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Related Experiment Video

Updated: Jun 23, 2026

Collecting Sleep, Circadian, Fatigue, and Performance Data in Complex Operational Environments

Collecting Sleep, Circadian, Fatigue, and Performance Data in Complex Operational Environments

Published on: August 8, 2019

Process data: a means to measure operational performance and implement advanced analytical models.

Pablo Santibañez¹, Vincent S Chow, John French

¹British Columbia Cancer Agency, Vancouver, BC, Canada. psantibanez@bccancer.bc.ca

Studies in Health Technology and Informatics

|April 22, 2009

Summary

This summary is machine-generated.

Operational reviews in ambulatory clinics identified inefficiencies in appointment scheduling. Limited process data necessitated manual collection, highlighting the need for continuous data gathering for future healthcare modeling and simulation.

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Last Updated: Jun 23, 2026

Collecting Sleep, Circadian, Fatigue, and Performance Data in Complex Operational Environments

Collecting Sleep, Circadian, Fatigue, and Performance Data in Complex Operational Environments

Published on: August 8, 2019

Area of Science:

Healthcare Operations Research
Clinical Informatics

Background:

Ambulatory clinics face challenges in optimizing appointment scheduling and resource allocation.
Accurate operational data is crucial for identifying inefficiencies and implementing improvements.

Purpose of the Study:

To conduct an operational review of an ambulatory clinic to identify efficiency opportunities.
To assess the availability of process data for analytical modeling and simulation.

Main Methods:

An operational review was performed in an ambulatory clinic setting.
Process data was collected manually due to its initial scarcity.
Analytical models were planned for development using collected operational metrics.

Main Results:

The review identified significant opportunities for improving appointment scheduling and capacity allocation.
A critical lack of readily available operational process data was observed.
Manual data collection proved to be a time-intensive necessity.

Conclusions:

Continuous, perpetual collection of operational process data is essential for ambulatory clinics.
Implementing systematic data collection will enable advanced modeling and simulation for enhanced efficiency.
Future healthcare operational improvements depend on robust data infrastructure.