Session ID: 
182

Challenges of Capturing Clinically Accurate eCQM Data

2:30pm - 3:30pm Wednesday, March 11
Orlando - Orange County Convention Center
W304E

Description

The electronic Clinical Quality Measures (eCQM) were created as part of Meaningful Use; at the time, they held the promise of automatically extracting the discrete data elements required to capture a clinical quality measure, without human intervention. The intent of the initial set of eCQMs were based on capturing processes of care provided to patients to determine if a patient received quality care based on evidence based practices. But 10 years after eCQMs were first proposed, EHR vendors and healthcare providers still struggle with extracting the existing eCQMs in an accurate way that reflects the quality of care. Throughout the years of trial and error, many lessons have been learned. This presentation examines these challenges and how they can be avoided in future eCQM development. Participants will benefit from learning why the discrete data that resides in a clinical data warehouse, might not reflect what is actually happening at the point of care when it is provided to a patient.

Learning Objectives

  • Define what an electronic Clinical Quality Measure (eCQM) is and how it applies to clinical care
  • Recognize at least on challenge of capturing clinically accurate data with an eCQM
  • Describe at least one method of overcoming the risk of capturing clinically inaccurate eCQM data elements

Speaker(s)

Enterprise Director of Clinical Quality Informatics, Regulatory Performance,
Memorial Hermann Health System

Continuing Education Credits

ABPM
1.00
CAHIMS
1.00
CME
1.00
CNE
1.00
CPHIMS
1.00

Audience

Clinical Informaticists
Data Scientist
Quality Professional

Level

Intermediate