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The nursing history captures and records the patient's health status, so that a care plan evolves to meet the patient's individual needs. The nursing health history is a part of the initial assessment. A comprehensive history covers all health dimensions and plays a significant role in the assessment process. A comprehensive history includes the patient's biographical information, reasons for seeking health care, expectations, present and past health history, medications, and...
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The physical assessment examines the patient for objective data that defines the patient's condition, and aids in formulating the nursing care plan. The purpose of physical assessment is a health status appraisal, which includes identifying health problems, and establishing a database for nursing intervention.
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Data collection gathers information needed to make accurate judgments about a patient's present condition. During a health history interview, subjective data is collected from the patient, their caregivers, or family members, and objective data is collected through observations and physical assessment. Patients are the primary source of subjective data. Thus information gathered from patients through interviews, observations, and physical examination is primary data. Secondary sources of...
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Roxborough Park Community Wildfire Evacuation Drill: Data Collection and Model Benchmarking.

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Wildfire evacuation models are sensitive to pre-evacuation time data. This study benchmarks two models using a community drill dataset, highlighting the impact of data sources on simulation accuracy for wildland-urban interface (WUI) communities.

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Area of Science:

  • Environmental Science
  • Disaster Management
  • Computational Social Science

Background:

  • Wildfires are escalating in severity and frequency, necessitating improved community evacuation strategies, particularly in wildland-urban interface (WUI) areas.
  • Effective evacuation planning requires accurate data on community response dynamics, including pre-evacuation delays and route choices.

Purpose of the Study:

  • To present a novel dataset from a community wildfire evacuation drill in Roxborough Park, Colorado.
  • To benchmark two distinct evacuation models (WUI-NITY and Evacuation Management System) using this dataset.
  • To analyze the sensitivity of these models to variations in input data, particularly pre-evacuation times and route usage.

Main Methods:

  • A community evacuation drill was conducted in a WUI setting, collecting data via observation and surveys on population location, pre-evacuation times, route use, and arrival times.
  • Two evacuation models, WUI-NITY and Evacuation Management System, were applied using the collected data across various scenarios with modified assumptions for pre-evacuation delays and routes.
  • Model performance was evaluated based on sensitivity to different data inputs (observations vs. self-reporting) and the evacuation phases modeled.

Main Results:

  • Evacuation model outcomes were primarily influenced by assumptions regarding pre-evacuation time inputs, especially in low-congestion environments.
  • Model performance demonstrated sensitivity to the type of data used (observed vs. self-reported) and the specific evacuation phases incorporated into the models.
  • The study underscored that the impact of data on model outcomes depends significantly on the underlying modeling methodologies.

Conclusions:

  • The accuracy of wildfire evacuation models is highly dependent on the quality and source of pre-evacuation time data.
  • Different modeling approaches exhibit varying sensitivities to input datasets, emphasizing the need to understand how data is processed.
  • The released open-access dataset provides a valuable resource for future research in wildfire evacuation model calibration and validation.