User Experience Data

KLAS Research

KLAS Research

Improving EHR Satisfaction in Ambulatory Settings

Across Clinical Roles, Optimization Sprints Dramatically Improve EHR Satisfaction. See more findings in the full report.


Optimization Sprints Show Early Promise

Reporting significant benefits, including increased EHR satisfaction and more effective teamwork, four Arch Collaborative organizations have implemented EHR optimization sprints† in their ambulatory clinics. Based on pre- and post-intervention surveys from over 400 clinicians that participated in these sprints, this report seeks to (1) evaluate the effectiveness of the sprint methodology by examining changes in participants’ overall EHR satisfaction, degree of burnout, and satisfaction with ongoing training and (2) share overarching principles and best practices for successfully implementing your own optimization sprint.

Visit KLAS website for more details

Across Clinical Roles, Optimization Sprints Dramatically Improve EHR Satisfaction

On average, providers, nurses, and allied health professionals all saw large increases in their Net EHR Experience Score (NEES)‡ following an optimization sprint, and each group also reported improved satisfaction with how their organization has implemented, supported, and trained on the EHR. As IT and operational departments invest in reaching out to their clinics, they can dramatically change how clinicians view the EHR.


Pre and post sprint burnout and satisfaction with ongoing training

On average, the percentage of providers reporting at least some degree of burnout dropped by nine percentage points following an optimization sprint. Several factors likely contribute to this reduction in burnout. However, of particular note is that pre-intervention, less than half of participating providers viewed their HER as a tool that enables efficiency; post-intervention, that number rose to almost two-thirds, with several organizations reporting a dramatic reduction in afterhours charting. Provider perceptions of the efficacy of their ongoing HER training also saw a significant boost. Other Collaborative data has shown that providers who don’t agree that their ongoing training is sufficient are 3.0–4.5 times more likely to report plans to leave their organization within two years.


Framework for Implementing a Successful HER Optimization Sprint

While the Arch Collaborative organizations that have completed an optimization sprint offered a variety of helpful advice for their peers, the following two overarching guidelines were mentioned by all four organizations:

Leadership matters—The individuals chosen to lead the sprint and the specific clinics chosen for the pilot will make or break the project. Look for leaders who are excited to champion operational improvements and increased clinician engagement.

Utilize a pilot and then grow organically as you achieve success—For the organizations in this report, optimization sprints have become a key element of their efforts to support the HER. However, this broad investment was only made after pilot programs demonstrated that sprints were an effective way to improve satisfaction with the HER.

Steps of a Successful Sprint

Step 1: Build your sprint team

Team members should be highly competent in either training clinicians or understanding EHR workflows. These individuals should also be generous in how they work with others, as they will likely be working with many clinicians who have very negative perceptions of the IT team and the EHR.

Step 2: Choose your pilot clinic

Start with a clinic that has a pressing need to improve the EHR and whose leadership is already bought into the idea of a sprint.

Step 3: Prepare for the sprint

The preparation phase typically includes a kickoff meeting followed by several additional meetings to identify the build scope and establish relationships between the sprint team and the clinic. These preparations are key to being able to hit the ground running once the sprint team is on-site at the clinic.

Step 4: Collect a pre-sprint measurement

Several organizations have utilized their EHR’s native tracking of metrics like afterhours charting and chart-closure rates to set a pre-sprint benchmark. Additionally, three of the four Collaborative members in this research established a benchmark utilizing the Collaborative’s pre/post surveys, which are included in all Collaborative memberships (alternatively, a recently completed full Collaborative measurement can be used as the pre-sprint benchmark).

Step 5: Complete the sprint

Sprints generally have three components: clinician training, workflow redesign, and the creation of specialty-specific tools. The training is typically done one on one and focuses on helping clinicians become proficient with new and pre-existing functionality and tools as well as any newly developed workflows. For specific details on how to implement a sprint, please see this comprehensive article in the Mayo Clinic Proceedings.

Step 6: Collect a post-sprint measurement

Once the sprint is complete, use the same survey instrument leveraged for the pre-sprint measurement to capture any changes in clinician satisfaction.

Step 7: Adjust and iterate

Using feedback from clinician surveys and interviews with clinic leadership to identify any needed adjustments, select the next clinic to participate in the sprint.

† As championed by Dr. CT Lin, CMIO at UCHealth, EHR optimization sprints aim to quickly optimize EHR efficiency through a three-pronged, team-based approach that includes (1) clinician training, (2) workflow redesign, and (3) the creation of specialty-specific tools. Dr. Lin—a longtime friend of the Collaborative and an early advisor to its members—graciously shared details of his EHR 2.0 optimization sprints at the Eastern US Arch Collaborative Workshop, held in January 2020. Additional details about UCHealth’s sprints can be found in this article by Mayo Clinic.

‡ Each individual clinician’s responses to the Arch Collaborative EHR Experience Survey regarding core factors such as the EHR’s efficiency, functionality, impact on care, and so on are aggregated into an overall Net EHR Experience Score (NEES), which represents a snapshot of the clinician’s overall satisfaction with the HER environment at their organization. The NEES is calculated by subtracting the percent of negative user feedback from the percent of positive user feedback. An NEES can range from -100 (all negative feedback) to 100 (all positive feedback).

More for you

Loading data for hdm_tax_topic #clinician-experience...