Clinical Data Reconciliation as Part of a Report Generation Solution

Abstract

An automated system updates electronic medical records (EMRs) based on dictated reports, without requiring manual data entry into on-screen forms. A dictated report is transcribed by an automatic speech recognizer, and facts are extracted from the report and stored in encoded form. Information from a patient's report is also stored in encoded form. The resulting encoded information from the report and EMR are reconciled with each other, and changes to be made to the EMR are identified based on the reconciliation. The identified changes are made to the EMR automatically, without requiring manual data entry into the EMR.

Description

BACKGROUNDAn Electronic Medical Record (EMR) is a database record or other data structure that is used by hospitals and other health care facilities to store current information about patients. Ideally, all information about the patient is stored within the patient's EMR, thereby eliminating the need for traditional paper files.Within an EMR system used by a particular health care facility, each patient has his or her own EMR for storing both current and historical information about the patient. Some of the data stored within a particular EMR may be divided into discrete fields, such as a “First Name” field, a “Last Name” field, a “Date of Birth” field, “Medications,”“Allergens,” and so on. To store information in an EMR, the EMR system typically displays an on-screen form in which the name of each field is displayed adjacent to a blank space. A healthcare worker types the appropriate information into the blank space associated with each field. Although other user interface elements...

AI Technical Summary

Problems solved by technology

This process can be tedious, time-consuming, and error prone.

More problematic is the process of keeping EMRs up to date as the information associated with the corresponding patient changes.

There are, however, many barriers to updating EMRs.

This is a tedious, time-consuming, and error-prone way of updating the discrete data elements in the patient's EMR.

In fact, the barriers raised by this method of updating discrete data elements in the patient's EMR often leads to such updates not being made at all.

As a result, the patient's EMR may become increasingly out-of-date, and therefore increasingly inaccurate, over time.

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