JP2007141063A - Prescription determination device, prescription determination processing program, disease name estimation device, disease name estimation processing program, and data structure for disease name estimation processing - Google Patents

Prescription determination device, prescription determination processing program, disease name estimation device, disease name estimation processing program, and data structure for disease name estimation processing Download PDF

Info

Publication number
JP2007141063A
JP2007141063A JP2005335892A JP2005335892A JP2007141063A JP 2007141063 A JP2007141063 A JP 2007141063A JP 2005335892 A JP2005335892 A JP 2005335892A JP 2005335892 A JP2005335892 A JP 2005335892A JP 2007141063 A JP2007141063 A JP 2007141063A
Authority
JP
Japan
Prior art keywords
drug
name
disease name
estimated
disease
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Pending
Application number
JP2005335892A
Other languages
Japanese (ja)
Inventor
Hideo Shimodaira
秀夫 下平
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
HACHIOJI YAKUZAI CENTER KK
HACHIOJI YAKUZAI CT KK
Original Assignee
HACHIOJI YAKUZAI CENTER KK
HACHIOJI YAKUZAI CT KK
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by HACHIOJI YAKUZAI CENTER KK, HACHIOJI YAKUZAI CT KK filed Critical HACHIOJI YAKUZAI CENTER KK
Priority to JP2005335892A priority Critical patent/JP2007141063A/en
Publication of JP2007141063A publication Critical patent/JP2007141063A/en
Pending legal-status Critical Current

Links

Images

Landscapes

  • Medical Treatment And Welfare Office Work (AREA)

Abstract

<P>PROBLEM TO BE SOLVED: To provide a prescription determination device capable of estimating the disease of a patient from the prescription drug information of the patient, and determining a drug likely to be contraindicated for the patient in the prescription drug of the patient from the estimated disease name, thereby preventing an inappropriate and risky drug from being dispensed. <P>SOLUTION: This prescription determination device 1 has: a storage means 7 for estimating disease name; a disease name etimation processing means 8; a storage means 9 for determining the contraindicated drug; and a contraindicated drug determination processing means 10. A drug name, an estimated disease name for which the drug may be dispensed are stored in association with estimated scores indicating possibility that the patient suffers from a disease of the estimated disease name when the drug of the drug name is dispensed to the patient in the storage means 7 for estimating disease name. The disease name processing means 8 refers to the storage means 7 for estimating disease name to estimate the disease name of the patient based on the input prescription drug name and a contraindicated determination processing means 10 refers to the storage means 9 for determining contraindicated drug and when the drug contraindicated to the disease of the estimated disease name is included in the input prescription drug, outputs information about the contraindicated drug to an output means 4. <P>COPYRIGHT: (C)2007,JPO&INPIT

Description

本発明は、不適正で危険な投薬の防止に貢献可能な処方判定装置などに関する。   The present invention relates to a prescription determination device that can contribute to prevention of inappropriate and dangerous medication.

患者別の医薬品に対する禁忌情報、副作用情報を格納したデータベースを構築し、医師がデータベースに記憶された情報に基づいて投薬品を決定するシステムが知られている（例えば、特許文献１等参照）。しかしながら、この場合、患者毎の医薬品に対する禁忌情報、副作用情報をデータベースに登録しなければならず、データベースの構築が大変である。また、医師は、自分の専門分野以外の分野で使用される薬については知識の少ない場合も多い。例えば、皮膚科の医師は内科で使用される薬の知識を知らない場合も多く、内科に通院していた患者が皮膚科に通院した場合に、皮膚科の医師は内科で処方された薬の内容からその患者がどのような病気を患っているのかわからないことが多い。患者の患っている病気がわからなければ、その病気に対する禁忌薬もわからないため、その病気に対する禁忌薬を処方してしまうということもあり得る。
また、処方箋に基づいて薬の調剤を行う保険調剤薬局では、薬剤師が、患者の処方箋に記載された処方薬中にその患者に対して禁忌薬となる薬を含んでいると判断した場合は、疑義照会して誤投薬を回避する。すなわち、薬剤師は、処方箋に記載された処方薬からその患者の患っている病気が何であるかの見当をつけ、その病気を患っている患者に対しての禁忌薬の見当をつけたり調べたりすることによって、処方薬の中に禁忌薬となる薬が含まれていると判断すれば、疑義照会を行って誤投薬防止に努めている。しかしながら、処方箋に記載された処方薬からその患者の患っている病気が何であるかの見当をつけることが困難な場合もある。例えば、薬剤師は、ある１つの薬が処方されていればある病気を患っていることがほぼ確実であると判断できる場合もあるが、ある１つの薬だけではその患者の患っている病気が何であるかを判断することが困難な場合もある。また、複数の薬が組み合わされて処方されている場合、その薬の組み合わせから病気を判断しなければならず、その患者の患っている病気が何であるかを判断することが困難な場合もある。このような薬剤師による判断作業は、人による判断作業であり、薬剤師毎の経験や知識に頼っているため、薬剤師の誤判断や経験不足や知識不足などによって患者の患っている病気が何であるかを判断することができずに誤投薬を発生することがあり得る。
特開２００５−１９０４４５号公報 There is known a system in which a database storing contraindication information and side effect information for pharmaceuticals by patient is constructed, and a doctor determines a drug based on information stored in the database (see, for example, Patent Document 1). However, in this case, contraindication information and side effect information for pharmaceuticals for each patient must be registered in the database, and the construction of the database is difficult. In addition, doctors often have little knowledge about drugs used in fields other than their own specialty. For example, dermatologists often do not know the knowledge of drugs used in internal medicine, and when a patient who has been attending internal medicine visits dermatology, The contents often do not tell what kind of disease the patient suffers from. If you do not know the illness the patient is suffering from, you may not know the contraindications for the illness, and may prescribe contraindications for the illness.
In addition, an insurance dispensing pharmacy that dispenses medicines based on a prescription, if the pharmacist determines that the prescription drug listed in the patient's prescription contains a drug that is contraindicated for the patient, Inquire about doubts to avoid medication errors. In other words, the pharmacist must figure out what the patient's illness is from the prescription drugs listed on the prescription, and then identify or examine contraindicated drugs for the patient suffering from the illness. Therefore, if it is judged that prescription drugs contain drugs that are contraindicated, we are making inquiries and trying to prevent mismedication. However, it may be difficult to figure out what the patient is suffering from the prescription drugs listed in the prescription. For example, a pharmacist may be able to determine that it is almost certain that he has a certain illness if a single drug is prescribed. It may be difficult to determine if there is. In addition, when multiple drugs are prescribed in combination, the disease must be determined from the combination of the drugs, and it may be difficult to determine what the patient is suffering from . Such judgment work by a pharmacist is a judgment work by a person and depends on the experience and knowledge of each pharmacist, so what is the disease that the patient suffers due to misjudgment of the pharmacist or lack of experience or knowledge? It is possible that a wrong medication may occur without being able to judge.
JP 2005-190445 A

従来、医師や薬剤師が、患者の処方薬の内容に基づいてその患者の患っている病気（合併症）を判断できない場合には、不適正で危険な投薬を行う可能性が高くなるという課題があった。   Conventionally, if a doctor or pharmacist cannot determine the disease (complication) that the patient suffers based on the contents of the patient's prescription drug, there is a problem that the possibility of inappropriate and dangerous medication increases. there were.

本発明の処方判定装置は、患者の処方薬情報を入力して処方薬の適否を判定する処方判定装置であって、病名推定用記憶手段と病名推定処理手段と禁忌薬判定用記憶手段と禁忌薬判定処理手段とを備え、病名推定用記憶手段には、薬品名と、その薬品名の薬が投与される可能性のある推定病名と、その薬品名の薬が患者に投与された場合に推定病名の病気をその患者が患っている可能性の高さを表す推定点数とが対応付けられて記憶され、禁忌薬判定用記憶手段には、推定病名と推定病名の病気に対する禁忌薬とが対応付けられて記憶され、病名推定処理手段は、入力された患者の処方薬品名に基づいて病名推定用記憶手段を検索することによって、入力された処方薬品名と同じ薬品名に対応付けられた推定病名を抽出し、抽出した推定病名に対応付けられた推定点数を推定病名毎に集計し、推定点数の合計が基準点に達した推定病名を出力手段及び禁忌薬判定処理手段に出力し、禁忌薬判定処理手段は、病名推定処理手段から推定点数の合計が基準点に達した推定病名を入力し、入力された推定病名に基づいて禁忌薬判定用記憶手段を検索することによって、入力された推定病名の病気に対する禁忌薬を抽出し、抽出された禁忌薬品名が入力された処方薬情報の処方薬品名に存在するか否かを判定し、存在すれば、処方薬の中に禁忌薬が含まれていることを示す情報を出力手段に出力することを特徴とする。
本発明の処方判定処理プログラムは、コンピュータを、上記病名推定処理手段と禁忌薬判定処理手段として機能させることを特徴とする。
本発明の病名推定装置は、患者の処方薬情報を入力して処方薬情報から病名を推定する病名推定装置であって、病名推定用記憶手段と病名推定処理手段とを備え、病名推定用記憶手段には、薬品名と、その薬品名の薬が投与される可能性のある推定病名と、その薬品名の薬が患者に投与された場合に推定病名の病気をその患者が患っている可能性の高さを表す推定点数とが対応付けられて記憶され、病名推定処理手段は、入力された患者の処方薬品名に基づいて病名推定用記憶手段を検索することによって、入力された処方薬品名と同じ薬品名に対応付けられた推定病名を抽出し、抽出した推定病名に対応付けられた推定点数を推定病名毎に集計し、推定点数の合計が基準点に達した推定病名を出力手段に出力することを特徴とする。
本発明の病名推定処理プログラムは、コンピュータを、上記病名推定処理手段として機能させることを特徴とする。
本発明の病名推定処理のためのデータ構造は、薬品名と、その薬品名の薬が投与される可能性のある推定病名と、その薬品名の薬が患者に投与された場合に推定病名の病気をその患者が患っている可能性の高さを表す推定点数とが対応付けられて記憶手段に記憶されたことを特徴とする。 A prescription determination apparatus according to the present invention is a prescription determination apparatus that inputs prescription drug information of a patient and determines the suitability of a prescription drug, and includes a disease name estimation storage unit, a disease name estimation processing unit, a contraindicated drug determination storage unit, and a contraindication A medicine determination processing means, and a disease name estimation storage means for a medicine name, an estimated disease name with which the medicine with the medicine name may be administered, and a medicine with the medicine name is administered to the patient. An estimated score indicating the likelihood that the patient is suffering from the disease of the estimated disease name is stored in association with each other, and the contraindication drug storage means stores the estimated disease name and the contraindicated drug for the disease of the estimated disease name. The disease name estimation processing means is associated with the same drug name as the input prescription drug name by searching the memory for estimating the disease name based on the input prescription drug name of the patient. Extract the estimated disease name and extract the estimated disease name The associated estimated score is totaled for each estimated disease name, and the estimated disease name in which the total estimated score has reached the reference point is output to the output means and the contraindication drug determination processing means, and the contraindication drug determination processing means is the disease name estimation processing means Enter the name of the estimated disease whose total estimated number of points reached the reference point, and search the storage means for contraindication determination based on the input estimated disease name to extract the contraindicated drug for the disease with the input estimated disease name. , It is determined whether or not the extracted contraindicated drug name exists in the prescription drug name of the input prescription drug information, and if it exists, information indicating that the prescription drug contains a contraindicated drug is output. Output to the means.
The prescription determination processing program of the present invention causes a computer to function as the disease name estimation processing means and the contraindication determination processing means.
The disease name estimation device of the present invention is a disease name estimation device that inputs prescription drug information of a patient and estimates a disease name from prescription drug information, and includes a disease name estimation storage unit and a disease name estimation processing unit, and includes a disease name estimation memory. The measures include the name of the drug, the estimated disease name that the drug with that drug name may be administered, and the patient may have the disease with the estimated disease name when the drug with that drug name is administered to the patient. The estimated score indicating the high sex is stored in association with each other, and the disease name estimation processing means searches the disease name estimation storage means based on the inputted prescription drug name of the patient, thereby inputting the inputted prescription drug. The estimated disease name associated with the same drug name as the name is extracted, the estimated points associated with the extracted estimated disease name are aggregated for each estimated disease name, and the estimated disease name whose total of the estimated points has reached the reference point is output means It is characterized by being output to.
The disease name estimation processing program of the present invention causes a computer to function as the disease name estimation processing means.
The data structure for the disease name estimation process of the present invention includes a drug name, an estimated disease name with which the drug with the drug name may be administered, and an estimated disease name when the drug with the drug name is administered to the patient. It is characterized by being stored in the storage means in association with an estimated score representing the high possibility that the patient suffers from the disease.

本発明の処方判定装置によれば、患者の処方薬情報によってその患者が患っている病気を推定でき、推定した病名から患者の処方薬にその患者にとって禁忌薬となる可能性の高い薬を判定するので、不適正で危険な投薬の防止に貢献できる。
本発明の処方判定処理プログラムによれば、コンピュータを病名推定処理手段と禁忌薬判定処理手段として機能させることができる。
本発明の病名推定装置によれば、患者の処方薬情報によってその患者が患っている病気を推定できるので、不適正で危険な投薬の防止に貢献できる。
本発明の病名推定処理プログラムによれば、コンピュータを病名推定処理手段として機能させることができる。
本発明の病名推定処理のためのデータ構造によれば、上記処方判定装置や病名推定装置の病名推定用記憶手段として機能させることができる。 According to the prescription determination apparatus of the present invention, it is possible to estimate the disease that the patient suffers from based on the prescription drug information of the patient, and determine a drug that is highly likely to be a contraindicated drug for the patient from the estimated disease name Therefore, it can contribute to prevention of inappropriate and dangerous medication.
According to the prescription determination processing program of the present invention, the computer can function as a disease name estimation processing means and a contraindication drug determination processing means.
According to the disease name estimation apparatus of the present invention, the disease that the patient suffers can be estimated from the patient's prescription drug information, which can contribute to prevention of inappropriate and dangerous medication.
According to the disease name estimation processing program of the present invention, the computer can function as disease name estimation processing means.
According to the data structure for the disease name estimation process of the present invention, it can function as the disease name estimation storage means of the prescription determination device or the disease name estimation device.

最良の形態１．
図１乃至図３は最良の形態１を示す。図１は処方判定装置のブロック構成を示し、図２は病名推定用記憶手段に記憶されたデータ構造及びデータ例を示し、図３は禁忌薬判定用記憶手段に記憶されたデータ構造及びデータ例を示す。 Best Mode
1 to 3 show the best mode 1. FIG. FIG. 1 shows a block configuration of the prescription determination apparatus, FIG. 2 shows a data structure and data example stored in the disease name estimation storage means, and FIG. 3 shows a data structure and data example stored in the contraindication drug determination storage means. Indicates.

図１に示すように、処方判定装置１は、処方判定手段２、キーボードやマウスなどのような入力手段３、表示装置や印刷装置などのような出力手段４により構成され、例えば保険調剤薬局や病院の診察室に設置される。処方判定手段２は、病名推定手段５、禁忌薬判定手段６を備える。病名推定手段５は、病名推定用記憶手段７、病名推定処理手段８を備える。禁忌薬判定手段６は、禁忌薬判定用記憶手段９、禁忌薬判定処理手段１０を備える。病名推定処理手段８、禁忌薬判定処理手段１０は、プログラムと当該プログラムを実行するＣＰＵのようなコンピュータハードウエアとによって実現される。すなわち、処方判定装置１は、コンピュータを病名推定処理手段８及び禁忌薬判定処理手段１０として機能させる処方判定処理プログラムを備える。   As shown in FIG. 1, the prescription determination device 1 includes a prescription determination unit 2, an input unit 3 such as a keyboard and a mouse, and an output unit 4 such as a display device and a printing device. It will be installed in the hospital examination room. The prescription determination unit 2 includes a disease name estimation unit 5 and a contraindication drug determination unit 6. The disease name estimation means 5 includes a disease name estimation storage means 7 and a disease name estimation processing means 8. The contraindicated drug determination means 6 includes a contraindication drug determination storage means 9 and a contraindication drug determination processing means 10. The disease name estimation processing means 8 and the contraindication drug determination processing means 10 are realized by a program and computer hardware such as a CPU that executes the program. That is, the prescription determination apparatus 1 includes a prescription determination processing program that causes a computer to function as the disease name estimation processing means 8 and the contraindication drug determination processing means 10.

図２に示すように、病名推定用記憶手段７には、薬品名を示すデータと、その薬品名の薬が投与される可能性のある推定病名を示すデータと、その薬品名の薬が投与された場合に推定病名の病気をその患者が患っている可能性の高さを表す推定点数を示すデータとが対応付けられて記憶されている。すなわち、病名推定用記憶手段７は、薬品名データ２１と推定病名データ２２と推定点数データ２３とが対応付けられて記憶された病名推定処理のためのデータ構造を有する記憶手段である。薬品名データとして、商品名を示すデータと一般名を示すデータとが対応付けて記憶されている。推定点数は、薬剤師や医師の経験によって得られた知識に基づいて設定される。人が、患者の処方箋に記載された処方薬情報、すなわち、処方薬品名を入力手段３で入力すると、病名推定処理手段８は、入力された処方薬品名に基づいて病名推定用記憶手段７を検索することによって、入力された処方薬品名と同じ薬品名に対応付けられた推定病名を抽出し、抽出した推定病名に対応付けられた推定点数を推定病名毎に集計する。そして、病名推定処理手段８は、推定点数の合計が基準点である１０点に達した推定病名とその推定病名を推定する対象となった薬品名とを推定情報として出力手段４及び禁忌薬判定処理手段１０に出力する。よって、薬剤師や医師は、出力手段４に出力された推定情報を確認することで、病名推定処理手段８によって推定された推定病名を知ることができ、その患者が患っている可能性の高い病名を知ることができる。   As shown in FIG. 2, the disease name estimation storage means 7 administers data indicating a drug name, data indicating an estimated disease name to which a drug with the drug name may be administered, and a drug with the drug name. In this case, data indicating the estimated number of points indicating the high possibility that the patient suffers from the disease having the estimated disease name is stored in association with each other. That is, the disease name estimation storage means 7 is a storage means having a data structure for disease name estimation processing in which drug name data 21, estimated disease name data 22, and estimated score data 23 are stored in association with each other. As medicine name data, data indicating a product name and data indicating a general name are stored in association with each other. The estimated score is set based on knowledge obtained from experience of a pharmacist or doctor. When a person inputs the prescription drug information described in the patient's prescription, that is, the prescription drug name, using the input unit 3, the disease name estimation processing unit 8 stores the disease name estimation storage unit 7 based on the input prescription drug name. By searching, an estimated disease name associated with the same drug name as the input prescription drug name is extracted, and the estimated points associated with the extracted estimated disease name are tabulated for each estimated disease name. Then, the disease name estimation processing means 8 uses the output means 4 and the contraindicated drug determination with the estimated disease name and the drug name for which the estimated disease name is estimated as the estimated information whose estimated points have reached 10 points as the reference point. Output to the processing means 10. Therefore, the pharmacist or doctor can know the estimated disease name estimated by the disease name estimation processing unit 8 by confirming the estimated information output to the output unit 4, and the disease name that the patient is likely to suffer from Can know.

禁忌薬判定用記憶手段９には、図３に示すように、推定病名を示すデータと推定病名の病気に対する禁忌薬を示すデータとが対応付けられて記憶されている。すなわち、禁忌薬判定用記憶手段９は、推定病名データ２５と禁忌薬データ２６とが対応付けられて記憶された禁忌薬判定処理のためのデータ構造を有する記憶手段である。禁忌薬判定処理手段１０は、推定処理手段８から入力した推定病名に基づいて禁忌薬判定用記憶手段９を検索して当該推定病名の病気に対する禁忌薬を抽出し、抽出された禁忌薬が、入力された処方薬品名の中に存在するか否かを判定し、存在すれば、警告とともに処方薬の中に禁忌薬が含まれていることを示す禁忌情報を出力手段４に出力する。よって、薬剤師や医師は、出力手段４に出力された禁忌薬の情報を確認することで、その患者に禁忌となる可能性の高い禁忌薬を知ることができる。   As shown in FIG. 3, the contraindicated drug determination storage means 9 stores data indicating the estimated disease name and data indicating the contraindicated drug for the disease of the estimated disease name in association with each other. That is, the contraindicated drug determination storage unit 9 is a storage unit having a data structure for a contraindication drug determination process in which the estimated disease name data 25 and the contraindication drug data 26 are stored in association with each other. The contraindication drug determination processing means 10 searches the contraindication drug determination storage means 9 based on the estimated disease name input from the estimation processing means 8 to extract a contraindication drug for the disease of the estimated disease name, and the extracted contraindication drug is It is determined whether or not it exists in the inputted prescription drug name. If it exists, contraindication information indicating that a prescription drug is contained in the prescription drug is output to the output unit 4 together with a warning. Therefore, the pharmacist or doctor can know the contraindicated drugs that are likely to be contraindicated for the patient by checking the information on the contraindicated drugs output to the output unit 4.

例えば、患者の処方箋に記載された処方薬情報である処方薬品名が、
１．ジゴシン錠
２．ラシックス細粒
３．セレスタミン錠
４．プレタール錠
であり、この処方薬品名を入力手段３により病名推定処理手段８に入力したとする。この場合、病名推定処理手段８は、図２の病名推定用記憶手段７を検索して、ジゴシン錠の推定病名が心不全でその推定点数が４、ラシックス細粒の推定病名が心不全でその推定点数が６であることを抽出し、推定病名が心不全での推定点数の合計が１０点となるので、推定病名を心不全と決定し、出力手段４としての表示装置に、例えば推定情報として、
・推定病名「心不全」
・推定対象薬「ジゴシン錠、ラシックス細粒」
という情報を表示する。
そして、禁忌薬判定処理手段１０は、病名推定処理手段８から入力した推定病名に基づいて判定用記憶手段９を検索し、心不全に対する禁忌薬を抽出する。この場合、処方薬情報として入力した薬の中に心不全に対する禁忌薬であるプレタール錠が存在するので、表示装置に、例えば禁忌情報として、
・プレタール錠は、心不全の患者への投与は禁忌です。添付文書をご確認ください。
という情報を表示する。
したがって、薬剤師や医師は、表示装置に表示された結果を見て、処方薬情報の入力された患者の病名は心不全である可能性が高く、この患者に処方されているプレタール錠は当該患者に対して禁忌薬であることを知ることができるため、不適正で危険な投薬、いわゆる誤投薬を防止できるようになる。また、推定対象薬の出力により、薬剤師や医師は、推定されたプロセスを知ることができるので、禁忌薬投与による不適正使用か否かを容易に判断できる。 For example, the prescription drug name, which is prescription drug information on the patient's prescription,
1. Digosin tablet 2. Lasix fine granules3. 3. Celestamine tablets It is a pretal tablet, and this prescription drug name is input to the disease name estimation processing means 8 by the input means 3. In this case, the disease name estimation processing means 8 searches the disease name estimation storage means 7 of FIG. 2, and the estimated disease name of the digosin tablet is heart failure and the estimated score is 4, and the estimated disease name of the LASIX granules is heart failure and the estimated score. 6 is estimated, and the total estimated score for heart failure is 10 points. Therefore, the estimated disease name is determined to be heart failure, and the display device serving as the output means 4 has, for example, estimated information as
-Estimated disease name "heart failure"
・ Estimated drug “Digocin Tablets, LASIX Fine Granules”
Is displayed.
Then, the contraindicated drug determination processing means 10 searches the determination storage means 9 based on the estimated disease name input from the disease name estimation processing means 8, and extracts a contraindication for heart failure. In this case, since there is a pretal tablet that is a contraindication for heart failure in the medicine entered as prescription drug information, for example, as contraindication information on the display device,
・ Pretal tablets are contraindicated for administration to patients with heart failure. Please check the attached document.
Is displayed.
Therefore, pharmacists and doctors look at the results displayed on the display device, and it is highly likely that the patient's disease name for which prescription drug information has been entered is heart failure. On the other hand, since it can be known that it is a contraindicated drug, inappropriate and dangerous medication, so-called erroneous medication can be prevented. Moreover, since the pharmacist and the doctor can know the estimated process based on the output of the estimation target drug, it is possible to easily determine whether or not the drug is inappropriately used by the administration of the contraindicated drug.

最良の形態１の処方判定装置１によれば、患者の処方薬情報によってその患者が患っている病気を推定でき、推定した病名から患者の処方薬にその患者にとって禁忌薬となる可能性の高い薬を判定するので、不適正で危険な投薬の防止に貢献できる。
処方判定装置１を病院の診察室に設置して使用すれば、医師の誤処方による誤投薬を防止できる。例えば、内科に通院していた患者が皮膚科に通院した場合に、皮膚科において、内科で処方された処方薬の情報を処方判定装置１に入力することによって、病名推定処理手段８によりその患者がどのような病気を患っているかが推定され、禁忌薬判定処理手段１０によりその病気に対する禁忌薬もわかるので、皮膚科の医師が処方箋を作成する際において、禁忌薬を処方するといった誤処方を防止できる。
また、経験の浅い医師や薬剤師、学生などに、病気と禁忌薬との関係を学習させるための学習用にも利用できる。さらに、その患者が患っている可能性の高い病名を知ることができるので、その患者へのその病気に対する生活指導や服薬指導ができるようになる。 According to the prescription determination apparatus 1 of the best mode 1, the disease that the patient suffers can be estimated based on the prescription drug information of the patient, and the patient's prescription drug is highly likely to be a contraindicated drug for the patient from the estimated disease name. Since the medicine is judged, it can contribute to prevention of inappropriate and dangerous medication.
If the prescription determination apparatus 1 is installed and used in an examination room of a hospital, it is possible to prevent erroneous medication due to an erroneous prescription by a doctor. For example, when a patient who has been attending an internal medicine visits a dermatology, by inputting information on prescription drugs prescribed in the internal medicine to the prescription determination device 1 in the dermatology, the patient is estimated by the disease name estimation processing means 8. It is estimated what kind of illness is suffering, and the contraindicated drug determination processing means 10 also knows the contraindicated drug for the illness. Therefore, when a dermatologist prepares a prescription, an erroneous prescription is prescribed. Can be prevented.
It can also be used for learning for inexperienced doctors, pharmacists and students to learn the relationship between illnesses and contraindications. Furthermore, since it is possible to know the name of the disease that the patient is likely to suffer, the patient can be given guidance on living and medication for the disease.

尚、上記では、薬品名の推定病名に対する推定点数のランク付け（重み付け）を１０段階で示したため基準点を１０点に設定したが、薬品名の推定病名に対する推定点数のランク付けのランク数を多くし、薬品名の推定病名に対する推定点数のランク付けを細かく設定することによって病名の推定精度を高くできる可能性がある。逆に、薬品名の推定病名に対する推定点数のランク付けのランク数を少なくし、薬品名の推定病名に対する推定点数のランク付けを粗く設定することによって病名の推定精度を低くできる可能性がある。よって、薬品の推定病名に対する推定点数のランク付けのランク数、すなわち、基準点は、要求する推定精度などに応じて設定することも可能である。また、添付文書の改定、治療ガイドラインの改定に応じて、病名推定用記憶手段７の薬品に対する推定病名の推定点数を適切に変えること、すなわち、データをメンテナンスすることで、推定精度を高い精度に維持し続けることができる。また、病院などに保管された過去の多量のレセプトデータを処方判定装置１によって判定処理することで、その病院などで薬の適正使用が行われているか否かを解析することも可能となる。   In the above, the ranking (weighting) of the estimated score for the estimated disease name of the drug name is shown in 10 stages, so the reference point is set to 10. However, the rank number of the estimated score ranking for the estimated disease name of the drug name is There is a possibility that the accuracy of estimating the disease name can be increased by setting the ranking of the estimated score with respect to the estimated disease name of the drug name in detail. On the contrary, there is a possibility that the estimation accuracy of the disease name can be lowered by reducing the rank number of the estimation score for the estimated disease name of the drug name and roughly setting the rank of the estimated score for the estimated disease name of the drug name. Therefore, it is possible to set the rank number for ranking the estimated score for the estimated disease name of the drug, that is, the reference point according to the required estimation accuracy. In addition, according to the revision of the package insert and the revision of the treatment guidelines, the estimation accuracy of the estimated disease name for the medicine in the disease name estimation storage means 7 is appropriately changed, that is, by maintaining the data, the estimation accuracy can be increased to a high accuracy. Can continue to maintain. In addition, it is possible to analyze whether or not proper use of a medicine is performed in the hospital or the like by processing the large amount of past receipt data stored in the hospital or the like by the prescription determination apparatus 1.

最良の形態２．
図４に示すように、本発明の病名推定装置１１は、病名推定手段５、キーボードやマウスなどのような入力手段３、表示装置や印刷装置などのような出力手段４により構成され、例えば保険調剤薬局や病院の診察室に設置される。すなわち、病名推定装置１１は、図１の最良の形態１の禁忌薬判定手段６を備えない構成である。禁忌薬判定手段６を備えない構成の病名推定装置１１であっても、病名推定手段５によって、患者の処方薬情報に基づいてその患者の患っている病名を推定できるので、薬剤師や医師がその患者の患っている可能性の高い病名を知ることができる。薬剤師や医師はその患者の患っている可能性の高い病名を知ることができれば、経験からその患者への禁忌薬を予想できたり、あるいは、その病気に対する禁忌薬について調べることによって、不適正で危険な投薬を防止できるようになる。また、その患者が患っている可能性の高い病名を知ることができるので、その患者へのその病気に対する生活指導や服薬指導ができるようになる。 Best Mode 2
As shown in FIG. 4, the disease name estimation device 11 of the present invention is composed of a disease name estimation means 5, an input means 3 such as a keyboard and a mouse, and an output means 4 such as a display device and a printing device. It is installed in the dispensing pharmacy and hospital examination rooms. That is, the disease name estimation apparatus 11 is configured not to include the contraindicated drug determination means 6 of the best mode 1 of FIG. Even in the case of the disease name estimation device 11 that does not include the contraindicated drug determination means 6, the disease name estimation means 5 can estimate the name of the disease affected by the patient based on the prescription drug information of the patient. You can know the name of the disease that the patient is likely to suffer. If the pharmacist or doctor knows the name of the disease that the patient is likely to have, it can be inadequate and dangerous by predicting contraindications for the patient from experience or by investigating contraindications for the disease. Can prevent proper medication. In addition, since it is possible to know the name of the disease that the patient is likely to suffer from, the patient can be given guidance on living and medication for the disease.

最良の形態１の処方判定装置１や最良の形態２の病名推定装置１１を、病院内の薬局や一般販売業や薬種商販売業（薬店）のような薬局、あるいは、個人宅に設けて使用してもよい。このように使用しても、患者への不適正で危険な投薬の防止に貢献できる。また、病名推定用記憶手段７及び禁忌薬判定用記憶手段９に注射薬（図３参照）もデータとして反映させることによって、病院において、外来患者に対する処方管理だけでなく、入院患者に対する処方管理も可能となる。さらに、病名推定用記憶手段７及び禁忌薬判定用記憶手段９に、薬品の規格（剤形、含有量など）も考慮して禁忌薬のデータを細分類化することによって、病名推定精度、禁忌薬判定精度を高めることができる。   The prescription determination device 1 of the best form 1 and the disease name estimation device 11 of the best form 2 are used at a pharmacy in a hospital, a general pharmacy, a drug dealer business (pharmacy), or a private house. May be. Even if used in this way, it can contribute to prevention of inappropriate and dangerous medication to the patient. In addition, by reflecting the injection drug (see FIG. 3) as data in the disease name estimation storage means 7 and the contraindicated drug determination storage means 9, not only prescription management for outpatients but also prescription management for inpatients can be performed in the hospital. It becomes possible. Further, by subdividing the data of contraindications into the disease name estimation storage means 7 and the contraindication drug determination storage means 9 in consideration of drug specifications (dosage form, content, etc.), the accuracy of disease name estimation, contraindications Drug determination accuracy can be increased.

処方判定装置を示すブロック構成図（最良の形態１）。The block block diagram which shows a prescription determination apparatus (best form 1). 病名推定用記憶手段に記憶されたデータ構造及びデータ例を示す図（最良の形態１）。The figure which shows the data structure and data example which were memorize | stored in the memory means for disease name estimation (best form 1). 禁忌薬判定用記憶手段に記憶されたデータ構造及びデータ例を示す図（最良の形態１）。The figure which shows the data structure and data example which were memorize | stored in the memory | storage means for contraindication medicine determination (best form 1). 病名推定装置を示すブロック構成図（最良の形態２）。The block block diagram which shows a disease name estimation apparatus (best form 2).

符号の説明Explanation of symbols

１ 処方判定装置、７ 病名推定用記憶手段、８ 病名推定手段、
９ 禁忌薬判定用記憶手段、１０ 禁忌薬判定処理手段、１１ 病名推定装置。 1 prescription determination device, 7 disease name estimation storage means, 8 disease name estimation means,
9 storage means for incompatible drug determination, 10 incompatible drug determination processing means, 11 disease name estimation device.

Claims (5)

患者の処方薬情報を入力して処方薬の適否を判定する処方判定装置であって、病名推定用記憶手段と病名推定処理手段と禁忌薬判定用記憶手段と禁忌薬判定処理手段とを備え、病名推定用記憶手段には、薬品名と、その薬品名の薬が投与される可能性のある推定病名と、その薬品名の薬が患者に投与された場合に推定病名の病気をその患者が患っている可能性の高さを表す推定点数とが対応付けられて記憶され、禁忌薬判定用記憶手段には、推定病名と推定病名の病気に対する禁忌薬とが対応付けられて記憶され、病名推定処理手段は、入力された患者の処方薬品名に基づいて病名推定用記憶手段を検索することによって、入力された処方薬品名と同じ薬品名に対応付けられた推定病名を抽出し、抽出した推定病名に対応付けられた推定点数を推定病名毎に集計し、推定点数の合計が基準点に達した推定病名を出力手段及び禁忌薬判定処理手段に出力し、禁忌薬判定処理手段は、病名推定処理手段から推定点数の合計が基準点に達した推定病名を入力し、入力された推定病名に基づいて禁忌薬判定用記憶手段を検索することによって、入力された推定病名の病気に対する禁忌薬を抽出し、抽出された禁忌薬品名が入力された処方薬情報の処方薬品名に存在するか否かを判定し、存在すれば、処方薬の中に禁忌薬が含まれていることを示す情報を出力手段に出力することを特徴とする処方判定装置。   A prescription determination apparatus that inputs prescription drug information of a patient and determines the propriety of a prescription drug, comprising a disease name estimation storage means, a disease name estimation processing means, a contraindication drug determination storage means, and a contraindication drug determination processing means, The storage means for estimating the disease name includes the drug name, the estimated disease name with which the drug with the drug name may be administered, and the disease with the estimated disease name when the drug with the drug name is administered to the patient. The estimated score indicating the likelihood of suffering is stored in association with each other, and in the contraindicated drug determination storage means, the estimated disease name and the contraindicated drug for the disease of the estimated disease name are stored in association with each other, and the disease name The estimation processing means extracts the estimated disease name associated with the same drug name as the input prescription drug name by searching the disease name estimation storage means based on the input prescription drug name of the patient, and extracted Estimated points associated with the estimated disease name Aggregate for each estimated disease name, and output the estimated disease name whose estimated points have reached the reference point to the output means and the contraindication drug determination processing means, and the contraindication drug determination processing means is based on the total estimated points from the disease name estimation processing means Enter the estimated disease name that reached the point, search the storage means for contraindication determination based on the input estimated disease name, extract the contraindicated drug for the disease of the input estimated disease name, and extract the incompatible drug name Is included in the prescription drug name of the inputted prescription drug information, and if it exists, the information indicating that the prescription drug contains a contraindicated drug is output to the output means. A prescription determination device. コンピュータを、請求項１に記載された病名推定処理手段と禁忌薬判定処理手段として機能させることを特徴とする処方判定処理プログラム。   A prescription determination processing program that causes a computer to function as the disease name estimation processing means and the contraindication determination processing means described in claim 1. 患者の処方薬情報を入力して処方薬情報から病名を推定する病名推定装置であって、病名推定用記憶手段と病名推定処理手段とを備え、病名推定用記憶手段には、薬品名と、その薬品名の薬が投与される可能性のある推定病名と、その薬品名の薬が患者に投与された場合に推定病名の病気をその患者が患っている可能性の高さを表す推定点数とが対応付けられて記憶され、病名推定処理手段は、入力された患者の処方薬品名に基づいて病名推定用記憶手段を検索することによって、入力された処方薬品名と同じ薬品名に対応付けられた推定病名を抽出し、抽出した推定病名に対応付けられた推定点数を推定病名毎に集計し、推定点数の合計が基準点に達した推定病名を出力手段に出力することを特徴とする病名推定装置。   A disease name estimation device that inputs prescription drug information of a patient and estimates a disease name from prescription drug information, comprising a disease name estimation storage means and a disease name estimation processing means, and the disease name estimation storage means includes a drug name, Estimated disease name that may be given the drug of the drug name, and an estimated score that indicates the likelihood that the patient will have the disease of the estimated disease name when the drug of the drug name is administered to the patient Are associated and stored, and the disease name estimation processing means searches the disease name estimation storage means based on the input prescription drug name of the patient, thereby associating with the same drug name as the input prescription drug name. The estimated disease names extracted are extracted, the estimated points associated with the extracted estimated disease names are aggregated for each estimated disease name, and the estimated disease names whose estimated points have reached the reference point are output to the output means Disease name estimation device. コンピュータを、請求項３に記載された病名推定処理手段として機能させることを特徴とする病名推定処理プログラム。   A disease name estimation processing program that causes a computer to function as the disease name estimation processing means according to claim 3. 薬品名と、その薬品名の薬が投与される可能性のある推定病名と、その薬品名の薬が患者に投与された場合に推定病名の病気をその患者が患っている可能性の高さを表す推定点数とが対応付けられて記憶手段に記憶されたことを特徴とする病名推定処理のためのデータ構造。   The name of the drug, the estimated disease name that the drug with that drug name is likely to be administered, and the likelihood that the patient will have the disease with the estimated disease name when the drug with that drug name is administered to the patient The data structure for the disease name estimation process characterized by the fact that the estimated number of points representing is associated and stored in the storage means.
JP2005335892A 2005-11-21 2005-11-21 Prescription determination device, prescription determination processing program, disease name estimation device, disease name estimation processing program, and data structure for disease name estimation processing Pending JP2007141063A (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
JP2005335892A JP2007141063A (en) 2005-11-21 2005-11-21 Prescription determination device, prescription determination processing program, disease name estimation device, disease name estimation processing program, and data structure for disease name estimation processing

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
JP2005335892A JP2007141063A (en) 2005-11-21 2005-11-21 Prescription determination device, prescription determination processing program, disease name estimation device, disease name estimation processing program, and data structure for disease name estimation processing

Publications (1)

Publication Number Publication Date
JP2007141063A true JP2007141063A (en) 2007-06-07

Family

ID=38203826

Family Applications (1)

Application Number Title Priority Date Filing Date
JP2005335892A Pending JP2007141063A (en) 2005-11-21 2005-11-21 Prescription determination device, prescription determination processing program, disease name estimation device, disease name estimation processing program, and data structure for disease name estimation processing

Country Status (1)

Country Link
JP (1) JP2007141063A (en)

Cited By (8)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP2012113654A (en) * 2010-11-26 2012-06-14 Toshiba Tec Corp Article sale support system
JP5329706B1 (en) * 2012-09-21 2013-10-30 東日本メディコム株式会社 Disease name estimation apparatus and program
KR101404503B1 (en) 2013-10-01 2014-06-10 배형준 Method for extracting diseases and providing information of extracted diseases from prescription of patient
JP2020095518A (en) * 2018-12-13 2020-06-18 アイエムエス ソフトウェア サービシズ リミテッド Information processing device, information processing method, and program
CN112116976A (en) * 2019-06-20 2020-12-22 上海智臻智能网络科技股份有限公司 Method and device for processing medicine information and computer readable storage medium
JP2021005410A (en) * 2018-12-13 2021-01-14 アイエムエス ソフトウェア サービシズ リミテッド Information processing device, information processing method, and program
JP2021060932A (en) * 2019-10-09 2021-04-15 株式会社イーエムシステムズ Disease name inference system, disease name inference method, disease name inference program, and data structure
JP7174127B1 (en) 2021-07-12 2022-11-17 株式会社カケハシ Apparatus, method and program for managing multiple patients visiting pharmacy

Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JPH0994287A (en) * 1995-09-29 1997-04-08 Bousei Yatsukiyoku:Kk Medicine dispensation assisting system and medicine retailing system
JP2002368899A (en) * 2001-06-08 2002-12-20 Kazuhiko Saeki Internet communication system and health management aid system
JP2004185196A (en) * 2002-12-02 2004-07-02 Higashi Nihon Medicom Kk Disease state presumption database by prescribed medicine

Patent Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JPH0994287A (en) * 1995-09-29 1997-04-08 Bousei Yatsukiyoku:Kk Medicine dispensation assisting system and medicine retailing system
JP2002368899A (en) * 2001-06-08 2002-12-20 Kazuhiko Saeki Internet communication system and health management aid system
JP2004185196A (en) * 2002-12-02 2004-07-02 Higashi Nihon Medicom Kk Disease state presumption database by prescribed medicine

Cited By (12)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP2012113654A (en) * 2010-11-26 2012-06-14 Toshiba Tec Corp Article sale support system
JP5329706B1 (en) * 2012-09-21 2013-10-30 東日本メディコム株式会社 Disease name estimation apparatus and program
JP2014063396A (en) * 2012-09-21 2014-04-10 Higashi Nihon Medicom Kk Name of disease estimation device and program
KR101404503B1 (en) 2013-10-01 2014-06-10 배형준 Method for extracting diseases and providing information of extracted diseases from prescription of patient
JP2020095518A (en) * 2018-12-13 2020-06-18 アイエムエス ソフトウェア サービシズ リミテッド Information processing device, information processing method, and program
JP2021005410A (en) * 2018-12-13 2021-01-14 アイエムエス ソフトウェア サービシズ リミテッド Information processing device, information processing method, and program
JP7324390B2 (en) 2018-12-13 2023-08-10 アイエムエス ソフトウェア サービシズ リミテッド Information processing device, information processing method and program
CN112116976A (en) * 2019-06-20 2020-12-22 上海智臻智能网络科技股份有限公司 Method and device for processing medicine information and computer readable storage medium
JP2021060932A (en) * 2019-10-09 2021-04-15 株式会社イーエムシステムズ Disease name inference system, disease name inference method, disease name inference program, and data structure
JP7402008B2 (en) 2019-10-09 2023-12-20 株式会社イーエムシステムズ Disease name inference system, disease name inference method, disease name inference program, and data structure
JP7174127B1 (en) 2021-07-12 2022-11-17 株式会社カケハシ Apparatus, method and program for managing multiple patients visiting pharmacy
JP2023011480A (en) * 2021-07-12 2023-01-24 株式会社カケハシ Apparatus and method for managing plurality of patients coming to pharmacy and program thereof

Similar Documents

Publication Publication Date Title
US11923083B2 (en) Method and apparatus for verification of medication administration adherence
Roughead et al. The extent of medication errors and adverse drug reactions throughout the patient journey in acute care in Australia
Ray et al. Out-of-hospital mortality among patients receiving methadone for noncancer pain
Lasser et al. Timing of new black box warnings and withdrawals for prescription medications
Monane et al. Improving prescribing patterns for the elderly through an online drug utilization review intervention: a system linking the physician, pharmacist, and computer
Gomes et al. Opioid dose and drug-related mortality in patients with nonmalignant pain
Flynn et al. National observational study of prescription dispensing accuracy and safety in 50 pharmacies
Masoudi et al. The complexity and cost of drug regimens of older patients hospitalized with heart failure in the United States, 1998-2001
Lenahan et al. A drug by any other name: patients' ability to identify medication regimens and its association with adherence and health outcomes
Hohl et al. Clinical decision rules to improve the detection of adverse drug events in emergency department patients
KR101920466B1 (en) Method, system and portable device able to analyze the prescription drug
JP2007141063A (en) Prescription determination device, prescription determination processing program, disease name estimation device, disease name estimation processing program, and data structure for disease name estimation processing
US7596503B2 (en) Adverse drug reaction reduction
Taylor et al. Prescription writing errors in the pediatric emergency department
McMullin et al. Impact of a Web-based clinical information system on cisapride drug interactions and patient safety
Turjamaa et al. How smart medication systems are used to support older people's drug regimens: A systematic literature review
Overhage et al. Ambulatory computerized prescribing and preventable adverse drug events
Andrus et al. Accuracy of pharmacy benefit manager medication formularies in an electronic health record system and the Epocrates mobile application
Lin et al. Cost‐effectiveness of an adherence‐enhancing intervention for gout based on real‐world data
Lesselroth et al. Medication review software to improve the accuracy of outpatient medication histories: protocol for a randomized controlled trial
Chin et al. Repurposing clinical decision support system data to measure dosing errors and clinician-level quality of care
Ho et al. Integrating patient-centric indications into the prescribing process: experience at a tertiary academic medical center
US20160019369A1 (en) System and method for prescribing diagnostic based therapeutics to patients
Dougherty et al. The future CPOE workflow: augmenting clinical decision support with pharmacist expertise
Hampton Similar drug names a risky prescription

Legal Events

Date Code Title Description
A621 Written request for application examination

Free format text: JAPANESE INTERMEDIATE CODE: A621

Effective date: 20081107

A977 Report on retrieval

Free format text: JAPANESE INTERMEDIATE CODE: A971007

Effective date: 20101210

A131 Notification of reasons for refusal

Free format text: JAPANESE INTERMEDIATE CODE: A131

Effective date: 20101214

A02 Decision of refusal

Free format text: JAPANESE INTERMEDIATE CODE: A02

Effective date: 20110405