Optimizing the Discharge Process for Neurosurgical Patients: A Quality Improvement Project

Introduction: Discharge delays increase infection risk, reduce bed availability, and decrease satisfaction. This study’s objective was to use a quality improvement (QI) framework to increase the neurosurgery discharge by noon rates by 25%.

Methods: A team included representatives from major stakeholder groups, including neurosurgery leadership, surgeons, residents, nurse practitioners/physician assistants (NP/PA), nurses, therapists, and pharmacists, with a QI coach. The project was conducted at the Mayo Clinic, St. Mary’s Hospital, from May 2020-Aug 2022. The project followed Standards for QI Reporting Excellence guidelines, Define-Measure-Analyze-Improve-Control framework, and Awareness-Desire-Knowledge-Ability-Reinforcement paradigm. This initiative did not require institutional review board approval. The process was defined using a gap analysis, a detailed process map, and the Suppliers-Inputs-Processes-Outputs-Customers+Requirements tool, and analyzed with an Ishikawa diagram. Under the baseline system, residents managed patients during the day while they were scrubbed in for surgery. Plan-design-study-act (PDSA) cycles were used to develop a new system where two neurosurgery NP/PAs were assigned to manage neurosurgery patients during weekdays. In the control phase, the team discussed lessons learned. Awareness was established during focus groups, desire was developed during a stakeholder meeting, and knowledge and ability were generated during PDSA cycles.

Results: At baseline, 43.5% of patients were discharged by noon. During the project, a novel day call system was designed, implemented, and iteratively improved. However, pilot data returned a similar discharge by noon rate (43.6%).

Conclusion : Although discharge by noon rates remained stable, the new process allowed greater ability to focus on patient care, which likely enhanced patient safety. The team recommends including a representative from all stakeholder groups on the team, including QI and clinical experts as advisors, using change management strategies, and proceeding through the QI phases sequentially and efficiently.