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

1.9K
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...
1.9K

You might also read

Related Articles

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

Sort by
Same author

Pneumococcal meningitis among hospitalised children after introduction of pneumococcal conjugate vaccine in India: a sentinel hospital surveillance (2019-2022).

The Lancet regional health. Southeast Asia·2026
Same author

Mindful approaches: Association between atopic dermatitis and autism spectrum disorder and use of visual storyboards.

Dermatology online journal·2026
Same author

Viral threats to pregnancy: Global health risks in the era of pandemics.

Advances in virus research·2026
Same author

Introducing the Investigator Global Assessment of Hidradenitis Suppurativa (I-GLASS) instrument.

The British journal of dermatology·2026
Same author

Hidradenitis Suppurativa and Risk of Self-Harm and Suicide.

JAMA dermatology·2026
Same author

Defining Moderate Disease and Progression in Hidradenitis Suppurativa: An Expert Framework to Unlock the Window of Opportunity for Prompt Treatment.

American journal of clinical dermatology·2026

Related Experiment Video

Updated: Mar 3, 2026

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

Validation of a Case-Finding Algorithm for Hidradenitis Suppurativa Using Administrative Coding from a Clinical

Andrew Strunk1, Margaretta Midura, Vassiliki Papagermanos

  • 1Department of Dermatology, Hofstra Northwell School of Medicine, New Hyde Park, NY, USA.

Dermatology (Basel, Switzerland)
|April 28, 2017
PubMed
Summary
This summary is machine-generated.

Identifying hidradenitis suppurativa (HS) cases using administrative codes in clinical databases is crucial for research. This study found that using at least one ICD-9 code for HS offers a balanced and accurate method for cohort identification.

Keywords:
AccuracyCaseCohortDatabaseHidradenitis suppurativaPositive predictive valueSensitivitySpecificityValidation

More Related Videos

Comparison of Predictive Performance of Three Lymph Node Staging Systems in Colorectal Signet Ring Cell Carcinoma Based on Machine Learning Model
07:13

Comparison of Predictive Performance of Three Lymph Node Staging Systems in Colorectal Signet Ring Cell Carcinoma Based on Machine Learning Model

Published on: April 18, 2025

828
Identification of Disease-related Spatial Covariance Patterns using Neuroimaging Data
14:27

Identification of Disease-related Spatial Covariance Patterns using Neuroimaging Data

Published on: June 26, 2013

16.4K

Related Experiment Videos

Last Updated: Mar 3, 2026

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
Comparison of Predictive Performance of Three Lymph Node Staging Systems in Colorectal Signet Ring Cell Carcinoma Based on Machine Learning Model
07:13

Comparison of Predictive Performance of Three Lymph Node Staging Systems in Colorectal Signet Ring Cell Carcinoma Based on Machine Learning Model

Published on: April 18, 2025

828
Identification of Disease-related Spatial Covariance Patterns using Neuroimaging Data
14:27

Identification of Disease-related Spatial Covariance Patterns using Neuroimaging Data

Published on: June 26, 2013

16.4K

Area of Science:

  • Medical informatics
  • Dermatology
  • Observational research

Background:

  • Accurate case identification is essential for observational research using clinical databases in hidradenitis suppurativa (HS).
  • Administrative codes are increasingly utilized for cohort identification in large datasets.

Purpose of the Study:

  • To evaluate the accuracy and validity of using administrative (ICD-9) codes to establish a hidradenitis suppurativa (HS) cohort from a large clinical database.
  • To determine the diagnostic performance of ICD-9 codes for HS case ascertainment.

Main Methods:

  • Retrospective chart review was employed as the reference standard.
  • Diagnostic accuracy metrics were calculated for the presence of at least one ICD-9 code indicative of HS.
  • Key metrics included sensitivity, specificity, positive and negative predictive values, overall accuracy, and kappa statistic.

Main Results:

  • The algorithm using at least one ICD-9 code for HS demonstrated high sensitivity (100%) and negative predictive value (100%).
  • Specificity was 83%, positive predictive value was 79%, and overall accuracy was 90%.
  • The kappa statistic indicated substantial agreement (79%).

Conclusions:

  • The case-finding algorithm utilizing at least one ICD-9 code for HS provides a valid and accurate method for cohort identification in clinical databases.
  • This approach balances diagnostic accuracy with adequate statistical power, crucial for studying less common diseases like HS and their associations.