JP3950118B2 - Receipt screening apparatus, control method therefor, and computer program - Google Patents

Description

  The present invention relates to a receipt screening apparatus, a control method thereof, and a computer program.

Conventionally, examination of receipts (medical remuneration specifications) by a computer has been performed by comparing correspondence data of drug names and injury and disease names already in a database (see Patent Document 1 and Patent Document 2). Here, the data used as a reference for comparison is data of an indication disease name set in advance for each medical practice.
JP 2002-366648 A JP 2003-196383 A

  Since the above-mentioned conventional receipt screening system is a uniform screening system based on the description contents of the indication document, it does not match the description of the indication document itself, but it is determined based on the pharmacological judgment of the doctor. Even a receipt that contains a drug prescribed for the name of an injured person and passes the examination of the actual examination organization does not necessarily give a pass judgment, and the examination result in the system and the actual examination result are different It did not function as an effective system.

The present invention for solving the above problems is as follows.
A receipt screening device,
A storage means for storing receipt data including information on a medical practice performed on a patient and a name of a wound and disease in association with each patient, and indication data of text data including information on a name of a wound and disease applicable to a medical practice; ,
The check data for determining the name of the disease applicable to the medical practice by editing the indication data is separated from the indication data based on the presence or absence of a symbol for separating a sentence or a segment, and a specific character Generating means for generating in advance for each medical practice by removing the column and dividing the character string by a predetermined number so that a part of the preceding and following character strings overlaps;
First extraction means for extracting, from the receipt data for each patient in the examination month, first medical practice information and first wound name information associated with the first patient;
Using the check data corresponding to the extracted first medical practice information, the first medical practice information, and the first injury name information, a receipt of the examination month of the first patient It is determined whether or not the data includes the names of wounds and sickness names that can be applied to the medical practice included in the first medical practice information for all the medical practices included in the first medical practice information. First determination means;
Determining means for determining acceptance / rejection of the receipt data for each patient based on the result of the determination ;
The generating means includes
Second extraction means for extracting second medical practice information and second wound name information for each patient from the receipt data for each patient for a plurality of months including the examination month;
Based on the second wound name information, a determination means for determining for each patient whether or not there is wound name information corresponding to a wound name newly added in the examination month,
Using the check data corresponding to the second medical practice information, the second medical practice information, and the second injury name information, the second medical examination data is included in the multi-month receipt data. Second determination for determining for each patient whether or not injury name information of an injury and illness name applicable to an operation information corresponding to the operation information is included for all the medical operations included in the second medical operation information Means,
Corresponding to the medical practice included in the second medical practice information when it is judged by the second judgment means that it is determined that it is included and there is a newly added injury / illness name by the discrimination means From the check data including the character string of the newly added wound name among the check data to be checked, at least of the wound names other than the newly added wound name among the wound names included in the second wound name information Editing means for deleting a character string that matches a part and adding a character string of the newly added disease name
The provided, characterized that you previously generate the check data.

  According to the present invention, the receipt screening process can be performed with high accuracy in accordance with the actual state of screening.

  Embodiments of the present invention will be described below. Of course, the embodiment described below is merely a subordinate concept of the present invention disclosed as a superordinate concept. That is, the following embodiments are only a part of the embodiments included in the technical scope of the present invention defined by the claims. Therefore, the invention in common with the present invention described in the scope of claims is an invention corresponding to an embodiment not directly described in the present specification or drawings. It is included in the technical scope.

  FIG. 1 is an overall conceptual diagram of the present invention and shows an overall structural concept of the implementation of the present invention. In FIG. 1, reference numeral 1 denotes a receipt examination apparatus according to the present invention, which accepts input of receipt data relating to a medical practice performed by a doctor on a patient, generates check text as check data for receipt check, and generates the check The text correction processing is performed and stored in the database 2, and the examination result of the receipt is displayed and printed out. In addition, it accepts correction data input from the operator and enables manual correction of the check text.

  In general, "medical practice" in the reception is classified into 9 categories: "diagnosis", "medicine", "injection", "treatment", "surgery", "examination", "diagnosis", "other", and "hospitalization" The drugs used are to be listed in the medication and injection categories. In the present embodiment, “medicine” and “injection” in the medical practice will be described in order to avoid complicated explanation. However, the medical practice to which the present invention can be applied is not limited to this category, and the present invention can naturally be applied to medical practices belonging to other categories.

  In the present embodiment, the check text is text data obtained by converting information related to drug indications into a character string in the check text generation processing of the present invention, and is data that is corrected to reflect the contents of past receipts.

  Here, the indication refers to the names of wounds and the like that can be applied to the medicines recognized for each drug used in insurance medical treatment. This indication is defined by the Ministry of Health, Labor and Welfare, and the indication includes the name of the wound, but there are cases where various annotations other than the name of the injury and the disease state to be indicated are described. Since the reception only has a column for the name of the wound, the examination is performed based on the name of the wound that will be indicated based on the indication. In addition, the text data of the indication is hereinafter referred to as indication data.

  FIG. 2a is a diagram showing a hardware configuration of the receipt screening apparatus 1 of the present invention. In FIG. 2, a CPU 3 is a processing unit that controls the entire receipt screening apparatus 1. The input unit 4 includes a user interface such as a mouse and a keyboard, and accepts input of receipt data. The internal storage device 5 is a storage means such as a hard disk and stores a processing program corresponding to the present invention. A RAM (random access memory) 6 functions as a data work area and a temporary save area. The display unit 7 is a display device composed of a CRT or a liquid crystal monitor, and displays an input reception screen for receiving receipt data and a display screen for a receipt examination result. The printer 8 is a printing apparatus that outputs a receipt examination result to a recording medium such as paper, and is connected to the receipt examination apparatus 1 through an interface such as a USB.

  In the above configuration shown in FIG. 2a, the processing program stored in the internal storage device 5 from the medical information stored in the database 2 using the RAM 6 is used to check text generation processing, receipt screening processing, etc. The processing is executed, and processing results such as receipt data and check text are stored in the database 2. The processing result is output via the display unit 7 and the printer 8.

  Next, an outline of processing in the receipt screening apparatus 1 will be described with reference to FIG. FIG. 2b is a diagram showing an outline of processing in the receipt screening apparatus 1 of the present invention. First, the processing in the present embodiment is broadly divided into a process of generating a check text for receipt examination and a process of examining receipt data based on the generated check text.

  In the check text generation step, first, indication data corresponding to the drug name described in the receipt is extracted from the database 2 in F1. A check text is generated using the indication data extracted in F2. Details of the check text generation method will be described later. The generated check text is appropriately corrected in F3 and stored in the internal storage device 5 and the database 2.

  In the review process of the receipt data, first, in F4, the drug name and injury / illness name in the input receipt data are extracted, and in F5, the presence / absence of a character string matching the injury / illness name in the extracted drug check text Is judged to be acceptable, if not, it is rejected.

  Hereinafter, embodiments of the present invention will be described in detail with reference to flowcharts.

  FIG. 3 is a flowchart of check text generation processing executed in the receipt screening apparatus 1 corresponding to the present embodiment. A program corresponding to the flowchart of FIG. 3 is stored in the internal storage device 5, read into the RAM 6, and executed by the CPU 3.

  In FIG. 3, the check text generation process will be described first. In step 100, the patient code, name, disease name start date, medical practice, Ministry of Health and Welfare code, medical treatment are obtained from the patient's receipt data in a plurality of months including the examination month inputted from the input unit 4 of the receipt examination apparatus 1 and stored in the database 2. Information such as the action start date is sequentially extracted in association with each other. An example of the extracted data is as shown in FIG. 13 and is made into a database in the database 2 corresponding to each item. Therefore, by storing this database, it is possible to perform various item-specific searches, statistical processing, and the like. The database processing method is a well-known technique, and the description of the operation of the database itself is omitted here in order to avoid complexity.

  Next, in step 101, it is determined whether or not there is a newly appearing drug for the data registered in the database 2. If there is a new medicine (“YES” in step 101), the process proceeds to step 102. On the other hand, if there is no new medicine, the routine proceeds to step 104. In step 101, the presence or absence of a new disease name is also determined. Here, “new disease name” means the name of the disease whose start date is the examination month, and “old disease name” means the name of the disease whose start date is before the previous month.

  In step 102, it is determined whether there is indication data for the new drug. Information including indication data of a drug that has not been converted into a check text is stored in the database 2 in advance, and the presence or absence of indication data can be determined based on the registered contents of the database 2. As a result of the determination, if data exists, the process proceeds to step 103, and if data does not exist, the process proceeds to step 104.

  In step 103, a check text for a new drug is generated based on the indication data. Details of the processing in step 103 are as shown in the flowchart of FIG. FIG. 4 is a flowchart illustrating an example of processing for editing the indication data and generating check text corresponding to the present embodiment. Here, in step 201, indication data of a new drug is separated based on symbols (for example, “,” “.” “,” “.” “;” “:”, Etc.) that delimit sentences or clauses. For example, when an indication for explanation of indication as shown on the right side of FIG. 10 is separated for each symbol, data as shown in FIG. 11 is obtained.

  In step 202, a specific character string (for example, “acute”, “chronic”, “senile”, “disease”, “disease”, etc.) is deleted from the separated data.

  Next, in step 203, it divides | segments so that the word before and behind may overlap within two characters. For example, in the case of “deformable joint”, it is divided into “deformation”, “formality”, “sex”, and “joint”. An example of dividing the data of FIG. 11 in this way is as shown in FIG. The number of characters to be divided is not limited to two characters, and may be three or more characters, for example.

  The check text of the drug generated as described above is added to the check text related to other drugs in step 204 and stored in the database 2.

  In step 104, the operator is prompted to make a decision and a manual check text input is accepted. Here, the input of the character string of the content corresponding to the check text produced | generated in step 103 is received.

  Here, in the case of a drug, there is basically indication data, so that it is rare to receive an operator's manual input in this step. On the other hand, when other actions such as “examination” and “diagnosis” are performed, the indications are not prescribed by the Ministry of Health, Labor and Welfare, and doctors who are operators are based on medical knowledge. The name of the wound corresponding to the indication can be entered.

  The processing in step 104 may be performed collectively without being performed in real time. In the present embodiment, a case where processing is performed in real time has been shown in order to avoid complicated description.

  Next, in step 105, disease name processing is performed. The disease name process is a process in which the description in the disease name column of the receipt is made independent for each wound name in order to enable the process using the check text. Specifically, in the disease name column, there may be a plurality of injury names such as “angina, hyperlipidemia and acute bronchitis”. In this case, in order to determine the indication of the drug Must distinguish between three wound names. Therefore, the names of wounds and diseases are separated based on the presence or absence of a punctuation mark (,) or a word “Kane”, which is a criterion for distinguishing between the names of wounds and diseases.

  Next, in step 106, processing for removing the suspected disease name is performed. The names of wounds and illnesses listed on the receipt are not all confirmed wounds and illnesses. If a doctor suspects that the patient's condition falls under the name of the wound or illness, such as “suspected liver dysfunction” Description is made. Such a description is made at the time of the examination, but since a specific drug is not prescribed based on an indefinite disease name, in this embodiment, an unidentified disease name such as “suspected” Are excluded from processing. Therefore, in this step, when the word “suspect” is present in the character string of the disease name separated in step 105, the character string itself is deleted from the check text.

  Subsequently, in step 106, a drug corresponding to unconditional adaptation among the drugs described in the receipt is determined. “Unconditional indication drug” refers to a drug that has been used continuously over a certain period for the same patient, regardless of the name of the target disease.

  Specifically, in step 106, among the data extracted in step 100, the names of drugs that have been used continuously over a plurality of months including the examination month are selected from the drugs used in medication or injection as a medical practice. Extract. At this time, “multiple months” can be set as a default of, for example, three months, but it is not always necessary to match the period extracted in step 100. That is, in step 100, half a year is extracted, but the threshold for the period of continuous use in this step can be set to 3 months including the examination month.

  In addition, the target disease name here refers to a name of an injury or disease that includes at least one character string included in the check text of the drug. For example, when the word “nervous” is included in the check text of drug A, “autonomic dystonia” as the name of the wound includes “nerve” and thus becomes the target disease name of drug A. The medicine corresponding to “unconditional indication” is newly registered in the unconditional indication medicine table as shown in FIG. Therefore, in the subsequent processing, it is possible to determine whether or not the predetermined medicine corresponds to the unconditional application medicine by referring to the unconditional adaptive medicine table without performing the processing in this step.

  Next, in step 107, collation processing is performed. The collation process is a target for a specified medicine in a receipt (excluding medicines that have been excluded from processing in advance, that is, unregistered adaptive medicine table and medicine registered in a non-examined medicine table to be described later). This is a process for determining whether or not a disease name exists.

  Details of the collation processing will be described with reference to FIG. First, in step 301, the drug name and injury / illness name described in the receipt within a predetermined period including the examination month are extracted for each patient. At that time, the medicine registered in the unconditional indication medicine table and the non-examination medicine table is not extracted. Next, in step 302, it is determined using the check text whether or not there is a wound name corresponding to the target disease name of the extracted drug name in the extracted wound name.

  Specifically, when a drug having the name “Camphatanine Tablet” as shown in FIG. 12 is present in the receipt, the name of the injury / disorder “degenerative arthropathy” in the receipt is “deformation” in FIG. 12. Since it matches the character string of “formality”, “sexuality”, and “joint”, it is determined that osteoarthritis is the target disease name of the camphatanine tablet. Similar processing is executed for drugs other than those determined to be unconditional adaptation in step 106.

  As a result, if there is a target disease name for all the drugs to be processed (“YES” in step 303), it is determined in step 304 that the receipt is acceptable, and there is no drug for which there is no target disease name. If so ("NO" in step 303), in step 305, the receipt is determined to be unacceptable.

  Next, in step 108, grouping processing is performed. This grouping process is a process of grouping each receipt data into four types of group A, group B, group C, and group D based on the determination result of the presence or absence of a new disease name in step 101 and the collation result in step 107. . Group A includes a receipt that has been determined to pass in the verification process and has no new disease name. Group B includes those that pass the verification process and have a new disease name. Group C belongs to those that fail the verification process and have no new disease name. Group D includes those that fail the verification process and have a new disease name.

  The receipt belonging to group B (“GrB” in step 108) is subjected to group B processing in step 109. Details of the group B processing will be further described with reference to FIG.

  First, in step 401, it is verified based on the check text whether or not a drug whose target disease name is “new disease name” (hereinafter referred to as “FP drug”) is included in the receipt. In the collation processing in step 107, the search for the injury / illness name is performed from the drug side, but in this step, the drug search is performed based on the new disease name. If there are a plurality of “new disease names”, each is processed.

  Based on the verification result in step 401, in step 402, group B is further subdivided according to the number of FP drugs existing for one new disease name. Specifically, a group in which one FP drug exists is referred to as group B1, a group in which a plurality of FP drugs exist is referred to as group B2, and a group in which no FP drug exists is referred to as group B3.

  The process in the above steps will be described more specifically. If “vitamin B1 deficiency” is added as a new disease name in the receipt in which the names of wounds and drugs as shown in FIG. 16 are described, the target disease name is “ It is verified whether there is a drug containing “vitamin B1 deficiency”.

  In the case of FIG. 16, the indication of “Biogen 50 injection” includes the word “vitamin B1 deficiency”, but there is a character string included in “vitamin B1 deficiency” in other drugs. do not do. Therefore, the FP drug becomes a Biogen 50 injection solution. Therefore, this receipt belongs to the group B1.

  Here, the old disease names include “cervical neuralgia” and “autonomic dystonia”, and the word “nerve” is included in the description column of the indication of “Biogen 50 injection”. That is, in the check text as it is, “cervical neuralgia” or “autonomic dystonia” may be detected as the target disease name of Biogen 50 injection solution. For example, even if “vitamin B1 deficiency” is not described as the name of the wound, if “cervical neuralgia” is described, it is determined that the verification process is successful.

  As described above, in the present embodiment, a case where a drug is mistakenly determined to have “target disease name” even though there is no actual disease name for a certain drug is defined as False Positive (FP). If the FP exists, the “non-adapted” drug is determined as “adapted”, so that the “failed” receipt is mistakenly determined as “accepted”.

  In order to prevent such FP, in step 403, which is the process for the group B1, a part that matches the “old disease name” of the FP drug is deleted from the check text and becomes the target disease name of the FP drug. Check text correction, such as adding a new disease name to the check text. In the above example, the word “nerve” is deleted from the check text of the Biogen 50 injection, and “vitamin B1 deficiency” corresponding to the new disease name is added. As a result, it is not determined that the name of the disease is a target disease name based on the check text, but the name of the disease can be reliably identified.

  Next, the processing in steps 401 and 402 will be described for a receipt belonging to group B2. For example, in the receipt in which the name of the wound and the drug as shown in FIG. 17 is described, if “neurosis” is added as a new disease name, whether or not there is a drug containing “neuropathy” as the target disease name. Is verified. In this case, since the character strings of “nerve” are included in the check texts of “Selenal Tablets” and “Neovitacaine Injection”, these drugs are FP drugs for “neuropathy”. Therefore, it is determined that this receipt belongs to the group B2.

  Here, “sciatica” is described in the old disease name. “Sciatica” is not included in the indication of the Serenal tablet, but because it includes the word “nerve”, it is determined as the name of the target disease in the matching process in step 107. Here, in order to change the check text so that “sciatica” is not determined as the target disease name, the related FP drug must be determined. Here, the “related FP drug” refers to a drug having the highest correlation with a new disease name among a plurality of FP drugs.

  Therefore, in step 404, if there is a drug that is the same as the drug in group B1 and has the same new disease name as the FP drug in group B2, the FP drug is set as the related FP drug.

  Next, in step 405, group B2 is grouped for each FP drug (excluding the drug determined as the related FP drug in step 404). In step 406, the number of FP drugs having the same new disease name is equal to or greater than g, and the number of FP drugs present in the ratio of q is equal to or greater than 100 per 100 group B receptors is set as the related FP drug. Here, g and q are integers of 1 or more, and the initial values can be set as g = 3 and q = 3.

  Through the above processing, a drug having the highest correlation with a new disease name is determined from among a plurality of FP drugs. In step 407, the check text is corrected such that the portion of the related FP drug that matches the “old disease name” in the receipt is deleted from the check text, and the new disease name that is the target disease name of the related FP drug is added to the check text. Do. In the case of FIG. 17, “Selenal tablet” is determined as the related FP drug, “nerve” in the check text of “Selenal tablet” is deleted, and the character string “neuropathy” corresponding to the new disease name itself is added.

  Note that no special processing is performed for the group B3.

  Next, processing for groups C and D (“GrC, D” in step 108) will be described. Groups C and D may include a drug (hereinafter referred to as an FN drug) that is mistakenly determined as “no target disease name” even though the target disease name exists. In addition, since there is a possibility that the FN drug includes a drug that is not subject to examination, in step 110, processing for determining a drug that is not subject to examination is performed. Details of the processing in step 110 will be described with reference to FIG. FIG. 7 is a flowchart of the non-examination drug determination process.

  Here, the “non-examination drug” refers to a drug that is not subject to subsequent reception examination processing in the receipt examination apparatus 1 of the present invention regardless of the presence or absence of the target disease name in the receptor. In actual examinations, the drug price is generally low, and drugs used for symptoms rather than disease names such as antipyretic drugs, intestinal preparations, stomach medicines, and coughs are often excluded from examination. Drugs that satisfy this condition are determined not to be examined, so that the presence of the drug does not affect the acceptance / rejection determination of the receipt. Note that the data on non-examined drugs is tabulated in the database 2 (non-examined drug table), and is used to determine whether the drug falls under non-examined drugs. A configuration example of the non-examined drug table is as shown in FIG.

  First, in step 501, the receipts to be processed are processed again every month for all drugs (excluding drugs registered in the unconditional indication table and non-examination drug table) for all wound names. Execute the verification process.

  As a result, since it can be newly divided into groups A ′ to D ′, in step 502, for the receptors belonging to group C ′ and group D ′, for each drug for which no target disease name exists (hereinafter referred to as non-labeled drug). Regroup. Here, the term “non-indication drug” is used to distinguish the drug from the FN drug, which is a drug that is mistakenly determined as “no target disease name” even though the target disease name exists.

  In step 503, the number of receptors included in a group of off-label drugs is i or more, and j is 100 or more per 100 cases included in groups C ′ and D ′, and the price of the off-label drugs is e yen. If the drug is less than 1, the drug is excluded from the review. Here, i, j, and e are integers of 1 or more, respectively, and initial values can be i = 20, j = 10, and e = 10.

  As described above, it is possible to determine non-examined drugs included in the Group C and D receipts. Next, in step 111, FN test processing is performed. The FN test process is a process for determining an FN drug by determining the correlation between the off-label drug in groups C and D and the name of the wound. Details of the FN test process will be described with reference to FIG.

  In step 601, all the names of wounds and diseases in the processing target receipt are totaled, and the expression frequency (t1) of each wound name is calculated. Next, in step 602, the processing target receptors of groups C and D are grouped for each off-label drug. Subsequently, in step 603, the names of wounds and diseases included in each group are tabulated, and the frequency of occurrence (t2) of the names of each disease is calculated.

  In step 604, if the number of receipts in a certain group is greater than or equal to u, the number of receipts including the name of the disease is greater than or equal to s per 100 receipts in groups C and D, and t2 / t1> k. It is determined that the name of the wound is strongly correlated with the off-label drug. Here, u, s, and k can be integers of 1 or more, and initial values can be n = 5, s = 3, and k = 10. In other words, this indicates that the off-label drug is an FN drug in groups C and D.

  For group D receptors, the correlation between the off-label drug and the new disease name is further tested. Specifically, in step 605, only group D is selected, and in step 606, the receptors including the new disease name are grouped for each off-label drug among the group D of the processing target receptors.

  Next, in step 607, for each group, the number of receptors having the same new disease name is equal to or greater than y and the rate is equal to or greater than z per 100 group D receptors. (Y and z are integers of 1 or more, and initial values are y = 3 and z = 3).

  In step 608, the name of the wound determined to have a strong correlation with the drug in steps 604 and 607 is added to the check text of the corresponding drug.

  As a result, it becomes possible to exclude the FN drug from non-adapted drugs, so that there is no misjudgment of “no target disease name” even though there is an applicable disease name for a certain drug. Can be prevented from being mistakenly judged as “failed”.

  Thus, the check text generation process ends. Next, the process proceeds to a receipt screening process. Details of the receipt screening process will be described with reference to FIG. A program corresponding to the flowchart of FIG. 9 is stored in the internal storage device 5, read into the RAM 6, and executed by the CPU 3.

  First, in step 701, the pass list and the fail list are cleared as an initialization process. Next, in step 702, a matching process corresponding to step 107 is performed on the receipt to be examined. If it is determined to be acceptable in step 702 (“YES” in step 703), the receipt is added to the acceptable list in step 704.

  On the other hand, the receipt that failed in step 702 (“NO” in step 703) is printed out from the printer 8 in step 705 and displayed on the display unit 7. Next, as a process at this time, in step 706, an inquiry is made to the operator as to whether or not to correct the receipt. When a correction instruction is received from the operator (“YES” in step 706), the correction by the operator in step 707 is performed. Accept input. The correction input can be received in real time as shown here, or can be received collectively at the end of all the processes. On the other hand, if a correction command is not received from the operator (“NO” in step 706), the rejection is confirmed, and the corresponding receipt is added to the rejection list in step 708.

  The processing from the above steps 702 to 708 is executed for all the receipts in the examination month.

  As described above, according to the present invention corresponding to the present embodiment, text-based indication data can be customized to reflect the input tendency of doctors who are operators. In addition, since this customization reflects the contents of a receipt that has passed the actual examination, it is possible to efficiently inspect whether the receipt passes the examination.

[Other Embodiments]
The above processing (for example, processing according to the flowcharts shown in FIGS. 3 to 9 in the above embodiment) is stored as a program in a storage medium such as a CD-R, ROM, DVD-ROM, or MO, and stored in this storage medium. By reading (installing or copying) the stored program by the computer, the computer can perform the above processing. Therefore, it is obvious that this storage medium is also within the scope of the present invention.

It is a figure for demonstrating the whole concept corresponding to embodiment of this invention. It is a figure which shows an example of the hardware constitutions of the receipt screening apparatus 1 corresponding to embodiment of this invention. It is a figure for demonstrating the outline | summary of the process in the receipt screening apparatus 1 corresponding to embodiment of this invention. It is a flowchart which shows an example of the production | generation process of the check text corresponding to embodiment of this invention. It is a flowchart which shows an example of the edit process of the indication data corresponding to embodiment of this invention. It is a flowchart corresponding to an example of the collation process corresponding to the embodiment of the present invention. It is a flowchart corresponding to an example of the group B process corresponding to the embodiment of the present invention. It is a flowchart corresponding to an example of the non-examination drug processing corresponding to the embodiment of the present invention. It is a flowchart corresponding to an example of the FN test | inspection process corresponding to embodiment of this invention. It is a flowchart which shows an example of the receipt examination process corresponding to embodiment of this invention. It is a figure which shows an example of the indication data corresponding to embodiment of this invention. It is a figure which shows the example which divided | segmented the indication data corresponding to embodiment of this invention based on the predetermined | prescribed symbol. It is a figure which shows an example of the check text corresponding to embodiment of this invention. It is a figure which shows an example of the data extracted from the receipt data in the check text production | generation process corresponding to embodiment of this invention. It is a figure which shows an example of the unconditional adaptive medicine table corresponding to embodiment of this invention. It is a figure which shows an example of the chemical | medical agent table not to be examined corresponding to embodiment of this invention. It is a figure which shows an example of the sickness name and drug name of the receptor which belongs to the group B1 corresponding to embodiment of this invention. It is a figure which shows an example of the wound name and drug name of the receptor which belongs to the group B2 corresponding to embodiment of this invention.

Claims (9)

A receipt screening device,
A storage means for storing receipt data including information on a medical practice performed on a patient and a name of a wound and disease in association with each patient, and indication data of text data including information on a name of a wound and disease applicable to a medical practice; ,
The check data for determining the name of the disease applicable to the medical practice by editing the indication data is separated from the indication data based on the presence or absence of a symbol for separating a sentence or a segment, and a specific character Generating means for generating in advance for each medical practice by removing the column and dividing the character string by a predetermined number so that a part of the preceding and following character strings overlaps;
First extraction means for extracting, from the receipt data for each patient in the examination month, first medical practice information and first wound name information associated with the first patient;
Using the check data corresponding to the extracted first medical practice information, the first medical practice information, and the first injury name information, a receipt of the examination month of the first patient It is determined whether or not the data includes the names of wounds and sickness names that can be applied to the medical practice included in the first medical practice information for all the medical practices included in the first medical practice information. First determination means;
Determining means for determining acceptance / rejection of the receipt data for each patient based on the result of the determination ;
The generating means includes
Second extraction means for extracting second medical practice information and second wound name information for each patient from the receipt data for each patient for a plurality of months including the examination month;
Based on the second wound name information, a determination means for determining for each patient whether or not there is wound name information corresponding to a wound name newly added in the examination month,
Using the check data corresponding to the second medical practice information, the second medical practice information, and the second injury name information, the second medical examination data is included in the multi-month receipt data. Second determination for determining for each patient whether or not injury name information of an injury and illness name applicable to an operation information corresponding to the operation information is included for all the medical operations included in the second medical operation information Means,
Corresponding to the medical practice included in the second medical practice information when it is judged by the second judgment means that it is determined that it is included and there is a newly added injury / illness name by the discrimination means From the check data including the character string of the newly added wound name among the check data to be checked, at least of the wound names other than the newly added wound name among the wound names included in the second wound name information Editing means for deleting a character string that matches a part and adding a character string of the newly added disease name
The provided, receipt examination apparatus characterized that you previously generate the check data.   The receipt judging apparatus according to claim 1, wherein the first determination unit performs the determination on the first medical practice information other than the medical practice information that is previously determined not to be determined.   The receipt examination apparatus according to claim 2, wherein the medical practice information that is determined not to be determined in advance includes information related to a medical practice continuously performed for the same patient for a predetermined period. The intervention information is information of a drug that is administered to the patient, the intervention is to any one of claims 1 to 3, characterized in that the act of administration or injection of the drug The receipt screening device described. A storage unit for storing receipt data including information on a medical practice performed on a patient and a name of a wound and disease in association with each patient, and indication data of text data including information on a name of a wound that can be applied to a medical practice The check data for determining the name of the disease applicable to the medical practice by editing the indication data, separating the indication data based on the presence or absence of a symbol for separating a sentence or a segment, A method for controlling a receptor apparatus including a generation unit that generates a character string in advance and divides the character string by a predetermined number of characters so that a part of the character string before and after the character string overlaps,
The control method of the receptor apparatus is as follows:
A first extraction step of extracting first medical practice information and first wound name information associated with the first patient from the receipt data for each patient in the examination month;
Using the check data corresponding to the extracted first medical practice information, the first medical practice information, and the first injury name information, a receipt of the examination month of the first patient It is determined whether or not the data includes the names of wounds and sickness names that can be applied to the medical practice included in the first medical practice information for all the medical practices included in the first medical practice information. A first determination step;
A determination step for determining acceptance / rejection of the receipt data for each patient based on the result of the determination, and
The generator is
Second extraction means for extracting second medical practice information and second wound name information for each patient from the receipt data for each patient for a plurality of months including the examination month;
Based on the second wound name information, a determination means for determining for each patient whether or not there is wound name information corresponding to a wound name newly added in the examination month,
Using the check data corresponding to the second medical practice information, the second medical practice information, and the second injury name information, the second medical examination data is included in the multi-month receipt data. Second determination for determining for each patient whether or not injury name information of an injury and illness name applicable to an operation information corresponding to the operation information is included for all the medical operations included in the second medical operation information Means,
Corresponding to the medical practice included in the second medical practice information when it is judged by the second judgment means that it is determined that it is included and there is a newly added injury / illness name by the discrimination means From the check data including the character string of the newly added wound name among the check data to be checked, at least of the wound names other than the newly added wound name among the wound names included in the second wound name information Editing means for deleting a character string that matches a part and adding a character string of the newly added disease name
The provided method for controlling a receipt examination apparatus characterized that you previously generate the check data. 6. The receipt screening apparatus according to claim 5 , wherein, in the first determination step, the determination is performed on the first medical practice information other than the medical practice information determined in advance as not to be determined. Control method. 7. The receipt examination apparatus according to claim 6 , wherein the medical practice information determined not to be determined in advance includes information on a medical practice continuously performed for the same patient for a predetermined period. Control method. The intervention information is information of a drug that is administered to the patient, the intervention is to any one of claims 5 to 7, characterized in that the act of administration or injection of the drug The control method of the receipt examination apparatus of description. A computer program for causing a computer to function as the receipt examination apparatus according to any one of claims 1 to 4 .

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