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Related Concept Videos

Flow Sheet01:17

Flow Sheet

Flowsheets are valuable tools in nursing documentation. They enable healthcare professionals to efficiently record and monitor various patient assessments and measurements in a consolidated format.
Here's a closer look at the examples of flowsheets commonly used by nurses:
Graphic Sheet Documentation:
Maximum Power Flow and Line Loadability01:23

Maximum Power Flow and Line Loadability

The maximum power flow for lossy transmission lines is derived using ABCD parameters in phasor form. These parameters create a matrix relationship between the sending-end and receiving-end voltages and currents, allowing the determination of the receiving-end current. This relationship facilitates calculating the complex power delivered to the receiving end, from which real and reactive power components are derived.
Physiological Pharmacokinetic Models: Blood Flow-Limited Versus Diffusion-Limited Models00:57

Physiological Pharmacokinetic Models: Blood Flow-Limited Versus Diffusion-Limited Models

Physiological pharmacokinetic models, often called flow-limited or perfusion models, typically assume a swift drug distribution between tissue and venous blood, creating a rapid drug equilibrium. This premise is based on the idea that drug diffusion is extremely fast, and the cell membrane presents no barrier to drug permeation. In this scenario, where no drug binding occurs, the drug concentration in the tissue equals that of the venous blood leaving the tissue. This greatly simplifies the...
Methods of Medium Optimization01:28

Methods of Medium Optimization

Optimizing growth media enhances microbial proliferation and maximizes product yield. Statistical experimental design methodologies provide structured and reproducible approaches, offering progressively higher levels of robustness and efficiency.The One-Factor-at-a-Time (OFAT) MethodThe One-Factor-at-a-Time (OFAT) method involves adjusting a single variable while keeping all others constant. However, it cannot detect interactions between variables, often leading to suboptimal outcomes when...
Design Example: Analyzing Capacity Contours for Flood Risk Assessment01:17

Design Example: Analyzing Capacity Contours for Flood Risk Assessment

Flood risk assessment involves careful planning and analysis to ensure the safety of communities near water retention structures. Capacity contours are a vital tool in this process, as they illustrate the potential spread of water at specific levels in a given area. In the context of building a bund across a small valley, these contours play a critical role in evaluating the safety of nearby residential areas.In this example, the bund is intended to store stormwater in the valley. The engineers...
Methods of Documentation VI: Case Management Model01:15

Methods of Documentation VI: Case Management Model

The case management model is a multidisciplinary approach that involves healthcare professionals from diverse disciplines, such as physicians, nurses, therapists, social workers, and pharmacists, working collaboratively to address the various needs of patients. Each healthcare professional brings unique expertise and perspectives, contributing to a more comprehensive understanding of the patient's condition and tailoring treatment plans accordingly.
For example, a patient with a chronic illness...

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Related Experiment Videos

A network flow approach to optimizing hospital bed capacity decisions.

Elif Akcali1, Murray J Côté, Chin Lin

  • 1Department of Industrial and Systems Engineering, University of Florida, Gainesville, FL 32611-6595, USA. akcali@ise.ufl.edu

Health Care Management Science
|December 26, 2006
PubMed
Summary

This study presents a network flow model to optimize hospital bed capacity planning. The model efficiently determines optimal capacity, addressing increased demand and limited resources in US hospitals.

Related Experiment Videos

Area of Science:

  • Health Care Management
  • Operations Research
  • Health Economics

Background:

  • Delivering cost-effective, quality hospital care is a persistent challenge in the US.
  • Rising inpatient demand, coupled with limited resources and outpatient alternatives, strains hospital capacity.
  • Accurate hospital bed capacity planning is crucial for healthcare decision-makers.

Purpose of the Study:

  • To develop a network flow model for optimizing hospital bed capacity.
  • To incorporate facility performance and budget constraints into capacity planning.
  • To provide a computationally efficient method for determining optimal bed capacity.

Main Methods:

  • Developed a network flow model to represent hospital operations.
  • Incorporated facility performance metrics and budget limitations.
  • Analyzed the model's computational intensity for realistic scenarios.

Main Results:

  • The network flow model provides optimal hospital bed capacity plans.
  • The formulation is computationally efficient for realistic problem sizes.
  • Optimal plans can be obtained rapidly, aiding decision-making.

Conclusions:

  • The network flow model offers an effective solution for hospital bed capacity planning.
  • The approach balances demand, resources, and financial constraints.
  • This method enables quick and optimal capacity decisions for healthcare facilities.