Engineering High-Reliability Learning Lab (EHRLL)
We endeavor to establish an Engineering High Reliability Learning Lab (EHRLL) within a well-established and highly functioning learning collaborative of Harvard-affiliated primary care practices to enhance capacity for innovation and to develop highly reliable systems that address communication and coordination challenges at the intersection of primary care and specialty practices that pose patient safety risks.
Our major goals remain as described in our specific aims:
Aim 1: To build a reengineering and shared learning infrastructure that comprises an Administrative/Learning Core, an Engineering Core, and a multidisciplinary team comprised of investigators, engineers with expertise in healthcare challenges, and “Disrupters,” a cadre of innovators and experts from disciplines and industries outside of healthcare; and that stimulates a systematic approach for identifying, designing, developing, spreading, and evaluating patient safety innovations.
Aim 2: To engage in research projects that will apply systems engineering and operations management theory and methods to the development of innovative, cross-disciplinary team-based solutions for improving HIT-supported processes for high-risk patients, referrals, and tests and designing highly reliable systems that are generalizable. Currently, project teams are working to engineer a close the loop system for external primary to specialty referrals at Atrius Health (Project 1), coordination system for children with medical complexity undergoing surgery within Boston Children’s Hospital (Project 2), and reliably safe opioid medication management processes for adults with complex care needs (Project 3) at the Phyllis Jen Center for Primary Care within Brigham and Women’s Hospital.
Aim 3: To implement and spread redesigned systems across a range of hospital/community-based primary care practices; and to test systems’ generalizability in alternative settings and with other medical conditions.
Aim 4: To assess the impact of redesigned systems on practice, team, provider, and patient outcomes and disseminate findings as well as tools and resources to support national replication, as appropriate.
Sara Singer, PhD
James Benneyan, PhD
Russell Phillips, MD
Each project has an R&D team that is currently working on a project with one common and one unique system engineering tool. The teams have all identified reliability metrics, suggested data sources, and have begun tracking the data. The teams also meet in a cross project seminar every few months for a half day Learning Session. These sessions make sure the aims of each partner meet standard consistent requirements, and that they are SMART: specific, measurable, achievable, relevant, and time bound. At this point all of the results of each project are preliminary, and we will update as the results are finalized and published.