JP2008165679A - Incident analysis system and incident analysis program - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To improve accuracy in medical accident prevention, regarding an incident analysis system and its program intended for prevention of medical accidents. <P>SOLUTION: The incident analysis system is provided with: an input section 11 for input of information related to the occurrence of an accident factor in a plurality of related medical practices in terms of work procedures; a calculation section 13 for quantitatively calculating accident occurrence prediction in a medical practice at present or future time point based on the severity of the input accident factor and the relevance between the medical practices or accident factors; and a warning notification section 15 for outputting the calculated accident occurrence prediction. <P>COPYRIGHT: (C)2008,JPO&INPIT

Description

  The present invention relates to an incident analysis system and its program for the purpose of preventing medical accidents.

  In Patent Literature 1, a medical action scheduled to be input by the portable information input device 100 is collated with information held by the medical plan information management device 200, and if there is an error, a warning is issued and a medical performance log information 10 is stored. Store as part. The medical accident prevention information collection device 300 extracts the medical accident prevention performance information from the medical performance log information 10 and transmits it as the medical accident prevention performance information 20 to the medical accident prevention information recording device 500. Is processed into a common format with other reports input from the medical accident information input device 400 and stored in the medical accident prevention information DB 600. The medical accident analyzer 700 reads the medical accident prevention result information 20 as appropriate, and analyzes the tendency of occurrence of medical accidents.

  In Patent Document 2, the warning system 10 includes a server 12, and the server 12 is connected to a plurality of stations 18 via a network 14. Each nurse wears the sensor unit 20, and the nurse ID transmitted therefrom is detected at the station 18, and information on the detected nurse ID is transmitted to the server 12. The server 12 knows the location of the nurse from this information. For example, when a nurse performs a nursing service, the server 12 detects the location of the nurse, and detects whether the nursing service is being performed correctly or whether a device or medicine necessary for the nursing service has been selected correctly. To do. If it is not correct, a warning corresponding to the content is issued through the PDA possessed by the nurse. Further, when the patient is in a dangerous state such as a state where the patient is likely to fall, the location of the nurse in charge of the patient is detected and a warning is issued. However, if the location of the nurse cannot be confirmed, a similar warning is issued to the chief nurse or padlock.

  In Patent Document 3, the medical support system 1 generates a care instruction for each nurse from the care flow data group stored in the data store 210 and transmits the care instruction to the portable information terminal 40. A warning generated by the execute composition unit 290 is added to the care instruction. The incident report generation unit 220 generates an incident report IRP using information input from the portable information terminal 40. In the medical support system 1, when the incident report IRP is added, the KSD model 302 is updated. Furthermore, the data structure conversion characteristics of the incident query structure model 291, the data structure model 212, and the translator 240 that are used for alert generation are updated to reflect the KSD model 302.

  In Patent Document 4, the behavior analysis apparatus 10 includes a computer 12, and data on the number of steps of the nurse and an inclination angle (an angle at which the upper body is inclined) measured by the measuring device 30 are transmitted to the computer 12. A nurse's behavior feature vector is created based on the measured number of steps and the tilt angle. For example, dictionary data for a specific accident is created based on the behavior feature vector when an accident (accident) occurs. After the dictionary data is created, the behavior characteristic data of the nurse at a certain time (current time) is created and compared with the dictionary data to determine whether or not an accident may occur. If there is a possibility that an accident will occur, a warning for avoiding this will be issued.

  The current incident analysis is based on the incident report, but small problems that occur on a daily basis are not recognized as incidents by the parties in the first place. I can't take it. However, in fact, before a serious incident or accident occurs, an incident with a low impact that triggers the incident often occurs.

It is an object of the present invention to accurately predict the occurrence of a serious incident or accident resulting from the occurrence of incidents having a low impact level.
JP 2004-030554 A Japanese Patent Laying-Open No. 2005-092440 Japanese Patent Laying-Open No. 2005-063269 JP 2004-157614 A

  The present invention aims to improve the accuracy of preventing medical accidents.

  The incident analysis system according to the present invention described in claim 1 includes an input unit that inputs information on occurrence of an accident factor in a plurality of medical practices that are related to work procedures, and the severity of the input accident factor; Based on the relationship between the medical practice or accident factors, a calculation unit that quantitatively calculates the accident occurrence prediction at the current or future medical practice, and an output unit that outputs the calculated accident occurrence prediction It comprises.

  The incident analysis program according to the present invention as set forth in claim 8 includes means for inputting information on occurrence of accident factors in a plurality of mutually related medical practices, the inputted accident factors, and the medical practices or accidents. Based on the relationship between factors, the computer realizes means for quantitatively calculating an accident occurrence prediction in the current or future medical practice and means for outputting the calculated accident occurrence prediction.

  According to the present invention, it is possible to improve the accuracy of preventing medical accidents.

Embodiments of the present invention will be described below with reference to the drawings.
FIG. 1 shows the overall configuration of an incident analysis system and related systems according to the present embodiment. The operation planning system 3 is connected to the input of the incident analysis system according to the present embodiment. The surgery planning system 3 is a system for drafting a plan related to a series of medical actions performed in surgery before surgery. The operation planning system 3 determines all the items from the preparation to the completion of the operation, such as the operation method of the operation, the detailed procedure in the operation method, the assignment of the person in charge, the medicine used, the medical instrument, etc. . When making a decision, patient information and medical record information are often obtained from an electronic medical record system, and studies are carried out based on that information.

  Further, the operation recording system 4 is connected to the input of the incident analysis system according to the present embodiment via the incident determination system 5. The surgical recording system 4 is configured to record images and videos from the medical device 1 such as an X-ray imaging apparatus, and to record patient voices and videos, doctor voices and videos from the action record input unit 2. System.

  FIG. 20 shows the surgery recording system 4 and the action record input unit 2 as its peripheral equipment. The surgical recording system 4 includes a plurality of video signal connectors 125-1, 125-2, 125-3, 125-4 and a plurality of audio signal connectors 126-1 and 126-2. The apparatus main body 111 of the brain function testing apparatus 101 is connected to the video signal connector 125-1. The surgical recording system 4 receives a video signal related to the same display screen as the patient task presentation display 112 for presenting a task to the patient from the device main body 111 of the brain function testing apparatus 101 via the video signal connector 125-1. Supplied. Connected to the video signal connector 125-2 is a patient imaging camera 113 whose position and orientation are set in order to mainly image the face of the patient whose brain function is to be examined. The surgical recording system 4 is supplied with a video signal related to the patient's facial expression from the patient photographing camera 113. The video signal connector 125-3 is connected to the camera of the surgical microscope 103 having an imaging function. The surgical recording system 4 is supplied with video signals relating to the surgical field from the camera of the surgical microscope 103. Further, the navigator device 104 having a surgery support function is connected to the video signal connector 125-4. The operation recording system 4 is supplied with a video signal relating to the display screen of the navigator device 104.

  The audio signal connector 126-1 is used to convert mainly the sound emitted by the patient attached to the patient imaging camera 113 whose position and orientation are set to mainly image the patient's face into an electrical signal. Microphone 118 is connected. The operation recording system 4 is supplied with an audio signal mainly related to the audio generated by the patient from the microphone 118. The audio signal connector 126-2 is connected to a microphone 105 for converting audio generated mainly by the surgeon into an electrical signal. The operation recording system 4 is supplied with an audio signal related to the audio generated mainly by the surgeon from the microphone 105. The surgery recording system 4 includes a four-screen synthesizer 124 with the surgery record control unit 121 as a control center. The 4-screen synthesizer 124 is connected to a plurality of video signal connectors 125-1, 125-2, 125-3, 125-4. As shown in FIG. 21, the 4-screen synthesizer 124 presents a patient task as a plurality of video signals supplied via video signal connectors 125-1, 125-2, 125-3, 125-4. The video signal of the display screen of the display 112, the video signal of the patient photographed by the patient photographing camera 113, the video signal of the surgical field photographed by the camera of the surgical microscope 103, and the video signal of the display screen of the navigator device 104 are Composite to the screen (frame). The video signal combined on a single screen is sent to and displayed on an information presentation monitor 122 installed in the operating room, and recorded on a video tape recorder (VTR) 123 as a recording unit. A plurality of audio signals supplied from the microphones 105 and 118 via the audio signal connectors 126-1 and 126-2 are supplied to the video tape recorder 123 so that they can be individually reproduced as shown in FIG. Is recorded.

  The incident determination system 5 was created by the image and video from the medical device 1 recorded by the surgery recording system 4, the voice and video of the patient, the medical action information as the voice and video of the doctor, and the surgery planning system 3. The operation plan is used to detect the occurrence of “an obvious or potential accident factor (hereinafter referred to as an incident) that may cause a medical accident”. Basically, when an operation or situation occurs that deviates from a surgical plan prepared in advance, it is picked up as an incident.

  In addition, incidents include, for example, labor shortage, work time excess, work time shortage, chemical use error (type of chemical, brand, quantity, order, etc.), machine / equipment used (type, order, quantity, use time) Etc.), blood loss, blood pressure, heart rate, blood component, depth of anesthesia.

  The incident analysis system 6 according to the present embodiment inputs information (incident occurrence information) related to the occurrence of an incident in a plurality of medical practices that are related in the work procedure determined by the incident determination system 5, and the input incident incident The severity frequency (frequency that quantifies the possibility of inducing a medical accident (importance frequency)) and the relevance coefficient between medical practices (the degree of impact that an incident that occurred in one medical practice has on the next medical practice Based on the quantified coefficient (propagation coefficient)), the accident occurrence prediction (accident occurrence prediction value) in the current or future medical practice is quantitatively calculated, and the calculated accident occurrence prediction value is, for example, a network It has a function to display and output warning information on the monitor 7 of any connected computer.

FIG. 2 shows the configuration of the incident analysis system 6 according to the present embodiment. The incident information input unit 11 inputs data related to incident occurrence from the incident determination system 5 and stores the data in the incident storage unit 12. The data related to incident occurrence includes the following items.
・ Identification information that identifies the medical practice in which the incident occurred (if it can be uniquely identified in the surgical plan)
・ Identification information that identifies the incident that occurred
-Incident occurrence time
・ Location of incident
・ Identification information of the parties involved in the occurrence of the incident
Patient State at Incident Occurrence The incident storage unit 12 stores data related to the surgical plan from the surgical planning system 3 and data related to the occurrence of incident from the incident determination system 5.

The medical practice map storage unit 14 stores data of a plurality of medical practice maps respectively corresponding to a plurality of types of treatment treatments. As illustrated in FIG. 3, the medical practice map is formed by associating a plurality of medical practices constituting a treatment procedure with a tree structure according to a work procedure. In practice, the medical practice map data is composed of the following items.
・ Medical stage name and identification information
・ Medical practice name and medical practice identification information
・ Medical practice supplementary information (information on medical practice)
・ Association between medical practices
・ Propagation coefficient a between medical practices (see Fig. 5)
・ Types of incidents that may occur in each medical practice and the severity IVA of each incident (see Figure 4)
Conversion table f for converting the propagation frequency IVP (see FIG. 6)
The index values handled in the present embodiment are as follows.
-IVA: A value that quantifies the severity of each incident that occurs in each medical practice (incident severity)
・ A: Value that quantifies the possibility that an incident that occurred in one medical practice will induce an incident in the next medical practice (incident propagation coefficient)
-IVP: Incident propagation frequency (a x IVE) of the predicted incident occurrence value transmitted from one medical practice to the next medical practice
-IVE: the sum of the incident importance degree IVA of an incident that occurred in a certain medical practice and the value f (IVP) obtained by converting the incident propagation degree IVP propagated to the medical practice using the conversion table of FIG. 6 (f (IVP) + IVA), a value that quantifies the possibility of occurrence of a serious incident or accident that induces an accident (hereinafter referred to as an accident occurrence prediction value)
The incident warning determination unit 13 calculates an accident occurrence predicted value IVE. The calculated accident occurrence predicted value IVE is supplied to the incident warning notification unit 15. The incident warning notification unit 15 may display the accident occurrence predicted value IVE as numerical information on the external system or the computer monitor 7 as it is, or the occurrence of a threshold value arbitrarily set by the user in advance as shown in FIG. When the predicted value IVE exceeds, a warning message may be displayed, or a warning message or voice may be notified through the speaker 16 as shown in FIG.

  The incident analysis operation of this embodiment will be described with reference to FIG. In FIG. 9, each block individually represents a medical practice. The arrow indicates the relationship between medical practices, and the direction of the arrow distinguishes the source and destination. A1, a2, and a3 indicate incident propagation coefficients (the degree of influence of incidents caused by other medical practices). Further, here, three medical stages are illustrated. For convenience of explanation, medical stages are identified by stage numbers (i-2), (i-1), i, and medical actions included in each medical stage are serial numbers such as 1, 2,... It shall be indicated by the medical practice number. Each medical action can be specified by a combination of a stage number and a medical action number. In FIG. 9, the time point at which the anesthesia stage (i-1) is shifted to the craniotomy stage (i) is shown as the present time.

  First, in the first preparation stage (i-2), preparation for anesthesia is performed by medical practice (i-2, 1). Assume that an incident occurs in the medical practice (i-2, 1) that the brand of the medicine has been changed from the scheduled brand to another brand. The incident importance level IVA of this incident is 4. Assume that no other incident occurred. Further, since it is the first medical stage, there is no incident propagation, that is, the incident propagation frequency IVP is zero, and the incident propagation frequency f (IVP) converted in the table of FIG. 6 is also zero as it is. Therefore, the accident occurrence predicted value IVE (i−2, 1) given as the sum of the incident importance degree IVA and the incident propagation degree IVP is 4. When other incidents occur in the medical practice (i-2, 1), the importance level IVA assigned to the incident is added to the accident occurrence predicted value IVE as needed, and the accident occurrence predicted value IVE is successively added. Updated immediately.

  In the next anesthesia stage (i-1), two medical actions (i-1, 1) and (i-1, 2) are performed in parallel. On the other hand, in the medical practice (i-1, 1) for introducing anesthesia, for example, an incident that the working time was exceeded occurred. The incident importance level IVA of this incident is 4. The medical action (i-1, 1) for introducing anesthesia is related to the medical action (i-2, 1) for preparing anesthesia in the previous stage, that is, the propagation coefficient is not zero. The incident propagation frequency IVP in which the anesthesia-introducing medical action (i-1, 1) is propagated from the preceding anesthetic preparation medical action (i-2, 1) is the preceding anesthesia preparation medical action (i-2, 1) The incident occurrence prediction value IVE of 4) is a value 2 (= 0.5 × 4) obtained by multiplying the propagation coefficient 0.5 set between both medical practices. The incident propagation frequency IVP of 2 is converted into a value 4 by the conversion table of FIG. The total value 8 of the converted incident propagation frequency f (IVP) 4 and the importance level IVA of the incident that occurred in the medical practice is an accident occurrence predicted value IVE (in the medical practice (i-1, 1)) i-1, 1) becomes 8. When another incident occurs in the medical practice (i-1, 1), the importance level IVA assigned to the incident is added to the accident occurrence predicted value IVE as needed, and the accident occurrence predicted value IVE is successively added. Updated immediately.

  In the other medical practice (i-1, 2) in preparation for craniotomy, for example, an incident that the working time was insufficient occurred. The incident importance level IVA of this incident is 4. The medical action (i-1, 2) for preparation of craniotomy has no relation to the medical action (i-2, 1) for preparation of anesthesia in the preceding stage, that is, the propagation coefficient is zero. The incident propagation frequency IVP that the medical action (i-1, 2) is propagated from the medical action (i-2, 1) of the previous stage of anesthesia preparation is 0, and the converted incident propagation frequency f (IVP) is also It is zero as it is. Accordingly, the total value 4 of the value 0 of the conversion value f (IVP) of the incident propagation frequency IVP and the importance level IVA of the incident occurring in the medical action (i-1, 2) is the medical action (i-1). , 2), the accident occurrence predicted value IVE (i-1, 2) is 4. When another incident occurs in the medical practice (i-1, 1), the importance level IVA assigned to the incident is added to the accident occurrence predicted value IVE as needed, and the accident occurrence predicted value IVE is successively added. Updated immediately.

  By taking over the above calculation result and shifting to the next craniotomy stage (i), the accident occurrence predicted value IVE (i, 1) in the craniotomy stage (i) is finally calculated. Immediately after the transition to this open medical practice (i, 1), no incident has yet occurred, so the incident importance number IVA is zero. The medical practice of craniotomy (i, 1) is related to both the medical practice of introduction of anesthesia (i-1, 1) and the medical practice of preparation of craniotomy (i-1, 2). The coefficient is not zero.

  The incident propagation frequency IVP in which the craniotomy medical action (i, 1) is propagated from the one-stage anesthesia-introducing medical action (i-1, 1) is the value of the anesthesia-introducing medical action (i-1, 1) It is a value 8 obtained by multiplying the incident occurrence prediction value IVE 8 by a propagation coefficient 1 set between both medical practices.

  In addition, the incident propagation frequency IVP in which the craniotomy medical action (i, 1) is propagated from the other preparatory craniotomy medical action (i-1, 2) is the preceding craniotomy medical action (i-1, 2). The incident occurrence prediction value IVE of 4) is multiplied by a propagation coefficient of 0.2 set between both medical practices, and is 0.8.

  Therefore, the incident propagation frequency IVP that the craniotomy medical action (i, 1) receives from all the medical actions is the incident propagation frequency IVP (8) from the medical action (i-1, 1) of introducing anesthesia, The total value with the incident propagation frequency IVP (0.8) from the medical practice (i-1, 2) is (8.8). The incident propagation frequency IVP (8.8) is converted to the value 10 in the conversion table of FIG. Therefore, the total value 10 of the value 10 of the conversion value f (IVP) of the incident propagation frequency IVP and the value 0 of the importance level IVA of the incident occurring in the medical activity (i, 1) is the medical activity (i, 1). ) Is 10 as the predicted occurrence occurrence value IVE (i, 1). Note that when another incident occurs in the medical practice (i, 1), the importance level IVA assigned to the incident is added to the accident occurrence predicted value IVE as needed, and the accident occurrence predicted value IVE is immediately instantaneous. Updated to

  In addition, for convenience of explanation, it has been described that one type of incident occurs in each medical practice, but the number of incidents that occur in one medical practice is not limited to one type, and actually a plurality of incidents occur There are also many. In this case, the same incident propagation coefficient may be applied to all incidents that occur in the same medical practice, or a unique incident coefficient may be defined and used.

  That is, as shown in FIG. 9, the incident propagation frequency IVP of the next medical action is determined in the medical action unit, that is, by multiplying the accident occurrence predicted value IVE by the propagation coefficient a based on the relationship (propagation coefficient) between the medical actions. As shown in FIG. 14, a propagation coefficient is individually set between an incident and the next medical practice, and the propagation coefficient a is added to the incident importance degree IVA for each incident that occurred in the previous stage medical practice. It is also possible to calculate a value obtained by multiplying by and calculate the degree of propagation IVP (i) to the medical action of the next stage using the total value. Further, as shown in FIG. 15, a representative value such as a maximum value is selected from IVA of a plurality of incidents for each medical practice, and a value obtained by multiplying the selected incident importance number IVA by a propagation factor a specific to the incident importance is calculated. The value may be set as the propagation frequency IVP (i) to the medical action of the next stage.

  In addition, as shown in FIG. 16, the relationship is not limited to the relationship between the medical practices, but the relationship between the incidents is given, that is, a unique propagation coefficient is set between the incidents, and the plurality of incidents in the previous stage are individually set. You may make it calculate for every incident as the incident propagation frequency of the next stage as a total value of the value which multiplied the propagation frequency.

  Note that the accident occurrence predicted value IVE may be reduced by performing some recovery process (recovery process) such as increasing the number of persons or administering a blood pressure increasing agent for the incident that has occurred. As shown in FIG. 18, information related to the execution of the recovery process is input from the incident information input unit 11 together with information related to the occurrence of the incident. The incident warning information storage unit 18 associates the accident occurrence predicted value IVE calculated by the incident warning determination unit 13 with identification information (such as an operation serial number) identifying the series of medical practices, a warning occurrence time, and a warning incident type. Store sequentially. The incident warning determination unit 13 recalculates the accident occurrence predicted value triggered by the storage of information related to the recovery process in the incident storage unit 12 as a trigger. At this time, the most recent accident occurrence predicted value from the incident warning information storage unit 18 is compared with the accident occurrence predicted value recalculated with the recovery process, the amount of change is calculated, and the accident occurrence predicted value is set as a threshold value. It is determined whether or not the threshold value is improved below the threshold value. The determination result and the latest accident occurrence predicted value are notified to the incident warning notifying unit 15 to notify the user together with, for example, the improvement message shown in FIG.

  Next, an accident occurrence warning method by the incident warning determination unit 13 and the incident warning notification unit 15 will be described. As shown in FIG. 8, the warning level may be expressed by sound from the speaker 16. In this case, the warning level may be expressed by sound quality (frequency level, continuity). Moreover, when the accident occurrence predicted value IVE exceeds a threshold value, a warning may be generated by voice. Further, as shown in FIG. 10A, the medical action of the current medical stage is displayed in a map format at the lower part of the recording display screen of another system, for example, the surgery recording system 4, and is color-coded according to the predicted occurrence value IVE of the medical action. May be displayed. In this case, display in another system can be realized more easily by transmitting data to another system in a highly versatile data format such as HTML. Further, when the accident occurrence predicted value IVE exceeds a threshold value, a warning message such as “the accident occurrence predicted value is increasing (deteriorating)” may be generated. In addition, as a warning means other than voice and message display, it is possible to realize a system that warns the occurrence of an incident using a vibration sensor, an optical sensor, or the like.

  As shown in FIG. 10B, it may be displayed on a dedicated screen. The monitor shown in FIG. 10A or FIG. 10B may be installed in a place that can be easily seen by medical personnel. Based on the accident occurrence prediction displayed by sound or image, the health care professional can decide whether to proceed with the original plan, change the plan, or cancel the plan. Accident can be avoided.

  As a warning generation timing, a warning is generated in synchronization with the start timing of each stage. As shown in FIG. 17, the stage information input unit 17 receives stage information of a medical practice from an external system. The incident warning determination unit 13 calculates an accident occurrence predicted value using the stage information input from the stage information input unit 17 as a trigger. Based on the stage information transmitted from the stage information input unit 17, the accident occurrence predicted value is calculated based on the stage information transmitted from the medical action map storage unit 14. Based on this, each accident occurrence prediction value is calculated.

  FIG. 11 shows an example of a medical practice map creation screen. A medical practice map creation support device (not shown) can easily create a new medical practice map and update the medical map stored in the medical practice map storage unit 14 using the graphic user interface GUI. The medical action map stored in the medical map storage unit 14 may be imported from an external system such as the surgery planning system 3.

  The box in FIG. 11 represents one medical practice. Arrows indicate that an incident is propagated between medical practices (affected by the incident). Arrange blocks by mouse operation. The Prev and Next buttons at the bottom right of the screen allow you to switch between medical stages. By pressing the SAVE button, the edited map information is stored in the medical practice map storage unit 14.

  The medical stage setting screen illustrated in FIG. 12 is displayed by designating the medical action of FIG. 11 by double clicking. The screen of FIG. 12 has three tabs. In the input setting tab and the output setting tab, a medical action that is related to the double-clicked medical action (medical action to be transmitted) is selected, and a propagation coefficient a from the medical action is specified. Select the target medical practice from the list on the right side of the screen. At this time, if the medical practice can be narrowed down in units of stages, the medical practice can be selected more easily and with less errors. Select from the list on the right of the screen and add to the list with the Add button. Regarding the added medical practice, the propagation coefficient can be registered in the medical practice list on the left side of the screen.

  In the incident setting tab of FIG. 13, an incident that is predicted to occur in each medical practice and the importance level IVA of each incident are defined. By selecting an incident whose occurrence is predicted from the incident list on the right side of the screen and pressing an Add button in the center of the screen, the selected incident can be registered as an incident whose occurrence is predicted. At this time, the importance of each incident can be defined in the selected incident list on the left side of the screen. The types of incidents registered here include, for example, labor shortage, work time excess, work time shortage, chemical errors (type, brand, quantity, order, etc.) used, machinery / equipment used (type, order, Volume, usage time, etc.), excessive bleeding, increased blood pressure, decreased blood pressure, decreased heart rate, increased heart rate, blood component change, insufficient depth of anesthesia.

  Note that the present invention is not limited to the above-described embodiment as it is, and can be embodied by modifying the constituent elements without departing from the scope of the invention in the implementation stage. In addition, various inventions can be formed by appropriately combining a plurality of constituent elements disclosed in the embodiment. For example, some components may be deleted from all the components shown in the embodiment. Furthermore, constituent elements over different embodiments may be appropriately combined.

1 is an overall configuration diagram of an incident analysis system and related systems according to an embodiment of the present invention. The block diagram of the incident analysis system of FIG. The figure which shows an example of the medical practice map memorize | stored in the medical practice map memory | storage part of FIG. The figure which shows the typical meaning of the eigenvalue (level) of each incident (accident factor) on the medical practice map of FIG. The figure which shows the typical meaning of each propagation coefficient (relevance coefficient) on the medical practice map of FIG. The figure which shows the conversion table for converting the incident propagation frequency by the incident warning determination part of FIG. 2 into an accident occurrence predicted value. The figure which shows the example of a warning threshold value setting screen by the incident warning determination part of FIG. The figure which shows the structure for the warning notification by the sound of the incident warning notification part of FIG. Explanatory drawing of the calculation method of the accident occurrence predicted value by the incident warning determination part of FIG. The figure which shows an example of the monitor screen for the alert notification of the incident alert notification part of FIG. The figure which shows the other example of the monitor screen for the warning notification of the incident warning notification part of FIG. The figure which shows an example of the creation screen of the medical practice map memorize | stored in the medical practice map memory | storage part of FIG. The figure which shows an example of the setting screen of the propagation coefficient on the medical practice map memorize | stored in the medical practice map memory | storage part of FIG. The figure which shows an example of the setting screen of the incident on the medical practice map memorize | stored in the medical practice map memory | storage part of FIG. 2, and its eigenvalue. Explanatory drawing of the other calculation method of the accident generation | occurrence | production predicted value by the incident warning determination part of FIG. Explanatory drawing of the other calculation method of the accident generation | occurrence | production predicted value by the incident warning determination part of FIG. Explanatory drawing of the other calculation method of the accident generation | occurrence | production predicted value by the incident warning determination part of FIG. The figure which shows the other structural example of the incident analysis system of FIG. The figure which shows the other structural example of the incident analysis system of FIG. The figure which shows the example of a notification screen for recovery | restoration (decrease) of accident occurrence predicted value corresponding to the structure of FIG. The figure which shows the structural example of the surgery recording system of FIG. The supplementary explanatory drawing of the surgery recording system of FIG.

Explanation of symbols

  DESCRIPTION OF SYMBOLS 1 ... Medical device, 2 ... Action record input part, 3 ... Surgery planning system, 4 ... Surgery record system, 5 ... Incident determination system, 6 ... Incident analysis system, 7 ... Monitor, 11 ... Incident information input part, 12 ... Incident Storage unit, 13 ... incident warning determination unit, 14 ... medical action map storage unit, 15 ... incident warning notification unit.

Claims (8)

An input unit for inputting information on the occurrence of accident factors in a plurality of medical practices related to the work procedure;
A calculation unit that quantitatively calculates an accident occurrence prediction in a current or future medical practice based on the seriousness of the input accident factor and the relationship between the medical practice or accident factors;
An incident analysis system comprising: an output unit that outputs the calculated accident occurrence prediction.   The incident analysis system according to claim 1, wherein the accident factor candidates include work hours, drug changes, and personnel changes that differ from the plan.   The incident analysis system according to claim 1, further comprising a storage unit that stores data of eigenvalues for the accident factor and data of a propagation coefficient corresponding to the association between the medical practice or the accident factor.   The incident analysis system according to claim 3, wherein the calculation unit quantitatively calculates the accident occurrence prediction from a product of an eigenvalue corresponding to the input accident factor and a propagation coefficient and / or a chain thereof.   2. The output unit according to claim 1, wherein when the calculated accident occurrence prediction value exceeds a threshold value, a warning is generated by a screen display and / or sound or a control signal necessary for generating the warning is generated. Incident analysis system.   The incident analysis system according to claim 1, wherein the output unit generates the warning or a control signal necessary for generating the warning substantially in synchronization with a start time of the medical practice.   The incident analysis system according to claim 1, wherein the calculation unit reduces the value of the accident occurrence prediction due to occurrence of a recovery action. A means for entering information regarding the occurrence of accident factors in multiple interrelated medical practices;
Means for quantitatively calculating an accident occurrence prediction at a current or future medical practice based on the inputted accident factor and the medical practice or the relationship between accident factors;
An incident analysis program for causing a computer to realize the means for outputting the calculated accident occurrence prediction.

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