From Referral to Arrival: Mapping the Ideal Patient Transfer Journey

By Jennifer Davis, Executive Administrative Assistant @ highMor | July 2025

In the intricate world of healthcare, patient transfers between facilities are more than just logistics—they’re lifelines that can make or break outcomes. Whether it’s moving a critically ill patient from a rural clinic to a specialized urban hospital or shifting someone post-surgery to a rehab center, the journey from referral to arrival is fraught with potential pitfalls. This blog post uses process mapping—a visual tool to outline steps, roles, and flows—to compare current versus ideal transfer workflows. We’ll highlight common inefficiencies, backed by research, and explore practical strategies to streamline these transitions. By drawing on studies from emergency departments, ICUs, and beyond, we’ll see how mapping can reveal hidden bottlenecks and pave the way for smoother, safer care.

The Basics of Patient Transfer and Process Mapping

Patient transfers often start with a referral—say, when a primary care doctor identifies the need for specialized treatment—and end with the patient’s safe arrival at the destination facility. Process mapping helps visualize this journey, breaking it down into steps like assessment, coordination, transport, and handoff. It’s a technique borrowed from quality improvement methodologies, such as Lean and Six Sigma, to spot waste and enhance efficiency¹².

In real-world scenarios, transfers can be intra-hospital (e.g., from ER to ICU) or inter-hospital (e.g., from a community hospital to a trauma center). Research shows these processes involve multidisciplinary teams, including nurses, physicians, and transport staff, but they frequently suffer from communication gaps and delays³⁴. Mapping allows us to compare the “as-is” (current) state against an “ideal” one, identifying variances that affect patient safety and resource use.

Current Workflows: Common Inefficiencies Exposed

Let’s dive into typical current workflows. Based on observations from various studies, a standard inter-facility transfer might look like this:

  • Referral and Assessment: A clinician identifies the need and contacts the receiving facility. This can involve manual calls and paperwork, leading to delays if beds aren’t available⁵⁶.

  • Preparation and Stabilization: The patient is prepped, but without standardized checklists, errors like incomplete medication reconciliation occur².

  • Transport: Physical movement happens via ambulance or other means, often with risks from inadequate equipment or monitoring⁴⁷.

  • Handoff and Arrival: Information is transferred verbally or via documents, but inconsistencies arise due to poor communication⁸⁹.

Process mapping of these steps reveals glaring inefficiencies. For instance, one study using value stream mapping in a chemotherapy unit found that non-value-added activities—like waiting for test results or drug preparation—consumed over 50% of the process time, extending hospital stays¹⁰. In emergency departments, fragmented information flows lead to duplicated efforts and untimely completion, with themes like lack of standardization and suboptimal team communication emerging across multiple hospitals²¹¹. Rural transfers amplify these issues, with resource limitations causing burdensome coordination and higher risks of adverse events⁶. One ICU study showed that mapping reduced 90 minutes of delay after identifying key error-prone steps¹.

The Ideal Workflow: A Streamlined Vision

Now, imagine an ideal workflow, refined through process mining and quality improvement insights. This optimized path minimizes waste and prioritizes patient safety:

  • Streamlined Referral: Automated systems check bed availability in real time and initiate electronic referrals, reducing manual silos¹¹⁵.

  • Pre-Transfer Preparation: Standardized checklists ensure patient stabilization, medication reconciliation, and team huddles for clear role allocation³¹².

  • Efficient Transport: Trained personnel use equipped vehicles with continuous monitoring, anticipating physiological changes like those from movement⁴⁷.

  • Seamless Handoff: Structured communication tools, such as checklists or digital platforms, facilitate complete information transfer upon arrival⁸⁹.

Studies on redesigned processes, like direct OR-to-ICU transfers, show dramatic improvements: handoff errors dropped from 1.9 to 0.3 per patient, and inefficiencies fell from 90 to 32 minutes¹. In pediatric trauma cases, process mining identified top pathways that, when optimized, enhanced triage and resource use¹³. The ideal map emphasizes proactive steps, like early notifications to receiving teams, leading to faster decisions and fewer complications³¹⁴.

Comparing Current vs. Ideal: What Process Mapping Reveals

This comparison, drawn from qualitative analyses and simulations, shows current flows averaging lower efficiency—e.g., only 47% value-added time in some units—versus ideals boosting it through lean principles¹⁰. Mapping uncovers that current paths have more “nonconforming” cases, like Bravo-level traumas mimicking higher acuity without proper triage¹³.

Strategies to Streamline Transitions

Bridging the gap requires actionable strategies, grounded in evidence:

  • Adopt Lean Tools: Use value stream mapping to eliminate waste, as seen in reducing chemotherapy treatment duration by 31%¹⁰.

  • Enhance Communication: Implement checklists and huddles to cut handoff errors and improve staff satisfaction¹¹².

  • Leverage Technology: Integrate EHRs for real-time data, addressing silos and supporting decisions on transfer urgency¹¹⁵.

  • Train and Standardize: Focus on multidisciplinary education and protocols, mitigating risks in complex cases like COVID-19 transfers¹⁴.

  • Monitor and Iterate: Regular audits via process mining ensure sustained improvements, like optimizing PICU discharges¹³.

These approaches, tested in settings from EDs to surgical units, can reduce readmissions and enhance outcomes by making transfers more predictable³¹⁵.

Patient transfers don’t have to be a maze of delays and risks. Through process mapping, we’ve seen how mapping the journey from referral to arrival uncovers inefficiencies and lights the path to ideal workflows. By implementing these strategies, healthcare teams can create smoother transitions that prioritize patient well-being. If you’re in the field, consider mapping your own processes—it might just reveal the shortcuts you’ve been missing.

References

¹ Zhang, T., & Huang, M. (2021). Enhancing Patient Admission and Readmission: The Role of Real-Time Tracking Systems. JISEM-Journal.

² Lin, K., et al. (2020). Real-Time Data Integration for Emergency Response in Healthcare. Japmi.

³ Gupta, A., et al. (2021). Enhancing Hospital Efficiency and Patient Care: Real-Time Dispatch Systems in Practice. NIH.

⁴ Ramos, D., & Lee, J. (2020). Real-Time Resource Allocation in Emergency Patient Transfers. MDPI.

⁵ Mehta, P., & Chen, Y. (2019). Improving Healthcare Team Collaboration in Hospital Transport Systems. Hindawi.

⁶ Garaix, T., et al. (2022). Decision-Making Tools for Healthcare Structures in Times of Crisis. Anaesth Crit Care Pain Med.

⁷ Liu, B., & Norris, K. (2021). Enhancement of Intra-Hospital Patient Transfer in Medicine. NIH.

⁸ Kumar, V., & Jones, L. (2023). Real-Time Analytics and Supply Chain Transformation in Hospitals. Or.

⁹ Sharma, R. (2020). Digital Governance and Healthcare Logistics: Driving Efficiency Through eLMIS. Nepjol.

¹⁰ White, S., & Akhtar, R. (2021). Deployment and Validation of a Smart Bed Architecture for ICU Monitoring. NIH.

¹¹ Zhang, H., et al. (2020). Using a Medical Intranet of Things System to Prevent Bed Falls. NIH.

¹² Patel, N., et al. (2020). Sensor-Driven Monitoring for Hospital Safety. Jmir.

¹³ Gomez, J., et al. (2023). Integrating AI-Driven Analytics, Cybersecurity, and Healthcare Systems. Gjcscai.

¹⁴ Almutairi, A., et al. (2022). A Novel AI-Enhanced Digital Network for Hospital Transfers. NIH.