Reply to Zhao: Integrating Implementation Science in Quality Improvement for Patient Discharge Optimization

We sincerely thank Dr. Zhao for the insightful and constructive letter regarding our quality improvement project, “Reengineering Patient Discharge with Lean Methodology and RED Framework: A Model for Safer, Faster, Patient-Centered Transitions,” published in the Global Journal on Quality and Safety in Healthcare.[1,2] We appreciate the opportunity to further elaborate on our work from an implementation science perspective and to clarify aspects related to implementation strategies, fidelity, and generalizability.

Key strategies included early discharge preparation using the single-minute exchange of die (SMED) approach—reassignment and training of unit-based discharge coordinators, structured patient education, and phased introduction of the RED toolkit. These strategies were operationalized through clearly defined roles and responsibilities, standardized workflows, staff training sessions, daily and weekly multidisciplinary huddles, and continuous feedback mechanisms. Importantly, the intervention was implemented in a phased manner—beginning with pilot testing in a single inpatient unit, followed by refinement and hospital-wide spread—allowing for contextual adaptation in response to variable physician engagement, staffing constraints, and departmental workflows.

Although space limitations inherent to quality improvement reporting constrained the level of operational detail that could be included, we aimed to provide sufficient transparency regarding the core components, sequence, and adaptive nature of the implementation to support replication and contextual tailoring in similar healthcare settings.

IMPLEMENTATION FIDELITY

We agree that implementation fidelity is a critical determinant of intervention effectiveness. In our study, fidelity was monitored pragmatically through multiple complementary process measures selected to balance rigor with feasibility in a real-world clinical environment. These included physician compliance with preliminary discharge documentation, accuracy of documented discharge plans, proportion of patients discharged with an after-hospital care plan (AHCP), and timely postdischarge follow-up contacts.

These indicators were monitored continuously and reviewed during regular project meetings, enabling real-time feedback, targeted retraining, and iterative refinement of the intervention. Although we did not employ formal fidelity checklists or direct observational audits, such as item-level verification of patient education documentation, the combination of process monitoring, staff engagement, and repeated plan-do-check-act (PDCA) cycles promoted the consistent delivery of the intervention as intended. We acknowledge that future studies could enhance methodological depth by incorporating more granular fidelity assessment tools, such as structured audits or standardized teach-back verification, particularly in multicenter or implementation-focused research designs.

GENERALIZABILITY AND SCOPE

The primary aim of our project was to improve local systems within a single tertiary care hospital. As such, we acknowledge limitations related to generalizability, resource availability, and the targeted implementation of RED components in high-risk patient populations. These considerations were explicitly addressed in our discussion and limitations sections. Nonetheless, we believe that the underlying principles applied, Lean-based process redesign, early discharge planning, role clarification, patient-centered education, and structured postdischarge follow-up, are broadly transferable and can be adapted to diverse organizational contexts with appropriate contextual tailoring.

In summary, we are grateful for Dr. Zhao’s thoughtful perspective and for highlighting the importance of integrating implementation science concepts into quality improvement research. We view this exchange as an opportunity to strengthen the interpretation and applicability of our findings and to encourage continued dialogue between quality improvement and implementation science communities.