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

Data Reporting and Recording01:24

Data Reporting and Recording

5.5K
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...
5.5K
Health Literacy01:21

Health Literacy

5.4K
Health literacy is an individual's or a community's capacity to comprehend, receive, read, and use relevant healthcare information and services. The World Health Organization (WHO, 2018) defines health literacy as the cognitive and social skills that determine the ability of individuals to gain access to, understand, and use information in ways that promote and maintain good health. As a result, the WHO helps individuals manage long-term health concerns, participate in preventative...
5.4K
How Data are Classified: Categorical Data01:11

How Data are Classified: Categorical Data

44.8K
A variable, usually notated by capital letters such as X and Y, is a characteristic or measurement that can be determined for each member of a population. Data are the actual values of variables. They may be numbers, or they may be words. Datum is a single value.
Data are classified based on whether they are measurable or not. Categorical data cannot be measured; instead, it can be divided into categories. For example, if Y denotes a person's party affiliation, some examples of Y include...
44.8K
How Data are Classified: Numerical Data00:59

How Data are Classified: Numerical Data

38.1K
Data that are countable or measurable in specific units are called numerical or quantitative data. Quantitative data are always numbers. Quantitative data are the result of counting or measuring the attributes of a population. Amount of money, pulse rate, weight, number of people living in a town, and number of students who opt for statistics are examples of quantitative data.
Quantitative data may be either discrete or continuous. All quantitative data that take on only specific numerical...
38.1K
Purpose of Health Records I01:11

Purpose of Health Records I

1.8K
The vital purpose of health records is to provide a complete and accurate account of a patient's medical history, including communication, diagnostic and therapeutic orders, care planning, research, and quality review.
Here's a breakdown of how health records serve these purposes:
1.8K
Purpose of Health Records II01:19

Purpose of Health Records II

1.4K
Health records serve various essential purposes in the healthcare system. Here are some key purposes:
1.4K

You might also read

Related Articles

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

Sort by
Same author

Ethical considerations in managing hidradenitis suppurativa in women of childbearing potential.

Journal of the American Academy of Dermatology·2026
Same author

Reframing AI for Rare Disease Recognition.

Research square·2026
Same author

Translating AI research into reality: summary of the 2025 voice AI Symposium and Hackathon.

Frontiers in digital health·2026
Same author

The need to develop health data transaction disclosure requirements to balance transparency, privacy, and progressive use.

The Lancet. Digital health·2026
Same author

"No BLT": The Rise and Risk of Acronyms in the Medical Record.

HEC forum : an interdisciplinary journal on hospitals' ethical and legal issues·2026
Same author

Scale-up Unlearnable Examples Learning with High-Performance Computing.

IS&T International Symposium on Electronic Imaging·2025

Related Experiment Video

Updated: Feb 6, 2026

Project-Based Learning Guidelines for Health Sciences Students: An Analysis with Data Mining and Qualitative Techniques
13:44

Project-Based Learning Guidelines for Health Sciences Students: An Analysis with Data Mining and Qualitative Techniques

Published on: December 9, 2022

4.5K

Between Access and Privacy: Challenges in Sharing Health Data.

Bradley Malin1,2, Kenneth Goodman3,

  • 1Department of Biomedical Informatics, Vanderbilt University, Nashville, Tennessee, USA.

Yearbook of Medical Informatics
|August 30, 2018
PubMed
Summary

Research in 2017 highlights innovative approaches to biomedical data sharing and privacy. Emerging technologies offer solutions for balancing data utility with participant privacy risks.

More Related Videos

Inverse Probability of Treatment Weighting Propensity Score using the Military Health System Data Repository and National Death Index
06:55

Inverse Probability of Treatment Weighting Propensity Score using the Military Health System Data Repository and National Death Index

Published on: January 8, 2020

15.4K
Methodology for Establishing a Community-Wide Life Laboratory for Capturing Unobtrusive and Continuous Remote Activity and Health Data
11:21

Methodology for Establishing a Community-Wide Life Laboratory for Capturing Unobtrusive and Continuous Remote Activity and Health Data

Published on: July 27, 2018

8.9K

Related Experiment Videos

Last Updated: Feb 6, 2026

Project-Based Learning Guidelines for Health Sciences Students: An Analysis with Data Mining and Qualitative Techniques
13:44

Project-Based Learning Guidelines for Health Sciences Students: An Analysis with Data Mining and Qualitative Techniques

Published on: December 9, 2022

4.5K
Inverse Probability of Treatment Weighting Propensity Score using the Military Health System Data Repository and National Death Index
06:55

Inverse Probability of Treatment Weighting Propensity Score using the Military Health System Data Repository and National Death Index

Published on: January 8, 2020

15.4K
Methodology for Establishing a Community-Wide Life Laboratory for Capturing Unobtrusive and Continuous Remote Activity and Health Data
11:21

Methodology for Establishing a Community-Wide Life Laboratory for Capturing Unobtrusive and Continuous Remote Activity and Health Data

Published on: July 27, 2018

8.9K

Area of Science:

  • Medical Informatics
  • Biomedical Data Science
  • Health Data Privacy

Background:

  • The increasing volume and complexity of biomedical data necessitate robust strategies for sharing and privacy.
  • Ensuring data access while safeguarding sensitive patient information is a critical challenge in medical informatics.

Purpose of the Study:

  • To identify and summarize key research contributions from 2017 focused on data sharing and privacy in medical informatics.
  • To highlight advancements in managing access, privacy risks, and utility of biomedical data.

Main Methods:

  • An extensive literature search was performed across major scientific databases (PubMed/Medline, Web of Science, ACM, IEEE, AAAI).
  • Candidate papers were selected, reviewed by international experts against predefined criteria, and finalized by an editorial board.
  • The review focused on research addressing biomedical data sharing, access, and privacy, particularly for data used in research and clinical settings.

Main Results:

  • Five significant papers were selected, covering the entire lifecycle of biomedical data.
  • Contributions include novel consenting strategies, software for distributed data retrieval, methods for assessing privacy risks (especially for genomic data), cryptographic techniques for clinical data querying, and game theoretic approaches for genome-phenome studies.

Conclusions:

  • There is no universal solution for ensuring privacy in biomedical data sharing; context-specific strategies are required.
  • Emerging technologies present opportunities to enhance data utility while effectively mitigating privacy risks for participants.