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Related Concept Videos

Guidelines and Strategies for Safe Computer Charting01:18

Guidelines and Strategies for Safe Computer Charting

The guidelines and strategies provided by the American Nurses Association (ANA) and the Canadian Nurses Association (CNA) offer essential principles for ensuring safe and secure computer charting systems in healthcare settings. Let's break down each recommendation:
Maintain Confidentiality and Security:
Clinical Trials01:16

Clinical Trials

Clinical trials are prospective experimental studies conducted on humans to determine the safety and efficacy of treatments, drugs, diet methods, and medical devices. Using statistics in clinical trials enables researchers to derive reasonable and accurate conclusions from the collected data, allowing them to make wise decisions in uncertain situations. In medical research, statistical methods are crucial for preventing errors and bias.
There are four phases in a clinical trial. A phase one...
Documentation of Nursing Diagnosis01:10

Documentation of Nursing Diagnosis

The nurse documents nursing diagnoses and enters them into the patient record. The identified patient's nursing diagnosis is either written out with a plan of care or entered into the electronic health record.
In some settings, data-driven computerized decision support systems are in place, allowing for more accurate nursing diagnoses. The database within one of these systems includes diagnostic labels defining characteristics, activities, and indicators for nursing. A nurse enters assessment...
Data Validation01:03

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 Recording01:24

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...
Methods of Documentation VII: EMR01:30

Methods of Documentation VII: EMR

Electronic Medical Records (EMRs) primarily center around electronically documenting patients' health information within a single healthcare organization or practice. They contain essential clinical data related to a patient's medical history, diagnoses, medications, treatment plans, lab results, and other pertinent information relevant to the specific encounter or episode of care. EMRs are designed to streamline documentation and workflow processes within individual healthcare settings,...

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Related Experiment Video

Updated: May 7, 2026

TBase - an Integrated Electronic Health Record and Research Database for Kidney Transplant Recipients
09:00

TBase - an Integrated Electronic Health Record and Research Database for Kidney Transplant Recipients

Published on: April 13, 2021

Evaluation of Data Entry Errors and Data Changes to an Electronic Data Capture Clinical Trial Database.

Jules T Mitchel1, Yong Joong Kim, Joonhyuk Choi

  • 1President, Target Health Inc, New York.

Drug Information Journal
|September 24, 2013
PubMed
Summary

Monitoring clinical trial data entry errors is crucial. Direct data entry in electronic data capture (EDC) systems significantly reduces transcription mistakes and improves data quality for trials.

Keywords:
Data managementEDCRisk-based monitoring

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Databases to Efficiently Manage Medium Sized, Low Velocity, Multidimensional Data in Tissue Engineering
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Databases to Efficiently Manage Medium Sized, Low Velocity, Multidimensional Data in Tissue Engineering

Published on: November 22, 2019

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Last Updated: May 7, 2026

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Databases to Efficiently Manage Medium Sized, Low Velocity, Multidimensional Data in Tissue Engineering

Published on: November 22, 2019

Area of Science:

  • Clinical Trial Management
  • Data Management
  • Pharmacovigilance

Background:

  • Clinical trial monitoring involves diverse expertise and skill sets.
  • Ensuring data integrity in clinical trials is paramount for accurate results.

Purpose of the Study:

  • To identify database changes and data entry errors in an electronic data capture (EDC) clinical trial database.
  • To assess the impact of these changes and errors on the clinical trial data.

Main Methods:

  • Utilized Target e*CRF as the electronic data capture (EDC) tool.
  • Analyzed data from a multinational, dose-finding, multicenter, double-blind, randomized, parallel, placebo-controlled trial.
  • Focused on identifying transcription errors from paper source documents to the EDC database.

Main Results:

  • The primary errors identified were simple transcription errors from paper source documents to the EDC database.
  • Acknowledged that all data transactions have an inherent error rate.
  • Highlighted the importance of risk-based monitoring within a comprehensive data monitoring plan.

Conclusions:

  • Direct data entry in EDC systems is expected to dramatically reduce error rates by eliminating transcription.
  • Direct data entry allows for real-time identification of protocol violations and out-of-range data.
  • Implementing robust data monitoring plans is essential for maintaining clinical trial data integrity.