Data collection for annual status reports (ASRs) can be challenging for accredited and recognized diabetes self-management education and support (DSMES) services. Joycelyn Ashby Cornthwaite, MBA, MS, RD, LD, CDCES, is the DEAP quality coordinator in the Department of Obstetrics, Gynecology, and Reproductive Sciences at UTHealth Houston and manager for the UT Physicians-Women’s Center Diabetes Program. She and her team have successfully built an electronic health record (EHR) dashboard. She shares her experience, insights, and advice.
1. What led up to the decision to pursue a dashboard?With the growth of our program, the decision was made to move from purely manual data collection to working with IT to request reports. The project champions for the team were Chery Hughes, RD, LD, CDCES, and Gladys Ortiz, MS, RD, LD, CDCES. We initially focused on structuring clinical notes in EPIC to ensure that data were captured in a standardized format. However, we quickly realized that free-text documentation, although flexible for clinicians, could not be automated. This meant that data extraction for accreditation reports was still highly manual, requiring IT intervention and substantial time investment.
Once we realized that using free-text notes had limitations, we switched to using specific data fields instead, which allowed automation while preserving personalization options where needed. With structured data in place, we began requesting manual reports from IT, thinking this would be a sustainable approach. However, it became clear that each report had to be requested individually every year, making it an inefficient and reactive process.
At this stage, our EPIC Business Intelligence Technical Specialist proposed a dashboard as a more permanent, self-service solution.
2. Can you describe the dashboard that was created and the information it captures?The Diabetes Education Accreditation Dashboard, developed within EPIC, was designed to streamline DSMES accreditation reporting and reduce the burden of manual data collection. It is a report summary screen that provides real-time tracking of patient engagement, clinical outcomes, and accreditation compliance, allowing DSMES managers to monitor program performance, track A1C trends, and identify opportunities for quality improvement.
Unlike our previous manual reporting process, this dashboard enables DSMES managers to select date ranges, generate reports on demand, and monitor program trends in real time. The ability to access data instantly, rather than waiting for IT-generated annual reports, has transformed the way we manage and optimize DSMES programs.
3. How do you use the data that your dashboard provides?Initially, the dashboard was created to automate ASR reporting, but its impact has extended far beyond that. It now helps us monitor program performance, optimize staffing, and drive quality improvement initiatives.
With real-time access to population health data, we can proactively identify resource needs and tailor interventions accordingly. The ability to track patient engagement trends has improved resource allocation, allowing us to deploy staff more effectively or verify the need for additional staffing. Instead of just collecting data for accreditation, we now use it to enhance programming and improve patient outcomes.
4. Whose support did you need to pursue the creation of the dashboard?The project required collaboration from multiple internal teams:
a. EPIC business intelligence application specialist (liaison role): Acted as the bridge between DSMES staff and IT, ensuring clinical needs and DSMES workflow needs were effectively translated into technical requirements.
b. EPIC business intelligence technical specialist: Led data extraction, dashboard architecture, and automation processes to ensure real-time functionality.
c. DSMES program clinicians and manager: Defined accreditation and reporting requirements, ensuring compliance and usability.
d. Leadership and IT leadership: Provided resource allocation and institutional approval to support dashboard development.
5. What did the process of building the dashboard look like?It took a total of 9 months to build the dashboard. The process consisted of 2 phases and involved the EPIC business intelligence application specialist (liaison), the EPIC business intelligence technical specialist, and the DSMES manager/quality coordinator. To guide phases 1 and 2, the technical team utilized a business requirements document process. The purpose of this process was to understand the needs of the DSMES program and translate those needs to development. This process allowed for back and forth between the DSMES team and the technical team to refine requirements, answer questions, and gather feedback.
Phase 1 focused on curating the reports needed to capture all of the necessary clinical and DSMES reporting data. This phase spanned over 8 months and required monthly meetings with the team. Phase 2 focused on compiling each report from phase 1 into the dashboard so that the data would be in one place. This phase spanned the course of 4 weeks, and during this time, the team met weekly and did multiple rounds of testing to ensure that the correct information was being captured. There was also consistent email communication between team members throughout this time, which was critical in allowing the work to continue and be completed quickly.
Ultimately, we were able to develop an embedded dashboard in EPIC that provides real-time, on-demand reporting capabilities, which eliminated the need for manual report requests.
6. What were the biggest challenges you encountered?These challenges were not hindrances but moments of recognition that led to quick solutions due to the team’s complementary expertise and commitment to improvement:
• Recognizing that free-text data could not be automated: Once we realized free-text fields could not be systematically extracted, we transitioned to discrete data fields, requiring retraining staff and updating documentation templates.
• Ensuring that IT could extract the correct data fields: The application specialist played a key role in translating clinical needs into technical specifications that the technical specialist could implement.
7. Based on your experience building the dashboard, what were the key learnings?One of our biggest lessons was recognizing that the dashboard should have been a design goal from the start. Had we anticipated its impact, we would have structured our clinical notes around the data needs of the dashboard rather than retrofitting them later. Using discrete data fields early on is essential.
Another key takeaway was the importance of having a dedicated liaison role. The EPIC business intelligence application specialist ensured seamless communication between IT and DSMES teams, preventing misunderstandings and ensuring that both groups remained aligned.
Securing leadership buy-in took less time than expected. Because accreditation already consumed excessive time, leadership immediately saw the efficiency gains and supported the initiative.
Lastly, we learned that recognition is the first step to resolution. Because our team was curious and committed, once we identified a challenge, solutions were often found quickly.
8. What advice do you have for other quality coordinators that may want to pursue building their own dashboard?
• Start with the right data structure—free-text data is a barrier to automation. Use discrete data fields to ensure seamless reporting.
• Engage IT early and establish a liaison role to bridge the gap between clinical workflows and technical requirements. This will help prevent miscommunication and accelerate development.
• Rather than trying to build everything at once, take an iterative approach—start with key ASR outputs, test the system, and refine functionality based on feedback.
• Position the dashboard as more than just an accreditation tool. Leadership buy-in is much easier when framed as a solution that reduces workload, improves efficiency, and enhances care.
9. How can a DSMES program get started with replicating or adapting a dashboard?Engage IT early and identify a dedicated liaison—such as our business intelligence application specialist. Begin with manual reports before transitioning to a dashboard. Structure documentation with discrete fields from the start to enable automation and scalability.
I would like to acknowledge two early champions of this initiative: Cheryl Hughes, RD, LD, CDCES, and Gladys Ortiz, MS, RD, LD, CDCES, whose contributions played a key role in laying the foundation for this work.
If you would like to learn more about becoming an accredited DSMES program, contact deap@adces.org.
