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Data Collection I

Data Collection I

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 data...

Data Collection III

Data Collection III

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.
The principles to begin the physical assessment include conducting a comprehensive or problem-related history in a quiet, well-lit room, emphasizing privacy and comfort for the patient.

Data Validation

Data Validation

Data validation is an essential part of a comprehensive assessment. Validation is confirming or verifying and opening the door to gathering more assessment data as it clarifies vague or unclear data. The process of checking and verifying the collected information is called data validation. The primary purpose of data validation is to ensure data is as free from error, bias, and misinterpretation as possible.
Nursing assessment guides are generally based on holistic models rather than medical...

Statistical Methods for Analyzing Epidemiological Data

Statistical Methods for Analyzing Epidemiological Data

Epidemiological data primarily involves information on specific populations' occurrence, distribution, and determinants of health and diseases. This data is crucial for understanding disease patterns and impacts, aiding public health decision-making and disease prevention strategies. The analysis of epidemiological data employs various statistical methods to interpret health-related data effectively. Here are some commonly used methods:

Data Collection II

Data Collection II

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 family,...

Methods of Documentation V: CBE

Methods of Documentation V: CBE

Charting by Exception, or CBE, is a method of documentation used in healthcare, particularly in nursing, that focuses on documenting only significant or abnormal findings rather than recording every detail. This approach aims to streamline the documentation process, improve efficiency, and ensure that healthcare providers can quickly identify deviations from normalcy in patient assessments.
In CBE, healthcare professionals establish predefined standards of practice that define what constitutes...

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Related Experiment Video

Updated: May 26, 2026

A Metadata Extraction Approach for Clinical Case Reports to Enable Advanced Understanding of Biomedical Concepts

A Metadata Extraction Approach for Clinical Case Reports to Enable Advanced Understanding of Biomedical Concepts

Published on: September 20, 2018

Methods to identify standard data elements in clinical and public health forms.

Neil F Abernethy¹, Kathy DeRimer, Peter M Small

¹University of Washington, Seattle, WA, USA.

AMIA ... Annual Symposium Proceedings. AMIA Symposium

|December 24, 2011

Summary

Public health data collection varies widely across states, hindering standardization. Tuberculosis contact investigation forms show significant differences, with only "Name" being a common field, complicating data integration efforts.

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Area of Science:

Public Health Informatics
Health Data Standardization
Epidemiological Surveillance

Background:

Fragmented clinical and public health systems lead to inconsistent data collection practices.
Variations in data forms across public health jurisdictions impede data integration and electronic health record (EHR) certification.
Differences in patient treatment, monitoring, evaluation, and follow-up practices contribute to data collection disparities.

Purpose of the Study:

To analyze variations in data elements collected on tuberculosis contact investigation forms nationwide.
To identify common data fields and regional practices in public health data collection.
To inform efforts toward standardizing public health data and improving data integration.

Main Methods:

Survey of tuberculosis contact investigation forms from all 50 U.S. states, 3 municipalities, and 2 countries.
Application of statistical analysis and cluster analysis to examine data field content.
Comparative analysis to identify ubiquitous and regionally specific data elements.

Main Results:

Widespread variation in data elements was observed across surveyed states.
The "Name" field was the only data element consistently present across all forms.
Cluster analysis identified distinct regional groupings of data fields, highlighting variations in practice.

Conclusions:

Significant heterogeneity exists in public health data collection for tuberculosis contact investigations.
Establishing a common core of data fields is essential for standardization and interoperability.
Understanding regional variations can guide the development of more integrated and effective public health information systems.