JP6203155B2 - Management analysis device and management analysis program - Google Patents

Description

  The present invention relates to a management analysis apparatus and a management analysis computer program that can easily grasp an element index that affects the fluctuation of a management index.

  In the management of medical facilities such as clinics and hospitals, various analyzes are performed using a large amount of medical data in order to improve hospital operation efficiency and improve profits.

  Patent Document 1 discloses a hospital management support system that displays a transition of income as a bar graph in a graph display area in the screen and also displays a bar graph of expenses side by side. In addition, this hospital management support system can display analysis results of income and length of hospital stay while switching the analysis range, such as by department or disease type.

JP 2005-004260 A

  However, with the technology described in Patent Document 1, it is easy to read how changes in the number of individual patients, length of hospital stay, unit price of medical treatment, etc. have an effect on the final profit as elements constituting the profit. In the case of a large fluctuation in revenue, even if the cause is completely unrelated to the element used to display the above bar graph, it is mistakenly determined that the cause is the cause. There is a risk that.

  SUMMARY OF THE INVENTION An object of the present invention is to provide a management analysis apparatus and a management analysis computer program that can easily grasp an element index that affects fluctuations in a management index.

  The present invention for solving such a problem provides a business analysis device. This management analysis device is a management analysis device that analyzes the statistical values of management indicators based on the performance data group to be evaluated by comparing them with a comparison target, and includes a plurality of element indicators that constitute the analysis target management indicators and management indicators. Statistic values to calculate the statistical values of the management indicators and the statistical values of each element indicator for each of the relationship between and the storage unit that stores a plurality of results data, and the results data group to be evaluated and the results data group to be compared A calculation unit, and for each element index, an influence calculation unit that calculates the influence of the fluctuation of the element index statistic on the amount of difference between the evaluation target statistic value and the comparison target statistic value; A screen data generation unit that generates screen data for displaying the difference amount of the management index and the degree of influence of each element index on the display device.

  Further, in the business analysis device according to the present invention, the influence calculation unit includes a difference amount between the statistical value of the evaluation target in the management index and the statistical value of the comparison target, the statistical value of the evaluation target in each element index, and the comparison target. It is preferable to calculate a difference amount with each statistical value, and convert the difference amount of each element index into the difference amount of the management index to calculate the degree of influence of each element index.

  In the business analysis device according to the present invention, the plurality of element indices include a plurality of element indices in the second hierarchy constituting the management indices as the first hierarchy and a third hierarchy constituting the element index in the second hierarchy. It is preferable that the degree of influence of the element index of the second layer is equal to the sum of the degree of influence of the element indices of the third layer constituting the element index of the second layer.

  In the business analysis device according to the present invention, the plurality of element indices include a plurality of element indices in the second hierarchy constituting the management indices as the first hierarchy and a third hierarchy constituting the element index in the second hierarchy. It consists of multiple layers including multiple element indexes, and the screen data generation unit generates screen data for displaying in a hierarchical tree form that connects the difference amount of the management indexes and the influence degree of the element indexes of each layer, It is preferable.

  Further, in the business analysis device according to the present invention, the performance data is medical information indicating medical treatment results regarding patients, the management index is the total income from medical treatment, and a plurality of element indexes constituting the management index are an index regarding the number of patients and It is preferable to use it as an index relating to income per unit of patients.

  According to another aspect of the present invention for solving this problem, a computer program for business analysis is provided. This computer program for business analysis is a program that analyzes the statistical values of management indicators based on the performance data group to be evaluated by comparing with the comparison target, each of the performance data group to be evaluated and the performance data group to be compared. For each element indicator, the difference between the statistical value of the evaluation target and the statistical value of the comparison target is calculated for each element indicator. A process for calculating the degree of influence caused by fluctuations in the statistical values of the element indicators, and a process for generating screen data for displaying the difference between the management indicators and the influence degree of each element indicator on the display device. To run.

  The management analysis apparatus and the management analysis computer program according to the present invention have an effect of easily grasping the element index that affects the fluctuation of the management index.

It is a figure which shows the structural example of the medical treatment information analysis system which concerns on embodiment of this invention. It is a figure which shows an example of medical treatment information. It is a functional block diagram which shows the structural example of a terminal device. It is a schematic diagram which shows the example of an analysis screen. It is a schematic diagram which shows the example of an analysis screen. It is a block diagram which shows the structural example of a server apparatus. It is a figure which shows the structural example of the database for analysis. It is a figure for demonstrating the influence degree of the fluctuation | variation of the total number of patients and daily allowance with respect to the increase / decrease in hospitalization income. It is a figure for demonstrating the increase / decrease number of a total patient number by the fluctuation | variation of the estimated number of new hospitalizations and an average hospital stay. It is a figure for demonstrating the influence degree of the fluctuation | variation of the estimated number of new hospitalizations and the average hospitalization days with respect to the increase / decrease in hospitalization income. It is a flowchart which shows the operation | movement of the analysis information display process performed by a server apparatus. It is an operation | movement sequence of the analysis information display process in a medical treatment information analysis system.

  Hereinafter, a medical care information analysis system according to an embodiment of the present invention will be described with reference to the drawings.

A medical care information analysis system to which the present invention is applied is a system that analyzes a statistical value of a management index based on a performance data group to be evaluated by comparison with a comparison target. And a storage unit for storing a plurality of performance data. This medical care information analysis system calculates a statistical value of a management index and a statistical value of each element index for each of a performance data group to be evaluated and a performance data group to be compared. In addition, this medical care information analysis system calculates, for each element index, the degree of influence that the fluctuation of the statistical value of the element index has on the difference amount between the statistical value of the evaluation target in the management index and the statistical value of the comparison target. And this medical care information analysis system produces | generates the screen data for displaying the difference amount of a management parameter | index, and the influence degree of each element parameter | index on a display apparatus.
In the medical care information analysis system of the present embodiment, medical information indicating the medical care results related to patients is used as the performance data to be analyzed, the management index is the total income from the medical care, and the plurality of element indexes constituting the management index are the number of patients. And an index related to income per unit of patient.

  FIG. 1 is a diagram illustrating a configuration example of a medical care information analysis system according to an embodiment of the present invention.

  As shown in FIG. 1, the medical care information analysis system 1 includes a plurality of terminal devices 2-1 to 2-n (n is an integer of 2 or more) and a server device 3, and includes a plurality of terminal devices 2-1. ˜2-n and the server device 3 are connected to each other via the network 4.

  The plurality of terminal devices 2-1 to 2-n are installed in, for example, medical facilities 100-1 to 100-n, respectively. The server device 3 has a database server and a web server. The server device 3 is installed in a facility outside the medical facilities 100-1 to 100-n, and periodically (for example, from the terminal devices 2-1 to 2-n installed in the medical facilities 100-1 to 100-n). Every month), for example, medical information indicating the medical treatment result of the patient who has been treated is received. In addition, although this embodiment demonstrates the example which uses this medical treatment information as performance data to analyze, this invention is not limited to this.

  Hereinafter, details of the medical information in the present embodiment will be described.

  FIG. 2 is a diagram illustrating an example of medical information.

  As shown in FIG. 2, the medical information 200 includes a facility code 210, patient code 220, hospitalization date 230, discharge date 240, hospitalization period 250, diagnosis group classification (DPC) upper six digits 260, medical treatment date. 270, a new hospitalization flag 280, a DPC hospitalization fee 290, an operation fee 300, a volume examination fee 310, an operation flag 320, and the like. Items included in the medical information 200 are not limited to these items. For example, patient attribute information such as age and gender, an inpatient route indicating a route in which the patient was hospitalized, and a destination (location) after the patient was discharged. Other information related to medical records at medical institutions such as discharge destinations and medical departments may be included. The medical information 200 corresponds to a medical record from the hospitalization to the discharge of the patient, and is created when the medical care at the medical institution is completed.

  The facility code 210 is a code for specifying each medical facility 100-1 to 100-n, and is assigned to each medical facility 100-1 to 100-n. The patient code 220 is a code for specifying a patient, and is assigned to each patient.

  The hospitalization date 230 is an item indicating the date on which the patient was hospitalized. The discharge date 340 is an item indicating the date on which the patient was discharged, and is blank if the patient has not been discharged. The hospitalization period 250 is an item indicating the period during which the patient was hospitalized.

  The DPC first six digits 260 is an item for specifying the name of the patient's injury based on the DPC code.

  The DPC code is composed of 14-digit numbers assigned to all diagnostic group classifications of 2,873 (according to the 2014 medical fee revision), and is roughly divided into three layers. The first layer is based on the “injury name” and is defined by the 10th edition of the International Statistical Classification of Diseases and Related Health Problems (ICD-10). The second layer is a layer based on the presence / absence of “surgery” and is defined by a medical score table. The third layer is the other layer, and includes “treatment”, “secondary injury name”, “severity”, and the like.

  The upper six digits of the fourteen digits constituting the DPC code indicate the first layer, the ninth and tenth digits indicate the second layer, and the remaining numbers indicate the third layer. The first two digits of the six digits constituting the first layer indicate a major diagnostic group (MDC), and the third to sixth digits indicate a classification code in each MDC. .

  MDC classifies wounds into 18 groups. For example, “01” indicates a nervous system disease, “04” indicates a respiratory disease, “05” indicates a circulatory disease, and “16” indicates trauma / burn / addiction. Yes.

  The classification code is a code of a group into which the wounds and diseases in which medical resources are most invested are classified. A specific injury / illness name is specified by the MDC and the classification code. For example, “050050” indicates “cerebral infarction angina, chronic ischemic heart disease”, “020110” indicates “cataract, lens disease”, “010060” indicates “cerebral infarction”, “160080” indicates “proximal hip fracture”.

  In the present embodiment, the upper six digits of the DPC code are set as elements in the upper six digits of the DPC in order to specify the name of the patient's injury or illness. Note that the information for specifying the patient's injury or sickness is not limited to the first six digits of the DPC code, and may be, for example, only the first two digits of the DPC code, that is, the MDC. It may be information for specifying the department that has treated the patient.

  The medical treatment date 270 is an item indicating the date of medical treatment of the patient. The new hospitalization flag 280 is turned on when the patient is newly hospitalized.

  The DPC hospitalization fee 290 is an item indicating the hospitalization fee paid by the patient according to the daily fixed fee calculation system based on the diagnosis group classification. The surgical fee 300 is an item indicating the surgical fee when the patient is operated. The volume examination fee 310 is an item indicating the examination fee paid by the patient in accordance with the volume payment system. In the present embodiment, hospitalization income including hospitalization fee, operation fee, and volume examination fee will be described as an example of a management index to be evaluated and analyzed, but the present invention is not limited to this.

  The operation flag 320 is a flag indicating whether or not the patient has been operated. For example, the operation flag 320 is turned off if the patient is not operated, and is turned on if the patient is operated.

  Next, details of the terminal devices 2-1 to 2-n according to the present embodiment will be described. Since the configurations of the terminal devices 2-1 to 2-n are the same, the terminal device 2-1 will be described below as a representative.

  FIG. 3 is a functional block diagram illustrating a configuration example of the terminal device.

  As illustrated in FIG. 3, the terminal device 2-1 includes a communication processing unit 21, a display unit 22, an operation unit 23, a storage unit 24, and a control unit 25. A so-called personal computer can be used for the terminal device 2-1.

  The communication processing unit 21 includes an interface circuit for connecting the terminal device 2-1 to the network 4. The communication processing unit 21 transmits various information and requests to the server device 3 via the network 4 under the control of the control unit 25. In addition, the communication processing unit 21 supplies various types of information received from the server device 3 via the network 4 to the control unit 25.

  The display unit 22 includes a display such as a liquid crystal display, for example, and displays various information received from the control unit 25.

  The operation unit 23 is an operation interface for the user of the terminal device 2-1 to operate the terminal device 2-1. The operation unit 23 includes input devices such as a keyboard and a numeric keypad, receives various operations from the user, and outputs signals corresponding to these operations to the control unit 23. The display unit 22 and the operation unit 23 may be integrally configured as a touch panel display.

  The storage unit 24 includes at least one of a semiconductor memory, a magnetic recording medium, and an access device thereof, and an optical recording medium and an access device thereof. The storage unit 24 stores a computer program, various parameters, data, and the like for controlling the terminal device 2-1.

The control unit 25 has one or a plurality of processors and their peripheral circuits. In the present embodiment, the control unit 25 accesses the server device 3 via a web browser displayed on the display unit 22 and sends an analysis screen display request for requesting display of the analysis screen to the server device via the communication processing unit 21. 3 to send. The analysis screen display request includes a terminal code for specifying the terminal device 2-1, a facility code for specifying the medical facility 100-1 in which the terminal device 2-1 is installed, and the like.
Thereafter, the control unit 25 receives screen data for displaying the analysis screen via the communication processing unit 21. And the control part 25 displays an analysis screen on a web browser based on screen data.

  FIG. 4 is a schematic diagram illustrating an example of an analysis screen.

  As shown in FIG. 4, the analysis screen 400 includes an evaluation target setting pull-down menu 401 for selecting a medical facility and period to be evaluated, and a comparison target for selecting a medical facility and period to be compared. A setting pull-down menu 402, an output icon 403, and the like are displayed. In addition, the analysis screen 400 may display a pull-down menu for setting the range of medical information to be analyzed. Note that the evaluation target setting pull-down menu 401 and the comparison target setting pull-down menu 402 may be capable of selecting information related to injuries such as medical departments, MDCs, and DPCs, in addition to the medical facility and period.

  In response to the user clicking on the output icon 403 after selecting the medical facility and period in the evaluation target setting pull-down menu 401 and the comparison target setting pull-down menu 402 via the operation unit 23, the control unit 25 The analysis request is generated and transmitted to the server device 3 via the communication processing unit 21. The analysis request includes information indicating a medical facility and period to be evaluated, a medical facility and period to be compared, and the like. In addition, the analysis request includes a terminal code for specifying the terminal device 2-1, a facility code for specifying the medical facility 100-1 in which the terminal device 2-1 is installed, and the like.

  Thereafter, the control unit 25 receives screen data for displaying an analysis screen showing the analysis information and the like of hospitalization income via the communication processing unit 21. And the control part 25 displays the analysis screen which showed the analysis result etc. of the hospitalization income based on screen data. In the present embodiment, the statistical value of the management index will be described by taking, as an example, hospitalization income that is the sum of the DPC hospitalization fee, operation fee, and volume examination fee at the selected medical facility and period, etc. It is not limited to, but may be, for example, outpatient income or costs. Further, in this embodiment, as a statistical value of the management index, the DPC hospitalization fee, the operation fee, the work volume examination fee and the total in the selected medical facility and period will be described as an example, but the present invention is limited to this. For example, an average value of these may be used.

  FIG. 5 is a schematic diagram illustrating an example of an analysis screen.

  As shown in FIG. 5, in addition to the evaluation target setting pull-down menu 501, the comparison target setting pull-down menu 502, the output icon 503, and the like, the analysis screen 500 includes analysis information 510 regarding hospitalization income that is a management index to be analyzed. , And the analysis information about each element index constituting the factor of hospitalization income are displayed in a tree shape expressing the connection of a plurality of layers with hospitalization income as the first layer.

  The analysis screen 500 displays the analysis information 510 of the number of patients and the analysis information 530 of the daily allowance for the second hierarchy, with the analysis information 510 of hospitalization income as the first hierarchy. The analysis screen 500 displays the analysis information 540 of the estimated number of new hospitalizations and the analysis information 550 of the average length of stay in the third hierarchy with the analysis information 520 of the total number of patients as the upper hierarchy. Also, the analysis screen 500 includes daily-yen-yen analysis information 530 as an upper layer, and DPC hospital fee analysis information 560, operation fee analysis information 570, and other volume examination fee analysis information 580 in the third layer. It is displayed. Further, the analysis screen 500 displays the operation fee analysis information 590 and the operation unit price analysis information 600 in the fourth layer with the surgical fee analysis information 570 as the upper layer.

  In the hospitalization income analysis information 510, an increase / decrease rate of the evaluation subject hospitalization income with respect to the comparison subject hospitalization income is shown as a percentage (in this example, + 0.1%). Although illustration is omitted, the inpatient income analysis information 510 indicates the inpatient income for each of the evaluation object and the comparison object, and the amount of increase or decrease thereof.

  Here, the hospitalization income, which is a management index, can be broken down into the total number of patients and the daily allowance as elemental indices constituting this. The total number of patients is an index based on the daily hospitalization per patient, and represents the total number of hospitalization days of the patient. The daily allowance is an index indicating the unit price per patient per day, and represents the daily income per patient.

  The total number of patient analysis information 520 indicates the degree of influence of the change in the total number of patients on the increase or decrease in hospitalization income as a percentage (in this example, -2.0%). Although not shown, the total patient number analysis information 520 indicates the total number of patients, the number of increase / decrease, and the rate of increase / decrease for each of the evaluation target and the comparison target.

  In the daily allowance yen analysis information 530, the degree of influence of the change in daily allowance on the increase or decrease in hospitalization income is shown as a percentage (in this example, + 2.1%). Although not shown in the figure, the daily allowance yen analysis information 530 indicates the daily allowance yen, the amount of increase / decrease, and the rate of increase / decrease for each of the evaluation target and the comparison target. Further, although not shown, the daily allowance analysis information 530 includes a graph showing the breakdown of the DPC hospitalization fee, the operation fee, and the volume examination fee for each of the evaluation object and the comparison object.

  Here, the sum of the influence degree −2.0% shown in the analysis information 520 of the total number of patients and the influence degree + 2.1% shown in the analysis information 530 of the daily allowance is the hospitalization income of these higher ranks. The increase / decrease indicated in the analysis information 510 is equal to 0.1%.

  That is, the influence degree of the total number of patients−2.0% indicates that the difference in the total number of patients had an effect of depressing the hospitalization income to be evaluated by 2.0% with respect to the hospitalization income to be compared. Moreover, the influence degree of daily allowance yen + 2.1% shows that the difference of the daily allowance had the effect of raising the hospitalization income of the evaluation object by 2.1% relative to the hospitalization income of the comparison object.

  The total number of patients, which is an elemental index of hospitalization income, can be further broken down into the estimated number of new hospitalizations and the average length of hospitalization as an elemental index constituting this. The estimated number of new hospitalizations is an index indicating the number of newly hospitalized patients, and is the number of patients included in the medical information to be analyzed. For example, the estimated number of new hospitalizations can be the number of patients whose new hospitalization flag is on, but may be the average of the number of patients whose new hospitalization flag is on and the number of discharged patients, and are included in the scope of analysis It may be the number of patients. The average hospital stay is an index representing the average number of days of hospitalization per patient.

  In the analysis information 540 of the estimated number of new hospitalizations, the degree of influence of the fluctuation of the estimated number of new hospitalizations on the increase or decrease in hospitalization income is indicated as a percentage (in this example, + 0.9%). Moreover, although illustration is abbreviate | omitted, the analysis information 540 of the estimated new hospitalization number shows the estimated new hospitalization number, the increase / decrease number, and the increase / decrease rate of each evaluation object and comparison object.

  In the analysis information 550 of the average hospital stay, the degree of influence of the change in the average hospital stay on the increase / decrease in the hospitalization income is shown as a percentage (-2.9% in this example). Moreover, although illustration is abbreviate | omitted, in the analysis information 550 of an average hospital stay, the average hospital stay of each evaluation object and comparison object, the increase / decrease number, and the increase / decrease rate are shown.

  Here, the sum of the percentage + 0.9% shown in the analysis information 540 of the estimated number of new hospitalizations and the percentage -2.9% shown in the analysis information 550 of the average length of stay is the total number of patients in the upper hierarchy. The degree of influence shown in the numerical analysis information 520 is equal to −2.0%.

  The degree of influence of the estimated number of new hospitalizations + 0.9% indicates that the difference in the estimated number of new hospitalizations has had an effect of raising the evaluation hospitalization income by 0.9% relative to the comparison hospitalization income. In addition, the influence degree of average hospital stay -2.9% indicates that the difference in average hospital stay had the effect of lowering the hospitalization income to be evaluated by 2.9% against the hospitalization income to be compared. .

  The daily allowance yen, which is an elemental index of hospitalization income, can be further broken down into DPC hospitalization charges, surgery charges, and volumetric examination charges as elemental indices constituting it. The DPC hospitalization fee is an index indicating the amount per day of the hospitalization fee to be covered by the comprehensive medical treatment fee, and the operation fee is an index indicating the operation fee converted into the amount per day. The volume examination fee is an index indicating the amount of money that is a target of the payment of the amount not included in the DPC hospitalization fee and the operation fee.

  In the analysis information 560 of the DPC hospitalization fee, the degree of influence of the fluctuation of the DPC hospitalization fee on the increase / decrease in the hospitalization income is shown as a percentage (in this example, + 2.1%). Although not shown, the DPC hospitalization fee analysis information 560 indicates the daily allowance of the DPC hospitalization fee for each of the evaluation target and the comparison target, the amount of increase / decrease, and the rate of increase / decrease. Further, although not shown in the drawing, the DPC hospitalization fee analysis information 560 shows a graph indicating the number of days of hospitalization for each of the evaluation object and the comparison object.

  In the surgical fee analysis information 570, the degree of influence of fluctuations in the surgical fee on the increase or decrease in hospitalization income is indicated as a percentage (in this example, + 1.1%). Although illustration is omitted, the surgical fee analysis information 570 shows the daily allowance of the surgical fee for each of the evaluation target and the comparison target, the amount of increase / decrease, and the rate of increase / decrease.

  In the analysis information 580 of the volume examination fee, the degree of influence of the fluctuation of the volume examination fee on the increase / decrease in the hospitalization income is shown as a percentage (in this example, −1.1%). Although not shown, the volume examination fee analysis information 590 shows the daily examination yen, the amount of increase / decrease, and the rate of increase / decrease of the volume examination fee for each of the evaluation target and the comparison target.

  Here, the percentage shown in the DPC hospitalization fee analysis information 560 + 2.1%, the percentage shown in the surgical fee analysis information 570 + 1.1%, and the percentage shown in the volume examination fee analysis information 580-1. The sum of 1% is equal to the percentage + 2.1% indicated in the analysis information 530 of the daily allowance yen of these upper layers.

  The degree of influence of the DPC hospitalization fee + 2.1% indicates that the difference in the DPC hospitalization fee has an effect of increasing the hospitalization income of the evaluation object by 2.1% relative to the hospitalization income of the comparison object. The influence rate of the surgical fee + 1.1% indicates that the difference in the surgical fee has an effect of raising the hospitalization income of the evaluation object by 1.1% with respect to the hospitalization income of the comparison object. The influence degree of the volume examination fee of -1.1% indicates that the difference in the volume examination fee had an effect of depressing the hospitalization income of the evaluation object by 1.1% with respect to the hospitalization income of the comparison object.

  The surgical fee, which is an element index of the daily allowance, can be further broken down into an operation execution rate and an operation unit price as an element index constituting this. The operation implementation rate is an index indicating the proportion of patients who have undergone surgery among hospitalized patients, and the operation unit price is an index indicating the operation fee per operation.

  In the operation execution rate analysis information 590, the degree of influence of the change in the operation execution rate on the increase / decrease in hospitalization income is shown as a percentage (in this example, + 0.0%). In addition, although illustration is omitted, the surgical operation rate analysis information 590 indicates the surgical operation rate, the increase / decrease width, and the increase / decrease rate of each evaluation object and comparison object.

  In the analysis information 600 of the operation unit price, the influence degree of the change of the operation unit price with respect to the increase / decrease in the hospitalization income is shown as a percentage (in this example, + 1.1%). Although not shown in the figure, the surgical unit price analysis information 600 indicates the surgical unit price, the amount of increase / decrease, and the rate of increase / decrease for each of the evaluation target and the comparison target.

  Here, the sum of the percentage + 0.0% indicated in the surgical operation rate analysis information 590 and the percentage + 1.1% indicated in the surgical unit price analysis information 600 is the surgical fee analysis information 570 of these higher layers. It is equal to the percentage shown in FIG.

  The influence rate of the surgical operation rate + 0.0% indicates that the difference in the surgical operation rate has neither an effect of increasing or decreasing the hospitalization income of the evaluation target with respect to the hospitalization income of the comparison target. The influence rate of the operation unit price + 1.1% indicates that the difference in the operation unit price has an effect of increasing the evaluation subject hospitalization income by 1.1% with respect to the comparison subject hospitalization income.

As described above, the medical care information analysis apparatus 1 includes the analysis information 510 indicating the increase or decrease in hospitalization income, and the analysis information indicating the degree of influence that each element index has on the increase or decrease in hospitalization income, such as the total number of patients and daily allowance. Since 520 to 600 are displayed in the form of a tree that visualizes the connection of the hierarchized elements, it is possible to easily grasp the element index that affects the increase or decrease in hospitalization income.
In addition, since the medical information analysis apparatus 1 converts and displays the increase / decrease of each element index such as the total number of patients and the daily allowance yen into a percentage indicating the increase / decrease of the hospitalization income, it affects the increase / decrease of the hospitalization income. Intuitively and easily grasp the element index being given.

  Furthermore, the medical information analysis apparatus 1 not only makes it easy to compare how much each element index in the same hierarchy affects the increase / decrease in hospitalization income, which is a management index, but also makes it easy to compare each level index. Since the degree of influence on the increase / decrease in hospitalization income is obtained and displayed in the element index, the degree of influence on the increase / decrease in hospitalization income can be easily compared even if the element index is between different levels.

The inpatient income analysis information 510 displayed on the display screen 500 has a function as an icon. When the user clicks on the inpatient income analysis information 510 as an icon, the influence degree for each medical department, the MDC The degree of influence and the degree of influence every six digits on the DPC may be displayed.
Details of the degree of influence will be described later together with details of the server device 3.

  Next, details of the server device 3 according to the present embodiment will be described.

  FIG. 6 is a block diagram illustrating a configuration example of the server apparatus. As illustrated in FIG. 6, the server device 3 includes a communication processing unit 31, a storage unit 32, and a control unit 33.

  The communication processing unit 31 includes an interface circuit for connecting the server device 3 to the network 4. The communication processing unit 31 receives various information and requests transmitted from the terminal devices 2-1 to 2-n via the network 4 and supplies them to the control unit 33. Further, the communication processing unit 21 transmits various types of information to the terminal devices 2-1 to 2-n via the network 4 according to the control of the control unit 23.

  The storage unit 32 has at least one of a semiconductor memory, a magnetic recording medium and its access device, and an optical recording medium and its access device. The storage unit 32 stores a computer program, various parameters, data, and the like for controlling the server device 3. In addition, the storage unit 32 stores a hierarchical relationship among a plurality of element indexes constituting the management index, and calculation formulas, parameters, and the like necessary for calculating a statistical value and an influence degree of each index.

  In the present embodiment, the storage unit 32 stores a medical information database 321 and an analysis database 322.

  The medical information database 321 stores the medical information 200 received via the communication processing unit 31 as it is for each medical facility 100-1 to 100-n. When the data configuration is different for each of the medical facilities 100-1 to 100-n, it is converted into a unified data configuration and stored.

  The analysis database 322 stores information on items used for displaying analysis information on the terminal devices 2-1 to 2-n among the medical information stored in the medical information database 321.

  FIG. 7 is a diagram illustrating a configuration example of the analysis database.

  As shown in FIG. 7, the analysis database 322 includes a facility code 210, a patient code 220, a hospitalization date 230, a discharge date 240, a hospitalization period 250, a diagnosis, extracted from the medical treatment information for each medical treatment information. In the group classification, the six digits 260, the medical treatment date 270, the new hospitalization flag 280, the DPC hospitalization fee 290, the operation fee 300, the volume examination fee 310, and the operation flag 320 are stored in association with each other.

The control unit 33 has one or a plurality of processors and their peripheral circuits. And the control part 33 produces | generates the database 322 for analysis used for the display of the analysis information in the terminal devices 2-1 to 2-n. Moreover, the control part 33 calculates | requires the influence degree of the fluctuation | variation of the element parameter | index with respect to the increase / decrease in hospitalization income for every several element parameter | index obtained by decomposing hospitalization income, and produces | generates analysis information. And the control part 33 produces | generates the screen data for displaying the analysis screen which shows the analysis information of hospitalization income.
For this purpose, the control unit 33 includes a registration unit 331, an analysis unit 332, and a screen data generation unit 333 as functional modules implemented by software operating on the processor.
Note that these units included in the control unit 33 may be configured by independent integrated circuits, firmware, a microprocessor, and the like.
Hereinafter, each part of the control part 33 is demonstrated in detail.

  The registration unit 331 generates an analysis database 322 used to display analysis information on the terminal devices 2-1 to 2-n.

  The registration unit 331 refers to the medical information database 321 and, for each medical information, for example, from the medical information, the facility code, patient code, hospitalization date, discharge date, hospitalization period, and six digits in the diagnostic group classification The medical treatment date, the new hospitalization flag, the DPC hospitalization fee, the operation fee, the volume examination fee, and the operation flag are extracted. The registration unit 331 registers each item of the above-described medical information extracted for each medical information in the analysis database 322 in association with each other.

  For example, the analysis unit 332 changes the element index with respect to the increase / decrease in the hospitalization income for each of the plurality of element indices constituting the hospitalization income up to the hierarchy selected by the user via the terminal devices 2-1 to 2-n. The analysis information is generated by obtaining the degree of influence. In the following, in accordance with the example shown in FIG. 5, an example in which hospitalization income is decomposed to the fourth level will be described as an example, but the level to be decomposed may be up to the second level or the third level. , It may be decomposed to a lower hierarchy than this example.

  The analysis unit 332 first extracts medical information corresponding to the evaluation target period in the evaluation target medical facility identified from the analysis request from the analysis database 322. Further, the analysis unit 332 extracts from the analysis database 322 medical information corresponding to the comparison target period in the comparison target medical facility identified from the analysis request.

Next, the analysis part 332 calculates the statistical value of the evaluation object and comparison object in a management parameter | index. The analysis unit 332 extracts the DPC hospitalization fee, the operation fee, and the work volume examination fee from each of the extracted evaluation target medical information, and sums them to obtain the evaluation subject hospitalization income. In addition, the analysis unit 332 extracts the DPC hospitalization fee, the operation fee, and the work volume examination fee from each of the extracted medical information for comparison, and adds them together to obtain the hospitalization income for comparison.
And the analysis part 332 calculates | requires the difference by subtracting the hospitalization income of a comparison object from the hospitalization income of an evaluation object, and divides the difference by the hospitalization income of a comparison object, and the hospitalization of the evaluation object with respect to the hospitalization income of a comparison object Find the increase or decrease in income.

Subsequently, the analysis unit 332 calculates a statistical value for each element index of the second hierarchy constituting the hospitalization income. The analysis unit 332 calculates the total number of patients to be evaluated by totaling the hospitalization periods of the patients included in each of the extracted medical information to be evaluated. And the analysis part 332 calculates | requires the daily allowance yen of evaluation object by dividing the hospitalization income of evaluation object by the total number of patients.
Similarly, the analysis unit 332 calculates the total number of patients to be compared by summing the hospitalization periods of the patients included in each extracted medical information to be compared. And the analysis part 332 calculates | requires the daily allowance yen of a comparison object by dividing the hospitalization income of a comparison object by the total number of patients.

  Subsequently, the analysis unit 332 calculates the influence of the change in the total number of patients and the daily allowance on the increase / decrease in hospitalization income.

  FIGS. 8A to 8D are diagrams for explaining the influence of the change in the total number of patients and daily allowance on the increase / decrease in hospitalization income.

  8A to 8D, the vertical axis P indicates the total number of patients, and the horizontal axis Q indicates the daily allowance. P1 indicates the total number of patients to be evaluated, and Q1 indicates the daily allowance yen to be evaluated. P2 indicates the total number of patients to be compared, and Q2 indicates the daily allowance for comparison. Since the hospitalization income is indicated by the total number of patients × daily allowance, the hospitalization income to be evaluated is indicated by P1 × Q1, and the hospitalization income to be compared is indicated by P2 × Q2.

  In the example shown in FIG. 8A, the total number of patients P1 to be evaluated is smaller than the total number of patients P2 to be compared. The daily allowance Q1 to be evaluated is higher than the daily allowance Q2 to be compared.

  In the example shown in FIG. 8B, the total number of patients P1 to be evaluated is larger than the total number of patients P2 to be compared, contrary to the example shown in FIG. The daily allowance Q1 to be evaluated is cheaper than the daily allowance Q2 to be compared.

  The smaller value of the total number of patients P1 and P2 is A, the difference value between P1 and P2 is A ', the smaller one of the daily allowances Q1 and Q2 is B, and the difference value between Q1 and Q2 is When B ′, in the example shown in FIGS. 8A and 8B, the increase / decrease in revenue I-1 due to the change in the total number of patients and the increase / decrease in revenue I-2 due to the fluctuation in the daily allowance are as follows: Is required.

  And the influence degree E-1 of the change of the total number of patients with respect to the increase / decrease in the hospitalization income is the increase / decrease yield I-1, and the influence degree E-2 of the fluctuation of the daily allowance with respect to the increase / decrease in the hospitalization income is the increase / decrease profit I-2. Is divided by the hospitalization income P2 × Q2 to be compared, respectively, as follows.

  In the example shown in FIG. 8C, the total number of patients P1 to be evaluated is larger than the total number of patients P2 to be compared. The daily allowance Q1 to be evaluated is also higher than the daily allowance Q2 to be compared.

  In the example shown in FIG. 8D, the total number of patients P1 to be evaluated is smaller than the total number of patients P2 to be compared. The daily allowance yen Q1 to be evaluated is also lower than the daily allowance yen Q2 to be compared.

  Similarly, the smaller value of the total number of patients P1 and P2 is A, the difference value between P1 and P2 is A ′, and the smaller value of the daily allowance circles Q1 and Q2 is B, Q1, and Q2. When the difference value is B ′, in the example shown in FIGS. 8C and 8D, the increase / decrease in revenue I-1 due to the change in the total number of patients and the increase / decrease in revenue I-2 due to the change in the daily allowance are: It is calculated as follows.

  And the influence degree E-1 of the change of the total number of patients with respect to the increase / decrease in the hospitalization income is the increase / decrease yield I-1, and the influence degree E-2 of the fluctuation of the daily allowance with respect to the increase / decrease in the hospitalization income is the increase / decrease profit I-2. Is divided by the hospitalization income P2 × Q2 to be compared, respectively, as follows.

  Moreover, the analysis part 332 calculates a statistical value about each element parameter | index of the 3rd hierarchy which comprises the total number of patients. The analysis unit 332 further divides the total number of patients into the estimated number of new hospitalizations and the average length of hospitalization, and estimates the number of patients whose new hospitalization flag is turned on from the extracted medical information of the evaluation target Find the number of new hospitalizations. And the analysis part 332 calculates | requires the average hospitalization length of evaluation object by dividing the total number of patients of evaluation object by the estimated new hospitalization number, ie, the number of patients.

  Similarly, the analysis unit 332 calculates the estimated number of new hospitalizations by counting the number of patients whose new hospitalization flag is turned on from the extracted medical information to be compared. And the analysis part 332 calculates | requires the average hospitalization length of a comparison object by dividing the total number of patients of a comparison object by the estimated new hospitalization number.

  Subsequently, the analysis unit 332 obtains the number of changes in the total number of patients due to fluctuations in the estimated number of new hospitalizations and the average length of stay.

  FIGS. 9A to 9D are diagrams for explaining the increase or decrease in the total number of patients due to changes in the estimated number of new hospitalizations and the average length of stay.

  In FIG. 9A, the vertical axis R represents the estimated number of new hospitalizations, and the horizontal axis S represents the average length of hospital stay. R1 represents the estimated number of new hospitalizations to be evaluated, and S1 represents the average number of days of hospitalization to be evaluated. R2 represents the estimated number of new hospitalizations to be compared, and S2 represents the average length of stay for comparison. Since the total number of patients is indicated by the estimated number of new hospitalizations × the average length of stay, the total number of patients is indicated by R1 × S1, and the hospitalization income for comparison is indicated by R2 × S2.

  In the example shown in FIG. 9A, the estimated new hospitalization number R1 to be evaluated is smaller than the estimated new hospitalization number R2 to be compared. The average hospital stay S1 to be evaluated is larger than the average hospital stay S2 to be compared.

  In the example shown in FIG. 9B, the estimated new hospitalization number R1 to be evaluated is larger than the estimated new hospitalization number R2 to be compared with the example shown in FIG. 9A. The average hospital stay S1 to be evaluated is smaller than the average hospital stay S2 to be compared.

  The smaller value of the estimated new hospitalizations R1 and R2 is a, the difference value between R1 and R2 is a ', the smaller of the average hospital stays S1 and S2, the smaller value is b, and the difference between S1 and S2 Assuming that the value is b ′, in the example shown in FIGS. 9A and 9B, the increase / decrease number K−1 of the total number of patients due to the change in the estimated number of new hospitalizations and the increase / decrease number K due to the change in the average length of stay. -2 is obtained as follows.

  In the example shown in FIG. 9C, the estimated new hospitalization number R1 to be evaluated is larger than the estimated new hospitalization number R2 to be compared. Also, the average hospital stay S1 to be evaluated is larger than the average hospital stay S2 to be compared.

  In the example shown in FIG. 9D, the estimated new hospitalization number R1 to be evaluated is smaller than the estimated new hospitalization number R2 to be compared. Further, the average hospital stay S1 to be evaluated is also smaller than the average hospital stay S2 to be compared.

  Similarly, the smaller value of the estimated new hospitalization numbers R1 and R2 is a, the difference value between R1 and R2 is a ', and the smaller value of the average hospital stays S1 and S2 is b, S1 and S2. When the difference value is b ′, in the case of the example shown in FIGS. 9C and 9D, the increase / decrease number K-1 of the total number of patients due to the change in the estimated number of new hospitalizations and the change in the average length of stay The increase / decrease number K-2 is obtained as follows.

  And the analysis part 332 calculates | requires the influence degree of the fluctuation | variation of the estimated number of new hospitalizations and average hospitalization days with respect to the increase / decrease in hospitalization income.

  In the case of the example shown in FIGS. 9A and 9B, when the increase / decrease in income I-1 due to the change in the total number of patients and the increase / decrease in income I-2 due to the change in the daily allowance have the relationship of Equation 3, The influence degree E-3 of the fluctuation of the estimated number of new hospitalizations with respect to the increase / decrease of the income and the influence degree E-4 of the fluctuation of the average length of stay to the increase / decrease of the hospitalization income are obtained as follows.

  On the other hand, in the case of the example shown in FIGS. 9A and 9B, the increase / decrease in revenue I-1 due to the change in the total number of patients and the increase / decrease in revenue I-2 due to the fluctuation in the daily allowance have the relationship of Equation 1. When it has, the influence degree E-3 of the fluctuation of the estimated number of new hospitalizations for the increase / decrease of the hospitalization income and the influence degree E-4 of the fluctuation of the average length of stay for the increase / decrease of the hospitalization income are obtained as follows. .

  In the case of the example shown in FIGS. 9C and 9D, when the increase / decrease in income I-1 due to the change in the total number of patients and the increase / decrease in income I-2 due to the change in the daily allowance have the relationship of Equation 1, The influence degree E-3 of the fluctuation of the estimated number of new hospitalizations with respect to the increase / decrease of the income and the influence degree E-4 of the fluctuation of the average length of stay to the increase / decrease of the hospitalization income are obtained as follows.

  On the other hand, in the case of the example shown in FIGS. 9C and 9D, the increase / decrease in revenue I-1 due to the change in the total number of patients and the increase / decrease in revenue I-2 due to the fluctuation of the daily allowance have the relationship of Equation 1. When it has, the influence degree E-3 of the fluctuation of the estimated number of new hospitalizations for the increase / decrease of the hospitalization income and the influence degree E-4 of the fluctuation of the average length of stay for the increase / decrease of the hospitalization income are obtained as follows. .

  Specifically, in the example shown in FIG. 5, the estimated new hospitalization number R1 to be evaluated is larger than the estimated new hospitalization number R2 to be compared, while the average hospital stay S1 to be evaluated is the comparison target. This corresponds to the case shown in FIG. 9B, since the average hospital stay is less than the average hospital stay S2. In this case, since R1> R2 and S2> S1, the increase / decrease number K-1 of the total number of patients due to fluctuations in the estimated number of new hospitalizations and the increase / decrease number K-2 due to fluctuations in the average length of stay From Equation 5, the following is obtained.

  In the example shown in FIG. 5, the total number of patients P1 to be evaluated is smaller than the total number of patients P2 to be compared, while the daily allowance Q1 to be evaluated is the daily allowance Q2 to be compared. This is the case shown in FIG. 8A. Since P1 = R1 × S1 and P2 = R2 × S2, the total number of patients P1 to be evaluated and the total number of patients P2 to be compared, and the increase / decrease number K− of the total number of patients due to changes in the estimated number of new hospitalizations K− For example, as shown in FIG. 10, the following relationship is associated with 1 and the increase or decrease number K−2 of the total number of patients due to the change in the average hospital stay.

  Then, the increase / decrease in revenue I-3 due to fluctuations in the estimated number of new hospitalizations and the increase / decrease in revenue I-4 due to fluctuations in the average hospital stay are obtained as follows.

  Therefore, the impact E-3 of the change in the estimated number of new hospitalizations with respect to the increase or decrease in hospitalization income is the increase or decrease I-3, and the impact E4 of the change in average length of stay with respect to the increase or decrease in the hospitalization income is the increase or decrease I -4 is divided by the hospitalization income P2 × Q2 to be compared, respectively, as follows.

The analysis unit 332 calculates a statistical value for each element index of the third hierarchy constituting the daily allowance circle (corresponding to “element statistical value” in the present invention). The analysis unit 332 further divides the daily allowance into a daily allowance for DPC hospitalization, a daily allowance for surgery, and a daily allowance for turnover examination fee. The fee, operation fee and work-up examination fee are extracted, and the total amount of each is obtained. Then, by dividing the total amount by the total number of patients, the daily allowance for DPC hospitalization fee, the daily allowance for operation fee, and the daily allowance for volume examination fee are calculated.
Similarly, the analysis unit 332 calculates the daily allowance for the DPC hospitalization fee, the daily allowance for the operation fee, and the daily allowance for the volume examination fee from each of the extracted medical information to be compared.

  Subsequently, the analysis unit 332 calculates a difference between the daily allowance for the DPC hospitalization fee to be evaluated and the daily allowance for the DPC hospitalization fee to be compared. And the analysis part 332 calculates | requires the numerical value obtained by dividing this difference by the comparison daily allowance yen as an influence degree of the fluctuation | variation of the allowance of DPC hospitalization charges with respect to the increase / decrease in hospitalization income.

  Further, the analysis unit 332 obtains a difference between the daily allowance for the evaluation operation fee and the comparison operation fee. And the analysis part 332 calculates | requires the numerical value obtained by dividing this difference by the comparison daily allowance yen as an influence degree of the fluctuation | variation of the daily allowance of the operation fee with respect to the increase / decrease in hospitalization income.

  Furthermore, the analysis unit 332 obtains a difference between the daily allowance for the volume examination fee to be evaluated and the daily allowance for the comparison volume. And the analysis part 332 calculates | requires the numerical value obtained by dividing this difference by the total daily allowance of a comparison object as an influence degree of the fluctuation of the daily allowance of the volume examination fee with respect to the increase / decrease in hospitalization income.

  Further, the analysis unit 332 calculates a statistical value for each element index of the fourth layer constituting the surgical fee (corresponding to “element statistical value” of the present invention). The analysis unit 332 further divides the surgical fee into the number of operations performed and the unit price of the operation, and obtains the number of operations by counting the number of patients whose operation flag is turned on from the extracted medical treatment information to be evaluated. And the analysis part 332 calculates | requires the surgery implementation rate of evaluation object by dividing the number of operations and dividing by the number of patients.

  Similarly, the analysis unit 332 calculates the number of operations by counting the number of patients whose operation flag is turned on from the extracted medical information to be compared. And the analysis part 332 calculates | requires the operation implementation rate of a comparison object by dividing the number of operations and dividing by the number of patients.

  Subsequently, the analysis unit 332 calculates the surgical unit price of the evaluation target by dividing the surgical fee to be evaluated by the number of operations performed. Similarly, the analysis unit 332 calculates the operation unit price for comparison by dividing the operation fee for comparison by the number of operations performed.

  And the analysis part 332 calculates | requires the increase / decrease in the operation fee by the fluctuation | variation of the number of surgery implementations and a surgery unit price by the same method as having calculated | required the increase / decrease number of the total patient number by the fluctuation | variation of the estimated number of new hospitalizations and average hospitalization days. Subsequently, the analysis unit 332 uses the same technique as the degree of influence of the daily allowance fluctuation of the operation fee on the increase or decrease of the hospitalization income, and the degree of influence of the number of operations performed and the change of the operation unit price on the increase or decrease of the hospitalization income. Ask for.

  Then, the analysis unit 332 passes to the screen data generation unit 333 analysis information such as the degree of influence of the variation of each element index on the obtained increase or decrease in hospitalization income.

  The screen data generation unit 333 generates screen data for displaying on the terminal devices 2-1 to 2-n an analysis screen that indicates the degree of influence of each element index change on the increase or decrease in hospitalization income. Hereinafter, a case where a request is received from the terminal device 2-1 will be described as an example, but the same applies to other terminal devices.

  First, the screen data generation unit 333 receives an analysis screen display request from the terminal device 2-1 via the communication processing unit 31. Next, the screen data generation unit 333 generates screen data for displaying the analysis screen. Then, the screen data generation unit 333 transmits the generated screen data to the terminal device 2-1 via the communication processing unit 31. Thereby, the analysis screen 400 shown in FIG. 4 is displayed on the web browser of the display unit 22 of the terminal device 2-1.

  In addition, the screen data generation unit 333 generates screen data for displaying an analysis screen showing analysis information such as the degree of influence of changes in each element index with respect to an increase or decrease in hospitalization income. Then, the screen data generation unit 333 transmits the generated screen data to the terminal device 2-1 via the communication processing unit 31. Thereby, the analysis screen 500 shown in FIG. 5 is displayed on the web browser of the display unit 22 of the terminal device 2-1.

  FIG. 11 is a flowchart showing the operation of analysis information display processing executed by the server device. In this example, it is assumed that the analysis database 322 has already been constructed in the server device 3.

  When the server apparatus 3 receives the analysis screen display request from the terminal apparatus 2-1 via the communication processing unit 31, the server apparatus 3 starts the analysis information display process.

  The screen data generation unit 333 of the server device 3 first transmits screen data for displaying the analysis screen to the terminal device 2-1 via the communication processing unit 31 (step S101).

  Next, the analysis unit 332 determines whether or not an end request for requesting the end of the analysis information display process has been received from the terminal device 2-1 via the communication processing unit 31 (step S102). If the termination request has been received (step S102; Yes), the analysis unit 332 terminates the analysis information display process.

  If an end request has not been received (step S102; No), the analysis unit 332 determines whether an analysis request has been received from the terminal device 2-1 via the communication processing unit 31 (step S103). If the analysis request has not been received (step S103; No), the analysis unit 332 returns to step S102.

  If the analysis request has been received (step S103; Yes), the analysis unit 332 uses the evaluation-target medical information and the comparison-target medical information identified from the analysis request to each element index for the increase or decrease in hospitalization income. The analysis information is generated by obtaining the degree of influence of the fluctuations in step S104.

Subsequently, the screen data generation unit 333 generates screen data for displaying an analysis screen indicating the analysis information obtained by the analysis unit 332 (step S105).
Then, the screen data generation unit 333 transmits the generated screen data to the terminal device 2-1 via the communication processing unit 31 (Step S106).

  Next, an operation sequence between the terminal device 2-1 and the server device 3 in the medical care information analysis system 1 will be described.

  FIG. 12 is an operation sequence of analysis information display processing in the medical care information analysis system 1. In this example, it is assumed that the analysis database 322 has already been constructed in the server device 3.

  First, the control unit 25 of the terminal device 2-1 transmits an analysis screen display request to the server device 3 (step S201).

On the other hand, the screen data generation unit 333 of the server device 3 receives the analysis screen display request from the terminal device 2-1 (step S202), and generates screen data for displaying the analysis screen (step S203).
Then, the screen data generation unit 333 of the server device 3 transmits the generated screen data to the terminal device 2-1 (step S204).

The control unit 25 of the terminal device 2-1 receives the screen data from the server device 3 (step S205), and displays an analysis screen based on the screen data (step S206).
Thereafter, the control unit 25 of the terminal device 2-1 selects an output icon 403 after the user selects a medical facility, a period, and the like in the evaluation target setting pull-down menu 401 and the comparison target setting pull-down menu 402 via the operation unit 23. In response to clicking, an analysis request is transmitted to the server device 3 (step S207).

  On the other hand, the analysis unit 332 of the server device 3 receives the analysis request from the terminal device 2-1 (Step S208), and uses the evaluation-target medical information and the comparison-target medical information identified from the analysis request, and the hospitalization income. The analysis information is generated by obtaining the degree of influence or the like of the variation of each element index with respect to the increase / decrease in the amount (step S209).

  Subsequently, the screen data generation unit 333 of the server device 3 generates screen data for displaying an analysis screen indicating the generated analysis information (step S210), and transmits the generated screen data to the terminal device 2-1. (Step S211).

  The control unit 25 of the terminal device 2-1 receives the screen data from the server device 3 (step S212), and displays analysis information indicating the degree of influence on the analysis screen of the display unit 22 based on the screen data (step S212). S213).

  As described above, the medical care information analysis system according to the present embodiment calculates an increase / decrease between hospitalization income as an evaluation target management index and hospitalization income as a comparison management index. This medical information analysis system uses the second-level element index (total number of patients, daily allowance yen) that constitutes hospitalization income, and further changes the evaluation index and comparison target for each element index for the third-level and subsequent element indices. Calculates the degree of influence that increases and decreases in hospitalization income. And this medical care information analysis system produces | generates the screen data for displaying the increase / decrease in hospitalization income and the influence degree of each element parameter | index on a terminal device. Accordingly, the user can easily grasp the element index that affects the increase / decrease in hospitalization income.

  The present invention is not limited to the above-described embodiment, and many changes and modifications can be made. In the embodiment described above, the analysis information obtained by the server device is displayed on the terminal device connected via the network. However, the present invention is not limited to this, and the analysis information obtained by the server device may be displayed on the display unit of the server device. Alternatively, instead of a configuration in which information on a plurality of medical facilities is managed and analyzed by a server device, a so-called stand-alone type medical information analysis system that records and analyzes medical information at a terminal device of each medical facility may be used. Good.

  Further, in the above-described embodiment, for convenience, the description has been made as a configuration in which various request signals such as a screen display request are transmitted to the server device based on an operation by the user at the terminal device. Needless to say, it is realized as a configuration for recognizing commands on the screen (clicking on icons, etc.) on the server device side.

DESCRIPTION OF SYMBOLS 1 Medical information analysis system 2-1 to 2-n Terminal device 3 Server apparatus 21, 31 Communication processing part 22 Display part 23 Operation part 22, 32 Storage part 25, 33 Control part 200 Medical information 321 Medical information database 322 Analysis database 331 Registration unit 332 Analysis unit 333 Screen data generation unit

Claims (6)

A management analysis device that analyzes a statistical value of a management index based on a performance data group to be evaluated by comparing with a comparison target,
A storage unit for storing a relationship between a management index to be analyzed and a plurality of elemental indexes constituting the management index, and a plurality of performance data;
For each of the performance data group to be evaluated and the performance data group to be compared, a statistical value calculation unit that calculates a statistical value of the management index and a statistical value of each element index,
For each element index, an influence degree calculation unit that calculates the degree of influence of the fluctuation of the statistical value of the element index on the difference amount between the statistical value of the evaluation target and the statistical value of the comparison target in the management index; ,
A screen data generating unit that generates screen data for displaying the difference amount of the management index and the influence of each element index on a display device;
Management analysis equipment. The influence calculation unit
A difference amount between the statistical value of the evaluation target and the statistical value of the comparison target in the management index, and a difference amount of the statistical value of the evaluation target and the statistical value of the comparison target in each element index are respectively calculated. ,
Converting the difference amount of each element index into the difference amount of the management index to calculate the degree of influence of each element index;
The business analysis device according to claim 1. The plurality of element indicators include a plurality of element indicators of a second hierarchy constituting the management indicator which is the first hierarchy, and a plurality of element indicators of a third hierarchy constituting the element indicator of the second hierarchy,
The degree of influence of the second layer element index is equal to the sum of the degree of influence of the plurality of third layer element indices constituting the second layer element index.
The business analysis device according to claim 1 or 2. The plurality of element indices include a plurality of element indices of a second hierarchy that constitute the management index that is the first hierarchy, and a plurality of element indices of a third hierarchy that constitutes the element index of the second hierarchy Consists of hierarchy,
The screen data generation unit generates screen data for displaying the difference amount of the management index and the influence level of the element index of each hierarchy in a hierarchical tree form;
The business analysis device according to any one of claims 1 to 3. The results data is medical information indicating medical results related to a patient,
The management index is the total income from medical treatment, and the plurality of element indexes constituting the management index are the index regarding the number of patients and the index regarding the income per unit of the number of patients,
The business analysis device according to any one of claims 1 to 4. A program that analyzes the statistical values of management indicators based on the performance data group to be evaluated by comparing with the comparison target,
For each of the performance data group to be evaluated and the performance data group to be compared, a process for calculating a statistical value of the management index and a statistical value of a plurality of elemental indicators constituting the management index,
For each element index, a process of calculating the influence of fluctuations in the statistical value of the element index with respect to the difference between the statistical value of the evaluation target and the statistical value of the comparison target in the management index;
Processing for generating screen data for displaying the difference amount of the management index and the degree of influence of each element index on a display device;
Program for management analysis to make a computer execute.

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