Learn how the University of Virginia Health System (UVA Health) created a training model to enhance ease of use and user satisfaction with their electronic health record system (EHR).
Under the direction of the Health Information Technology team, UVA Health conducted a KLAS Arch Collaborative survey designed to assess clinician satisfaction with the EHR.1 The results confirmed considerable opportunities to improve EHR user satisfaction with the UVA Health Epic system. Additionally, Provider Efficiency Profile (PEP, the precursor to the current Signal repository) data on system usage confirmed there was opportunity to improve the user experience, namely via personalized coaching.
Kate Bakich, the leader responsible for directing training programs in Health Information Technology at UVA Health, developed and championed a new training program centered on personalized coaching.
This training model was adapted from concepts detailed in the previously published Home4Dinner model implemented at Lucile Packard Children's Hospital Stanford, and tailored to meet UVA's particular challenges.2 This program at UVA Health is called SmartChart, and it is an ongoing initiative.3
The SmartChart team made 3 changes to expand the program that Stanford created:
They worked with analytics experts to build a repository of EMR usage data. The SmartChart team recognized the value of PEP data despite its inherent limitations, so the repository offered 2 advantages over the current Epic data: 1) it could be trended over time, and 2) it could blend data from other Epic sources to show other training indicators such as in-basket messages not read, number of appointments per review period, and open encounters. This richer data set allowed for easier identification of clinicians to target for coaching and enhanced outcome tracking. Examples of de-identified PEP data are shown in Figure 1.
They leveraged specialty-specific expertise. The SmartChart team identified and shadowed an expert Epic provider already working in a particular specialty. This shadowing exercise allowed trainers to familiarize themselves with the specialty's context of care, identify care concerns unique to that specialty, and benefit from any EHR efficiency tips that the expert Epic provider had already discovered. For example, in Ambulatory Internal Medicine, customizing favorites and preferences, making smart text, and finding other's dot phrases were important customizable features.
They escalated comments on both EHR-related tools or skills and issues affecting clinical care to clinical and IT leadership. Themes included team support (eg, nursing, medical assistant, pharmacy), practice organization, patient care flow, documentation demands, administrative tasks, and the balance of time needed versus time allotted to complete these tasks. Following this process, it became clear that both computer-based skills and clinical context of care played roles in satisfaction, stress, and burnout at UVA Health for clinicians and health care teams.
Specific components of the SmartChart training and performance improvement program at UVA Health are listed below, along with the time designated for each task (Table 1).
Table 1. Time to Complete SmartChart Tasks
| SmartChart Task | Clinician Time to Complete | Trainer Time to Complete |
|---|
| Completion of self-assessment survey | 5 minutes | -- |
| Observation of clinician during EHR use | -- | 2 hours |
| Review of self-assessment, observations, and Epic usage data | -- | 2-4 hours |
| Preparation of individualized learning plan | -- | 1-3 hours |
| Review of individualized learning plan | 1-2 hours | 1-2 hours |
| | |
| Total time out of clinical care | 1-2 hours | -- |
| Total time investment per clinician | -- | 6-11 hours |
The review process is of critical importance to the success of this program. As such, review represented a substantial time investment to ensure that the trainer could effectively tailor the learning plan to the clinician's unique practice patterns, the demands of their specialty, the workflows of their care team, and their unique preferences for providing exceptional patient care.
Physician burnout is a real concern. Engagement in SmartChart could be viewed as creating benefits and/or burdens. In order to blend SmartChart with the need for CME and MOC, physicians were offered an opportunity to use this performance improvement experience as part of their ongoing continuing professional development. The Office of Continuing Medical Education (CME) collaborated with the SmartChart team to provide AMA PRA Category 1 credit™ as well as Maintenance of Certification (MOC) Part II (self-assessment) and MOC Part IV (performance improvement) points for SmartChart training. Kathleen Bunch Meneses, the project manager from the UVA Office of Continuing Medical Education, helped with project management to ensure the program met accreditation standards and board requirements.
Lessons learned from these SmartChart sessions have empowered the project team to incorporate remedies into future program initiatives. For example, a program is underway now to standardize the use of intra-EHR communication tools, a problem that was a common refrain in individual coaching sessions.
The KLAS data that initially helped uncover the problem was used again to perform an internal evaluation of EHR user satisfaction. Results were also compared to that from other sites to identify specific needs and collect more information.
As of May 2020, 679 clinicians have enrolled and 380 have completed the SmartChart program.
“What I found really helpful is having Justin observe what I was doing (much of it wrong or inefficient), then design some customized tips to improve my efficiency. I am serious when I say it has been life changing.”
—Physician SmartChart participant
Clinicians and trainers found this program relatively cost effective to implement. The resource commitments from the Health Information Technology team included 3 full-time equivalent (FTE) trainers, a 0.5 FTE scheduler, and a 0.5 FTE project manager for oversight.
The SmartChart team also relied on evaluating PEP data over time to identify clinicians who may benefit from additional coaching and support. Usage pattern reviews tracked more than 200 different metrics over time viewed as important to improving clinician effectiveness and communication. As reviews progressed, the team quickly realized that the data must be considered in context. For example, it was not safe to assume that “pajama time”—time spent after hours in the EHR—was a negative indicator for all clinicians. Some clinicians valued the flexibility of their work schedules and used pajama time as a positive opportunity to have uninterrupted after-school family time. Likewise, a clinician's low Epic proficiency score might suggest that they do not use the tools that Epic provides to improve EHR efficiency, but instead the clinician may be bypassing these features of Epic by using dictation tools.
“He has shown ways to help with ordering and with closing charts. Not only is the charting quicker but my quality of life is better, which will result in better patient care.”
—Physician SmartChart participant
Conducting in-person sessions with a trainer yielded several important benefits:
Provided clinicians “at the elbow” EHR support with real-time observations within a real clinical care context
Offered clinicians the opportunity to customize EHR tools on the spot
Emphasized common themes and tools at the practice level that were found by assigning the same trainer to observe multiple clinicians in the same clinical setting
Enabled documentation and verification of issues in clinical context, which could easily be shared with local clinical leadership; specific practice stressors could then be highlighted and addressed
Facilitated stronger organizational relationships and communication between clinicians and their IT counterparts to set the stage for better collaboration in the future
Trainers noted a number of common issues with EHR tools for which they could offer asynchronous support. Trainers also highlighted which EHR tools were used most often, and how their use contributed to clinician engagement with Epic. Common issues found during SmartChart sessions, in order of priority, included:
Speed buttons
Chart review customization
Order panels
Chart search
Navigator customization
Patient reminder lists
Widescreen cheat sheet
MModal speech recognition setup
MModal usage
In-Basket QuickActions
QuickNotes
Haiku setup
Haiku usage
The time commitment for clinicians to participate was reasonable and was rewarded with improved EHR efficiency. However, for those clinicians whose time in the EHR didn't change, 2 opportunities were evident: first, some clinicians used time saved to invest in better clinical review or preparation; and second, practice factors remain that contribute to EHR inefficiency.
By seeking accreditation for this project, UVA Health provided a streamlined way for physicians to simultaneously meet their continuing professional development requirements while performing their day-to-day patient care responsibilities. The program has also created an outlet for participants to provide feedback regarding the impact of the EHR on their clinical practice. The accreditation process for the program was collaborative and helped ensure that program requirements are met consistently, since they are also a requirement to receive credit. Through an integrated feedback mechanism, physicians were also able to document their engagement. Since continuing professional development is a requirement for licensure, board certification, and credentialing, SmartChart participants can derive additional value from their involvement, which translates to a higher level of engagement with the program. As of January 2020, 69 physicians had received CME and MOC credit for their participation.
When comparing SmartChart participants to non-participants, UVA Health found striking differences in 2 target focus areas: whether ongoing training is sufficient and whether the individual uses personalizations. Results from the KLAS EMR Experience survey showed that SmartChart participants ranked UVA Health in the 90th percentile for sufficiency of ongoing training and the 95th percentile when asked about use of personalizations. In contrast, non-participants ranked UVA Health in the 15th percentile in both categories.3
There are still a few ongoing challenges that include:
Finding time and venues for clinical leadership to review and act on the clinical care context observations
Outreach to those clinicians who haven't yet completed the program
Determining how to best continue using and sharing PEP data
Defining ways to follow up with physicians who completed the initial SmartChart program to ensure that they are taking advantage of lessons learned; UVA has offered most participants follow-up sessions, and have found that this is a tremendous satisfier since optimal use of the EHR is an ongoing journey
Linking EHR usage changes with surveys of satisfaction, well-being, stress, and burnout to assess for any changes in these measures
“I am so grateful for his investment in my Epic charting and I am sure that it will positively impact my well-being and the care for my patients."
—Physician SmartChart participant
In response to positive feedback and demonstrated improvements in EHR efficiency, the SmartChart program will continue in perpetuity for interested clinicians. In addition to offering SmartChart refresher training, a new onboarding program called Smart Start launched in April 2020. Applying lessons learned from the SmartChart program, Smart Start offers an individualized training program for each incoming clinician, which will involve custom-designed eLearning, one-on-one specialty training, and coaching during the first EHR use for clinical care.
UVA Health is an academic health care organization associated with the University of Virginia. UVA Health provides inpatient and outpatient care and patient education, and conducts medical research and education. UVA Health also operates satellite locations throughout Virginia. Departments are made up of primary and subspecialty care represented by 1211 clinical faculty, 518 advanced practice providers, and 776 GME trainees serving patients.
UVA SmartChart PI Project. University of Virginia School of Medicine. Accessed May 5, 2020. https://med.virginia.edu/cme/learning/pi/smartchart
SmartChart. KLAS The Arch Collaborative Learning Center. Published May 26, 2020. Accessed June 12, 2020. https://klasresearch.com/archcollaborative/casestudy/smartchart/328
SmartChart: Change Management. KLAS The Arch Collaborative Learning Center. Published May 26, 2020. Accessed June 12, 2020. https://klasresearch.com/archcollaborative/casestudy/smartchart/327