Optimization of Ambulatory Documentation in the Electronic Health Record

Since integration of a major Electronic Health Record (EHR) system in 2012, Parkview Health providers across specialties have been experiencing increased workload and frustration in completing office visit documentation with significant addition of work beyond office hours. The new system approach of presented conflict with established practice while no clear direction of best practices exists to date. A combination of data analysis and field study was conducted to identify and test best practices for visit documentation.

Team

Ryan Ahmed, Romisa R. Ghahari (Parkview Research Center)

Objective

• Identify unique best practices by the most efficient users

• Validate effectiveness of targeted training through a small-scale trial

Process

Analytics

The quality improvement initiative was planned to utilize a data-driven approach to identify, from a pool of 155 primary care providers, 16 most efficient users (“Cheese finders”, reference from the book Who Moved My Cheese by Spencer Johnson, MD) and 53 with most opportunity to improve through system use analytics.

Field Study

In-situ observations were used to study the work process of 8 Cheese Finders and 8 providers with most opportunity during office visits and identify differentiating practices of Cheese Finders adopted for visit documentation.

Training

Training materials were developed using best practices learned from the Cheese Finders. A small sample of 4 users with most opportunity was trained by Operations team as a pilot to collect efficiency data over a period of one month.

Comparative Data Analysis

Post pilot analysis was completed to compare the performance of pilot participants before and after the training and also against the Cheese Finders.

Outcome

Data analysis and participant feedback collected through surveys indicated success of the study and identified best practices for EHR visit documentation were reported to Operations team to be included in provider training.

Publications

• Presented at 2017 EPIC User Group Meeting, Verona, WI.