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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...

Methods of Documentation III: PIE

Methods of Documentation III: PIE

Problem-intervention-evaluation (PIE) is a systematic approach to documentation used in healthcare settings for clinical decision-making and patient care planning. It is a structured approach to organizing patient data based on problems, interventions, and evaluations. Here's a breakdown of its key features and considerations:

Methods of Documentation I: Source-Oriented Records

Methods of Documentation I: Source-Oriented Records

Source-oriented records, or SOR, are medical record-keeping organized by the data source. The SOR system was first developed in the mid-1900s to organize the growing patient data in hospitals and other healthcare facilities.
In an SOR, each discipline involved in patient care maintains a separate medical record section. This record-keeping method enables easy tracking of patient progress and ensures healthcare staff have access to up-to-date information.
Key Attributes include the following:

Significance Testing: Overview

Significance Testing: Overview

Significance testing is a set of statistical methods used to test whether a claim about a parameter is valid. In analytical chemistry, significance testing is used primarily to determine whether the difference between two values comes from determinate or random errors. The effect of a particular change in the measurement protocol, analyst, or sample itself can cause a deviation from the expected result. In the case of a suspected deviation/outlier, we need to be able to confirm mathematically...

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...

Data Reporting and Recording

Data Reporting and Recording

Reporting and recording are crucial in data documentation. The timely, thorough, and accurate documentation of facts is essential when recording patient data. Failure to record findings during an assessment or interpretation of a problem will result in loss of information and make the patient document unreliable. The reader is left with general impressions if the information is not specific. A recording is documenting data of the individual's health information in a traceable, secure, and...

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Related Experiment Video

Updated: Jul 25, 2025

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

Signing data citations enables data verification and citation persistence.

Michael J Elliott¹, Jorrit H Poelen^2,3, José A B Fortes⁴

¹University of Florida, Gainesville, FL, USA. mielliott@ufl.edu.

Scientific Data

|June 27, 2023

Summary

This study introduces signed citations, enhancing data citation with verifiable digital content signatures. This ensures data integrity and persistence, addressing content drift challenges in digital repositories.

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Area of Science:

Data Science
Information Science
Computer Science

Background:

Current data citation methods often use unverifiable retrieval, leading to content drift where data changes over time.
This lack of verifiability impacts the reliability and reproducibility of scientific research.

Purpose of the Study:

To propose a novel data citation method, "signed citations," that incorporates verifiable digital content signatures.
To enhance the integrity, persistence, and verifiability of cited data.

Main Methods:

Developed signed citations by extending traditional data citations with standards-based, unique, fixed-length digital content signatures.
Demonstrated the ability of content signatures to enable independent verification of data content.

Main Results:

Signed citations improve citation persistence by decoupling data from specific locations or storage media.
Content signatures facilitate scalable storage, location, access, and verification across diverse data infrastructures.
Enabled the creation of robust, distributed knowledge graphs using embedded content signatures.

Conclusions:

Signed citations offer a robust solution to data citation challenges, ensuring content integrity and long-term accessibility.
This approach supports reliable data collection, identification, and citation in scientific workflows.
The proposed method enhances the trustworthiness and reusability of digital research data.