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EHR support system by R language
1.
R言語を用いた EHR (Electronic Health
Record) support system 2015.11.14 SappoRo.R#5 Masahiko Hida
2.
内科系の外来診察室には、かなりの確率で 電卓がおいてあります。 電子カルテの時代に何故?
3.
BMI:体重(kg)/身長(m)^2 標準体重:身長(m)^2 ×22 電卓でできる程度の計算が 組み込まれていない電子カルテが多い。
4.
インスリン分泌指数: (負荷後30分インスリン-空腹時インスリン)/(負荷後30分血糖-空腹時血糖) HOMA-R:空腹時インスリン×空腹時血糖÷405 FIB4 index:年齢×AST[IU/L]÷(血小板数[10^9/L]×ALT[IU/L]^0.5) NFS (NAFLD
fibrosis score)= -1.675+0.037×age+0.094×BMI+1.13×IFG/DM(yes=1,no=0) +0.99×AST/ALT-0.013×Plt-0.66×Alb このあたりまでは、何とか電卓でも ここまでくると、自分で入力した電卓の値が 信用できません。
5.
診療には必要ですが、煩雑な作業を で楽にしたい!
6.
どんな機能が、 診療の助けとなるのか?
7.
EHRの追加機能(案) ○自動計算機能 BMI、標準体重、必要栄養量、eGFR、eGFRcys、Ccr HOMA-R、インスリン分泌指数 FIB4index、NFS(NAFLD fibrosis score)
等。 ○簡便な血液検査の時系列出力、グラフ出力 ○サマリー機能 病歴サマリー等、患者情報の概要を簡潔に表示 現在の合併症の状態 患者の検査歴(検査項目、検査日) 疾患ごとに必要な情報をまとめて表示
8.
○位置情報 患者住所、職場、通勤経路の位置情報と、流行している感染症地域の 重ねあわせ機能。 紹介先医療機関、連携医療機関のMAP表示、交通機関の表示機能 ○診断基準の判定 薬剤性肝障害の診断基準 AIH診断基準 ○スコアリングの自動化 肝障害度、Child-Pugh score、IOIBD、CHADS2スコア等 ○鑑別診断の補助 不明熱、貧血、腹痛、胸痛、呼吸困難、浮腫、 電解質異常の鑑別診断
9.
○文献検索機能 ○画像処理 過去のレントゲン画像と比較し、変化の大きい陰影を抽出 US画像から脂肪肝の程度を定量化
10.
データベースへのアクセス
11.
データベースのテーブル構造 DiagrammeR package
12.
1. 患者IDを指定して 患者マスターを読み込み 住所情報はgeocoding→Lon,Lat 2. 連携医療機関dfの読み込み geocoding→leafletでHpmap関数作成 3.
近隣バス停住所をrvestで スクレイピング,geocoding→leafletで busmap関数作成 4. 血圧(BP)、体重(BW)等のデータを BP、BWオブジェクトに入れ、ggplotで作図する BPplot,BWplot関数を作成 5. 血液データを検査名のオブジェクト に代入し、検査+plotという名の関数を 作成 6. eGFRを計算し、プロット関数eGFRplot を作成、回帰直線を当てはめ腎予後予測も 7. 処方データをtimelineパッケージで 作図する,drugplot関数を作成 7. RISmedパッケージでPubMed(医学文献 データベース)から検索するPubMed関数 を作成
13.
Blood Pressure(BP) BP;オブジェクトの確認 BPplot();グラフの作成
14.
病名オブジェクト byoumei;オブジェクトの確認
15.
薬剤経過表
16.
糖尿病合併症チャート
17.
eGFR eGFR;オブジェクトの確認 eGFR();グラフの作成
18.
FIB4index FIB4 FIB4index;オブジェクトの確認 FIB4plot();グラフの作成
19.
検査履歴のセット出力
20.
貧血診断
21.
addressオブジェクト address;オブジェクトの確認 → geocoding → leaflet
package インフルエンザ、ウイルス性胃腸炎の 感染流行地域のマップを重ねてみる?
22.
近隣交通機関 rvest packageで近隣のバス停情報をスクレイピング google APIでgeocodingしてleafletでplot
23.
連携医療機関情報 患者住所情報から、近い順番に 紹介先病院を選択?
24.
Pubmed検索 RISmed packageを利用した自作関数;Pubmed
25.
実際のEHR support system の動作を確認
26.
RstudioによるEHR support system https://www.youtube.com/watch?v=jqYmHzK5lsI
27.
まとめ Rの豊富なpackageを使用することにより、電子カルテに さまざまな拡張機能を持たせることが可能となりました。 Rstudioのコードスニペットを利用することにより、実際の 電子カルテより短時間で、データの確認、グラフ作成が 行えました。
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