Introduction

“The data I am looking for is buried somewhere in the clinical narrative”

“There is no ICD-10 code for that!”

“I am wondering if there are other children injured or affected by this product…”

“How many of my patients live in a shelter?”

When data is imbedded in a clinical narrative, most clinicians and researchers will shy away from trying to retrieve the information of interest. We can change that.

DR^T (Document Review Tools) – is a product of collaboration between a clinician researcher and a computer science system architect. Its goal is to bring natural language processing [NLP] exposure and solutions to clinicians, researchers and quality improvement personnel who need to retrieve data imbedded in a clinical narrative.

DR^T will assist the user in sifting through lists of documents (Electronic health records, clinic notes, radiology reports) and present those documents containing the query of interest.

Similar to search engines (google, Bing) that sift through millions of webpages to present those pages that may meet your search criteria, DR^T will sift through your documents and present documents of interest for your review.

But wait, there’s more; DR^T will take your valuable input and retrain itself to find more documents with better accuracy and review the data presented to you.

DR^T has been used extensively by clinicians and quality improvement personnel at Children’s Hospital. Its impact on clinical research ranges from abstract presentations and clinical manuscripts, to national guidelines changes on clinical practice – all based on data retrieved from clinical narrative.