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

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...
Investigation of Disease Outbreaks01:23

Investigation of Disease Outbreaks

Multistate foodborne outbreaks pose significant public health risks and require meticulous investigation to identify sources and implement control measures. The Centers for Disease Control and Prevention (CDC) utilizes a dynamic seven-step process for these investigations, integrating data from laboratories, interviews, and environmental assessments to protect public health.Outbreak Detection: The detection of multistate outbreaks typically begins with PulseNet, the CDC's national laboratory...
Steps in Outbreak Investigation01:18

Steps in Outbreak Investigation

In the ever-evolving field of public health, statistical analysis serves as a cornerstone for understanding and managing disease outbreaks. By leveraging various statistical tools, health professionals can predict potential outbreaks, analyze ongoing situations, and devise effective responses to mitigate impact. For that to happen, there are a few possible stages of the analysis:
Causality in Epidemiology01:21

Causality in Epidemiology

Causality or causation is a fundamental concept in epidemiology, vital for understanding the relationships between various factors and health outcomes. Despite its importance, there's no single, universally accepted definition of causality within the discipline. Drawing from a systematic review, causality in epidemiology encompasses several definitions, including production, necessary and sufficient, sufficient-component, counterfactual, and probabilistic models. Each has its strengths and...
Cancer Survival Analysis01:21

Cancer Survival Analysis

Cancer survival analysis focuses on quantifying and interpreting the time from a key starting point, such as diagnosis or the initiation of treatment, to a specific endpoint, such as remission or death. This analysis provides critical insights into treatment effectiveness and factors that influence patient outcomes, helping to shape clinical decisions and guide prognostic evaluations. A cornerstone of oncology research, survival analysis tackles the challenges of skewed, non-normally...
Introduction To Survival Analysis01:18

Introduction To Survival Analysis

Survival analysis is a statistical method used to study time-to-event data, where the "event" might represent outcomes like death, disease relapse, system failure, or recovery. A unique feature of survival data is censoring, which occurs when the event of interest has not been observed for some individuals during the study period. This requires specialized techniques to handle incomplete data effectively.
The primary goal of survival analysis is to estimate survival time—the time until a...

You might also read

Related Articles

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

Sort by
Same author

Health Atlas: Tutorial of a Visualization Tool and Data Resource for Place-Based Social and Structural Determinants of Health.

Journal of medical Internet research·2026
Same author

Effect of use of ambient listening technology on patient-reported communication and satisfaction ratings.

Journal of the American Medical Informatics Association : JAMIA·2026
Same author

Factors Associated With Evidence of Self-Measured Blood Pressure Adoption in an Urban Safety-Net Health System.

Journal of clinical hypertension (Greenwich, Conn.)·2026
Same author

Material economic hardships are associated with second-year hospitalizations after pediatric liver transplantation: Results from the SOCIAL-Tx study.

Liver transplantation : official publication of the American Association for the Study of Liver Diseases and the International Liver Transplantation Society·2026
Same author

Association Between Delivery Mode and Postpartum Psychiatric Conditions.

Obstetrics and gynecology·2026
Same author

Lifetime Patterns of Earned Income Tax Credit Eligibility and Cognition: A Sequence Analysis Approach.

American journal of preventive medicine·2026

Related Experiment Video

Updated: May 28, 2026

Trajectory Data Analyses for Pedestrian Space-time Activity Study
16:14

Trajectory Data Analyses for Pedestrian Space-time Activity Study

Published on: February 25, 2013

Identifying trajectories across care modalities before and after COVID-19 using sequence analysis.

Taylor Rapson1,2, Kathryn E Kemper-McIsaac3, Elizabeth B Sherwin3

  • 1Department of Health Systems and Population Health, University of Washington, Seattle, WA, USA.

NPJ Digital Medicine
|May 26, 2026
PubMed
Summary

The COVID-19 pandemic accelerated virtual care, but its long-term effects on healthcare utilization are unclear. Analysis of diabetes patients shows disparities in accessing digital and in-person care, highlighting the need for equitable telehealth strategies.

Related Experiment Videos

Last Updated: May 28, 2026

Trajectory Data Analyses for Pedestrian Space-time Activity Study
16:14

Trajectory Data Analyses for Pedestrian Space-time Activity Study

Published on: February 25, 2013

Area of Science:

  • Health Services Research
  • Digital Health
  • Health Equity

Background:

  • The COVID-19 pandemic significantly increased virtual care adoption.
  • Longitudinal impacts of virtual care on healthcare utilization remain understudied.
  • Understanding patient stratification in digital and in-person care is crucial.

Purpose of the Study:

  • To classify outpatient utilization patterns in adults with diabetes using multichannel sequence analysis.
  • To examine how virtual care adoption affects different demographic and clinical groups.
  • To identify populations at risk of reduced access in expanding remote care models.

Main Methods:

  • Multichannel sequence analysis applied to outpatient utilization data.
  • Classification of 10,671 adult patients with diabetes.
  • Analysis of primary and diabetes care visits (remote and in-person) from April 2019 to March 2023.
  • Stratification by race, ethnicity, language preference, insurance, comorbidity, and portal engagement.

Main Results:

  • Patients transitioning to digital care were disproportionately Black or White, Medicare beneficiaries, with higher comorbidity.
  • Individuals increasing combined in-person and remote utilization were disproportionately Hispanic, Spanish-preferring, with greater disease burden.
  • Patients decreasing utilization were predominantly Asian, preferred Chinese, and had low patient portal engagement.

Conclusions:

  • Technology-enabled care models can improve access but may exacerbate disparities.
  • Certain populations face risks of reduced healthcare access with expanding telehealth.
  • Health systems need targeted interventions for equitable telehealth access, addressing digital exclusion.