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Related Concept Videos

SBAR I: Understanding the Concept01:29

SBAR I: Understanding the Concept

5.7K
Effective communication among healthcare professionals during hand-off reporting is essential to delivering safe and continuous patient care. Common professional interactions include reports to healthcare team members, hand-off, and transfer reports. Nurses routinely report information to other healthcare team members and also urgently contact healthcare providers to report changes in patient status.
Standardized methods of communication have been developed to ensure that information is...
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SBAR II: Application of SBAR01:14

SBAR II: Application of SBAR

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SBAR is an effective communication tool used by healthcare professionals to communicate patient information accurately. SBAR stands for Situation, Background, Assessment, and Recommendation. For a better understanding, an example is given below.
SBAR Report from a Nurse to a Health Care Provider
S: "Hello, Dr. Smith. This is Jane, RN, from the Med Surg unit. I am calling to tell you about Ms. White in Room 210, who is experiencing increased pain and redness at her incision site. Her recent...
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Related Experiment Video

Updated: Dec 22, 2025

Human Brown Adipose Tissue Depots Automatically Segmented by Positron Emission Tomography/Computed Tomography and Registered Magnetic Resonance Images
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Solving patient referral problems by using bat algorithm.

Huan-Chung Yao1,2, Pei-Jarn Chen2, Yu-Ting Kuo1

  • 1Department of Medical Imaging, Chi Mei Medical Center, Tainan, Taiwan.

Technology and Health Care : Official Journal of the European Society for Engineering and Medicine
|May 5, 2020
PubMed
Summary
This summary is machine-generated.

Optimizing patient referrals between two hospitals significantly reduced magnetic resonance imaging (MRI) wait times by 50%. The study recommends increasing monthly MRI referrals to improve patient care quality.

Keywords:
Patient referral problembat algorithmsimulation optimization

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Area of Science:

  • Healthcare Operations Research
  • Medical Systems Engineering
  • Health Informatics

Background:

  • Addresses the challenge of optimizing patient referral volumes between two hospitals.
  • Evaluates if current referral numbers are suboptimal, impacting patient care.

Purpose of the Study:

  • Develops a simulation-based optimization algorithm to determine ideal patient referral rates.
  • Aims to find optimal daily referral policies for inter-hospital patient transfers.

Main Methods:

  • Employs system simulation combined with a bat algorithm (BA) for optimization.
  • Constructs a simulation model reflecting the specific conditions of the two hospitals.

Main Results:

  • Demonstrates algorithm stability across 20 test instances.
  • Achieved a 50% reduction in average magnetic resonance imaging (MRI) patient wait time (from 16 to 8 days).
  • Identified an optimal strategy: increase average total monthly MRI referrals to 370 with a daily limit of 25 patients.

Conclusions:

  • Successfully investigated and modeled two-hospital patient referral dynamics.
  • The simulation model improved the case hospital's operational efficiency and medical care quality.
  • Findings are generalizable to other hospital departments and healthcare facilities.