JP2005050380A5 - - Google Patents
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- JP2005050380A5 JP2005050380A5 JP2004316962A JP2004316962A JP2005050380A5 JP 2005050380 A5 JP2005050380 A5 JP 2005050380A5 JP 2004316962 A JP2004316962 A JP 2004316962A JP 2004316962 A JP2004316962 A JP 2004316962A JP 2005050380 A5 JP2005050380 A5 JP 2005050380A5
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前記医療費予測サーバは、
複数種類の慢性疾患に関する年齢と発症率との相関を示す発症率相関データを、性別を少なくとも含む個人属性別に記憶している発症率相関データベースと、
喫煙、飲酒、及び運動の習慣を少なくとも一つ含む生活習慣が前記慢性疾患の発症率を変化させる度合いを示す生活習慣係数を、前記慢性疾患の種類別に、前記生活習慣の種類に対応付けて格納している生活習慣データベースと、
被保険者の健康状態を示す複数の検査項目からなる検診データが所定の基準値から外れている場合に当該被保険者に関する前記慢性疾患の発症率を補正する検診データ係数を、前記検査項目及び前記慢性疾患の種類に対応付けて格納している補正データベースと、
前記慢性疾患の治療にかかる標準医療費を、前記慢性疾患の種類に対応付けて格納している慢性疾患医療費データベースと、
前記慢性疾患を除く病気又はけがによる医療費である非慢性疾患医療費の、年齢との相関を示す医療費相関データを、前記個人属性別に記憶している非慢性疾患医療費データベースと
を有し、
前記団体用端末は、少なくとも性別と年齢を含む個人属性、既に発症している慢性疾患を示す告知情報、前記検診データ、前記生活習慣、及び被扶養者の前記個人属性と前記告知情報を含む個人情報の入力を当該団体に所属する複数の被保険者本人に関して受け付けると共に、当該団体が将来採用する予定の採用者の前記個人属性を年ごとに示す採用計画及び当該団体における定年年齢を含む団体情報の入力を受け付け、前記複数の被保険者本人に関する前記個人情報と当該団体情報とを前記医療費予測サーバに送信し、
前記医療費予測サーバは更に、
前記団体用端末から、前記複数の被保険者本人に関する前記個人情報と前記団体情報を受信して記憶する会員データベースと、
将来のある時点における、前記団体にかかる医療費を予測すべき旨のコマンドを受け付けた場合において、前記慢性疾患の種類別に、前記会員データベースから、前記将来の時点の年齢が前記団体の前記定年年齢を超過しない前記被保険者本人及びその被扶養者を抽出し、前記慢性疾患を既に発症している旨が前記告知情報に記録されている前記被保険者本人及び前記被扶養者を前記慢性疾患の既発症者として分類し、前記旨が記録されていない前記被保険者本人及び前記被扶養者を未発症者として分類する分類部と、
前記未発症者に関して前記会員データベースに記憶されている前記個人属性のそれぞれを検索キーとして、前記発症率相関データベースから順次前記発症率相関データを読み出し、前記将来の年齢に対応する前記慢性疾患の発症率を、前記未発症者のそれぞれに関する前記慢性疾患の前記将来の発症率として読み取ると共に、前記将来の時点までの前記採用計画に含まれる前記採用者に関して前記会員データベースに記憶されている前記個人属性をそれぞれ検索キーとして、前記発症率相関データベースから順次前記発症率相関データを読み出し、当該採用者の前記将来の年齢に対応する前記慢性疾患の発症率を、前記採用者に関する前記慢性疾患の前記将来の発症率として読み取る属性別発症率読取部と、
前記未発症者のうちで前記被保険者本人の前記検診データを検索キーとして、前記補正データベースから前記検診データ係数を読み出し、前記属性別発症率読取部が前記未発症者うちで前記被保険者本人に関して読み取った前記発症率を、当該検診データ係数で補正する検診データ反映部と、
前記未発症者のうちで前記被保険者本人について前記会員データベースに記憶されている前記生活習慣を検索キーとして、前記生活習慣データベースから前記生活習慣係数を読み出し、前記検診データ反映部が補正した前記発症率を当該生活習慣係数で補正する生活習慣反映部と、
前記生活習慣反映部が補正した前記未発症者のうちで前記被保険者本人に関する前記発症率と、前記属性別発症率読取部が読み取った前記未発症者のうちの前記被扶養者及び前記採用者に関する前記発症率とを前記団体について集計して平均をとることにより、前記将来の時点での、前記団体の前記未発症者及び前記採用者における前記慢性疾患の平均発症率を前記慢性疾患の種類毎に算出する平均発症率算出部と、
前記平均発症率に、前記未発症者及び前記将来の時点における前記採用者を合わせた人数と、前記慢性疾患について前記慢性疾患医療費データベースに格納されている前記標準医療費とを乗じることによって、前記慢性疾患に関して当該団体の前記未発症者及び前記採用者にかかる前記将来の医療費を算出し、さらに、前記慢性疾患について前記慢性疾患医療費データベースに格納されている前記標準医療費に、前記会員データベースに記憶されている当該団体の前記既発症者の数を乗じた医療費を加算することによって、前記慢性疾患に関して当該団体にかかる前記将来の医療費を算出し、当該将来の医療費を前記慢性疾患医療費データベースに格納されている全ての慢性疾患について算出して集計することにより、前記全ての慢性疾患に関して当該団体にかかる前記将来の医療費を算出する慢性疾患医療費算出部と、
前記分類部が分類した、前記定年年齢を超過しない全ての前記被保険者本人とその被扶養者、ならびに前記将来の時点までに採用される前記採用者のそれぞれについて、前記会員データベースに記憶されている前記個人属性を検索キーとして前記非慢性疾患医療費データベースから前記医療費相関データを読み出して、前記将来の年齢に対応する前記非慢性疾患医療費をそれぞれ読み取り、当該非慢性疾患医療費を当該団体に関する全ての前記被保険者、前記被扶養者、及び前記採用者について集計することにより、当該団体にかかる前記将来の前記非慢性疾患医療費を算出する非慢性疾患医療費算出部と、
当該団体について、前記慢性疾患医療費算出部及び非慢性疾患医療費算出部の算出結果を加算することにより、前記将来の時点で当該団体にかかる総医療費を算出して出力する団体総医療費出力部と、
疾病の治療にかかった医療費を示すレセプトデータを収集して前記慢性疾患毎に前記医療費の平均値を算出し、前記慢性疾患医療費データベースに記憶されている前記慢性疾患毎の前記標準医療費を、集計した前記平均値で更新するレセプト集計部と
を有する医療費予測システム。 A medical cost prediction system comprising a group terminal and a medical cost prediction server connected via a network, and predicting a future medical cost of the group,
The medical cost prediction server
An incidence correlation database storing incidence correlation data showing correlation between age and incidence for multiple types of chronic diseases by individual attributes including at least gender;
A lifestyle coefficient indicating the degree to which the lifestyle including at least one of smoking, drinking, and exercise habits changes the incidence of the chronic disease is stored in association with the lifestyle type for each chronic disease type. Lifestyle database and
When the examination data consisting of a plurality of examination items indicating the health condition of the insured person deviates from a predetermined reference value, the examination data coefficient for correcting the incidence of the chronic disease related to the insured person, the examination item and A correction database stored in association with the type of chronic disease;
Chronic disease medical cost database storing standard medical costs related to the treatment of the chronic diseases in association with the types of the chronic diseases, and
A non-chronic disease medical cost database storing medical cost correlation data showing correlation with age of non-chronic disease medical costs that are medical costs due to illness or injury other than the chronic disease, ,
The group terminal is a personal attribute including at least gender and age, notification information indicating a chronic disease that has already developed, the examination data, the lifestyle, and the individual attribute of the dependent and the notification information Acceptance of information regarding multiple insured persons who belong to the organization, and the recruitment plan that shows the individual attributes of the employers that the organization intends to employ in the future, and organization information including the retirement age of the organization And receiving the personal information and the group information related to the plurality of insured persons to the medical cost prediction server,
The medical cost prediction server further includes:
A member database for receiving and storing the personal information and the group information on the plurality of insured persons from the group terminal;
When receiving a command to predict the medical expenses for the organization at a certain time in the future, the age at the future time is the retirement age of the organization from the member database for each type of chronic disease. The insured person and the dependents who do not exceed the above are extracted, and the insured person and the dependents recorded in the notice information that the chronic disease has already occurred are recorded in the chronic disease. A classifying unit that classifies the insured person and the dependent who are not recorded as an unaffected person,
Using each of the personal attributes stored in the member database for the unaffected person as a search key, the incidence correlation data is sequentially read from the incidence correlation database, and the onset of the chronic disease corresponding to the future age The personal attribute stored in the member database for the employer included in the recruitment plan up to the future time point, while reading the rate as the future incidence of the chronic disease for each of the undeveloped persons As the search keys, sequentially reading out the incidence correlation data from the incidence correlation database, and determining the incidence of the chronic disease corresponding to the future age of the employer as the future of the chronic disease related to the employer. An attribute-specific onset rate reading unit that reads as an onset rate,
The examination data coefficient is read from the correction database using the examination data of the insured person among the unaffected persons as a search key, and the attribute-specific incidence reading unit is the insured person among the unaffected persons. A screening data reflecting unit that corrects the onset rate read about the person with the screening data coefficient;
Using the lifestyle stored in the member database for the insured person among the unaffected persons as a search key, the lifestyle coefficient is read from the lifestyle database, and the examination data reflection unit has corrected the A lifestyle reflecting section that corrects the incidence by the lifestyle coefficient,
Of the unaffected persons corrected by the lifestyle reflecting unit, the incidence of the insured person and the dependents of the unaffected persons read by the attribute-specific onset rate reading unit and the adoption The average incidence rate of the chronic disease in the unaffected person and the employer of the group at the future time point is calculated by calculating the average of the incidence rate for the person and taking the average for the group. An average incidence calculation unit for each type,
By multiplying the average incidence by the number of people who have not developed the disease and the employer at the future time point, and the standard medical cost stored in the chronic disease medical cost database for the chronic disease, Calculate the future medical expenses for the non-developed person and the employer for the chronic disease with respect to the chronic disease, and further, the standard medical expenses stored in the chronic disease medical expenses database for the chronic disease, By adding the medical cost multiplied by the number of the pre-existing persons of the group stored in the member database, the future medical cost for the group with respect to the chronic disease is calculated, and the future medical cost is calculated. By calculating and totaling all chronic diseases stored in the chronic disease medical cost database, A chronic disease medical cost calculation unit that calculates the future medical expenses relating to the organization and,
Stored in the member database for all the insured persons and their dependents who do not exceed the retirement age classified by the classification unit, and each of the employers employed by the future time point. The medical cost correlation data is read from the non-chronic disease medical cost database using the personal attribute as a search key, the non-chronic disease medical cost corresponding to the future age is read, and the non-chronic disease medical cost is A non-chronic disease medical cost calculation unit for calculating the future non-chronic disease medical cost for the group by counting up all the insured persons, dependents, and the employers related to the group;
The total medical cost of the group that calculates and outputs the total medical cost for the group at the future time point by adding the calculation results of the chronic disease medical cost calculation unit and the non-chronic disease medical cost calculation unit for the group An output section;
The standard medical care for each chronic disease stored in the chronic disease medical cost database is calculated by collecting the receipt data indicating the medical cost for the treatment of the disease and calculating the average value of the medical cost for each chronic disease. A medical cost prediction system , comprising: a receipt totaling unit that updates costs with the average value that has been totalized .
前記医療費予測サーバはさらに、
健康保険における、保険料率と、医療費の組合負担割合とを、前記保険組合毎に格納している保険組合データベースと、
前記将来において前記団体に所属する前記被保険者本人の前記予想給与の総額を、前記会員データベースに格納されたに昨年度又は今年度の給与実績及び今後の予想昇給率に基づいて算出し、前記保険組合データベースに格納されている現在の前記保険料率を掛け合わせることにより、前記保険組合が当該団体から徴収する前記将来の保険料徴収額を算出し、当該保険料徴収額を用いて前記保険組合の前記将来における収入を算出する健保収入算出部と、
前記団体総医療費出力部が出力した前記将来の前記総医療費に前記保険組合の現在の前記組合負担割合を乗じた金額を用いて、前記保険組合の前記将来における支出を算出する健保支出算出部と、
前記保険組合の前記将来における前記収入と前記支出とを均衡させる為に必要な、前記保険料率及び前記組合負担割合の少なくとも一方を算出し、算出結果を前記団体用端末に送信する均衡収支演算部と
を更に有し、
前記団体用端末は、前記均衡収支演算部から受信する前記算出結果を表示する、請求項１に記載の医療費予測システム。 The member database is further received and stored as the personal information, the salary performance of the insured person belonging to the group last year or the current fiscal year and the expected rate of future salary increase,
The medical cost prediction server further includes:
An insurance union database storing the insurance premium rate and the union share of medical expenses for each insurance union in health insurance;
The total amount of the expected salary of the insured who belongs to the group in the future is calculated based on the salary record of the previous fiscal year or current year and the expected rate of future salary increase stored in the member database, and the insurance By multiplying the current insurance premium rate stored in the association database, the insurance association calculates the future insurance premium collection amount collected from the organization and uses the insurance premium collection amount of the insurance association. A health insurance income calculation unit for calculating the income in the future;
Health insurance expenditure calculation for calculating the future expenditure of the insurance association using the amount obtained by multiplying the future total medical expenditure output by the group total medical expenditure output unit with the current union burden ratio of the insurance association And
An equilibrium balance calculation unit that calculates at least one of the insurance premium rate and the union burden ratio necessary for balancing the income and the expenditure of the insurance association in the future, and transmits the calculation result to the group terminal. And
The medical cost prediction system according to claim 1, wherein the group terminal displays the calculation result received from the balanced balance calculation unit.
前記検診データ反映部は、前記会員データベースに格納された前記被保険者の前記現在の検診データを前記過去の検診データと比較することにより前記検診データの改善量を判断し、前記検診データの改善量が前記検診項目毎に予め定められたしきい値よりも大きい場合、前記検診データ係数を小さく補正する、請求項１に記載の医療費予測システム。 The member database further stores past medical examination data of the insured,
The screening data reflection unit determines an improvement amount of the screening data by comparing the current screening data of the insured person stored in the member database with the past screening data, and improves the screening data. The medical cost prediction system according to claim 1, wherein when the amount is larger than a predetermined threshold value for each examination item, the examination data coefficient is corrected to be small.
前記検診データ反映部は、前記会員データベースに格納された前記被保険者の前記現在の検診データを前記過去の検診データと比較することにより前記検診データの悪化量を判断し、前記検診データの悪化量が前記検診項目毎に予め定められたしきい値よりも大きい場合、前記検診データ係数を大きく補正する、請求項１に記載の医療費予測システム。 The member database further stores past medical examination data of the insured,
The screening data reflection unit determines the deterioration amount of the screening data by comparing the current screening data of the insured person stored in the member database with the past screening data, and the deterioration of the screening data The medical cost prediction system according to claim 1, wherein when the amount is larger than a predetermined threshold value for each examination item, the examination data coefficient is corrected to be large.
前記慢性疾患医療費算出部は、前記慢性疾患医療費データベースから前記慢性疾患の入院時の医療費及び通院時の医療費を読み出し、前記未発症者及び前記将来の時点における前記採用者のうち一定割合の人数に対して入院時の医療費を乗じ、残りの人数に対して通院時の医療費を乗じることにより、前記慢性疾患に関して当該団体にかかる前記将来の医療費を算出する請求項１に記載の医療費予測システム。 The chronic disease medical expenses database stores medical expenses at the time of hospitalization and medical expenses at the time of hospitalization as the standard medical expenses of the chronic diseases,
The chronic disease medical cost calculation unit reads the chronic medical cost at the time of hospitalization and the medical cost at the time of hospitalization from the chronic disease medical cost database, and is constant among the undeveloped person and the employer at the future time point. 2. The future medical cost for the organization with respect to the chronic disease is calculated by multiplying the proportion of the number by the medical cost at the time of admission and the remaining number of people by the medical cost at the time of hospital visit. The medical cost prediction system described.
複数種類の慢性疾患に関する年齢と発症率との相関を示す発症率相関データを、少なくとも性別を含む個人属性別に記憶している発症率相関データベースと、
喫煙、飲酒、及び運動の習慣を少なくとも一つ含む生活習慣が前記慢性疾患の発症率を変化させる度合いを示す生活習慣係数を、前記慢性疾患の種類別に、前記生活習慣の種類に対応付けて格納している生活習慣データベースと、
被保険者の健康状態を示す複数の検査項目からなる検診データが所定の基準値から外れている場合に、当該被保険者に関する前記慢性疾患の発症率を補正する検診データ係数を、前記検査項目及び前記慢性疾患の種類に対応付けて格納している補正データベースと、
前記慢性疾患の治療にかかる標準医療費を、前記慢性疾患の種類に対応付けて格納している慢性疾患医療費データベースと、
前記慢性疾患を除く病気又はけがによる医療費である非慢性疾患医療費の、年齢との相関を示す医療費相関データを、前記個人属性別に記憶している非慢性疾患医療費データベースと、
ネットワークを介して接続された団体用端末から、当該団体に所属する被保険者本人に関する、少なくとも性別と年齢を含む個人属性、既に発症している慢性疾患を示す告知情報、前記検診データ、前記生活習慣、及び被扶養者の前記個人属性と前記告知情報を含む個人情報と、当該団体が将来採用する予定の採用者の前記個人属性を年ごとに示す採用計画及び当該団体における定年年齢を含む団体情報とを受信し、受信した前記個人情報及び前記団体情報を記憶する会員データベースと、
将来のある時点における、前記団体にかかる医療費を予測すべき旨のコマンドを受け付けた場合において、前記慢性疾患の種類別に、前記会員データベースから、前記被保険者本人のうちで、前記将来の時点の年齢が前記団体の前記定年年齢を超過しない被保険者本人及びその被扶養者を抽出し、前記慢性疾患を既に発症している旨が前記告知情報に記録されている前記被保険者本人及び前記被扶養者を前記慢性疾患の既発症者として分類し、前記旨が記録されていない前記被保険者本人及び前記被扶養者を未発症被保険者として分類する分類部と、
前記未発症者に関して前記会員データベースに記憶されている前記個人属性のそれぞれを検索キーとして、前記発症率相関データベースから順次前記発症率相関データを読み出し、前記将来の年齢に対応する前記慢性疾患の発症率を、前記未発症者のそれぞれに関する前記慢性疾患の前記将来の発症率として読み取ると共に、前記将来の時点までの前記採用計画に含まれる前記採用者に関して前記会員データベースに記憶されている前記個人属性をそれぞれ検索キーとして、前記発症率相関データベースから順次前記発症率相関データを読み出し、当該採用者の前記将来の年齢に対応する前記慢性疾患の発症率を、前記採用者に関する前記慢性疾患の前記将来の発症率として読み取る属性別発症率読取部と、
前記未発症者のうちの前記被保険者本人の前記検診データを検索キーとして、前記補正データベースから前記検診データ係数を読み出し、前記属性別発症率読取部が前記未発症者のうちの前記被保険者本人に関して読み取った前記発症率を、当該検診データ係数で補正する検診データ反映部と、
前記未発症者のうちの前記被保険者本人について前記会員データベースに記憶されている前記生活習慣を検索キーとして、前記生活習慣データベースから前記生活習慣係数を読み出し、前記検診データ反映部が補正した前記発症率を当該生活習慣係数で補正する生活習慣反映部と、
前記生活習慣反映部が補正した前記未発症者のうちの前記被保険者本人に関する前記発症率と、前記属性別発症率読取部が読み取った前記未発症者のうちの前記被扶養者及び前記採用者に関する前記発症率とを、前記団体について集計して平均をとることにより、前記将来の時点での、前記団体の前記未発症者及び前記採用者における前記慢性疾患の平均発症率を前記慢性疾患の種類毎に算出する平均発症率算出部と、
前記平均発症率に、前記未発症者及び前記将来の時点における前記採用者を合わせた人数と、前記慢性疾患について前記慢性疾患医療費データベースに格納されている前記標準医療費とを乗じることによって、前記慢性疾患に関して当該団体の前記未発症者及び前記採用者にかかる前記将来の医療費を算出し、さらに、前記慢性疾患について前記慢性疾患医療費データベースに格納されている前記標準医療費に、前記会員データベースに記憶されている当該団体の前記既発症者の数を乗じた医療費を加算することによって、前記慢性疾患に関して当該団体にかかる前記将来の医療費を算出し、当該将来の医療費を前記慢性疾患医療費データベースに格納されている全ての慢性疾患について算出して集計することにより、前記全ての慢性疾患に関して当該団体にかかる前記将来の医療費を算出する慢性疾患医療費算出部と、
前記分類部が分類した、前記定年年齢を超過しない全ての前記被保険者本人とその被扶養者、ならびに前記将来の時点までに採用される前記採用者のそれぞれについて、前記会員データベースに記憶されている前記個人属性を検索キーとして前記非慢性疾患医療費データベースから前記医療費相関データを読み出して、前記将来の年齢に対応する前記非慢性疾患医療費をそれぞれ読み取り、当該非慢性疾患医療費を当該団体に関する全ての前記被保険者本人、前記被扶養者、及び前記採用者について集計することにより、当該団体にかかる前記将来の前記非慢性疾患医療費を算出する非慢性疾患医療費算出部と、
当該団体について、前記慢性疾患医療費算出部及び非慢性疾患医療費算出部の算出結果を加算することにより、前記将来の時点で当該団体にかかる総医療費を算出して出力する団体総医療費出力部と、
疾病の治療にかかった医療費を示すレセプトデータを収集して前記慢性疾患毎に前記医療費の平均値を算出し、前記慢性疾患医療費データベースに記憶されている前記慢性疾患毎の前記標準医療費を、集計した前記平均値で更新するレセプト集計部と
を有する医療費予測サーバ。 A medical cost prediction server that predicts the future medical costs of an organization,
An incidence correlation database that stores incidence correlation data indicating correlation between age and incidence for multiple types of chronic diseases by individual attributes including at least sex,
A lifestyle coefficient indicating the degree to which the lifestyle including at least one of smoking, drinking, and exercise habits changes the incidence of the chronic disease is stored in association with the lifestyle type for each chronic disease type. Lifestyle database and
When the examination data consisting of a plurality of examination items indicating the health condition of the insured person is out of a predetermined reference value, the examination data coefficient for correcting the incidence of the chronic disease related to the insured person is the examination item. And a correction database stored in association with the type of chronic disease,
Chronic disease medical cost database storing standard medical costs related to the treatment of the chronic diseases in association with the types of the chronic diseases, and
Non-chronic disease medical cost database storing medical cost correlation data showing correlation with age of non-chronic disease medical costs that are medical costs due to illness or injury other than the chronic disease, and
From a group terminal connected via a network, personal attributes including at least gender and age, informed information indicating chronic disease that has already developed, screening data, life Organizations including customs, personal information including dependent personal attributes and notification information, recruitment plans that show the personal attributes of employers that the organization intends to employ in the future, and retirement age in the organization A member database for receiving information and storing the received personal information and group information;
In the case of receiving a command to predict the medical expenses for the organization at a certain time in the future, from the member database according to the type of chronic disease, among the insured person, the future time The insured person whose age does not exceed the retirement age of the group and its dependents are extracted, and the insured person who has already developed the chronic disease is recorded in the notification information and Classifying the dependent as an onset of the chronic disease, and classifying the insured who is not recorded as such and the dependent as an unaffected insured,
Using each of the personal attributes stored in the member database for the unaffected person as a search key, the incidence correlation data is sequentially read from the incidence correlation database, and the onset of the chronic disease corresponding to the future age The personal attribute stored in the member database for the employer included in the recruitment plan up to the future time point, while reading the rate as the future incidence of the chronic disease for each of the undeveloped persons As the search keys, sequentially reading out the incidence correlation data from the incidence correlation database, and determining the incidence of the chronic disease corresponding to the future age of the employer as the future of the chronic disease related to the employer. An attribute-specific onset rate reading unit that reads as an onset rate,
The examination data coefficient is read from the correction database using the examination data of the insured person among the unaffected persons as a search key, and the attribute-specific incidence rate reading unit reads the insured person among the unaffected persons. A screening data reflecting unit that corrects the onset rate read about the person himself / herself with the screening data coefficient;
Using the lifestyle stored in the member database for the insured person among the unaffected persons as a search key, the lifestyle coefficient is read from the lifestyle database, and the examination data reflection unit has corrected the A lifestyle reflecting section that corrects the incidence by the lifestyle coefficient,
The incidence of the insured person among the unaffected persons corrected by the lifestyle reflecting unit, and the dependent and the adoption of the unaffected persons read by the attribute-specific onset rate reading unit The average incidence of the chronic disease in the undeveloped person and the employer of the group at the future time point is calculated by taking the average for the group and taking the average for the group. An average onset rate calculation unit to calculate for each type,
By multiplying the average incidence by the number of people who have not developed the disease and the employer at the future time point, and the standard medical cost stored in the chronic disease medical cost database for the chronic disease, Calculate the future medical expenses for the non-developed person and the employer for the chronic disease with respect to the chronic disease, and further, the standard medical expenses stored in the chronic disease medical expenses database for the chronic disease, By adding the medical cost multiplied by the number of the pre-existing persons of the group stored in the member database, the future medical cost for the group with respect to the chronic disease is calculated, and the future medical cost is calculated. By calculating and totaling all chronic diseases stored in the chronic disease medical cost database, A chronic disease medical cost calculation unit that calculates the future medical expenses relating to the organization and,
Stored in the member database for all the insured persons and their dependents who do not exceed the retirement age classified by the classification unit, and each of the employers employed by the future time point. The medical cost correlation data is read from the non-chronic disease medical cost database using the personal attribute as a search key, the non-chronic disease medical cost corresponding to the future age is read, and the non-chronic disease medical cost is A non-chronic disease medical cost calculation unit for calculating the future non-chronic disease medical cost for the group by counting up all the insured persons, the dependents, and the employers related to the group;
The total medical cost of the group that calculates and outputs the total medical cost for the group at the future time point by adding the calculation results of the chronic disease medical cost calculation unit and the non-chronic disease medical cost calculation unit for the group An output section;
The standard medical care for each chronic disease stored in the chronic disease medical cost database is calculated by collecting the receipt data indicating the medical cost for the treatment of the disease and calculating the average value of the medical cost for each chronic disease. A medical cost prediction server , comprising: a receipt totaling unit that updates costs with the average value that has been totalized .
前記団体用端末が、少なくとも性別と年齢を含む個人属性、既に発症している慢性疾患を示す告知情報、前記検診データ、前記生活習慣、及び被扶養者の前記個人属性と前記告知情報を含む個人情報の入力を当該団体に所属する複数の被保険者本人に関して受け付けると共に、当該団体が将来採用する予定の採用者の前記個人属性を年ごとに示す採用計画及び当該団体における定年年齢を含む団体情報の入力を受け付け、前記複数の被保険者本人に関する前記個人情報と当該団体情報とを前記医療費予測サーバに送信するステップと、
前記医療費予測サーバにおいて、
会員データベースが、前記団体用端末から、前記複数の被保険者本人に関する前記個人情報と前記団体情報を受信して記憶するステップと、
分類部が、将来のある時点における、前記団体にかかる医療費を予測すべき旨のコマンドを受け付けた場合において、前記慢性疾患の種類別に、前記会員データベースから、前記将来の時点の年齢が前記団体の前記定年年齢を超過しない被保険者本人及びその被扶養者を抽出し、前記慢性疾患を既に発症している旨が前記告知情報に記録されている前記被保険者本人及び前記被扶養者を前記慢性疾患の既発症者として分類し、前記旨が記録されていない前記被保険者及び前記被扶養者を未発症者として分類するステップと、
属性別発症率読取部が、前記未発症者に関して前記会員データベースに記憶されている前記個人属性のそれぞれを検索キーとして、前記発症率相関データベースから順次前記発症率相関データを読み出し、前記将来の年齢に対応する前記慢性疾患の発症率を、前記未発症者のそれぞれに関する前記慢性疾患の前記将来の発症率として読み取ると共に、前記将来の時点までの前記採用計画に含まれる前記採用者に関して前記会員データベースに記憶されている前記個人属性をそれぞれ検索キーとして、前記発症率相関データベースから順次前記発症率相関データを読み出し、当該採用者の前記将来の年齢に対応する前記慢性疾患の発症率を、前記採用者に関する前記慢性疾患の前記将来の発症率として読み取るステップと、
検診データ反映部が、前記未発症者のうちの前記被保険者本人について前記会員データベースに記憶されている前記検診データを検索キーとして、前記補正データベースから前記検診データ係数を読み出し、前記属性別発症率読取部が前記未発症者のうちの前記被保険者本人に関して読み取った前記発症率を、当該検診データ係数で補正するステップと、
生活習慣反映部が、前記未発症者のうちの前記被保険者本人の前記生活習慣を検索キーとして、前記生活習慣データベースから前記生活習慣係数を読み出し、前記検診データ反映部が補正した前記発症率を当該生活習慣係数で補正するステップと、
平均発症率算出部が、前記生活習慣反映部が補正した前記未発症者のうちの前記被保険者本人に関する前記発症率と、前記属性別発症率読取部が読み取った前記未発症者のうちの前記被扶養者及び前記採用者に関する前記発症率とを前記団体について集計して平均をとることにより、前記将来の時点での、前記団体の前記未発症者及び前記採用者における前記慢性疾患の平均発症率を前記慢性疾患の種類毎に算出するステップと、
慢性疾患医療費算出部が、前記平均発症率に、前記未発症者及び前記将来の時点における前記採用者を合わせた人数と、前記慢性疾患について前記慢性疾患医療費データベースに格納されている前記標準医療費とを乗じることによって、前記慢性疾患に関して当該団体の前記未発症者及び前記採用者にかかる前記将来の医療費を算出し、さらに、前記慢性疾患について前記慢性疾患医療費データベースに格納されている前記標準医療費に、前記会員データベースに記憶されている当該団体の前記既発症者の数を乗じた医療費を加算することによって、前記慢性疾患に関して当該団体にかかる前記将来の医療費を算出し、当該将来の医療費を前記慢性疾患医療費データベースに格納されている全ての慢性疾患について算出して集計することにより、前記全ての慢性疾患に関して当該団体にかかる前記将来の医療費を算出するステップと、
非慢性疾患医療費算出部が、前記分類部が分類した、前記定年年齢を超過しない全ての前記被保険者本人とその被扶養者、ならびに前記将来の時点までに採用される前記採用者のそれぞれについて、前記会員データベースに記憶されている前記個人属性を検索キーとして前記非慢性疾患医療費データベースから前記医療費相関データを読み出して、前記将来の年齢に対応する前記非慢性疾患医療費をそれぞれ読み取り、当該非慢性疾患医療費を当該団体に関する全ての前記被保険者本人、前記被扶養者、及び前記採用者について集計することにより、当該団体にかかる前記将来の前記非慢性疾患医療費を算出するステップと、
団体総医療費出力部が、当該団体について、前記慢性疾患医療費算出部及び非慢性疾患医療費算出部の算出結果を加算することにより、前記将来の時点で当該団体にかかる総医療費を算出して出力するステップと、
疾病の治療にかかった医療費を示すレセプトデータを収集して前記慢性疾患毎に前記医療費の平均値を算出し、前記慢性疾患医療費データベースに記憶されている前記慢性疾患毎の前記標準医療費を、集計した前記平均値で更新するステップと
を有する医療費予測方法。 A group terminal connected via a network and a medical cost prediction server, wherein the medical cost prediction server includes gender and job type onset rate correlation data indicating correlation between age and onset rate regarding a plurality of types of chronic diseases. An incidence correlation database stored at least for each individual attribute, and a lifestyle coefficient indicating the degree to which the lifestyle including at least one habit of smoking, drinking, and exercise changes the incidence of the chronic disease, the chronic When the lifestyle data stored in association with the lifestyle type according to the type of disease and the examination data consisting of a plurality of examination items indicating the health status of the insured person are out of a predetermined reference value In addition, a screening data coefficient for correcting the incidence of the chronic disease related to the insured person is stored in association with the test item and the type of the chronic disease. A correction database, a chronic medical cost database that stores standard medical expenses for treatment of the chronic disease in association with the type of the chronic disease, and medical expenses due to illness or injury other than the chronic disease By using a medical cost prediction system having a non-chronic disease medical cost database that stores medical cost correlation data indicating the correlation of non-chronic medical costs with age, for each individual attribute, the future medical cost of the organization A method for predicting medical expenses,
The group terminal is a personal attribute including at least gender and age, notification information indicating chronic disease that has already developed, the examination data, the lifestyle, and the individual attribute of the dependent and the notification information Acceptance of information regarding multiple insured persons who belong to the organization, and the recruitment plan that shows the individual attributes of the employers that the organization intends to employ in the future, and organization information including the retirement age of the organization Receiving the input, and transmitting the personal information about the plurality of insured persons and the group information to the medical cost prediction server;
In the medical cost prediction server,
A member database receiving and storing the personal information and the group information on the plurality of insured persons from the group terminal;
When the classification unit receives a command to predict the medical expenses for the organization at a certain time in the future, the age at the future time is determined from the member database according to the type of the chronic disease. The insured person who does not exceed the retirement age and the dependent person are extracted, and the insured person and the dependent person in which the fact that the chronic disease has already occurred is recorded in the notification information Classifying as an onset of the chronic disease, and classifying the insured and the dependent not recorded as an unaffected person,
The attribute-specific onset rate reading unit sequentially reads out the onset rate correlation data from the onset rate correlation database using each of the individual attributes stored in the member database for the unaffected person as search keys, and the future age The incidence rate of the chronic disease corresponding to the above is read as the future incidence rate of the chronic disease for each of the undeveloped persons, and the member database regarding the employer included in the recruitment plan up to the future time point Each of the personal attributes stored in the search key is used as a search key, and the incidence rate correlation data is sequentially read from the incidence rate correlation database, and the incidence rate of the chronic disease corresponding to the future age of the employer is adopted. Reading as the future incidence of the chronic disease for a person,
The examination data reflection unit reads the examination data coefficient from the correction database using the examination data stored in the member database for the insured person among the unaffected persons as a search key, and the onset by attribute Correcting the onset rate read by the rate reading unit for the insured person among the unaffected individuals with the screening data coefficient; and
The lifestyle reflecting unit reads the lifestyle coefficient from the lifestyle database using the lifestyle of the insured person among the unaffected persons as a search key, and the incidence rate corrected by the screening data reflecting unit Correcting with the lifestyle coefficient,
The average incidence rate calculation unit is the incidence rate related to the insured person among the unaffected individuals corrected by the lifestyle reflecting unit, and the outbreak rate read by the attribute-specific incidence rate reading unit The average of the chronic illness in the unaffected person and the employer of the group at the future point in time by counting and averaging the incidence rate for the dependent and the employer for the group. Calculating the incidence for each type of chronic disease;
The chronic disease medical cost calculation unit, the average incidence rate, the total number of the unaffected persons and the employer at the future time point, and the standard stored in the chronic disease medical cost database for the chronic disease Multiplying by the medical cost, the future medical cost for the non-developed person and the employer of the group with respect to the chronic disease is calculated, and further, the chronic disease is stored in the chronic disease medical cost database. Calculating the future medical cost for the group with respect to the chronic disease by adding the medical cost obtained by multiplying the standard medical cost by the number of the onset patients of the group stored in the member database. The future medical expenses are calculated and totaled for all chronic diseases stored in the chronic disease medical expenses database. , And calculating the future medical expenses relating to the organization with respect to the all chronic disease,
The non-chronic disease medical cost calculation unit is classified by the classification unit, each of the insured person and his dependents who do not exceed the retirement age, and each of the employers employed by the future time point Read the medical cost correlation data from the non-chronic disease medical cost database using the personal attribute stored in the member database as a search key, and read the non-chronic disease medical cost corresponding to the future age, respectively. Calculating the future non-chronic disease medical expenses for the group by counting the non-chronic disease medical expenses for all the insured persons, the dependents, and the employers related to the group. Steps,
The group total medical cost output unit calculates the total medical cost for the group at the future time point by adding the calculation results of the chronic disease medical cost calculation unit and the non-chronic disease medical cost calculation unit for the group. And output step,
The standard medical care for each chronic disease stored in the chronic disease medical cost database is calculated by collecting the receipt data indicating the medical cost for the treatment of the disease and calculating the average value of the medical cost for each chronic disease. A medical cost prediction method , comprising: updating a cost with the average value .
少なくとも性別と年齢を含む個人属性、既に発症している慢性疾患を示す告知情報、前記検診データ、前記生活習慣、及び被扶養者の前記個人属性と前記告知情報を含む個人情報の入力を当該団体に所属する複数の被保険者本人に関して受け付けると共に、当該団体が将来採用する予定の採用者の前記個人属性を年ごとに示す採用計画及び当該団体における定年年齢を含む団体情報の入力を受け付け、前記複数の被保険者本人に関する前記個人情報と当該団体情報とを前記医療費予測サーバに送信させる機能を、前記団体用端末に実現させ、
前記医療費予測サーバに、
前記団体用端末から、前記複数の被保険者本人に関する前記個人情報と前記団体情報を受信して記憶する会員情報管理機能と、
将来のある時点における、前記団体にかかる医療費を予測すべき旨のコマンドを受け付けた場合において、前記慢性疾患の種類別に、前記会員データベースから、前記将来の時点の年齢が前記団体の前記定年年齢を超過しない前記被保険者本人及びその被扶養者を抽出し、前記慢性疾患を既に発症している旨が前記告知情報に記録されている被保険者本人及び前記被扶養者を前記慢性疾患の既発症者として分類し、前記旨が記録されていない前記被保険者本人及び前記被扶養者を未発症者として分類する分類機能と、
前記未発症者に関して前記会員データベースに記憶されている前記個人属性のそれぞれを検索キーとして、前記発症率相関データベースから順次前記発症率相関データを読み出し、前記将来の年齢に対応する前記慢性疾患の発症率を、前記未発症者のそれぞれに関する前記慢性疾患の前記将来の発症率として読み取ると共に、前記将来の時点までの前記採用計画に含まれる前記採用者に関して前記会員データベースに記憶されている前記個人属性をそれぞれ検索キーとして、前記発症率相関データベースから順次前記発症率相関データを読み出し、当該採用者の前記将来の年齢に対応する前記慢性疾患の発症率を、前記採用者に関する前記慢性疾患の前記将来の発症率として読み取る属性別発症率読取機能と、
前記未発症者のうちの前記被保険者本人について前記会員データベースに記憶されている前記検診データを検索キーとして、前記補正データベースから前記検診データ係数を読み出し、前記属性別発症率読取機能が前記未発症者のうちの前記被保険者本人に関して読み取った前記発症率を、当該検診データ係数で補正する検診データ反映機能と、
前記未発症者のうちの前記被保険者本人の前記生活習慣を検索キーとして、前記生活習慣データベースから前記生活習慣係数を読み出し、前記検診データ反映機能が補正した前記発症率を当該生活習慣係数で補正する生活習慣反映機能と、
前記生活習慣反映機能が補正した前記未発症者のうちの前記被保険者本人に関する前記発症率と、前記属性別発症率読取機能が読み取った前記未発症のうちの前記被扶養者及び前記採用者に関する前記発症率とを前記団体について集計して平均をとることにより、前記将来の時点での、前記団体の前記未発症者及び前記採用者における前記慢性疾患の平均発症率を前記慢性疾患の種類毎に算出する平均発症率算出機能と、
前記平均発症率に、前記未発症者及び前記将来の時点における前記採用者を合わせた人数と、前記慢性疾患について前記慢性疾患医療費データベースに格納されている前記標準医療費とを乗じることによって、前記慢性疾患に関して当該団体の前記未発症者及び前記採用者にかかる前記将来の医療費を算出し、さらに、前記慢性疾患について前記慢性疾患医療費データベースに格納されている前記標準医療費に、前記会員データベースに記憶されている当該団体の前記既発症者の数を乗じた医療費を加算することによって、前記慢性疾患に関して当該団体にかかる前記将来の医療費を算出し、当該将来の医療費を前記慢性疾患医療費データベースに格納されている全ての慢性疾患について算出して集計することにより、前記全ての慢性疾患に関して当該団体にかかる前記将来の医療費を算出する慢性疾患医療費算出機能と、
前記分類機能が分類した、前記定年年齢を超過しない全ての前記被保険者本人とその被扶養者、ならびに前記将来の時点までに採用される前記採用者のそれぞれについて、前記会員データベースに記憶されている前記個人属性を検索キーとして前記非慢性疾患医療費データベースから前記医療費相関データを読み出して、前記将来の年齢に対応する前記非慢性疾患医療費をそれぞれ読み取り、当該非慢性疾患医療費を当該団体に関する全ての前記被保険者本人、前記被扶養者、及び前記採用者について集計することにより、当該団体にかかる前記将来の前記非慢性疾患医療費を算出する非慢性疾患医療費算出機能と、
当該団体について、前記慢性疾患医療費算出機能及び非慢性疾患医療費算出機能の算出結果を加算することにより、前記将来の時点で当該団体にかかる総医療費を算出して出力する団体総医療費出力機能と、
疾病の治療にかかった医療費を示すレセプトデータを収集して前記慢性疾患毎に前記医療費の平均値を算出し、前記慢性疾患医療費データベースに記憶されている前記慢性疾患毎の前記標準医療費を、集計した前記平均値で更新するレセプト集計機能と
を実現させるプログラム。 The medical expenses prediction server includes a group terminal connected via a network and a medical expenses prediction server, and the medical expenses prediction server includes at least gender, onset rate correlation data indicating a correlation between age and onset rate regarding a plurality of types of chronic diseases. An incidence correlation database stored for each individual attribute, and a lifestyle coefficient indicating the degree to which the lifestyle including at least one of smoking, drinking, and exercise habits changes the incidence of the chronic disease, By type, when the lifestyle data stored in association with the type of lifestyle and the examination data consisting of a plurality of examination items indicating the health status of the insured person are out of a predetermined standard, Correction data for storing a screening data coefficient for correcting the incidence of the chronic disease related to the insured in association with the test item and the type of the chronic disease A chronic disease medical cost database that stores the base and standard medical costs for treatment of the chronic disease in association with the types of the chronic diseases, and non-chronic that is medical costs due to illness or injury other than the chronic diseases A program for predicting the future medical expenses of a group in a medical expenses prediction system having a non-chronic disease medical expenses database storing medical expenses correlation data indicating correlation with age of the medical expenses of diseases. Because
Personal group including at least gender and age, notification information indicating chronic disease that has already developed, the examination data, the lifestyle, and the input of personal information including the personal attribute of the dependent and the notification information Accepting the input of group information including the retirement age in the organization and the recruitment plan showing the individual attributes of the employer scheduled to be employed in the future by the organization and the organization's retirement age A function for causing the medical expenses prediction server to transmit the personal information and the group information related to a plurality of insured persons to the group terminal,
In the medical cost prediction server,
A member information management function for receiving and storing the personal information and the group information related to the plurality of insured persons from the group terminal;
When receiving a command to predict the medical expenses for the organization at a certain time in the future, the age at the future time is the retirement age of the organization from the member database for each type of chronic disease. The insured person and his dependents who do not exceed the above are extracted, and the insured person and the dependents whose chronicity is already developed are recorded in the notification information. Classifying as an onset person, a classification function to classify the insured person and the dependent who are not recorded as an unaffected person, and
Using each of the personal attributes stored in the member database for the unaffected person as a search key, the incidence correlation data is sequentially read from the incidence correlation database, and the onset of the chronic disease corresponding to the future age The personal attribute stored in the member database for the employer included in the recruitment plan up to the future time point, while reading the rate as the future incidence of the chronic disease for each of the undeveloped persons As the search keys, sequentially reading out the incidence correlation data from the incidence correlation database, and determining the incidence of the chronic disease corresponding to the future age of the employer as the future of the chronic disease related to the employer. An attribute-specific onset rate reading function to read as an onset rate,
The examination data coefficient is read from the correction database using the examination data stored in the member database for the insured person among the unaffected persons as a search key, and the attribute-specific incidence rate reading function is not used. The screening data reflecting function for correcting the incidence rate read about the insured person among the onset persons with the screening data coefficient,
Using the lifestyle of the insured person among the unaffected persons as a search key, the lifestyle coefficient is read from the lifestyle database, and the incidence rate corrected by the screening data reflection function is the lifestyle coefficient. A lifestyle reflection function to be corrected,
The incidence of the insured person among the unaffected persons corrected by the lifestyle reflecting function, and the dependent and the employer of the unaffected persons read by the attribute-specific incidence reading function The average incidence rate of the chronic disease in the undeveloped person and the employer of the group at the future time point is calculated by calculating the average of the incidence rate for the organization and taking the average. An average incidence calculation function to be calculated every time,
By multiplying the average incidence by the number of people who have not developed the disease and the employer at the future time point, and the standard medical cost stored in the chronic disease medical cost database for the chronic disease, Calculate the future medical expenses for the non-developed person and the employer for the chronic disease with respect to the chronic disease, and further, the standard medical expenses stored in the chronic disease medical expenses database for the chronic disease, By adding the medical cost multiplied by the number of the pre-existing persons of the group stored in the member database, the future medical cost for the group with respect to the chronic disease is calculated, and the future medical cost is calculated. By calculating and counting all chronic diseases stored in the chronic disease medical cost database, A chronic disease medical cost calculation function for calculating the future medical expenses relating to the organization and,
Stored in the member database for all the insured persons and their dependents who do not exceed the retirement age classified by the classification function, and each of the employers employed by the future time point. The medical cost correlation data is read from the non-chronic disease medical cost database using the personal attribute as a search key, the non-chronic disease medical cost corresponding to the future age is read, and the non-chronic disease medical cost is A non-chronic disease medical cost calculation function for calculating the future non-chronic disease medical cost for the group by counting up all the insured persons, the dependents, and the employers related to the group;
Calculate the total medical cost for the organization at the future point in time by adding the calculation results of the chronic disease medical cost calculation function and non-chronic disease medical cost calculation function for the group, and output the total medical cost for the group Output function,
The standard medical care for each chronic disease stored in the chronic disease medical cost database is calculated by collecting the receipt data indicating the medical cost for the treatment of the disease and calculating the average value of the medical cost for each chronic disease. A program for realizing a receipt totaling function for updating expenses with the average value calculated .
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