Reducing Employee Injury Rates with a Hospital-wide Employee Safety Program.

Introduction: Despite the well-known dangers of working in the healthcare industry, healthcare organizations have historically accepted workplace injuries as business as usual. In 2017, Children's National Hospital began our Employee and Staff Safety program to drive down the employee injury rate and address this disturbing industry trend. Methods: With guidance and support from executive leadership, we created an Employee and Staff Safety program that aligned employee safety work with existing patient safety and quality improvement efforts. Team leads collected and analyzed baseline employee injury data and identified areas of highest injuries. Dedicated subcommittees focused on five specific areas: slips, trips, and falls; sharps injuries; blood and body fluid exposures; verbal and physical violence; and overexertion injuries. Subcommittees established aims, identified key drivers, and brainstormed interventions for tests of change. Results: Because the inception of the Employee and Staff Safety program, Children's National has seen significant reductions in our Days Away Restricted or Transfer (DART) rate. The DART rate shows a sustained 37% reduction since the baseline period of FY16-FY17 (1.48 injuries/200,000 h worked to 0.93 injuries/200,000 h worked). The regression trend shows a significant decrease (38.3%) in DART injuries, from 1.544 to 0.952 over 56 months; P = 0.016. Conclusions: Active leadership support and analyzing data on specific employee harm areas coupled with targeted interventions, helped improve Children's National's DART rate. The Employee and Staff Safety program's success in utilizing patient safety and quality improvement tools creates a generalizable framework for other hospitals to advance their high-reliability journey.

Apparent Cause Analysis: A Safety Tool.

Causal analysis is a core function of safety programs. Although established protocols exist for conducting root cause analysis for serious safety events, there is limited guidance for apparent cause analysis (ACA) in health care. At our institution, through a novel facilitated ACA approach, we aim to improve safety culture and provide a clear approach to address precursor safety events and near-miss safety events. We define facilitated ACA as limited investigation (scope and duration) of a safety event that resulted in little to no harm. These investigations require fewer resources and focus on preventive strategies. Our facilitated ACA model, with an operational algorithm and structured process, was developed and implemented at our tertiary-care, freestanding, urban pediatric hospital in 2018. Sixty-four ACAs were completed, and 83% were identified with the algorithm. Process measures, including time from event reporting to ACA launch (median 3 days; interquartile range 2-6 days), are tracked. Patient safety consultants averaged 5 hours to complete a facilitated ACA. A median of 3 disciplines or departments participated in each facilitated ACA. Through an iterative process, we implemented a structured process for facilitated ACA, and the model's strength includes (1) right event, (2) right team, (3) right analysis, and (4) right action plans. This novel facilitated ACA model may support organizational cause analysis and improve safety culture with higher-reliability processes.

10,000 Good Catches: Increasing Safety Event Reporting In A Pediatric Health Care System.

BACKGROUND: In 2014, Children's National Health System's executive leadership team challenged the organization to double the number of voluntary safety event reports submitted over a 3-year period; the intent was to increase reliability and promote our safety culture by hardwiring employee event reporting. METHODS: Following a Donabedian quality improvement framework of structure, process, and outcomes, a multidisciplinary team was formed and areas for improvement were identified. The multidisciplinary team focused on 3 major areas: the perceived ease of reporting (ie, how difficult is it to report an event?); the perceived safety of reporting (ie, will I get in trouble for reporting?); and the perceived impact of reporting (ie, does my report make a difference?) technology, making it safe to report, and how reporting makes a difference. The team developed a key driver diagram and implemented interventions designed to impact the key drivers and to increase reporting. RESULTS: Children's National increased the number of safety event reports from 4,668 in fiscal year 2014 to 10,971 safety event reports in fiscal year 2017. Median event report submission time was decreased by nearly 30%, anonymous reporting decreased by 69%, the number of submitting departments increased by 94%, and the number of reports submitted as "other" decreased from a baseline of 6% to 2%. CONCLUSIONS: Children's National Health System's focus on increasing safety event reporting resulted in increased organizational engagement and attention. This initiative served as a tangible step to improve organizational reliability and the culture of safety and is readily generalizable to other hospitals.

Improving Apparent Cause Analysis Reliability: A Quality Improvement Initiative.

INTRODUCTION: Apparent cause analysis (ACA) is a process in quality improvement used to examine events. A baseline assessment of completed ACAs at a tertiary care free-standing pediatric academic hospital revealed they were ineffective due to low-quality analysis, unreliable action plans, and poor spread, leading to error recurrence. The goal of this project was to increase ACA action plan reliability scores while maintaining or decreasing turnaround time. METHODS: The Model for Improvement served as the framework for this quality improvement initiative. We developed a key driver diagram, established measures, tested interventions using plan- do-study-act cycles, and implemented the effective interventions. To measure reliability, we created a high reliability toolkit that links each action item/intervention to a level of reliability and scored each ACA action plan to determine overall reliability score. Action plans scored as low level of reliability required revision before implementation. RESULTS: Average ACA action plan reliability scores increased from 86.4% to 96.1%. ACA turnaround time decreased from a baseline of 13 days to 8.6 days. Stakeholders reported a subjective increase in satisfaction with the revamped ACA process. CONCLUSIONS: Incorporating high reliability principles into ACA action plan development increased the effectiveness of ACA while decreasing turnaround time. The high reliability toolkit was instrumental in providing an organizational resource for approaching this subset of cause analyses. The toolkit provides a way for safety/quality leaders to connect with stakeholders to design highly reliable solutions that improve safety for patients, families, and staff.