Case Study

Washington University in St. Louis

Washington University in St. Louis

Washington University in St. Louis Transforms Program Accreditation Process with Data Rocket

Washington University in St. Louis is an undergraduate, graduate and research institution in St. Louis, Missouri, serving more than 15,000 students. The Washington University School of Medicine is one of the top 12 medical schools in the United States, offering 76 clinical specialties and subspecialties in 13 degree programs.

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Project Highlights
  • Streamlined accreditation review for 103 medical training programs.
  • Visual analytics with organization-wide views and program drilldowns allowed leadership team to focus on programs that needed direct intervention.
  • Talend data ingestion into Snowflake Data Cloud removed human error from data handling, saves hundreds of hours of work per review cycle.
Testimonial

Our goal is Excellence. We know we've got the best foundational programs and the highest quality, well-structured training programs. Data Rocket tells us where our strengths and our weaknesses are, so we know how to bring people together to get the resources we need to be better than Good. Data Rocket gives us the data we need to say, here's how we know that we're Excellent.

Tia Drake, Executive Director of Graduate Medical Education at Washington University

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Project Details

Challenges

As the Executive Director of Graduate Medical Education at Washington University, Tia Drake is responsible for tracking the success of more than 100 ACGME accredited medical training programs and roughly 70 nonaccredited programs. The process is data intensive – using results from ACGME resident/fellow and faculty surveys alongside citations, outcome of certification exams, and institutional data from distinct hospitals and program resources.

Several years ago, Tia knew it was time to digitally transform her department’s annual review of training programs into a process that allowed for a high level summary of all sponsored programs. As it stood, the data collection for the review process was performed manually, and was both time and resource intensive. For each of the more than 170 programs being reviewed, Tia had to track down data from separate data sources and compile it into spreadsheets for review by the University’s accreditation council. From start to finish, it would take up to three weeks to assemble the necessary data, followed by a working session that identified areas for improvement. Moreover, without a clear overview of program standing, each program was given the same review treatment.

Solutions

To transform the review process, Tia knew she wanted a Tableau dashboard that would give her institutional leadership a clear picture of oversight for Graduate Medical Education programming – organizationally, and granularly.

“We need a 10,000-foot view of all of these training programs very quickly, and to be able to look at not just one training program, but the whole institution, and then department, and then compare departments by departments,” Tia said. “Those are all great measures, and something we’ve never been able to do.”

Tia was drawn to the end-to-end capabilities of the Data Rocket acceleration architecture. With Data Rocket, Talend ingests data from across the organization into the Snowflake Data Cloud. Once in the Data Cloud, integrated data is available through Tableau to users throughout the organization.

Data Rocket has dramatically increased the productivity of program reviews. With Tableau dashboards, programs are visually represented in green, yellow and red – yellow and red designations signal potential problems that may require closer scrutiny or institutional support prior to interventions by the accrediting body. In medical terms, Tia compared the new approach to operating with a scalpel instead of a sledgehammer.

“I’d rather spend more time on a small number of programs that need help,” Tia said. “Instead of spending time on all 170 plus programs, we can immediately drill down into the opportunities for improvements. We can spend our time identifying problems, assigning resources and making sure our faculty have the support they need. In order to mentor an underperforming program, you have to know who they are first.”

With Data Rocket, Tia and the institutional leadership team at Washington University will eventually be able to compare year over year data results, identifying opportunities for improvement and building on successes.

“As we get into that five-year range, even the three year range, to be able to lay data over data for the three years and see trends, it’s going to make a big difference in our strategic decision-making,” Tia said.

With the ability to track long-term program success, Data Rocket will help Washington University focus on its ultimate goal – training the best physicians, researchers, educators and public health professionals.

“We know we’ve got the best foundational programs and the highest quality, well-structured training programs,” Tia said. “This data tells us where our strengths and our weaknesses are, so we know how to bring people together to get the resources we need to be better than good. We want to be excellent. Data Rocket gives us the data we need to say, here’s how we know that we’re Excellent.”

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