Recommended new practices and a redesigned physical layout for the delivery of greater patient-centered care.

20% increase in patient capacity and $120K savings in annual labor costs

The Client

A Pediatric Oncology Department for an internationally acclaimed teaching hospital and medical treatment center

The Challenge

The Unit struggled when its mostly highly skilled and experienced nurses showed signs of burnout. Along with the requirement to answer the fluctuating needs of critically ill patients, the nursed faced uneven and unpredictable workloads.

Our Methods

With shared insights from the nurses and the application of engineering methods, Kairos Worldwide recommended new practices and a redesigned physical layout for the delivery of greater patient-centered care. Process improvement recommendations included changing bedside practices and better focusing on the patient by adding equipment, managing supplies inventory and optimizing the nursing schedule.

The Impact

Kairos Worldwide recommended:

  • Reengineered nursing workflows for the pediatric oncology unit, to drive labor saving opportunities:
    • Savings of more than $120,000 in annual labor costs
    • Increases in patient capacity of the unit by 20%
    • A recommended tracking system to monitor department labor overtime and other key metrics to sustain results
  • New practices and tools for patient-focused processes in compliance with hospital standards:
    • Nursing practices to increase nurse time in unit, enhance bedside care and improve the patient experience
    • Collaborative meetings to address nursing scheduling challenges immediately, with solutions promoting continuous improvement
  • Instituting the use of unit scorecards monitoring performance in specific areas, including Daily Overtime, Room Turnover and Time Spent Out of Unit
  • Nurse collaborative meetings to design training programs for the adoption of new methods and practices, allowing nurses to share their insights and support the effort to effectively address the challenges of uneven patient load and optimized scheduling
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