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Updated: May 28, 2026

Digital Home-Monitoring of Patients after Kidney Transplantation: The MACCS Platform
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Published on: April 12, 2021

Optimizing the patient transport function at Mayo Clinic.

Dustin Kuchera1, Thomas R Rohleder

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Quality Management in Health Care
|October 6, 2011
PubMed
Summary
This summary is machine-generated.

A new computerized scheduling tool optimized patient transport staffing at Mayo Clinic. This innovation reduced staff while maintaining excellent patient service levels.

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Area of Science:

  • Healthcare Operations Management
  • Health Informatics
  • Logistics Optimization

Background:

  • Efficient patient transport is crucial for hospital operations and patient flow.
  • Manual scheduling methods can lead to suboptimal staffing levels and increased patient wait times.
  • Balancing staffing efficiency with high-quality patient care presents a significant operational challenge.

Purpose of the Study:

  • To implement a computerized scheduling tool to optimize staffing for patient transport.
  • To evaluate the tool's impact on staffing efficiency and patient service quality.
  • To provide a model for improving healthcare logistics through technology.

Main Methods:

  • Development and implementation of a scheduling tool using Microsoft Excel and Visual Basic for Applications.
  • Incorporation of an easy-to-use interface for transport management.
  • Analysis of trade-offs between patient waiting times and staffing levels.

Main Results:

  • Successful implementation of a user-friendly computerized scheduling tool.
  • Demonstrated ability to reduce staffing levels while maintaining historical patient service levels.
  • Validation of the tool's effectiveness in optimizing patient transport operations.

Conclusions:

  • Computerized scheduling tools can significantly enhance efficiency in patient transport services.
  • Optimized staffing through technology can lead to cost savings without compromising patient care quality.
  • The developed tool offers a practical solution for improving hospital logistics and resource allocation.