Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

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...
Nursing Clinical Information System01:27

Nursing Clinical Information System

Nursing Clinical Information System (NCIS)
A Nursing Clinical Information System (NCIS) is a specialized type of healthcare information system tailored to meet the unique needs of nursing practice. It incorporates the principles of nursing informatics to streamline information management and improve the quality of care delivery.
Critical attributes of NCIS include:
Methods of Documentation VI: Case Management Model01:15

Methods of Documentation VI: Case Management Model

The case management model is a multidisciplinary approach that involves healthcare professionals from diverse disciplines, such as physicians, nurses, therapists, social workers, and pharmacists, working collaboratively to address the various needs of patients. Each healthcare professional brings unique expertise and perspectives, contributing to a more comprehensive understanding of the patient's condition and tailoring treatment plans accordingly.
For example, a patient with a chronic illness...
Health Information Technology and Healthcare Information System01:30

Health Information Technology and Healthcare Information System

Health Information Technology (HIT)
Health Information Technology, commonly called HIT, integrates advanced information systems and technology in healthcare settings. Its primary functions include:
Integrated Healthcare System01:20

Integrated Healthcare System

An integrated healthcare system (IHS) is a set of organizations that provides for or arranges to provide coordinated and continuous service to a defined population. The IHS takes responsibility for that particular population's health status and outcome, both clinically and fiscally. An integrated healthcare system is a well-organized, well-coordinated, and collaborative network. The integrated delivery system is a network that connects different healthcare providers to deliver organized,...
Methods of Documentation I: Source-Oriented Records01:18

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:

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Explainable Artificial Intelligence for Clinical Text Classification: A Scoping Review of Methods and Applications.

Studies in health technology and informatics·2026
Same author

Exploring Synergies Between Large Language Models and Knowledge Models in Healthcare: A Scoping Review.

Studies in health technology and informatics·2026
Same author

Clarifying the relationship between biomedical and health informatics and digital health: expert perspectives.

BMJ health & care informatics·2026
Same author

Using Large Language Models to Automate the Comparison and Integration of Evolving Clinical Practice Guidelines into Clinical Decision Support Systems.

Studies in health technology and informatics·2026
Same author

From Principles to Action: A French Framework for Operationalizing Ethics in Health AI.

Studies in health technology and informatics·2026
Same author

Scaling Up Digital Health Education at Sorbonne University: Year Two Evaluation of the SN@SU Training Program.

Studies in health technology and informatics·2026
Same journal

A GenAI Pipeline for Violinist Kinematic Data Management.

Studies in health technology and informatics·2026
Same journal

AMAL-For-Qatar: A Comprehensive AI Ecosystem for Fetal Ultrasound Analysis - Project Overview and Achievements.

Studies in health technology and informatics·2026
Same journal

Longitudinal Treatment-Aware Multimodal AI for Dermatology: A Scoping Review.

Studies in health technology and informatics·2026
Same journal

Predicting Postpartum Depression Using Imbalance-Aware Machine Learning.

Studies in health technology and informatics·2026
Same journal

Validation of Deep-Learning Models for Autosegmentation of Brain Metastases.

Studies in health technology and informatics·2026
Same journal

Delay-Dependent Gating in Modular RNNs.

Studies in health technology and informatics·2026
See all related articles

Related Experiment Video

Updated: May 19, 2026

A Computer-Based Platform for Aiding Clinicians in Eating Disorder Analysis and Diagnosis
04:19

A Computer-Based Platform for Aiding Clinicians in Eating Disorder Analysis and Diagnosis

Published on: May 10, 2022

Accuracy of clinical data entry when using a computerized decision support system: a case study with OncoDoc2.

Brigitte Séroussi1, Brigitte Blaszka-Jaulerry, Laurent Zelek

  • 1UPMC, UFR de Médecine, Paris, France. brigitte.seroussi@tnn.aphp.fr

Studies in Health Technology and Informatics
|August 10, 2012
PubMed
Summary
This summary is machine-generated.

Health information technology (HIT), like the OncoDoc2 clinical decision support system (CDSS), can improve breast cancer treatment guideline compliance. Despite some data entry errors, benefits of HIT outweigh disadvantages.

More Related Videos

Improving IV Insulin Administration in a Community Hospital
12:08

Improving IV Insulin Administration in a Community Hospital

Published on: June 11, 2012

Related Experiment Videos

Last Updated: May 19, 2026

A Computer-Based Platform for Aiding Clinicians in Eating Disorder Analysis and Diagnosis
04:19

A Computer-Based Platform for Aiding Clinicians in Eating Disorder Analysis and Diagnosis

Published on: May 10, 2022

Improving IV Insulin Administration in a Community Hospital
12:08

Improving IV Insulin Administration in a Community Hospital

Published on: June 11, 2012

Area of Science:

  • Medical Informatics
  • Oncology
  • Health Services Research

Background:

  • Health information technology (HIT) implementation can lead to unintended consequences, such as e-iatrogenesis.
  • Clinical decision support systems (CDSS) aim to improve patient care by integrating evidence-based guidelines into clinical workflows.

Purpose of the Study:

  • To evaluate the impact of the OncoDoc2 CDSS on guideline compliance in breast cancer management.
  • To assess the unintended consequences and data accuracy associated with CDSS use in a real-world clinical setting.

Main Methods:

  • Analysis of 394 navigations and 6,025 data entries from the OncoDoc2 system used in three hospitals over 10 months.
  • Comparison of clinical decision compliance rates with and without CDSS assistance.
  • Quantification of data entry error rates and identification of incorrect navigations.

Main Results:

  • The overall compliance rate with clinical guidelines increased from 72.8% without CDSS to 87.3% with OncoDoc2.
  • A data entry error rate of 4.2% was observed, with 52% of navigations containing errors (N-).
  • Compliance rates were 95% for correct navigations (N+) and 80% for incorrect navigations (N-).

Conclusions:

  • Despite some data entry errors and navigation issues, the OncoDoc2 CDSS significantly improved adherence to breast cancer treatment guidelines.
  • The benefits of implementing this health information technology in clinical practice outweighed its identified disadvantages.
  • This study highlights the potential of CDSS to enhance evidence-based practice in oncology, while also underscoring the need for careful implementation and error monitoring.