JP5711197B2 - Electronic receipt data processing system for summary analysis of disease status, medical expenses, etc. - Google Patents
Electronic receipt data processing system for summary analysis of disease status, medical expenses, etc. Download PDFInfo
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Description
本発明は、平成18年度から厚生労働省主導により電子化が進められているレセプトデータを活用した疾病状況、医療費等の集計・分析をより効果的かつ有効に行うための電子レセプトデータの処理システムに関する。 The present invention is an electronic receipt data processing system for more effectively and effectively collecting and analyzing illness status, medical expenses, etc. using the receipt data that has been digitized by the Ministry of Health, Labor and Welfare since 2006. About.
レセプトとは、「診療(調剤)報酬明細書」と言われ、患者が受けた診療について、医療機関が保険者(市町村や健康保険組合等)に請求する医療費の明細書のことである。レセプトには患者氏名、保険者番号、病名、診療月に行った注射、処置、手術、検査、診断、リハビリや処方した薬剤についての点数が記載されており、受診者毎に医療機関が月単位で作成する。 The “receipt” is referred to as a “medical care (dispensing) remuneration statement”, and is a medical cost statement that a medical institution charges an insurer (such as a municipality or a health insurance association) for medical treatment received by a patient. The receipt includes the patient's name, insurer number, disease name, injections, treatment, surgery, examination, diagnosis, rehabilitation and prescription drugs given in the month of medical care. Create with.
医療機関にて作成された電子レセプトデータは、社会保険診療報酬支払基金又は国保連合会に送られ、当該支払基金又は国保連合会で整理した後、保険者(各健康保険組合や市区町村)に送付される。 Electronic receipt data created by a medical institution is sent to the Social Insurance Medical Fee Payment Fund or the National Health Insurance Association, and is organized by the payment fund or National Health Insurance Association before being insured (each health insurance association or municipality). To be sent to.
保険者(各健康保険組合や市区町村)のうち、特に大企業等の健康保険組合の場合は、支払基金から送付された電子レセプトデータを、当該組合加入の企業等からの様々な要求に応じて集計・分析し、その結果を提供している。ただし、個人情報にかかわる内容については一切提供しない。 Of the insurers (each health insurance association and municipality), especially in the case of health insurance associations such as large corporations, the electronic receipt data sent from the payment fund can be used for various requests from companies participating in the association. The results are aggregated and analyzed, and the results are provided. However, we will not provide any content related to personal information.
当該組合加入企業は、各健康保険組合が実施する保健事業(健康増進策、疾病予防対策等)が効果的に実施されているのかどうかの判断材料として、上記レセプトデータの集計・分析を要求しているが、その理由は、上記保健事業を実施するための費用が、組合加入企業及び被保険者が支払う保険料の一部を利用しており、その費用対効果は、保険料を支払う組合加入企業及び被保険者にとって大きな問題であるからである。 The union-affiliated company requires the above-mentioned receipt data to be aggregated and analyzed as material for judging whether the health business (health promotion measures, disease prevention measures, etc.) implemented by each health insurance association is being implemented effectively. However, the reason for this is that the cost for implementing the above health service uses a part of the premium paid by the union member company and the insured, and the cost-effectiveness is the association that pays the premium. This is because it is a big problem for participating companies and insured persons.
一方、実際にレセプトに病名を記入するのは各担当医師であるが、同じ病気であっても全ての医師が同じ病名を記入するとは限らず、医師によって微妙に表現が違うケースもある。 On the other hand, it is each doctor in charge who actually enters the disease name in the reception, but even if the disease is the same, not all doctors enter the same disease name, and there are cases where the expression is slightly different depending on the doctor.
そのため、正確なデータ分析を行う上で、こうした医師毎に違う表現を統一する必要があり、例えば特開2002−366648号公報等に開示された技術では、「表記揺らぎ」を吸収して分析するシステムが提案されている。 Therefore, when performing accurate data analysis, it is necessary to unify different expressions for each doctor. For example, in the technique disclosed in Japanese Patent Laid-Open No. 2002-366648, analysis is performed by absorbing “notation fluctuation”. A system has been proposed.
しかしながら現状のレセプトデータは、そもそも診察した医師によって記載する傷病名(病名)が、「表記揺らぎ」以前の問題として、大雑把であったり、不適当であったりするケースがある。このため様々な要求に応じた正確な集計・分析を行う上で問題が残されている。 However, in the current receipt data, there are cases where the name of a disease (disease name) described by a doctor who has been examined is roughly or inappropriate as a problem before “notation fluctuation”. For this reason, problems remain in performing accurate tabulation and analysis according to various requirements.
本願発明は、上記の現状を踏まえ、電子レセプトデータを用いて疾病状況や医療費等を集計分析するための電子レセプトデータ処理システムであって、検査項目名及び薬剤名と、これらから推定される最適傷病名を記憶した診療行為・医薬品・傷病関連マスタと、前記電子レセプトデータ中に存在する傷病名、検査項目名、薬剤名と、前記診療行為・医薬品・傷病関連マスタとを比較する比較手段と、前記電子レセプトデータ中に存在する傷病名と前記最適傷病名とが異なる場合、当該傷病名を前記最適傷病名に読み替える読替手段とを備え、前記比較手段によって前記電子レセプトデータ中に存在する傷病名、検査項目名、薬剤名と、診療行為・医薬品・傷病関連マスタとを比較し、当該傷病名と前記最適傷病名とが異なる場合、前記読替手段によって前記最適傷病名を前記読替傷病マスタに記憶する、ことを特徴とする。
また本願発明は、前記読替手段によって読替えられた前記最適傷病名は、端末画面に不適切表示とともに表示され、目視確認の後、前記読替傷病マスタに記憶する、ことを特徴とする。
The present invention is an electronic receipt data processing system for collecting and analyzing disease states, medical expenses, etc. using electronic receipt data, based on the above-mentioned present situation, and is inferred from these test item names and drug names Comparing means for comparing the medical practice / pharmaceutical / injury related master storing the optimal medical / injury name with the medical care / medicine / injury related master in the electronic receipt data And, if the wound name and the disease name present in the electronic receipt data are different from the optimum disease name, the reading means replaces the wound name with the optimum wound name, and is present in the electronic receipt data by the comparison unit. Compare the name of the wound and disease, the name of the test item, the name of the drug, and the medical practice / medicine / injury related master. Storing said optimized injuries name to the re-reading disability master by stage, characterized in that.
The invention of the present application is characterized in that the optimal wound name replaced by the replacement means is displayed together with an inappropriate display on a terminal screen, and is stored in the replaced wound disease master after visual confirmation.
本発明によれば、患者に発症している正確な傷病名を特定でき、この正確なデータに基づいて疾病状況、医療費等を集計・分析することができる。その結果、健康保険組合で実施する各種の保健事業について、本当に効果があったかどうかを正確に判断するための基礎資料となりうる。 According to the present invention, it is possible to identify an accurate name of a disease occurring in a patient, and it is possible to tabulate and analyze a disease state, a medical cost, and the like based on this accurate data. As a result, it can be a basic material for accurately judging whether or not various health services implemented by the health insurance association have really been effective.
更には、正確な医療費の集計・分析結果に基づいた保健事業の企画、立案、実施、効果測定等を行うことができるため、最終的には、企業が受ける社会的損失(従業員の長期休業や退職による生産性の損失など)の防止、潜在的患者が本格的に発症するのを防ぐことにより、医療費全体の削減、抑制を可能とする。 Furthermore, because it is possible to plan, formulate, implement, and measure the effects of health services based on accurate medical cost tabulation / analysis results, ultimately the social loss (long-term (Such as loss of productivity due to absence from work or retirement) and the prevention of potential patients from developing seriously, it is possible to reduce and control overall medical expenses.
以下、本発明の実施例について詳細に説明する。図1に示す通り、各種医療機関で作成された電子レセプトデータは、インターネット回線等を通じて、支払基金や国保連合に送信される。 Examples of the present invention will be described in detail below. As shown in FIG. 1, electronic receipt data created by various medical institutions is transmitted to a payment fund or the National Health Insurance Union through an Internet line or the like.
支払基金や国保連合は、この電子レセプトデータを保険者毎に分類し、それぞれの健康保険組合や市区町村に送付する。 The payment fund and the National Health Insurance Association classify this electronic receipt data for each insurer and send it to each health insurance association and municipality.
なお現状において、医療機関によっては、レセプトを電子データの形式ではなく紙媒体で支払機関に送付する者も存在する。その場合、支払基金において必要情報のみを手作業でパンチ入力し電子データ化している。 Currently, depending on the medical institution, there is a person who sends a receipt to a payment institution not in the form of electronic data but in a paper medium. In that case, only necessary information is manually punched into the payment fund and converted into electronic data.
電子レセプトデータは、約256の項目から構成されているが、前記支払基金にて必要情報のみを手作業で入力したデータは約60項目である。本実施例では、約256項目からなる電子レセプトデータをレセ電コード情報、支払基金にて必要情報のみを手作業で入力したデータを固有テキスト情報と呼ぶが、電子レセプトデータと言う場合は、レセ電コード情報と固有テキスト情報を合わせたデータも意図する。 The electronic receipt data is composed of about 256 items, but there are about 60 items of data in which only necessary information is manually input by the payment fund. In this embodiment, electronic receipt data consisting of about 256 items is referred to as receipt code information, and data in which only necessary information is manually entered with a payment fund is referred to as unique text information. However, when referred to as electronic receipt data, Data that combines electronic code information and unique text information is also intended.
本実施例では、情報処理業者が、各健康保険組合等からレセ電コード情報、固有テキスト情報、被保険者情報、被扶養者情報、その他分析に必要な情報を入手して、様々な集計や分析処理サービスを行うビジネスモデルを想定している。 In this embodiment, the information processing company obtains the power code information, unique text information, insured information, dependent information, and other information necessary for analysis from each health insurance association, Assume a business model that provides analytical processing services.
情報処理業者は、図2に示す通り、電子レセプトデータを用いて各種の集計・分析を行うため、医科・調剤レセプト連結マスタ、傷病別分解マスタ、読替傷病マスタ、後発医薬品比較マスタの4つのマスタを作成する。 As shown in FIG. 2, the information processing company performs various tabulations and analyzes using the electronic receipt data, so that the four masters of the medical / dispensing receipt connection master, the wound disease-specific decomposition master, the replacement injury disease master, and the generic drug comparison master. Create
なお上記各マスタを作成する前に、レセプトデータと突き合わせるための傷病名マスタ、医薬品マスタ、診療行為マスタ、後発医薬品マスタ、診療行為・医薬品・傷病関連マスタ、重みづけデータを作成しておく。 Before creating each master, a wound name / patient name master, a medicine master, a medical practice master, a generic medicine master, a medical practice / medicine / wound related master, and weighting data for matching with the receipt data are created.
以下、上記医科・調剤レセプト連結マスタ、傷病別分解マスタ、読替傷病マスタ、後発医薬品比較マスタの4つのマスタを作成する過程につき、図3、図4に基づいて説明する。 In the following, the process of creating the four masters of the medical / dispensing receipt connection master, the wound disease-specific decomposition master, the replacement wound disease master, and the generic drug comparison master will be described with reference to FIGS.
情報処理業者は、各健康保険組合等から入手したレセ電コード情報、固有テキスト情報、被保険者情報、被扶養者情報、事業所情報、その他分析に必要なデータを自社サーバー内に読み込み処理する。 Information processing companies read and process the power code information, unique text information, insured person information, dependent information, establishment information, and other data required for analysis obtained from each health insurance association. .
1.医科・調剤連結合算処理
まず、レセ電コード情報及び固有テキスト情報から、医科レセプトとその際処方された薬剤レセプトを連結合算する。通常、医師が診療や処置及び検査したレセプトと、薬剤のレセプトとは別々になっているが、本処理では、特定個人のデータとして連結し合算する。この合算したデータを「医科・調剤レセプト連結マスタ」とする。
1. Medical / Dispensing Concatenated Combined Calculation Processing First, a medical receipt and a medicine receipt prescribed at that time are consecutively calculated from the receipt power code information and the unique text information. Usually, the medical treatment, treatment and examination received by the doctor are separate from the drug reception, but in this process, they are linked and combined as data of a specific individual. This combined data is referred to as “medical / dispensing receipt connection master”.
例えば、特許株式会社健康保険組合の特許太郎さんの2012年10月の医療費は100点、薬剤費は50点であった場合、連結後は150点とするデータを作成する。 For example, if the medical cost in October 2012 of Mr. Taro Patent of the Health Insurance Association of Patent Co., Ltd. is 100 points and the drug cost is 50 points, the data is created as 150 points after the connection.
2.PDM法による処理
次に、PDM(Proportional Disease Magnitude)法を利用して、レセプトごとの点数、日数について重みづけデータを参照し、レセプトに掲載された全ての傷病毎に分解した「傷病別分解マスタ1」を作成する。なお、PDM法とは、岡本悦司氏(国立保健医療科学院)が考案したレセプトの点数や日数を、それに記載された全ての傷病名に一定の「重み」を与えて比例配分する分類法である。
2. Processing by the PDM method Next, using the PDM (Proportional Disease Magnet) method, the weighted data for the scores and days for each receipt is referred to, and the “degradation master for each disease and disease is decomposed for every injury and disease listed in the receipt. 1 ”is created. In addition, the PDM method is a classification method that proportionally distributes the scores and days of receipts devised by Mr. Junji Okamoto (National Institute of Health Sciences) by giving a certain “weight” to all the names of wounds and diseases described therein. .
現在、一般的に行われているレセプトの集計・分析処理は、複数の傷病が列挙されていても、最上位に記載された傷病名しか集計・分析の対象としていないが、それでは正確な病状を把握できない。本実施例では、レセプトに列挙されている全ての傷病を集計・分析の対象とするため、PDM法を使って点数配分している。 At present, the general process for counting and analyzing receipts is to count and analyze only the names of the wounds and diseases listed at the top, even if multiple wounds are listed. I can't figure it out. In this embodiment, in order to collect and analyze all injuries and diseases listed in the receipt, the points are distributed using the PDM method.
例えば、上記特許株式会社健康保険組合の特許太郎さんの2012年10月の医療費100点、調剤50点、計150点の内訳は、PDM法による分解によって糖尿病治療70点、高血圧症治療50点、痛風治療30点とするデータを作成する。 For example, Taro Patent Taro of the above-mentioned Patent Co., Ltd. Health Insurance Association has a medical cost of 100 points in October 2012, 50 points of dispensing, and a total of 150 points. Create data for 30 gout treatments.
3.傷病読替処理
次に、レセプトデータ中に存在する傷病名、検査項目名、薬剤名と診療行為・医薬品・傷病関連マスタとを照合することによって、傷病名が正しく正確に記載されているかを判断し、正確でないと判断した場合には、傷病名を前記最適傷病名に読み替える読替処理を行って「読替傷病マスタ」を作成する。
3. Next, it is judged whether the name of the disease is correctly and correctly described by comparing the name of the disease, the name of the inspection item, the drug name and the medical treatment / medicine / injury related master in the receipt data. If it is determined to be inaccurate, a replacement process for replacing the wound name with the optimum wound name is performed to create a “read wound disease master”.
図5、図6は実際のレセプトの一例である。図5に示したレセプトには、診察を行った医師によって、その傷病名を「流行性感冒の疑い」と記載されているが、検査項目を見るとインフルエンザの判断に行う特有の検査が行われており、また図6に示すレセプトでは、処方された薬剤がタミフル(ロッシュ社の登録商標)となっていることから、正確な傷病名は「インフルエンザ」であると推定できる。 5 and 6 are examples of actual receipts. In the receipt shown in FIG. 5, the name of the wound is described as “suspected epidemic cold” by the doctor who performed the examination. In addition, in the receipt shown in FIG. 6, the prescribed medicine is Tamiflu (registered trademark of Roche), so it can be estimated that the correct name of the disease is “influenza”.
このように、本実施例では、医師による不適切な傷病名が記載されていても、検査項目や処方された薬剤によって、正確な病名に読替えることができるため、結果として、正しい分析を行うことが可能となっている。なお、前記傷病名の適切な名称への読替え処理は、プログラムによって自動的に最適名称を選択するか、或いはプログラムによって不適切表示が出され、目視確認の後、人的処理によって最適名称をデータ入力するようにしてもよい。 In this way, in this example, even if an injured disease name by a doctor is described, it can be replaced with an accurate disease name depending on the test item or prescribed medicine, and as a result, a correct analysis should be performed. Is possible. In the process of replacing the name of the disease with an appropriate name, the optimal name is automatically selected by the program, or an inappropriate display is given by the program. You may make it input.
4.ICD10傷病コードの付与処理
次に、傷病名に付されるコードに関する処理を、図7に基づいて説明する。日本国内の医療機関では、国内で定められた傷病名コード(7桁傷病コード)が付与されており、図7に示すとおり、傷病名ごとに特定の番号が付されている。例えば、同じインフルエンザのカテゴリーでも、A型、B型などバラバラであり、このコード番号だけでは、症状や病名をグルーピングすることができない。
4). Next, a process related to the code assigned to the name of the wound will be described with reference to FIG. In medical institutions in Japan, a wound name code (seven-digit wound code) determined in Japan is assigned, and a specific number is assigned to each wound name as shown in FIG. For example, even in the same influenza category, type A, type B, etc. are disjoint, and symptom and disease name cannot be grouped only by this code number.
これに対し、国際コードであるICD10傷病コードは、同じインフルエンザのカテゴリーであれば主たるコードが同一であるため、これらを一括りにグルーピング可能であり、かつ国際的な感染症名との比較も容易となる。このため、本実施例では、傷病名コード(7桁傷病コード)に対して、IDC10傷病コードを付与する処理を行っている。このIDC10傷病コードが付与されたデータを「傷病別分解マスタ2」とする。 In contrast, the ICD10 wound code, which is an international code, has the same main code in the same influenza category, so these can be grouped together and easily compared with international infectious disease names. It becomes. For this reason, in this embodiment, a process of assigning an IDC10 wound code to the wound name code (7-digit wound code) is performed. The data to which the IDC10 injury / illness code is assigned is referred to as “injury / disease-specific decomposition master 2”.
5.名寄処理
次に、保険証資格情報から、各レセプトを同一人物として集計・分析が可能なように名寄処理を行う。
5. Nayoro process Next, from the insurance card qualification information, the Nayoro process is performed so that each receipt can be aggregated and analyzed as the same person.
これまでのレセプトを用いた集計・分析処理では、ある特定の個人が、3カ月通院した場合、通院者3件として処理されていた。すなわち、実際の患者=病人は1人であるにも関わらず、集計結果は、あたかも3人の患者が発生したと判断されるような処理を行っていた。 In the totaling / analysis processing using the conventional receipt, when a certain individual goes to the hospital for 3 months, it is processed as 3 outpatients. That is, although the actual patient = sick person is one, the total result is processed so that it is determined that three patients have occurred.
例えば、組合員数2500人の特許株式会社健康保険組合の2011年の1年間の通院者は、特許太郎さんただ一人であるが、特許太郎さんは5月、6月、8月に通院したとすると、2011年の患者発生率は2500分の3と処理されていたが、実際には特許太郎さんただ一人であるため、2500分の1と処理する必要がある。 For example, if the number of members of the Patent Co., Ltd. Health Insurance Association, which has 2500 members, was the only one who visited the hospital in 2011, Taro Patent was the only one to visit in May, June, and August. The patient incidence in 2011 was treated as 3/2500, but since it is actually only Taro Taro, it needs to be treated as 1/2500.
本実施例では、こうした実態と合わない集計・分析を防止するため、名寄処理によって、本当の患者数が分かるようにしている。この名寄処理されたデータを「傷病別分解マスタ3」とする。 In the present embodiment, in order to prevent aggregation / analysis that does not match the actual situation, the true number of patients is known by the name processing. The data subjected to the name processing is referred to as “wound-and-disease-specific decomposition master 3”.
6.市区町村コードの付与
各医療機関が作成するレセプトには、患者の住所情報は存在しないが、本実施例では、健康保険組合等から入手した被保険者及び被扶養者の情報から市区町村のデータを抽出し、レセプトデータに追加する。なお、被保険者又は被扶養者の住所が特定できない場合には、医療機関の所在地データを付与する。住所情報が付与されたデータを「傷病別分解マスタ4」とする。
6). Granting of municipal code The patient's address information does not exist in the receipt created by each medical institution, but in this embodiment, the municipality is based on the information of the insured and dependents obtained from the health insurance association, etc. Is extracted and added to the receipt data. If the address of the insured person or dependent cannot be specified, the location data of the medical institution is given. The data to which the address information is assigned is referred to as “wound / sickness-specific decomposition master 4”.
この追加処理の目的は、例えば、インフルエンザ等の感染病がどこで最初に発生し、どこに拡大していったのかを時系列で分析可能とするためである。従来のように、レセプトデータのみを用いた場合には、住所による集計・分析は不可能であり、感染病の発生地、拡大範囲等を時系列で知ることができなかったが、本実施例によればこれらも集計・分析することができる。 The purpose of this additional processing is to make it possible to analyze, for example, where an infectious disease such as influenza first occurred and where it spread. As in the past, when only the receipt data was used, it was impossible to count and analyze by address, and it was impossible to know the location of the infectious disease and the expansion range in time series. According to this, these can also be aggregated and analyzed.
上記の集計・分析方法は、仮に全国の健康保険組合のレセプトデータを入手することができれば、各健康保険組合や個々の企業と言う範囲を超えて、全国規模での感染症予防対策にも役立てることが可能となる。 The above aggregation / analysis methods can be used for infectious disease prevention measures on a nationwide scale, beyond the scope of each health insurance association and individual company, if receipt data for health insurance associations nationwide can be obtained. It becomes possible.
なお、一般的にレセプトデータの集計・分析は、実際の診療行為から1〜2カ月後に行われるため、リアルタイムでの感染拡大を把握することは不可能であるものの、過去のデータの蓄積により、将来予測の基礎とするなど、有効活用することが可能である。 In general, receipt data is collected and analyzed one to two months after the actual medical practice, so it is impossible to grasp the spread of infection in real time, but by accumulating past data, It can be used effectively as a basis for future predictions.
7.未受診者データ作成処理
病気の発生率や患者率を把握するためには、分母となる母集団が必要となるが、電子レセプトデータのみでは、この母集団が不明であるため「率」を把握することができない。
7). Unexamined person data creation process To understand the incidence of illnesses and the rate of patients, a denominator population is required, but the electronic receipt data alone does not know this population, so it understands the "rate". Can not do it.
本実施例では、健康保険組合等から入手した被保険者及び被扶養者の情報から、レセプトデータの存在しない者、即ち、通院していない者についても未受診者としてのファイルを作成する。 In the present embodiment, a file as an unexamined person is created for those who do not have receipt data, that is, those who do not go to hospital, from information on the insured and dependents obtained from the health insurance association or the like.
上記未受診者のファイルは、レセプトデータと全く同じ項目を有するものであり、病名や検査名、薬剤名が「空」となっているファイルである。 The file of the unexamined person has exactly the same items as the receipt data, and is a file in which the disease name, examination name, and drug name are “empty”.
この空ファイルの者と電子レセプトデータが存在する者を合計した人数が、当該健康保険組合に加入する被保険者及び被扶養者の総数であるため、この数字を分母として集計することで、様々な「率」を把握することが可能となる。 The total number of people who have this empty file and those who have electronic receipt data is the total number of insured persons and dependents who join the health insurance association. It is possible to grasp the “rate”.
仮に、将来的に未受診者が病気となって通院した場合、その後に送られてくるレセプトデータによって、診療や処置及び検査、処方された薬剤の情報が記載されたデータと置き換える。 If, in the future, an undiagnosed person goes to the hospital because he / she is ill, he / she replaces it with data describing information on medical treatments, treatments and examinations, and prescribed medicines by means of receipt data sent thereafter.
この未受診者ファイルからなる未受診者マスタと、上記傷病別分解マスタ1〜4とを合体させて、最終的な「傷病別分解マスタ」を作成する。 The undiagnosed person master composed of the undiagnosed person file and the wound disease and disease separation masters 1 to 4 are combined to create a final “wound and disease separation master”.
8.後発医薬品比較マスタの作成
また、医療費に占める薬剤価格も大きな社会問題となっており、近年は後発医薬品、いわゆるジェネリック品の推奨も進められている。
8). The creation of generic drug comparison masters and the price of drugs in medical expenses are also a major social problem. In recent years, generic drugs, so-called generic products, have been recommended.
本実施例では、新薬とジェネリック品のデータベースからなる後発医薬品比較マスタを予め作成しておき、電子レセプトに記載された薬剤に対し、安価なジェネリック品が存在するかどうかも分析できるようにしている。 In this embodiment, a generic drug comparison master consisting of a database of new drugs and generic products is created in advance, so that it is possible to analyze whether or not cheap generic products exist for drugs listed on the electronic receipt. .
情報処理事業者は、以上のとおり作成された各マスタから、クライアントの求めに応じて患者別、傷病別等に集計処理し、帳票出力及び分析結果照会画面用データ等を作成する。 The information processing company aggregates each master created as described above for each patient, disease, etc. according to the client's request, and creates form output, analysis result inquiry screen data, and the like.
例えば、最も基本となる医療費の3要素別(1人当たり件数、1件当たり日数、1日当たり診療費)の集計処理は無論のこと、本発明のデータを用いて集計・分析する場合、従来のシステムやデータではなし得なかった正確な病名による集計・分析、住所情報に基づく感染症の発生や拡大状況の分析、個人単位での病気の発生率など多種の集計・分析を実施することができる。 For example, of course, the aggregation process of the most basic medical expenses by the three elements (number of cases per person, number of days per case, medical expenses per day) is, of course, when using the data of the present invention to calculate and analyze Aggregation / analysis based on accurate disease names that could not be achieved with systems and data, analysis of the occurrence and spread of infectious diseases based on address information, and the incidence and rate of illness on an individual basis. .
Claims (2)
検査項目名及び薬剤名と、これらから推定される最適傷病名を記憶した診療行為・医薬品・傷病関連マスタと、
前記電子レセプトデータ中に存在する傷病名、検査項目名、薬剤名と、前記診療行為・医薬品・傷病関連マスタとを比較する比較手段と、
前記電子レセプトデータ中に存在する傷病名と前記最適傷病名とが異なる場合、当該傷病名を前記最適傷病名に読み替える読替手段とを備え、
前記比較手段によって前記電子レセプトデータ中に存在する傷病名、検査項目名、薬剤名と、診療行為・医薬品・傷病関連マスタとを比較し、
当該傷病名と前記最適傷病名とが異なる場合、前記読替手段によって前記最適傷病名を前記読替傷病マスタに記憶する、
ことを特徴とする電子レセプトデータ処理システム。 An electronic receipt data processing system for collecting and analyzing disease states and medical expenses using electronic receipt data ,
The medical treatment / medicine / injury related master that memorizes the examination item name and drug name, and the optimal injury / injury name estimated from these,
Comparison means for comparing the name of the wound, the name of the test item, the name of the drug present in the electronic receipt data, and the medical treatment / medicine / injury related master,
When the wound name and the disease name present in the electronic receipt data are different from the optimum wound name, the reading means comprises replacing the wound name with the optimum wound name,
Compare the wound name, test item name, drug name, and medical practice / pharmaceutical / wound related masters present in the electronic receipt data by the comparison means,
If the wound name and the optimal wound name are different, the optimal wound name is stored in the replacement wound disease master by the replacement means.
An electronic receipt data processing system.
ことを特徴とする請求項1に記載の電子レセプトデータ処理システム。 The optimal wound name replaced by the replacement means is displayed with an inappropriate display on the terminal screen, and is stored in the replaced wound master after visual confirmation.
The electronic receipt data processing system according to claim 1 .
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