Background: Implementing technology with the goal of eliminating preventable hospital-acquired conditions (e.g., CAUTI, CLABSI, etc.) in the acute care setting is an ongoing challenge, but it is crucial to creating a safer healthcare system. Increasingly, organizations are collaborating with systems engineering, human factors, and data analytic experts to ensure successful design, development, and implementation of technologies that promise to create systems of care that reliably prevent harm. As part of our AHRQ-funded Patient Safety Learning Laboratory (PSLL), a collaboration between Brigham and Women’s Hospital and the Healthcare Systems Engineering Institute at Northeastern University, we have assembled an interdisciplinary team with diversified expertise to plan, design, and develop novel technologies (bedside display, provider safety dashboard, patient portal) that facilitate real-time identification of safety threats using data from our electronic health record (EHR). Our conceptual integration framework (Figure 1) ensures that individual tools, iteratively refined as part of a continuous safety improvement process, function together as a “System-of-Systems” to activate patients, clinicians, and stakeholders in identifying, assessing, and mitigating threats to safety in real-time.
Purpose: We report activities and preliminary observations based on our experience employing interdisciplinary methods during the implementation and evaluation phases of our PSLL.
Description: During design and development, we found a high degree of support for a real-time visualization strategy in which data inputted into the EHR by various types of clinicians are displayed for patients and clinicians in a user-friendly manner. This strategy was well-aligned with our institutional goal of reducing preventable harms due to hospital-acquired conditions while simultaneously mitigating effects of increasing cognitive burden on clinicians after implementation of a new EHR (Epic, Inc.). Currently, our methods include: 1) providing clinical-unit leaders weekly usage and quarterly process measure reports to demonstrate how use of tools directly impacts safety process measures (e.g., nurse-driven Foley catheter protocol ordering); 2) conducting usability assessments using the NASA Task Load Index (TLX) instrument to assess cognitive load for specific high-complexity tasks (e.g., assessing risk of opioid-related harm) that have public health implications; 3) conducting Failure Modes Effects Analyses and Root Cause Analyses in collaboration with safety leadership to prioritize potential failures of each tool and understand how they could be improved upon to reliably dissipate threats to safety, respectively; 4) using a Monte Carlo model to simulate how the system could perform under various conditions; and 5) conducting unit-based risk analyses to understand how the system actually performs under various “risky” states (e.g., high patient-turnover). See Table 1 for key findings.
Conclusions: Our activities have been well received by clinicians, clinical leadership, and safety and quality administrators. Our experience underscores the interdisciplinary effort required to facilitate organizational buy-in, adoption, and sustainability of new technologies aimed at improving patient safety in complex settings. Our planned evaluation will advance knowledge regarding impact on intermediate process measures, outcomes (adverse events), and patient activation and satisfaction.