JP5769595B2 - Medical evaluation device and medical evaluation program - Google Patents

Description

  The present invention relates to a medical evaluation apparatus that analyzes medical performance data and presents the analysis results.

  Conventionally, a medical practice evaluation system has been disclosed for evaluating “whether or not a response to injury or illness was appropriate”. Specifically, a list of medical practices in accordance with the medical treatment guidelines for wounds and sickness units is stored in advance, and the medical practices listed for each wounded and sickness unit are compared with the actually performed medical practices, and they match. The higher the evaluation, the lower the evaluation. (Patent Document 1)

JP 2010-191891 A

  By the way, in order to evaluate the quality of a medical practice, it is important to consider patient attributes when the medical practice is performed, such as the age, past illness, and physical condition of the patient who received the medical practice. In recent years, introduction of a comprehensive medical system and digitization of information in medical institutions have progressed, and patient information at the time of medical practice is being accumulated.

  However, conventional medical practice evaluation systems are not limited to evaluating the implementation status of medical practice in units of wounds and sickness, and do not evaluate the quality of medical practice taking into account patient attributes such as patient age at the time of medical practice. There wasn't.

  Therefore, an object of the present invention is to realize a medical treatment evaluation apparatus that analyzes and evaluates as objective data by combining medical practice result information and patient attributes in order to evaluate the quality of medical treatment.

  One aspect of the present invention provides, for each evaluation item for evaluating a medical practice in a medical institution, a medical practice related to the evaluation item, a patient attribute related to the medical practice, and a standard of the medical practice and the patient attribute. A storage unit that stores an evaluation standard table that associates a first standard indicating general relevance, and at least a patient attribute and medical practice information that is performed for each patient, and the evaluation standard table And an information processing unit that statistically processes a medical practice in the medical institution based on the medical treatment result information, and a display unit that displays a processing result in the information processing unit. A medical practice extraction means for receiving a selection of an item and extracting a medical practice corresponding to the selected evaluation item and a patient attribute related to the clinical practice from the evaluation criteria table; Patient number calculation means for obtaining the number of patients or the distribution of the number of patients in which the extracted medical practice is performed for each patient attribute related to the extracted medical practice with reference to information, and the selection from the evaluation criteria table The first standard corresponding to the evaluated evaluation item is extracted, the totaling means for compiling the number of patients or the distribution of the number of patients and the extracted first standard in a comparable manner, and the result totaled by the totaling means And a display unit for displaying on the display unit.

  According to another aspect of the present invention, a computer is provided for each evaluation item for evaluating a medical practice in a medical institution, a medical practice related to the evaluation item, a patient attribute related to the medical practice, and the medical practice and the patient. Refer to the storage unit that stores the evaluation standard table that associates the first standard indicating the standard relevance of the attribute, and at least the patient attribute and the medical practice information that is performed for each patient. An information processing unit that statistically processes a medical practice in the medical institution based on the evaluation criterion table and the medical treatment result information, and receives the selection of an evaluation item, and the selected evaluation from the evaluation criterion table A medical practice extraction means for extracting a medical practice corresponding to the item and a patient attribute related to the medical practice, and the medical practice information is referred to and related to the extracted medical practice A patient number calculating means for obtaining the number of patients who have been subjected to the extracted medical practice or a distribution of the number of patients for each patient attribute, and a first standard corresponding to the selected evaluation item is extracted from the evaluation criteria table Information including: a totaling means for compiling the number of patients or the distribution of the number of patients and the extracted first standard so as to be comparable; and a display means for displaying a result of the totaling by the totaling means on the display unit. A medical evaluation program that functions as a processing unit and a display unit that displays a processing result in the information processing unit.

  Here, the totaling means calculates the number of patients or the distribution of the number of patients and the state of divergence between the extracted first standard as an evaluation value, and the display means includes the evaluation value in the totalized result. It is preferable to display.

  The evaluation criteria table includes a second standard indicating a correlation between the first standards of a plurality of medical practices, and the counting unit is configured to associate a plurality of medical practices with the selected evaluation item. The distribution of the number of patients or the number of patients who have been subjected to the extracted medical practice is calculated for each combination of the medical practice and the related patient attributes, and the correlation between the number of patients or the distribution of the number of patients between the medical practice is calculated. Preferably, the deviation state from the second standard is calculated as an evaluation value, and the display means displays the evaluation value by including it in the totalized result.

  According to the present invention, it is possible to evaluate the “quality of individual medical practice” using medical treatment result data.

It is a figure which shows the structure of the medical treatment evaluation apparatus in embodiment of this invention. It is a figure which shows the example of registration of the medical treatment performance information in embodiment of this invention. It is a figure which shows the example of registration of the evaluation criteria table in embodiment of this invention. It is a flowchart of the medical treatment evaluation method in an embodiment of the present invention. It is a figure which shows the example of a display of the result of the medical treatment evaluation process in embodiment of this invention. It is a figure which shows the example of a display of the result of the medical treatment evaluation process in embodiment of this invention. It is a figure which shows the example of a display of the result of the medical treatment evaluation process in embodiment of this invention. It is a figure which shows the example of a display of the result of the medical treatment evaluation process in embodiment of this invention.

  As shown in FIG. 1, the medical treatment evaluation apparatus 100 according to the embodiment of the present invention includes a storage unit 110, an information processing unit 120, and a display unit 130. The medical treatment evaluation apparatus 100 can be realized by executing a medical treatment evaluation program by a computer.

  The information processing unit 120 is realized by a control unit such as a CPU of a computer. The information processing unit 120 functions as a medical practice extracting unit 121, a patient number calculating unit 122, and a totaling unit 123, which will be described later, by executing a medical evaluation program stored in advance in the storage unit 110. In addition, the information processing unit 120 includes input means (not shown) such as a keyboard and a mouse, receives input from the user of the medical evaluation device 100, and executes processing corresponding to the input.

  The storage unit 110 includes storage means such as a semiconductor memory, a hard disk, and an optical disk, and is connected to the information processing unit 120 so as to be accessible for reading and writing. The storage unit 110 stores a medical treatment evaluation program, medical treatment result information 111, and an evaluation criterion table 112.

  The display unit 130 includes output means such as a display and a printer, and presents information processed by the medical treatment record information 111 to the user. For example, the output from the totaling unit 123 is displayed as the evaluation result.

  Here, the medical treatment result information 111 and the evaluation criteria table 112 will be described.

  The medical treatment record information 111 is information including patient attributes (including attributes relating to the patient itself, genetic attributes of the patient, and the like) and the contents of the medical practice for the patient. In the present embodiment, as shown in FIG. 2, the medical treatment record information 111 includes “injury name”, “practical medical practice”, “age”, “gender” and the like associated with a patient (patient ID). Information. The medical treatment result information 111 may be stored in the external storage means as the medical treatment result DB 200, information may be acquired as necessary, or necessary information may be stored in the storage unit 110 in advance.

  The evaluation criteria table 112 is information relating to criteria for performing medical care evaluation. In the present embodiment, as shown in FIG. 3, the evaluation criterion table 112 includes “aggregation source selection item”, “medical practice”, “patient attribute”, and “patient attribute type” associated with “evaluation item”. , “First standard” and “second standard”.

  The “evaluation item” is an item that can evaluate the quality of the medical practice by analyzing the relationship between the medical practice and the attributes of the patient. The doctor selects a medical practice to be performed on the patient based on attributes such as the age of the patient based on medical guidelines and medical knowledge. For example, for patients with “mitral regurgitation”, two types of medical treatment, “valvuloplasty” and “valve replacement”, are selectively performed depending on the age and severity of the patient. . Among the criteria for selecting such medical practice, an item that is particularly important is set as an “evaluation item”, and various types of information used for evaluation are registered in association with the “evaluation item”.

  The “aggregation source selection item” is information for selecting a patient group as a population of the aggregation process from the medical treatment result information 111. The “aggregation source selection item” is an illness or medical practice. For example, when the evaluation item is “surgical method for mitral regurgitation”, a group of patients with mitral regurgitation becomes a population of the aggregation process. Further, when the evaluation item is “age and dose of vancomycin”, the patient group to which vancomycin has been administered becomes the population of the aggregation process.

  The “medical practice” is information indicating a medical practice to be noticed as a selection result of the medical practice among doctors' operations such as surgery and medication. When calculating the number of patients and the distribution of the number of patients with reference to “medical practice”, the aggregation target is selected. The population defined by the “aggregation source selection item” is further divided into a plurality of patient groups according to the medical practice performed by the doctor.

  “Patient attribute” is information indicating the patient attribute that is the axis when calculating the number of patients and the distribution of the number of patients for “medical practice”. When a doctor performs a medical practice, an appropriate medical practice is selected in consideration of patient attributes, but it is preferable to use patient attributes that are particularly recommended to be considered in the guidelines. For example, “patient attributes” are age, pregnancy status, serum creatinine concentration, and the like. Moreover, the patient attribute used as an axis | shaft may be not only one but two axes or more.

  “Patient attribute type” is information for identifying a patient attribute by the type of data. Here, information that can be expressed by continuous numerical values such as age is defined as quantitative data, and information that cannot be expressed by continuous numerical values such as sex is defined as qualitative data.

  The “first standard” is information indicating the standard value of the number of patients and the distribution of the number of patients, and an ideal value is considered in consideration of the relationship between the medical practice specified in the clinical practice guidelines and patient attributes. It is calculated in advance. The average value of the number of patients and the distribution of the number of patients calculated for a plurality of medical institutions may be used as the first standard. In addition, when it is desired to compare and evaluate medical institutions, the number of patients calculated for the medical institution to be compared and the distribution of the number of patients may be used as the first standard. For example, the “first standard” is a maximum value, a 75% percentile value, a median value, a 25% percentile value, a minimum value, and a patient treatment value for each “medical practice” corresponding to the “evaluation item”. It can be an implementation rate or the like.

  The “second standard” is information indicating the correlation of the first standard between each medical practice when there are a plurality of “medical practice” corresponding to the “evaluation item”, and the ideal value of the correlation between each medical practice. Is calculated in advance. Further, the average value of the correlation between each medical practice may be used as the second standard. Moreover, when it is desired to compare and evaluate the medical institutions, the correlation between the medical practices calculated for the medical institutions to be compared may be used as the second standard.

  Next, with reference to the flowchart of FIG. 4, the process in the medical care evaluation apparatus 100 in this Embodiment is demonstrated. The process starts when the user selects the “evaluation item”. In the present embodiment, the selection of “evaluation item” by the user is used as a trigger for starting the process, but the evaluation item may be automatically selected in turn regardless of the selection operation by the user.

  When the user selects “evaluation item”, the present invention starts processing, and the medical practice extraction means 121 inputs “evaluation item” (ST1). At this time, a group of “evaluation items” registered in the evaluation criteria table 112 is displayed on the display unit 130, and a user selects an “evaluation item” to be processed from the displayed group of “evaluation items”. Also good.

  The medical practice extraction means 121 refers to the evaluation criteria table 112 and extracts the aggregation source selection item corresponding to the “evaluation item” (ST2). The medical practice extraction means 121 extracts the medical treatment result information 111 including the same medical condition from the medical treatment result DB 200 and stores it in the storage unit 110 when the aggregation source selection item is “wound and sickness”. When the totaling source selection item is “medical practice”, the “medical practice” in the evaluation criteria table 112 is referred to, and the medical practice information 111 including the same medical practice is extracted from the medical practice DB 200 and stored in the storage unit 110. Store (ST3 to ST5).

  For example, if the selected “evaluation item” is “surgical method for mitral regurgitation”, the “aggregation source selection item” is “injury (mitral regurgitation)”. The medical record information 111 whose “injury” is mitral regurgitation is extracted from the DB 200 and stored in the storage unit 110. When the selected “evaluation item” is “age and dose of vancomycin”, since the “aggregation source selection item” is “medical practice (vancomycin administration)”, the “medical practice” is vancomycin from the clinical performance DB 200. The medical treatment result information 111 that is administration is extracted and stored in the storage unit 110.

  The medical practice extraction means 121 refers to the evaluation criteria table 112 and extracts a medical practice corresponding to the “evaluation item”. Further, the medical practice extraction means 121 refers to the evaluation criteria table 112 and extracts patient attributes and patient attribute types corresponding to “evaluation items” (ST6).

  For example, if the “assessment item” is a surgical method for mitral valve insufficiency, the medical treatment for it is “valvuloplasty” and “valve replacement”, “patient attribute” is age, and “patient attribute type” is It becomes quantitative data. In addition, when the “evaluation item” is the age and the dose of vancomycin, the medical treatments corresponding thereto are “less than 1 g of vancomycin administration” and “1 g or more of vancomycin administration”, “patient attribute” is age, and “patient attribute type” is It becomes quantitative data.

  Next, processing is changed depending on whether or not there are a plurality of extracted medical practices. If there are multiple, the process proceeds to ST8, and if not, the process proceeds to ST12 (ST7).

  If the patient attribute type is “quantitative data”, the patient number calculation means 122 extracts the patient corresponding to the “aggregation source selection item” for the selected “evaluation item” from the medical treatment record information 111, and the “evaluation item” For each “medical practice” corresponding to “,” the number of patients for whom the medical practice was performed is counted. In addition, a statistical distribution of the number of patients is calculated around the “patient attribute” corresponding to the “evaluation item”.

  The statistical distribution is, for example, a distribution (percentile value) of the number of patients with respect to medical practice and patient attributes. When the patient attribute values are rearranged in descending order, the counting unit 123 sets the value located at the center as the median value. 50% of patients are included above and below the median. Similarly, the values located at 25% and 75% are calculated as the 25th percentile value and the 75th percentile value, and are used as parameters for expressing the distribution of the number of patients.

  Further, using the percentile value for each medical practice calculated by the number-of-patient calculation means 122, a correlation value using the median difference is calculated (ST8, ST9). As an example of calculating the correlation value, the case where the medical practice is A and B will be described. The median value of group A is assumed to be lower than the median value of group B. The index numerator is the difference between the median values of group A and B, and the denominator is the sum of (absolute value from the median value of group A to the 75th percentile) and (absolute value from median value of group B to the 25th percentile). And The larger the calculated value, the larger the difference between the two groups, and it can be evaluated that the medical practice is selected according to the patient attribute. When the median value of group A is higher than the median value of group B, the denominator is (absolute value from the median value of group A to the 25th percentile) and (absolute value from the median value of group B to the 75th percentile). ). In the case of three or more, correlation values are similarly calculated for each combination.

  If the patient attribute type is “qualitative data”, the patient number calculation means 122 includes the patient attribute for each patient corresponding to the “aggregation source selection item” for the selected “evaluation item” and “patient attribute”. Each patient is extracted and counted. Then, the counting unit 123 calculates an implementation rate for each combination of medical practice and patient attributes, vectorizes each implementation rate, and calculates an inner product of the unit vectors as a correlation value (ST8, ST10). If the value of the inner product is small, there is little correlation between patient distributions in each medical practice, and it can be said that the medical practice is selected according to patient attributes.

  Subsequently, the counting unit 123 refers to the evaluation criterion table 112, extracts the second standard corresponding to the “evaluation item”, and compares it with the calculated correlation value. Then, the absolute value of the difference between the correlation value and the second standard is calculated and used as an evaluation value representing the deviation state (ST11).

  And a graph is produced | generated from a total result, and it outputs to the display part 130 with the calculated evaluation value. Display unit 130 receives the input from counting means 123 and displays a graph (ST16).

  On the other hand, if the number of “medical practice” is one, the process proceeds from step ST7 to ST12. If the patient attribute type is “quantitative data”, the patient number calculation means 122 extracts the patient corresponding to the “aggregation source selection item” for the selected “evaluation item” from the medical treatment result information 111 and becomes the target. The number of patients corresponding to each of “patient attributes” for “medical practice” is counted. In addition, a statistical distribution of the number of patients is calculated around the “patient attribute” corresponding to the “evaluation item”.

  The statistical distribution is, for example, the distribution (percentile value) of the number of patients for “medical practice” and “patient attributes”. Then, the aggregation unit 123 calculates the median value from the percentile value (ST12, ST13).

  If the patient attribute type is “qualitative data”, the patient number calculation means 122 includes the patient attribute for each patient corresponding to the “aggregation source selection item” for the selected “evaluation item” and “patient attribute”. Each patient is extracted and counted. The number of patients including the medical practice is counted from the extracted medical performance information 111, and the number of patients including the patient attribute is counted for each patient attribute. And the totaling means 123 calculates the implementation rate of medical practice for every patient attribute using the number of patients (ST12, ST14).

  Subsequently, the aggregation unit 123 refers to the evaluation criterion table 112, extracts the first standard corresponding to the “evaluation item”, and compares it with the calculated value (for example, the median or implementation rate of the percentile). Then, the calculated value and the correlation value of the first standard are calculated and set as an evaluation value representing the deviation state (ST15).

  That is, if it is “quantitative data”, the correlation value between the distribution of the facility and the standard distribution (first standard) is calculated using the percentile value for each medical practice calculated by the patient number calculation means 122. Let it be an evaluation value. The procedure for calculating the correlation value is the same as in the case where there are a plurality of “medical practice”. The value of the first standard refers to “first standard” in the evaluation criteria table 112.

  If it is “qualitative data”, a correlation value is calculated from the calculated execution rate and the standard execution rate (first standard), and is used as an evaluation value. The calculation procedure of the correlation value is calculated by the inner product of the vectors as in the case where there are a plurality of “medical practice”. The value of the first standard refers to “first standard” in the evaluation criteria table 112.

  The aggregation means 123 generates a graph from the information used for calculating the evaluation value, and outputs it to the display unit 130 together with the calculated evaluation value. Display unit 130 displays the graph in response to input from counting means 123 (ST16).

  The processing in the medical treatment evaluation apparatus 100 according to the present embodiment will be described with a specific example. In the following example, an example in which medical evaluation regarding the facility A is performed will be described.

  When the “evaluation item” is administration of angiotheosin to a patient with high blood pressure and impaired renal function, a patient corresponding to the wound or illness (high blood pressure, renal dysfunction), which is the “aggregation source selection item”, is extracted from the medical treatment result information 111. Then, the patients who have been administered antethecin as the corresponding “medical practice” are counted for each serum creatinine concentration of “patient attribute”. At this time, since there is one “medical practice” and the serum creatinine concentration of “patient attribute” is quantitative data, the distribution (percentile value) of the number of patients is determined according to the counting result. Specifically, the maximum value, 75% percentile value, median value, 25% percentile value and minimum value of serum creatinine concentration are determined. Further, the maximum value, the 75% percentile value, the median value, the 25% percentile value, and the minimum value of the serum creatinine concentration are read out from the evaluation criterion table 112 as the “first standard value”. Further, the distribution of the facility is calculated as the evaluation value with the group A and the standard distribution (first standard) as the group B, and the correlation value between the distribution in the facility A and the standard distribution.

  The statistical evaluation result can be shown as a graph in FIG. In FIG. 5, the range between the maximum value and the minimum value of serum creatinine concentration is indicated by a thin line for each of the facility A and the standard, and the ranges of the 75% percentile value and the 25% percentile value are overlaid on the thin line. It is shown as a rectangle. The median is shown as a line in a white rectangle. Further, an evaluation value indicating the correlation between the distribution in the facility A and the standard distribution is also displayed together with the graph.

  When the “evaluation item” is decompression craniotomy for one-sided cerebral hemisphere infarction, a patient corresponding to a wound or illness (one-side cerebral hemisphere infarction) that is a “counter selection item” is extracted from the medical treatment result information 111. Then, the implementation rate is obtained for each stroke severity evaluation scale (less than 15 and more than 15 severity) of the “patient attribute” for patients who have undergone decompression craniotomy, which is the corresponding “medical practice”. At this time, since there is one “medical practice” and the stroke severity evaluation scale of “patient attribute” is qualitative data, an X-axis vector component having an implementation rate with a severity of less than 15 as an absolute value, A composite vector of Y-axis vector components having an implementation rate of severity 15 or higher as an absolute value is obtained. Then, from the evaluation criteria table 112, an X-axis vector component having an implementation rate with a severity of less than 15 as the “first standard value” as an absolute value, and a Y-axis vector component having an implementation rate with a severity of 15 or more as an absolute value. And the inner product value of the calculated combined vector and the standard vector is calculated as an evaluation value indicating the correlation between the distribution in the facility A and the standard distribution.

  The statistical evaluation result can be shown as a graph in FIG. In FIG. 6, the implementation rate of the decompression craniotomy for each stroke severity evaluation scale is shown in a graph for each of the facility A and the standard. Further, an evaluation value indicating the correlation between the distribution in the facility A and the standard distribution is also displayed together with the graph.

  When the “evaluation item” is an operation method for mitral regurgitation, a patient corresponding to a wound or illness (mitral regurgitation), which is a “total source selection item”, is extracted from the medical treatment result information 111. And it counts for every age of "patient attribute" about each of the patient who performed the valve forming operation and valve replacement operation which are applicable "medical practice." At this time, the “medical practice” includes two types of annuloplasty and valve replacement, and the age of the “patient attribute” is quantitative data. Therefore, the distribution of the number of patients (percentile value) depends on the counting result. ) Specifically, for each of the valvuloplasty and valve replacement, the maximum value, 75% percentile value, median value, 25% percentile value, and minimum value of the age of the treated patient are determined. Further, the distribution value of the valvuloplasty in the facility A and the distribution of the valve replacement operation in the facility A are calculated as a group A and the distribution of the valve replacement operation in the facility A as the group B, respectively. Further, from the evaluation criteria table 112, the maximum value, 75% percentile value, median value, 25% percentile value and minimum value of the patient's age stored in advance for each of the plastic surgery and the valve replacement as the “first standard value”. Read the value. Further, a correlation value between the distribution of the valvuloplasty and the distribution of the valve replacement is calculated by setting the distribution of the standard valvuloplasty as the group A and the distribution of the standard valvular replacement as the group B. Then, the difference between the correlation value at the facility A and the correlation value at the standard is calculated as an evaluation value.

  The statistical evaluation result can be shown as a graph in FIG. FIG. 7 shows the age distribution of patients who have undergone valvuloplasty and valve replacement for each of Facility A and Standard. That is, the range between the maximum and minimum age of patients undergoing valvuloplasty and valve replacement is indicated by a thin line, and the range of 75% percentile value and 25% percentile value is outlined on top of it. It is shown as a rectangle. The median is shown as a line in a white rectangle. Furthermore, the correlation value between the distribution of the valvuloplasty in the facility A and the distribution of the valve replacement, and the distribution of the standard valvuloplasty and the distribution and correlation values of the standard valve replacement are also displayed together with the graph. . Further, the difference between the correlation value at the facility A and the correlation value at the standard is also shown as an evaluation value.

  When the “evaluation item” is the number of female epileptic chemotherapy doses, a female patient corresponding to a wound or illness (epilepsy), which is the “total source selection item”, is extracted from the medical treatment result information 111. And the implementation rate is calculated | required for the presence or absence of the pregnancy of "patient attribute" about the patient who performed single agent administration and 2 or more agents which are applicable "medical practice". At this time, since there are two “medical practices” and the presence / absence of pregnancy in the “patient attribute” is qualitative data, the X-axis vector having the absolute value of the implementation rate of single agent administration for female patients with pregnancy A first composite vector of the Y-axis vector component having the absolute value of the component and the single agent administration rate for a female patient without pregnancy is obtained. In addition, an X-axis vector component having an absolute value of the implementation rate of two or more drugs for a female patient with pregnancy and a Y-axis vector component having an absolute value of the implementation rate of two or more drugs for a female patient without pregnancy. Find two composite vectors. Then, the inner product value of the first combined vector and the second combined vector is calculated as a correlation value between two “medical practice” (single agent administration and administration of two or more agents). Further, the implementation rate of single agent administration for a female patient with pregnancy and the implementation rate of single agent administration for a female patient without pregnancy, which are “first standard values”, are read from the evaluation criterion table 112, and each of them is read as an X-axis vector component and A third composite vector as a Y-axis vector component is obtained. Further, from the evaluation standard table 112, the execution rate of two or more drugs administered to a female patient with pregnancy and the execution rate of two or more drugs administered to a female patient without pregnancy, which are “first standard values”, are read out, and each of them is an X-axis vector. A fourth composite vector as a component and a Y-axis vector component is obtained. Then, the inner product value of the third synthetic vector and the fourth synthetic vector is calculated as a standard correlation value between two “medical practice” (single agent administration and administration of two or more agents). Further, the difference between the correlation value at the facility A and the correlation value at the standard is calculated as an evaluation value.

  The statistical evaluation results can be shown as a table in FIG. In FIG. 8, for each of the facility A and the standard, the implementation rate of single agent administration and two agent administration or more for each pregnancy is shown as a percentage. Furthermore, the correlation value between the distribution of single-agent administration and the distribution of two or more agents in Facility A, and the correlation value between the standard single-agent administration distribution and the distribution of two or more agents are also shown. Further, the difference between the correlation value at the facility A and the correlation value at the standard is also shown as an evaluation value.

  In addition, the display method of the evaluation result of medical practice is not limited to the example of FIGS. What is necessary is just to display so that the process result in the medical treatment evaluation apparatus 100 can be compared with "first standard" or "second standard".

  As described above, according to the medical treatment evaluation apparatus 100 in the present embodiment, an objective evaluation is performed on an evaluation target designated as an “evaluation item” with reference to a graph or a table showing statistical values. Easy to do. Further, by comparing the evaluation value calculated for the facility to be evaluated with the standard evaluation value, it becomes easier to objectively evaluate the medical practice in the facility to be evaluated. In addition, when there is a possibility that multiple “medical practices” may be performed for one medical practice, it is easy to objectively evaluate each medical practice by referring to the correlation value of the implementation of multiple medical practices. .

  In addition, processing may be performed with a target period for medical evaluation limited. For example, the date and time of performing a medical practice may be registered in the medical treatment result information 111, and the information regarding the patient corresponding to the target period may be extracted and processed upon receiving the input of the target period during the evaluation process.

  Further, the treatment may be performed by limiting the department (for example, surgery, internal medicine, etc.) in which medical care is performed. For example, the department in which the medical practice has been performed is registered in the medical treatment record information 111, and only the information related to the patient who has received the medical practice in the target department is extracted in response to the input of the target department during the evaluation process. And may be processed. When there are two patient attributes corresponding to the evaluation item, a graph or a table may be displayed with the patient attributes as two axes.

  Further, correlation values and evaluation values calculated by the medical evaluation device 100 may be stored with time, and changes with time of those values may be displayed as a graph or a table. By showing changes in correlation values and evaluation values over time, it is possible to objectively determine whether the clinical practice performed at the facility being evaluated is approaching the standard clinical practice or the clinical practice carried out at other facilities. It is easy to make a judgment.

  DESCRIPTION OF SYMBOLS 100 Medical treatment evaluation apparatus, 110 Memory | storage part, 111 Medical treatment result information, 112 Evaluation criteria table, 120 Information processing part, 121 Medical treatment extraction means, 122 Patient number calculation means, 123 Totaling means, 130 Display part.

Claims (4)

For each evaluation item for evaluating a medical practice in a medical institution, a first showing a medical practice related to the evaluation item, a patient attribute related to the medical practice, and a standard relationship between the medical practice and the patient attribute An evaluation criteria table that associates standards,
Medical treatment record information that associates at least patient attributes with the medical practice performed for each patient;
A storage unit for storing
An information processing unit that statistically processes a medical practice in the medical institution based on the evaluation criteria table and the medical performance information,
A display unit for displaying a processing result in the information processing unit;
With
The information processing unit
A medical practice extracting means for receiving a selection of an evaluation item and extracting a medical practice corresponding to the selected evaluation item and a patient attribute related to the medical practice from the evaluation criteria table;
Patient number calculation means for obtaining the number of patients or the distribution of the number of patients in which the extracted medical practice is performed for each patient attribute related to the extracted medical practice with reference to the medical performance information,
A first unit that extracts the first standard corresponding to the selected evaluation item from the evaluation criterion table, and a totaling unit that tabulates the number of patients or the distribution of the number of patients and the extracted first standard in a comparable manner;
Display means for causing the display unit to display the result of the aggregation by the aggregation means;
A medical evaluation device characterized by comprising: The medical evaluation device according to claim 1,
The counting means calculates a deviation state between the number of patients or the distribution of the number of patients and the extracted first standard as an evaluation value,
The medical evaluation device, wherein the display means displays the evaluation value in a totaled result. The medical evaluation device according to claim 1 or 2,
The evaluation criteria table includes a second standard indicating a correlation between the first standards of a plurality of medical practices,
The counting means includes
When a plurality of medical practices are associated with the selected evaluation item, the number of patients who have been subjected to the extracted medical practices or the distribution of the number of patients is obtained for each combination of the medical practices and related patient attributes. , Calculate the correlation between the number of patients or the distribution of the number of patients between the medical practice, and calculate the deviation state from the second standard as an evaluation value,
The medical evaluation device, wherein the display means displays the evaluation value in a totaled result. Computer
For each evaluation item for evaluating a medical practice in a medical institution, a first showing a medical practice related to the evaluation item, a patient attribute related to the medical practice, and a standard relationship between the medical practice and the patient attribute With reference to a storage unit that stores an evaluation standard table in which standards are associated with each other and medical treatment result information in which at least patient attributes are associated with medical treatments performed, the evaluation standard table and the medical treatment result information are stored. An information processing unit that statistically processes medical practice in the medical institution based on
A medical practice extracting means for receiving a selection of an evaluation item and extracting a medical practice corresponding to the selected evaluation item and a patient attribute related to the medical practice from the evaluation criteria table;
Patient number calculation means for obtaining the number of patients or the distribution of the number of patients in which the extracted medical practice is performed for each patient attribute related to the extracted medical practice with reference to the medical performance information,
A first unit that extracts the first standard corresponding to the selected evaluation item from the evaluation criterion table, and a totaling unit that tabulates the number of patients or the distribution of the number of patients and the extracted first standard in a comparable manner;
An information processing unit including display means for displaying on the display unit the results obtained by the counting means;
A display unit for displaying a processing result in the information processing unit;
A medical evaluation program characterized by functioning as

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