitis C 1.03

[0102] The corrected body temperature Td may be calculated from the current body temperature T and a predetermined constant k2 for each disease, for example, Td = T + k2. In the case of seasonal influenza, the constant k2 may be set to, for example, +0.5.

[0103] By performing a temperature correction process based on the diagnosis results, the influence of the type of disease can be reduced, and the risk related to the health condition of the patient 100 can be calculated more accurately than before.

[0104] [Body temperature correction processing based on pulse rate] Generally, when a patient's body temperature rises, the pulse rate also increases. However, in some infections, the pulse rate may not increase significantly even when the body temperature rises. This condition is called "relative bradycardia." When relative bradycardia occurs, the patient's health is considered to be at higher risk than when relative bradycardia does not occur. Below, we will explain a method for correcting the patient's body temperature to take into account the effects of relative bradycardia.

[0105] Fig. 11 is a block diagram showing the configuration of a risk calculation system according to a modification of the first embodiment. The risk calculation system in Fig. 11 further includes a pulse meter 3 attached to the body of a patient 100, in addition to the risk calculation device 1 and thermometer 2 of the risk calculation system in Fig. 1.

[0106] The risk calculation device 1 in Figure 11 acquires the body temperature of the patient 100 from a thermometer 2, acquires the pulse of the patient 100 from a pulse meter 3, and calculates the risk related to the health condition of the patient 100 based on the body temperature and pulse of the patient 100. The risk calculation device 1 in Figure 11 is configured in the same way as the risk calculation device 1 in Figure 1, except that it is communicatively connected to the pulse meter 3 and executes risk calculation processing 102E, which will be described later.

[0107] The pulse meter 3 includes an electric pulse sensor 31, a signal processing circuit 32, and a communication device 33. The electric pulse sensor 31 acquires the pulse of the patient 100. The signal processing circuit 32 converts the pulse of the patient 100 acquired by the electric pulse sensor 31 into a format (for example, a digital value) that can be transmitted to the risk calculation device 1. The communication device 33 is communicatively connected to the risk calculation device 1, and transmits the pulse of the patient 100 to the risk calculation device 1.

[0108] The pulse meter 3 may be a dedicated device for measuring pulse, or may be another device having a function for measuring pulse, such as a pulse oximeter, an activity meter, a fatigue meter, or a glucose meter. The pulse meter 3 may be wirelessly connected to the risk calculation device 1 via Bluetooth (registered trademark) or WiFi (registered trademark), or may be wired to the risk calculation device 1. The pulse meter 3 may be provided separately from the thermometer 2, or may be integrated into the thermometer 2.

[0109] Fig. 12 is a flowchart showing a subroutine of pulse-based body temperature correction processing, which is a fifth example of step S102 in Fig. 2. In order to distinguish pulse-based body temperature correction processing from body temperature correction processing based on other patient condition information, the step of the body temperature correction processing in Fig. 12 is indicated by the symbol S102E. The processor 11 in Fig. 11 executes the risk calculation processing in Fig. 2, and executes the body temperature correction processing in Fig. 12 in step S102 in Fig. 2.

[0110] In step S151, the processor 11 acquires the measured pulse of the patient 100 from the pulse meter 3 via the communication device 14.

[0111] In step S152, the processor 11 calculates the relatively bradycardia based on the pulse rate, and corrects the current body temperature of the patient 100 based on the relatively bradycardia. Here, "correcting the current body temperature of the patient 100 based on the relatively bradycardia" includes correcting the current body temperature of the patient 100 so as to follow the magnitude of the difference between the actually measured first body temperature rise value and the second body temperature rise value estimated from the pulse rate. The corrected body temperature Te is calculated from the current body temperature T and the pulse rate p using the following equation:

[0112] Te = T + k3 × (measured body temperature rise value - body temperature rise value estimated from pulse rate) =T+k3×((T-Tm)-k4×(p-pm))

[0113] Tm indicates normal body temperature, and pm indicates normal pulse rate. k3 is a clinically determined constant, and is set to, for example, 0.2. k4 is set to, for example, 0.1 if the pulse rate increases by 10 beats per 1 degree increase in body temperature.

[0114] For example, if patient P1 has a normal body temperature Tm1=36.5 degrees and a normal pulse pm1=60 bpm, and has a measured body temperature T1=38.5 degrees and a measured pulse p1=80 bpm, then the corrected body temperature Te1 is calculated as follows:

[0115] Te1 =38.5+0.2×((38.5-36.5)-0.1×(80-60)) =38.5[℃]

[0116] In this case, the temperature rise estimated from the pulse rate p1 is 0.1×(80−60)=2 degrees, and the measured body temperature T1 agrees with this estimated value.

[0117] Also, if patient P2, who has a normal body temperature Tm2=36.8 degrees and a normal pulse pm2=60 bpm, has a measured body temperature T2=38.8 degrees and a measured pulse p2=65 bpm, the corrected body temperature Te2 is calculated as follows:

[0118] Te2 =38.8+0.2×((38.8-36.8)-0.1×(65-60)) =39.1[℃]

[0119] In this case, the temperature rise estimated from pulse rate p2 is 0.1 × (65 - 60) = 0.5 degrees, but the actual measured temperature rise is 2 degrees, so patient P2 can be said to be in a state of relatively bradycardia. Considering the risk of relatively bradycardia, patient P2's corrected temperature Te2 is increased by 0.3 degrees from the measured temperature T2.

[0120] Although patients P1 and P2 have the same level of fever compared to their normal body temperatures, patient P2's pulse rate barely increases from its normal value, which is judged to be a risk of patient P2 becoming seriously ill. As a result, patient P2's body temperature is corrected to increase.

[0121] 13 is a graph illustrating the occurrence of relatively bradycardia. Plots below the bold dashed line indicate relatively bradycardia. The lower the pulse rate below the bold dashed line, the greater the severity of the relatively bradycardia.

[0122] According to the formula for the corrected body temperature Te described above, when the body temperature is the same, the smaller the pulse rate, the larger the corrected body temperature Te, and it can be seen that the risk caused by relatively bradycardia is reflected in the risk regarding the health condition of the patient 100 that is ultimately determined.

[0123] By performing a temperature correction process based on the pulse, the risk related to the health condition of the patient 100 can be calculated more accurately than before, so as to reduce the influence of the relationship between an increase in the patient's pulse rate and an increase in body temperature.

[0124] Since the influence of the relationship between increased pulse rate and increased body temperature is reduced, body temperature can be effectively corrected even when the pulse rate is affected by differences between home and hospital care, or by whether or not oxygen is inhaled.

[0125] As described above, by performing the risk calculation process including the body temperature correction process, it is possible to calculate the risk related to the health condition of the patient 100 more accurately than before, regardless of the condition of the patient 100.

[0126] The processor 11 may execute a combination of two or more of the following: a body temperature correction process based on a circadian rhythm, a body temperature correction process based on a basal metabolic rate, a body temperature correction process based on medication, a body temperature correction process based on a diagnosis result, and a body temperature correction process based on a pulse rate, thereby enabling a more accurate calculation of the risk related to the health condition of the patient 100.

[0127] The set value may be equivalently corrected instead of correcting the measured current body temperature of the patient 100. Next, the risk calculation process including the set value correction process will be described.

[0128] [Risk calculation process including setting value correction process] Fig. 14 is a flowchart showing a second example of the risk calculation process executed by the processor 11 of Fig. 1, which includes a set value correction process. According to the process of Fig. 14, the processor 11 corrects (i.e., sets or resets) the set value before calculating the risk value.

[0129] In step S201, the processor 11 acquires the current measured body temperature of the patient 100 from the thermometer 2 via the communication device 14.

[0130] In step S202, the processor 11 executes a setting value correction process to correct the setting value based on the patient condition information.

[0131] In step S203, the processor 11 calculates a risk value based on the measured body temperature and the corrected set value.

[0132] In step S204, the processor 11 outputs the calculated risk value to the display device 16.

[0133] The processor 11 periodically repeats the risk calculation process of FIG.

[0134] As described above, the patient condition information includes, for example, at least one of the circadian rhythm of the body temperature of the patient 100, the basal metabolic rate of the patient 100 or information associated therewith, medication information on the medicine administered to the patient 100, the diagnosis result for the disease of the patient 100, and the pulse rate of the patient 100. Below, the setting value correction process based on the circadian rhythm, the setting value correction process based on the basal metabolic rate, the setting value correction process based on the medication, the setting value correction process based on the diagnosis result, and the setting value correction process based on the pulse rate will be described.

[0135] [Setting value correction processing based on circadian rhythm] Figure 15 shows Figure 14 15 is a flowchart showing a subroutine of the setting value correction process based on the circadian rhythm, which is a first example of step S202 in FIG. 15. In order to distinguish the setting value correction process based on the circadian rhythm from the setting value correction process based on other patient condition information, the step of the setting value correction process in FIG. 15 is indicated by the reference symbol S202A.

[0136] In step S211, the processor 11 reads the circadian rhythm of the body temperature of the patient 100 from the storage device 13.

[0137] In step S212, the processor 11 acquires time information indicating the current time from the clock RTC1, or acquires behavioral information indicating whether the patient 100 is currently asleep or awake via the input device 15.

[0138] Steps S211 and S212 are the same as steps S111 and S112 in FIG.

[0139] In step S213, the processor 11 corrects the set value based on the circadian rhythm and the current time or behavioral information so as to follow the fluctuations in body temperature of the patient 100 due to the circadian rhythm. Here, "following the fluctuations in body temperature" means at least partially following the rise or fall in body temperature due to the circadian rhythm.

[0140] By performing a setting value correction process based on the circadian rhythm, the influence of circadian fluctuations in the body temperature of the patient 100 can be reduced, and the risk related to the health condition of the patient 100 can be calculated more accurately than before, regardless of the time of day.

[0141] [Setting value correction process based on basal metabolic rate] Figure 16 shows Figure 14 16 is a flowchart showing a subroutine of the setting value correction process based on the basal metabolic rate, which is a second example of step S202 in FIG. 16. In order to distinguish the setting value correction process based on the basal metabolic rate from the setting value correction process based on other patient condition information, the step of the setting value correction process in FIG. 16 is indicated by the symbol S202B.

[0142] In step S221, the processor 11 acquires physical characteristic information of the patient 100.

[0143] In step S222, the processor 11 calculates the basal metabolic rate of the patient 100 based on the physical characteristic information of the patient 100.

[0144] Steps S221 and S222 are the same as steps S121 and S122 in FIG.

[0145] In step S223, the processor 11 corrects the set value based on the basal metabolic rate so as to follow the increase or decrease in the basal metabolic rate. Here, "following the increase or decrease in the basal metabolic rate" means at least partially following the increase or decrease in body temperature caused by individual differences in the basal metabolic rate.

[0146] By performing the setting value correction process based on the basal metabolic rate, the influence of individual differences in the basal metabolic rate can be reduced, and the risk related to the health condition of the patient 100 can be calculated more accurately than before.

[0147] [Setting value correction process based on medication] Figure 17 shows Figure 1417 is a flowchart showing a subroutine of medication-based setting value correction processing, which is a third example of step S202 in FIG. 17. In order to distinguish medication-based setting value correction processing from setting value correction processing based on other patient condition information, the step of the setting value correction processing in FIG. 17 is indicated by the symbol S202C.

[0148] In step S231, the processor 11 acquires medication information about the medication administered to the patient 100.

[0149] In step S232, the processor 11 obtains time information indicating the current time from the clock RTC1.

[0150] Steps S231 and S232 are the same as steps S131 and S132 in FIG.

[0151] In step S233, the processor 11 corrects the set value based on the medication information so as to follow the rise or fall in the body temperature of the patient 100 caused by the medication. Here, "following the rise or fall in the body temperature of the patient 100 caused by the medication" means at least partially following the rise or fall in the body temperature caused by the medication.

[0152] By performing the set value correction process based on medication, the influence of the drug administered to the patient 100 can be reduced, and the risk related to the health condition of the patient 100 can be calculated more accurately than before.

[0153] [Setting value correction processing based on diagnostic results] Figure 18 shows Figure 14 18 is a flowchart showing a subroutine of the setting value correction process based on a diagnosis result, which is a fourth example of step S202 in FIG. 18. In order to distinguish the setting value correction process based on a diagnosis result from the setting value correction process based on other patient condition information, the step of the setting value correction process in FIG. 18 is indicated by the symbol S202D.

[0154] In step S241, the processor 11 obtains a diagnosis by a doctor about the disease of the patient 100. Step S241 is similar to step S114 in FIG.

[0155] In step S242, the processor 11 corrects the set value based on the diagnosis result. The corrected set value is calculated by multiplying the original set value by a coefficient predetermined for each disease, or by adding or subtracting a constant predetermined for each disease to or from the original set value.

[0156] By performing the setting value correction process based on the diagnosis results, the influence of the type of disease can be reduced, and the risk related to the health condition of the patient 100 can be calculated more accurately than before.

[0157] [Setting value correction processing based on pulse rate] Figure 19 shows Figure 14 19 is a flowchart showing a subroutine of pulse-based setting value correction processing, which is a fifth example of step S202 in FIG. 19. In order to distinguish pulse-based setting value correction processing from setting value correction processing based on other patient condition information, the step of the setting value correction processing in FIG. 19 is indicated by the symbol S202E.

[0158] In step S251, the processor 11 acquires the measured pulse of the patient 100 from the pulse meter 3 via the communication device 14.

[0159] Step S251 is similar to step S151 in FIG.

[0160] In step S252, the processor 11 determines, based on the pulse rate, a first measured body temperature rise value; The set value of the patient 100 is corrected so as to offset the magnitude of the difference with the second body temperature rise value estimated from the pulse rate.

[0161] By performing the pulse-based setting value correction process, the influence of relatively bradycardia is taken into consideration, and the risk related to the health condition of the patient 100 can be calculated more accurately than before.

[0162] As described above, by performing the risk calculation process including the set value correction process, it is possible to calculate the risk related to the health condition of the patient 100 more accurately than before, regardless of the condition of the patient 100.

[0163] The processor 11 may execute a combination of two or more of the following: a circadian rhythm-based setting value correction process, a basal metabolic rate-based setting value correction process, a medication-based setting value correction process, a diagnosis result-based setting value correction process, and a pulse rate-based setting value correction process, thereby enabling more accurate calculation of the risk associated with the health condition of the patient 100.

[0164] The calculated risk value may be equivalently corrected instead of correcting the measured current body temperature of the patient 100. Next, the risk calculation process including the risk value correction process will be described.

[0165] [Risk calculation process including risk value correction process] Fig. 20 is a flowchart showing a third example of the risk calculation process executed by the processor 11 of Fig. 1, which includes a risk value correction process. According to the process of Fig. 20, the processor 11 calculates the risk value and then corrects (i.e., increases or decreases) the risk value.

[0166] In step S301, the processor 11 acquires the current measured body temperature of the patient 100 from the thermometer 2 via the communication device 14.

[0167] In step S302, the processor 11 calculates a risk value based on the measured body temperature and the set value.

[0168] In step S303, the processor 11 executes a risk value correction process to correct the risk value based on the patient condition information.

[0169] In step S304, the processor 11 outputs the corrected risk value to the display device 16.

[0170] The processor 11 periodically repeats the risk calculation process of FIG.

[0171] As described above, the patient condition information includes, for example, at least one of the circadian rhythm of the body temperature of the patient 100, the basal metabolic rate of the patient 100 or information associated therewith, medication information on the medication administered to the patient 100, the diagnosis result for the disease of the patient 100, and the pulse rate of the patient 100. Below, the risk value correction process based on the circadian rhythm, the risk value correction process based on the basal metabolic rate, the risk value correction process based on medication, the risk value correction process based on the diagnosis result, and the risk value correction process based on the pulse rate will be described.

[0172] [Circadian rhythm-based risk value correction processing] Figure 21 shows Figure 20 21 is a flowchart showing a subroutine of risk value correction processing based on circadian rhythms, illustrating a first example of step S303 in FIG. 21. In order to distinguish risk value correction processing based on circadian rhythms from risk value correction processing based on other patient condition information, the step of risk value correction processing in FIG. 21 is denoted by the reference symbol S303A.

[0173] In step S311, the processor 11 reads the circadian rhythm of the body temperature of the patient 100 from the storage device 13.

[0174] In step S312, the processor 11 acquires time information indicating the current time from the clock RTC1, or acquires behavioral information indicating whether the patient 100 is currently asleep or awake via the input device 15.

[0175] Steps S311 and S312 are the same as steps S111 and S112 in FIG.

[0176] In step S313, the processor 11 corrects the calculated risk value based on the circadian rhythm and the current time or behavioral information so as to offset fluctuations in the body temperature of the patient 100 due to the circadian rhythm. Here, "offsetting fluctuations in body temperature" means at least partially offsetting increases or decreases in body temperature due to the circadian rhythm.

[0177] By performing risk value correction processing based on circadian rhythms, the effects of circadian rhythm fluctuations in the body temperature of the patient 100 can be reduced, and the risk related to the health condition of the patient 100 can be calculated more accurately than before, regardless of the time of day.

[0178] [Risk value correction processing based on basal metabolic rate] Figure 22 shows Figure 20 22 is a flowchart showing a subroutine of risk value correction processing based on basal metabolic rate, which is a second example of step S303 in FIG. 22. In order to distinguish risk value correction processing based on basal metabolic rate from risk value correction processing based on other patient condition information, the step of risk value correction processing in FIG. 22 is designated by the reference symbol S303B.

[0179] In step S321, the processor 11 acquires physical characteristic information of the patient 100.

[0180] In step S322, the processor 11 calculates the basal metabolic rate of the patient 100 based on the physical characteristic information of the patient 100.

[0181] Steps S321 and S322 are the same as steps S121 and S122 in FIG.

[0182] In step S323, the processor 11 corrects the calculated risk value based on the basal metabolic rate so as to offset increases or decreases in the basal metabolic rate. Here, "offsetting increases or decreases in the basal metabolic rate" means at least partially offsetting increases or decreases in body temperature caused by individual differences in the basal metabolic rate.

[0183] By performing risk value correction processing based on the basal metabolic rate, the influence of individual differences in basal metabolic rate can be reduced, and the risk related to the health condition of the patient 100 can be calculated more accurately than before.

[0184] [Risk value correction process based on medication] Figure 23 shows Figure 20 23 is a flowchart showing a subroutine of medication-based risk value correction processing, which is a third example of step S303 in FIG. 23. In order to distinguish medication-based risk value correction processing from risk value correction processing based on other patient condition information, the step of risk value correction processing in FIG. 23 is designated by the reference symbol S303C.

[0185] In step S331, the processor 11 acquires medication information about the medication administered to the patient 100.

[0186] In step S332, the processor 11 obtains time information indicating the current time from the clock RTC1.

[0187] Steps S331 and S332 are the same as steps S131 and S132 in FIG.

[0188] In step S333, the processor 11 corrects the calculated risk value based on the medication information so as to offset the increase or decrease in body temperature of the patient 100 caused by the medication. Here, "offsetting the increase or decrease in body temperature of the patient 100 caused by the medication" means at least partially offsetting the increase or decrease in body temperature caused by the medication.

[0189] By performing risk value correction processing based on medication, the influence of the medicine administered to the patient 100 can be reduced, and the risk related to the health condition of the patient 100 can be calculated more accurately than before.

[0190] [Risk value correction processing based on diagnosis results] Figure 24 shows Figure 2024 is a flowchart showing a subroutine of risk value correction processing based on diagnosis results, which is a fourth example of step S303 in FIG. 24. In order to distinguish risk value correction processing based on diagnosis results from risk value correction processing based on other patient condition information, the step of risk value correction processing in FIG. 24 is designated by the reference symbol S303D.

[0191] In step S341, the processor 11 obtains a diagnosis by a doctor about the disease of the patient 100. Step S341 is similar to step S114 in FIG.

[0192] In step S342, the processor 11 corrects the calculated risk value based on the diagnosis result. The corrected risk value is calculated by multiplying the original calculated risk value by a coefficient predetermined for each disease, or by adding or subtracting a constant predetermined for each disease to the original calculated risk value.

[0193] By performing risk value correction processing based on the diagnosis results, the influence of the type of disease can be reduced, and the risk related to the health condition of the patient 100 can be calculated more accurately than before.

[0194] [Risk value correction processing based on pulse rate] Figure 25 shows Figure 20 25 is a flowchart showing a subroutine of pulse-based risk value correction processing, which is a fifth example of step S303 in FIG. 25. In order to distinguish pulse-based risk value correction processing from risk value correction processing based on other patient condition information, the step of risk value correction processing in FIG. 25 is denoted by the reference symbol S303E.

[0195] In step S351, the processor 11 acquires the measured pulse of the patient 100 from the pulse meter 3 via the communication device 14.

[0196] Step S351 is similar to step S151 in FIG.

[0197] In step S352, the processor 11 corrects the calculated risk value based on the pulse rate so that it follows the magnitude of the difference between the actually measured first body temperature rise value and the second body temperature rise value estimated from the pulse rate.

[0198] By performing risk value correction processing based on the pulse rate, the influence of relatively bradycardia can be taken into consideration, and the risk related to the health condition of the patient 100 can be calculated more accurately than before.

[0199] As described above, by performing the risk calculation process including the risk value correction process, it is possible to calculate the risk related to the health condition of the patient 100 more accurately than before, regardless of the condition of the patient 100.

[0200] The processor 11 may execute a combination of two or more of the risk value correction process based on circadian rhythm, the risk value correction process based on basal metabolic rate, the risk value correction process based on medication, the risk value correction process based on diagnostic results, and the risk value correction process based on pulse rate, thereby enabling a more accurate calculation of the risk related to the health condition of the patient 100.

[0201] [Summary of the first embodiment] The storage device 13 of the risk calculation device 1 of Figure 1 stores a program including instructions executable by a processor of a computer for calculating a risk related to the health condition of the patient 100. The instructions cause the processor to receive the temperature of the patient 100, patient The first step is to acquire the state information, and the second step is to compare the body temperature of the patient 100 with a reference temperature to calculate a comparison result, and calculate a risk related to the health state of the patient 100 from the comparison result. patient The process of correcting the body temperature based on the state information and comparing the body temperature with the reference temperature patient setting a reference temperature based on the status information; patient and a process of increasing or decreasing the comparison result based on the state information.

[0202] As described above, the parameters measured to calculate the risk of the patient's 100 health condition may fluctuate due to factors not directly related to the patient's illness, such as circadian rhythm, basal metabolic rate, and medication. As a result, the risk of the patient's 100 health condition may be calculated incorrectly. Furthermore, even if the measured values ​​of the parameters are the same, the magnitude of the risk varies depending on the type of illness the patient has or is suspected of having. According to the risk calculation device 1 according to the embodiment, the risk of the patient's 100 health condition can be accurately calculated in real time, regardless of the patient's condition, by correcting the current body temperature, temperature threshold, or risk value based on patient condition information. Therefore, signs of the onset or worsening of illness can be accurately detected at all times.

[0203] Conventionally, doctors have corrected measured body temperatures based on their own experience. However, the risk calculation device 1 according to the embodiment can automatically correct the current body temperature, temperature threshold, or risk value, reducing the workload of medical professionals.

[0204] [Second embodiment] 26 is a block diagram showing the configuration of a risk calculation system according to the second embodiment. The risk calculation system in FIG. 26 includes a thermometer 2, a pulse meter 3, a gateway device 4, a server device 5, and a client device 6.

[0205] 26 are attached to the body of a patient 100, and acquire the body temperature and pulse rate of the patient 100, respectively, in the same manner as the thermometer 2 and pulse rate meter 3 of FIG.

[0206] The gateway device 4 includes a communication device 41, a signal processing circuit 42, and a communication device 43. The communication device 41 is communicatively connected to the thermometer 2 and the pulse meter 3, and receives the body temperature of the patient 100 from the thermometer 2, and receives the pulse of the patient 100 from the pulse meter 3. The signal processing circuit 42 converts the received body temperature and pulse into a format that can be transmitted to the server device 5. The communication device 43 is communicatively connected to the server device 5, and transmits the body temperature and pulse to the server device 5.

[0207] The gateway device 4 may be communicatively connected to other devices that acquire parameters indicating the state of the patient 100, such as a pulse oximeter, an activity meter, a fatigue meter, or a glucometer, and may transmit the parameters acquired from these devices to the server device 5. The gateway device 4 may be wirelessly connected to the server device 5 by LTE or the like, or may be wired connected to the server device 5.

[0208] The server device 5 includes a bus 50, a processor 51, a memory 52, a storage device 53, a communication device 54, and a clock RTC 5. The processor 51 controls the overall operation of the server device 5. The memory 52 temporarily stores programs and data necessary for the operation of the server device 5. The storage device 53 is a non-volatile storage medium that stores programs and data necessary for the operation of the server device 5. The communication device 54 is communicatively connected to the gateway device 4, and acquires the body temperature and pulse rate of the patient 500 from the gateway device 4. The communication device 54 is also communicatively connected to the client device 6. The clock RTC 5 provides time information indicating the current time. The processor 51, the memory 52, the storage device 53, and the communication device 54 are connected to one another via the bus 50.

[0209] The client device 6 includes a bus 60, a processor 61, a memory 62, a storage device 63, a communication device 64, an input device 65, a display device 66, and a clock RTC 6. 61 controls the overall operation of the client device 6. 62 The storage device temporarily stores programs and data required for the operation of the client device 6. 63is a non-volatile storage medium that stores programs and data required for the operation of the client device 6. 64 is communicably connected to the server device 5. 65 receives user input that controls the operation of the client device 6. 65 includes, for example, a keyboard and a pointing device. 66 displays the calculated risk of the patient 500's health condition. 6 provides time information indicating the current time. 61 , memory 62 , storage device 63 , communication devices 64 , input device 65 , and a display device 66 is a bus 60 are connected to each other via

[0210] 26, the processor 51 of the server device 5 may execute the risk calculation process of FIG. 2, FIG. 14, or FIG. 20, and the client device 6 may acquire the calculated risk related to the health condition of the patient 500 from the server device 5 and display it on the display device 66. Alternatively, the server device 5 may temporarily store the measured body temperature and pulse rate of the patient 100 and the patient condition information in the storage device 53. In this case, the processor 61 of the client device 6 acquires the body temperature and pulse rate of the patient 100 and the patient condition information from the server device 5, executes the risk calculation process of FIG. 2, FIG. 14, or FIG. 20, and displays the calculated risk related to the health condition of the patient 500 on the display device 66. A computer-executable program for calculating the risk related to the health condition of the patient 100 is stored in the storage device 53 of the server device 5 or the storage device 63 of the client device 6.

[0211] According to the second embodiment, the risk calculation system can be configured with a high degree of freedom.

[0212] [Other variations] The processor 11 may execute a combination of two or three of the risk calculation process including the body temperature correction process, the risk calculation process including the set value correction process, and the risk calculation process including the risk value correction process.

[0213] "Summary of the embodiment" The risk calculation device, risk calculation system, and program according to each aspect of the present disclosure may have the following configuration.

[0214] The risk calculation device according to the first aspect comprises: A risk calculation device for calculating a risk related to a patient's health condition, an input unit for acquiring the patient's body temperature and patient condition information; a calculation unit that compares the body temperature acquired by the input unit with a reference temperature to calculate a comparison result, and outputs a risk related to the health condition of the patient from the comparison result; The calculation unit performs at least one of the following processes: correcting the body temperature based on the patient condition information when comparing the body temperature with the reference temperature; setting the reference temperature based on the patient condition information when comparing the body temperature with the reference temperature; and increasing or decreasing the comparison result based on the patient condition information.

[0215] According to the risk calculation device of the second aspect, in the risk calculation device of the first aspect, the patient condition information includes a circadian rhythm variation in the patient's body temperature; The calculation unit performs at least one of the following processes based on fluctuations due to the circadian rhythm: correcting the body temperature; setting the reference temperature; and increasing or decreasing the comparison result.

[0216] According to the risk calculation device of the third aspect, in the risk calculation device of the second aspect, The calculation unit performs at least one of the following processes: correcting the body temperature to offset fluctuations due to the circadian rhythm; setting the reference temperature; and increasing or decreasing the comparison result.

[0217] According to the risk calculation device of the fourth aspect, in the risk calculation device of the second aspect, The calculation unit performs at least one of the following processes: correcting the body temperature to follow fluctuations due to the circadian rhythm; setting the reference temperature; and increasing or decreasing the comparison result.

[0218] According to the risk calculation device of the fifth aspect, in the risk calculation device of one of the second to fourth aspects, The input unit continuously acquires the patient condition information; The calculation unit performs at least one of the following processes based on the time when the input unit acquires the patient's body temperature: correcting the body temperature; setting the reference temperature; and increasing or decreasing the comparison result.

[0219] According to the risk calculation device of the sixth aspect, in the risk calculation device of one of the second to fourth aspects, the patient status information includes behavioral information indicating whether the patient is currently asleep or awake; The calculation unit performs at least one of a process of correcting the body temperature, a process of setting the reference temperature, and a process of increasing or decreasing the comparison result based on the behavior information.

[0220] According to the seventh aspect of the risk calculation device, in the risk calculation device according to one of the first to sixth aspects, the patient condition information includes a basal metabolic rate of the patient or includes information for calculating a basal metabolic rate of the patient; The calculation unit performs at least one of the following processes based on the patient's basal metabolic rate and a reference basal metabolic rate: correcting the body temperature; setting the reference temperature; and increasing or decreasing the comparison result.

[0221] According to the risk calculation device of the eighth aspect, in the risk calculation device of the seventh aspect, The calculation unit performs at least one of the following processes: correcting the body temperature so as to offset an increase or decrease in the patient's basal metabolic rate relative to the reference basal metabolic rate; setting the reference temperature; and increasing or decreasing the comparison result.

[0222] According to the risk calculation device of the ninth aspect, in the risk calculation device of the seventh aspect, The calculation unit performs at least one of the following processes: correcting the body temperature to follow increases or decreases in the patient's basal metabolic rate relative to the standard basal metabolic rate; setting the standard temperature; and increasing or decreasing the comparison result.

[0223] According to the risk calculation device of the tenth aspect, in the risk calculation device of one of the first to ninth aspects, the patient condition information includes medication information for medications administered to the patient; The calculation unit performs at least one of a process of correcting the body temperature, a process of setting the reference temperature, and a process of increasing or decreasing the comparison result based on the medication information.

[0224] According to the risk calculation device of the eleventh aspect, in the risk calculation device of the tenth aspect, The calculation unit performs at least one of the following processes: correcting the body temperature to offset an increase or decrease in the patient's body temperature caused by the drug; setting the reference temperature; and increasing or decreasing the comparison result.

[0225] According to the risk calculation device of the twelfth aspect, in the risk calculation device of the tenth aspect, The calculation unit performs at least one of the following processes: correcting the body temperature to follow an increase or decrease in the patient's body temperature caused by the drug; setting the reference temperature; and increasing or decreasing the comparison result.

[0226] According to the risk calculation device of the thirteenth aspect, in the risk calculation device of one of the tenth to twelfth aspects, The medication information includes at least one of the type of the medication, the time elapsed since the medication was administered, and the administration method of the medication.

[0227] According to the risk calculation device of the fourteenth aspect, in the risk calculation device of one of the first to thirteenth aspects, the patient status information includes a diagnosis of a disease of the patient; The calculation unit performs at least one of a process of correcting the body temperature, a process of setting the reference temperature, and a process of increasing or decreasing the comparison result based on the diagnosis result.

[0228] According to the risk calculation device of the fifteenth aspect, in the risk calculation device of one of the first to fourteenth aspects, the patient condition information includes the patient's pulse; The calculation unit calculating a relatively bradycardia based on said pulse rate; Based on the relatively bradycardia, at least one of the following processes is performed: correcting the body temperature; setting the reference temperature; and increasing or decreasing the comparison result.

[0229] According to the risk calculation device of the sixteenth aspect, in the risk calculation device of the fifteenth aspect, The calculation unit performs at least one of the following processes: correcting the body temperature so as to follow the magnitude of the difference between an actually measured first body temperature rise value and a second body temperature rise value estimated from the pulse rate; setting the reference temperature; and increasing or decreasing the comparison result.

[0230] According to the risk calculation device of the seventeenth aspect, in the risk calculation device of the fifteenth aspect, The calculation unit performs at least one of the following processes: correcting the body temperature so as to offset the magnitude of the difference between the actually measured first body temperature rise value and the second body temperature rise value estimated from the pulse rate; setting the reference temperature; and increasing or decreasing the comparison result.

[0231] A risk calculation system according to an eighteenth aspect comprises: a temperature sensor for measuring the patient's body temperature; and a risk calculation device according to one of the first to seventeenth aspects.

[0232] According to the program of the nineteenth aspect, 1. A program comprising instructions executable by a processor of a computer for calculating a risk associated with a health condition in a patient, the instructions causing the processor to: a first step of acquiring the patient's temperature and patient condition information; a second step of comparing the patient's body temperature with a reference temperature to calculate a comparison result, and calculating a risk related to the patient's health condition from the comparison result; The second step includes at least one of the following processes: correcting the body temperature based on the patient condition information when comparing the body temperature with the reference temperature; setting the reference temperature based on the patient condition information when comparing the body temperature with the reference temperature; and increasing or decreasing the comparison result based on the patient condition information. [Industrial Applicability]

[0233] The risk calculation device, risk calculation system, and program according to the aspects of the present invention can be used to calculate the risk associated with a patient's health condition. [Explanation of symbols]

[0234] 1 Risk Calculator 2. Thermometer 3. Pulse monitor 4. Gateway Device 5. Server equipment 6 Client Device 10 Bus 11 processors 12 Memory 13 Storage device 14. Communications equipment 15 Input Devices 16 Display device 21 Temperature sensor 22 Signal processing circuit 23 Communication equipment 31 Electric pulse sensor 32 Signal processing circuit 33 Communication equipment 41 Communication equipment 42 Signal processing circuit 43 Communication equipment 50 Bus 51 processors 52 memory 53 Storage device 54 Communication equipment 60 Bus 61 processors 62 memory 63 Storage device 64 Communication Equipment 65 Input Devices 66 Display device 100 patients RTC1, RTC5, RTC6 clocks

Claims

1. A risk calculation device for calculating a risk related to a patient's health condition, an input unit for acquiring the patient's body temperature and patient condition information; a calculation unit that compares the body temperature acquired by the input unit with a reference temperature to calculate a comparison result, and outputs a risk related to the health condition of the patient from the comparison result; the calculation unit performs at least one of the following processes: a process of correcting the body temperature based on the patient condition information when comparing the body temperature with the reference temperature; a process of setting the reference temperature based on the patient condition information when comparing the body temperature with the reference temperature; and a process of increasing or decreasing the comparison result based on the patient condition information; the patient condition information includes medication information for medications administered to the patient; The calculation unit performs at least one of a process of correcting the body temperature, a process of setting the reference temperature, and a process of increasing or decreasing the comparison result based on the medication information. Risk calculator.

2. the calculation unit performs at least one of a process of correcting the body temperature so as to offset an increase or decrease in the body temperature of the patient caused by the drug, a process of setting the reference temperature, and a process of increasing or decreasing the comparison result; The risk calculation device according to claim 1 .

3. the calculation unit performs at least one of a process of correcting the body temperature so as to follow an increase or decrease in the body temperature of the patient caused by the drug, a process of setting the reference temperature, and a process of increasing or decreasing the comparison result; The risk calculation device according to claim 1 .

4. The medication information includes at least one of the type of the medication, the elapsed time since the medication was administered, and the administration method of the medication. The risk calculation device according to claim 1 .

5. the patient condition information includes a circadian rhythm variation in the patient's body temperature; the calculation unit performs at least one of a process of correcting the body temperature based on the fluctuation due to the circadian rhythm, a process of setting the reference temperature, and a process of increasing or decreasing the comparison result; A risk calculation device according to any one of claims 1 to 4.

6. the calculation unit performs at least one of a process of correcting the body temperature so as to offset the fluctuation due to the circadian rhythm, a process of setting the reference temperature, and a process of increasing or decreasing the comparison result; 6. The risk calculation device according to claim 5.

7. the calculation unit performs at least one of a process of correcting the body temperature so as to follow fluctuations due to the circadian rhythm, a process of setting the reference temperature, and a process of increasing or decreasing the comparison result; 6. The risk calculation device according to claim 5.

8. The input unit continuously acquires the patient condition information; the calculation unit performs at least one of a process of correcting the body temperature, a process of setting the reference temperature, and a process of increasing or decreasing the comparison result based on the time when the input unit acquired the body temperature of the patient; 6. The risk calculation device according to claim 5.

9. the patient status information includes behavioral information indicating whether the patient is currently asleep or awake; the calculation unit performs at least one of a process of correcting the body temperature, a process of setting the reference temperature, and a process of increasing or decreasing the comparison result based on the behavior information; 6. The risk calculation device according to claim 5.

10. the patient condition information includes a basal metabolic rate of the patient or includes information for calculating a basal metabolic rate of the patient; the calculation unit performs at least one of a process of correcting the body temperature based on the basal metabolic rate of the patient and a reference basal metabolic rate, a process of setting the reference temperature, and a process of increasing or decreasing the comparison result; A risk calculation device according to any one of claims 1 to 4.

11. the calculation unit performs at least one of a process of correcting the body temperature so as to offset an increase or decrease in the basal metabolic rate of the patient relative to the reference basal metabolic rate, a process of setting the reference temperature, and a process of increasing or decreasing the comparison result. The risk calculation device according to claim 10.

12. the calculation unit performs at least one of a process of correcting the body temperature so as to follow an increase or decrease in the basal metabolic rate of the patient relative to the reference basal metabolic rate, a process of setting the reference temperature, and a process of increasing or decreasing the comparison result. The risk calculation device according to claim 10.

13. the patient status information includes a diagnosis of a disease of the patient; the calculation unit performs at least one of a process of correcting the body temperature, a process of setting the reference temperature, and a process of increasing or decreasing the comparison result based on the diagnosis result; A risk calculation device according to any one of claims 1 to 4.

14. the patient condition information includes the patient's pulse; The calculation unit calculating a relatively bradycardia based on said pulse rate; performing at least one of a process of correcting the body temperature, a process of setting the reference temperature, and a process of increasing or decreasing the comparison result based on the relatively bradycardia; A risk calculation device according to any one of claims 1 to 4.

15. The calculation unit performs at least one of the following processes: correcting the body temperature so as to follow the magnitude of the difference between the actually measured first body temperature rise value and the second body temperature rise value estimated from the pulse rate; setting the reference temperature; and increasing or decreasing the comparison result.

15. The risk calculation device according to claim 14.

16. the calculation unit performs at least one of a process of correcting the body temperature so as to cancel out the magnitude of the difference between the actually measured first body temperature rise value and the second body temperature rise value estimated from the pulse rate, a process of setting the reference temperature, and a process of increasing or decreasing the comparison result; 15. The risk calculation device according to claim 14.

17. a temperature sensor for measuring the patient's body temperature; and a risk calculation device according to any one of claims 1 to 4. Risk calculation system.

18. A risk calculation device for calculating a risk related to a patient's health condition, an input unit for acquiring the patient's body temperature and patient condition information; a calculation unit that compares the body temperature acquired by the input unit with a reference temperature to calculate a comparison result, and outputs a risk related to the health condition of the patient from the comparison result; the calculation unit performs at least one of the following processes: a process of correcting the body temperature based on the patient condition information when comparing the body temperature with the reference temperature; a process of setting the reference temperature based on the patient condition information when comparing the body temperature with the reference temperature; and a process of increasing or decreasing the comparison result based on the patient condition information; the patient condition information includes a circadian rhythm variation of the patient's body temperature and behavioral information indicating whether the patient is currently asleep or awake; The calculation unit performs at least one of the following processes: a process of correcting the body temperature to approach an average body temperature due to the circadian rhythm based on the fluctuation due to the circadian rhythm and the behavioral information; a process of setting the reference temperature based on the fluctuation due to the circadian rhythm and based on time information or the behavioral information; and a process of increasing or decreasing the comparison result based on the fluctuation due to the circadian rhythm and the behavioral information to offset the fluctuation in the body temperature of the patient due to the circadian rhythm. Risk calculator.

19. The process of setting the reference temperature is set so as to follow fluctuations in the patient's body temperature due to the circadian rhythm.

19. The risk calculation device of claim 18.

20. A risk calculation device for calculating a risk related to a patient's health condition, an input unit for acquiring the patient's body temperature and patient condition information; a calculation unit that compares the body temperature acquired by the input unit with a reference temperature to calculate a comparison result, and outputs a risk related to the health condition of the patient from the comparison result; the calculation unit performs at least one of the following processes: a process of correcting the body temperature based on the patient condition information when comparing the body temperature with the reference temperature; a process of setting the reference temperature based on the patient condition information when comparing the body temperature with the reference temperature; and a process of increasing or decreasing the comparison result based on the patient condition information; the patient condition information includes a basal metabolic rate of the patient or includes information for calculating a basal metabolic rate of the patient; the calculation unit performs at least one of a process of correcting the body temperature based on the basal metabolic rate of the patient and a reference basal metabolic rate, a process of setting the reference temperature, and a process of increasing or decreasing the comparison result; Risk calculator.

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