JP2012210441A - 改良された糖尿病データ管理のためのシステムおよび方法、および使用法 - Google Patents
改良された糖尿病データ管理のためのシステムおよび方法、および使用法 Download PDFInfo
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Abstract
【解決手段】診断テストデバイス(たとえば、血糖計)および薬物送達デバイス(たとえば、インスリン送達デバイス)を使用し、データをリポジトリにリアルタイムかつ自動的に送る、疾病管理のための方法、デバイス、およびシステムが提供される。リポジトリデータを解析し、実際のテストストリップの使用、規定された範囲外の患者健康パラメータ、テストおよび薬物送達の遵守、促進物品または奨励金を受け取るための患者プロファイルまたは利害関係者などの情報を決定することができる。接続型メータおよび薬物送達デバイスならびにリポジトリデータ解析もまた、個人によって実施される治療介入のタイミングに基づいて診断テストを食事時間に関連付けるために使用される。
。
【選択図】図3
Description
BGM 血糖計
DM 糖尿病管理
DMC 疾病管理会社
DMD 糖尿病管理データ
WM ワイヤレスBGM
− 個人が最初の食事をすることになる、最新を表す単一の時間(M1)。
− 個人が2回目の食事をすることになる、最新を表す単一の時間(M2)。
− 個人が3回目の食事をすることになる、最新を表す単一の時間(M3)。
− 個人が眠ることになる、最新を表す単一の時間(S1)。
− 個人が夜中に血糖をテストすることになる、最新を表す単一の時間(N1)。
− 注入時間前30分以下である血糖テスト時間は、食前として分類される(ブロック310および318)。
− 注入時間後90分以上かつ180分以下である血糖テスト時間は、食後として分類される(ブロック314および320)。
− 注入時間前45分以下かつ前の注入時間後180分以上である血糖テスト時間は、食前として分類される(ブロック312および318)。
− 注入時間後30分以上かつ注入時間後90分以下である血糖テスト時間は、未知として分類される(ブロック316および322)。
− 所与の日に注入時間がM1前である場合、その注入は、その日の1回目の食事に関連付けられることになる。
− 所与の日に注入時間がM1後かつM2前である場合、その注入は、その日の2回目の食事に関連付けられることになる。
− 所与の日に注入時間がM2後かつM3前である場合、その注入は、その日の3回目の食事に関連付けられることになる。
− 所与の日に注入時間がM3後かつS1前である場合、その注入は、その日の就寝時間に関連付けられることになる。
− 所与の日に注入時間がN1後かつN1+5前になく、血糖テスト時間がN1後かつN1+5前である場合、その血糖テストは、夜間テストに関連付けられることになる。
− どの血糖テストが注入に関連付けられるか。
− 血糖テストが、3つの食事時間に関する食前テストまたは食後テストとして分類されるか、それとも就寝時テストか、夜間テストか。
− 日ごとの注入の数
− 日ごとの血糖テストの数(ブロック330)
を決定するために、個人のデータの解析を実施することに依拠する。さらに、その個人は、1日当たりの食事の典型的な数を表す数を提供することができる(ブロック332)。
− 注入時間前30分以下である血糖テスト時間は、食前として分類される(ブロック310および318)、
− 注入時間後90分以上かつ180分以下である血糖テスト時間は、食後として分類される(ブロック314および320)、
− 注入時間前45分以下かつ前の注入時間後180分以上である血糖テスト時間は、食前として分類される(ブロック312および318)、
− 注入時間後30分以上かつ注入時間後90分以下である血糖テスト時間は、未知として分類される(ブロック316および322)
を使用して、血糖テストが食前であるか、それとも食後であるか判定する。
1.個人が、固定された時間をその人の食事期間の前後に割り当てること。
2.個人が、テストまたは行動が食前もしくは食後、就寝時間、または夜間に行われたかどうか示すようなやり方で、その人のデータを「マークする」こと。
第1の従来の方法では、食事、就寝時間、または夜中のイベントのタイミングを変更する可能性がある日常生活における変動を、固定された時間で考慮することができない点で問題が生じる。その結果、食後の期間に由来するデータが、食前に発生したものとして誤って表され、逆も同様である。従来の第2の方法では、後で解析するために、またはその分類に従って遡って各値を「マークする」ために、余計な努力をして各イベントを分類するための負担がその個人にかかる。個人があらゆるイベントをマークするために時間を費やすことも、その人があらゆるイベントを、そのイベントが発生した時点で忘れずにマークすることも可能性が低い。さらに、「マークする」ことを遡って実施する場合、記憶の精度が低下し、したがってイベント割振りの精度が低下する。
Claims (16)
- テストストリップの使用を監視する方法であって、
それぞれの患者について、1日当たりの推奨テストの数、および供給者および保険業者の一方を介して前記患者に割り振られたテストストリップの数のうちの少なくとも一方を含む、患者に関するテスト用データを、リポジトリ内に記憶することと、
測定されたグルコースレベルを含むテスト結果を、ユーザの介入なしに、血糖計から前記リポジトリに自動的に送信することと、
前記患者によって実際に使用されたテストストリップの数、および選択された期間内に使用されない、割り振られたテストストリップの数のうちの少なくとも一方を決定するために、前記患者のうちの少なくとも選択された1人について、前記リポジトリ内に記憶されている前記テスト用データと前記テスト結果を比較することと
を含むことを特徴とする方法。 - 前記患者によって実際に使用されたテストストリップの数が前記患者に割り振られたテストストリップの数の選択された比率である場合、テストストリップに関する処方を自動的に補充することをさらに含むことを特徴とする請求項1に記載の方法。
- 前記患者がいつテストストリップを使い果たすかの推定を生成すること、および、前記患者に割り振られた、選択された数のテストストリップが未使用のままであると決定されたとき、前記患者に、より以上のテストストリップを自動的に送ることをさらに含むことを特徴とする請求項1に記載の方法。
- 前記患者によって実際に使用されたテストストリップの数に基づいて、保険業者およびヘルスケア支払者のうちの少なくとも一方に、テストストリップに対して支払い請求することをさらに含むことを特徴とする請求項1に記載の方法。
- 1日当たりの前記患者の対応する数の推奨テストを実施する前記患者の遵守と、前記患者の対応するテスト結果に基づく選択されたグルコースレベルとに基づいて、選択されたテスト慣行のうちの少なくとも1つを有する前記患者のうちの選択された1人を識別するために、前記リポジトリ内の前記テスト用データおよび前記テスト結果を解析することと、
促進物、教育的情報、および奨励金のうちの少なくとも1つを前記患者のうちの前記選択された1人に送信することと
をさらに含むことを特徴とする請求項1に記載の方法。 - 前記送信することは、
前記患者の対応するテスト結果に基づいて、選択された健康プロファイルのうちの少なくとも1つを有する前記患者のうちの選択された1人を識別するために、前記リポジトリ内の前記テスト用データおよび前記テスト結果を解析することと、
新しい糖尿病管理製品にとっての潜在的な消費者として前記患者のうちの前記選択された1人に送信するために、広告をベンダに販売することと
をさらに含むことを特徴とする請求項5に記載の方法。 - 前記リポジトリは、前記血糖計に関するメータ較正データ記憶し、
前記血糖計が故障しているかどうか判定するために、前記テスト結果および前記メータ較正データを解析することと、
前記血糖計が故障していると決定されたとき警報を送信することと
をさらに含むことを特徴とする請求項5に記載の方法。 - 前記テスト用データは、テストストリップ製造者、テストストリップ有効期限、ロット番号、較正データ、製造者識別、および配布国または地域を含むロジスティクス情報のデータのうちの少なくとも1つをさらに含み、
前記テストストリップのいずれかに欠陥があるかどうか判定するために、および前記リポジトリに記憶された前記テスト結果前記テスト用データを解析することと、
前記テストストリップのいずれかに欠陥があると決定されたとき警報を送信することと
をさらに含むことを特徴とする請求項5に記載の方法。 - 診断データを使用する方法であって、
治療データと、様々な治療イベントがいつ患者に施されたかに関する、対応するタイムスタンプとを受信することと、
診断テストデータと、診断テストがいつ前記患者に施されたかに関する、対応するタイムスタンプとを受信することと、
前記患者がいつ食事をするか、いつ眠るか、夜間テストがいつ前記患者に施されるかのうちの少なくとも2つに関するそれぞれのタイムスタンプを含むパラメータを受信することと、
ある治療イベントを、患者に施されたテストと、かつ食事時間、就寝時間、および夜間テストのうちの少なくとも1つと関連付けるために、前記治療データタイムスタンプと、前記診断テストデータタイムスタンプと、前記患者がいつ食事をするか、いつ眠るか、夜間テストがいつ患者に施されるかのうちの少なくとも2つに関するそれぞれのタイムスタンプとを解析することと
を含むことを特徴とする方法。 - 前記解析することは、
そのタイムスタンプがその日の1回目の食事の前である場合、治療イベントをその日の前記1回目の食事に関連付けることと、
そのタイムスタンプがその日の前記1回目の食事の後、かつ2回目の食事の前である場合、前記治療イベントをその日の前記2回目の食事に関連付けることと、
そのタイムスタンプがその日の前記2回目の食事の後、かつ3回目の食事の前である場合、前記治療イベントをその日の前記3回目の食事に関連付けることと、
そのタイムスタンプがその日の前記3回目の食事の後、かつ就寝時間の前である場合、前記治療イベントを就寝時間に関連付けることと
を含む、前記治療イベントに対応する前記タイムスタンプを割り振ることを含むことを特徴とする請求項9に記載の方法。 - 治療データと、様々な治療イベントがいつ患者に施されたかに関する、対応するタイムスタンプとを受信することと、
診断テストデータと、診断テストがいつ前記患者に施されたかに関する、対応するタイムスタンプとを受信することと、
1日当たり食される食事の典型的な数に対応するパラメータを受信することと、
1日を複数の食事時間に分割し、前記治療データタイムスタンプを食事時間に対して分類するように、前記治療データタイムスタンプおよび前記診断テストデータタイムスタンプが1日当たり食される食事の前記数に比べてどのようにクラスタ化するか判定するために、前記治療データタイムスタンプと、前記診断テストデータタイムスタンプと、1日当たり食される食事の前記数とを解析することと
を含むことを特徴とする方法。 - 前記解析することは、1日を複数の食事時間に分割するように、前記治療データタイムスタンプおよび前記診断テストデータタイムスタンプが1日当たり食される食事の前記数に比べてどのようにクラスタ化するか判定するために、平均時間と、前記平均時間の周りでの信頼区間および変動のうちの少なくとも一方の選択された尺度とを決定することを使用することを特徴とする請求項11に記載の方法。
- 前記解析することは、
選択された数の、治療イベント前A分以下である前記診断テストに対応する前記タイムスタンプを「食前」として分類することと、
選択された数の、前記治療イベント後B分以上、かつ選択された数の、前記治療イベント後C分以下である前記診断テストに対応する前記タイムスタンプを「食後」として分類することと、
選択された数の、前記治療イベント前D分以下、かつ前の治療イベント後C分以上である前記診断テストに対応する前記タイムスタンプを「食前」として分類することを含み、
A、B、C、Dが整数であり、A<B<CかつA<D<Bである、1組のタイミング閾値を適用することと
を含むことを特徴とする請求項9または請求項11に記載の方法。 - 前記タイムスタンプもまたデータを含み、
食前または食後としての前記治療イベントの前記分類の精度に関して、フィードバックデータを患者から受信することと、
前記データと、前記治療データおよび前記診断テストデータに対応するタイムスタンプとを解析し、連続する解析時に前記フィードバックを使用し、食前または食後としての前記治療イベントの前記分類を改善する反復学習アルゴリズムを使用することと
をさらに含むことを特徴とする請求項9または請求項11に記載の方法。 - 前記治療イベントは、インスリン注入であり、前記診断テストは、血糖テストであることを特徴とする請求項9または請求項11に記載の方法。
- 前記解析することが、血糖計、および血糖計と2方向通信するリポジトリのうちの一方内のプログラム型処理デバイスを介して実施されることを特徴とする請求項9または請求項11に記載の方法。
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WO2007112034A2 (en) | 2007-10-04 |
EP2529784B1 (en) | 2019-05-01 |
US20210290058A1 (en) | 2021-09-23 |
EP2529783A1 (en) | 2012-12-05 |
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