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

Pharmacokinetics in Pediatric Patients: Overview and Drug Absorption01:23

Pharmacokinetics in Pediatric Patients: Overview and Drug Absorption

967
Understanding the physiological differences in the pediatric population is crucial for effective pharmacotherapy. Neonates, infants, and children exhibit significant variations in gastric pH, gastric emptying time, intestinal transit time, and biliary function. These variations profoundly affect oral drug absorption, necessitating a nuanced approach to pediatric dosing.Neonates present with a unique physiological profile, having a gastric pH greater than 4 and faster and more irregular gastric...
967
Pharmacokinetics in Pediatric Patients: Drug Distribution01:17

Pharmacokinetics in Pediatric Patients: Drug Distribution

554
Drug distribution in the pediatric population exhibits unique challenges and considerations due to the physiological differences between children, particularly neonates and infants, and adults. A crucial aspect of pediatric pharmacology is understanding how these differences impact the pharmacokinetics of various drugs, necessitating age-specific dosing strategies to ensure efficacy and safety.Neonates and infants have a higher total body water content, ~75%–90% of their body weight,...
554
Pharmacokinetics in Pediatric Patients: Drug Excretion01:26

Pharmacokinetics in Pediatric Patients: Drug Excretion

408
In pediatric medicine, understanding the renal function and drug elimination nuances is crucial for administering safe and effective treatments. Newborns, in particular, display markedly slower renal functions than adults, profoundly affecting how drugs are cleared from their bodies. This slower drug clearance requires clinicians to extend the dosing intervals for many medications to prevent drug accumulation and toxicity while ensuring therapeutic efficacy.One key area where these adjustments...
408
Patient-centered Care01:13

Patient-centered Care

3.1K
Patient-centered care involves delivering care beyond inpatient hospitalization. Reflective practice can enhance a patient-centered approach. Reflective practice is a process of reasoning that considers all aspects of the present situation, including practicalities, learning from personal practice, and consideration of patient needs. Patients appreciate care decisions made while considering their input. Involving the patient in their care provides the patient with a sense of contribution rather...
3.1K
Pharmacokinetics in Pediatric Patients: Drug Metabolism01:24

Pharmacokinetics in Pediatric Patients: Drug Metabolism

410
In pediatric care, understanding the nuances of hepatic drug metabolism is crucial, as it significantly differs from that of adults. This divergence is primarily due to the developmental stage of drug-metabolizing enzymes, which affects how medications are processed in the body. In neonates, for instance, the activity of Phase I enzymes—critical for the initial breakdown of drugs—is markedly reduced, functioning at just 20–40% of the levels seen in adults. This reduction poses...
410
Drug Dosing: Infants and Children01:29

Drug Dosing: Infants and Children

1.0K
Pediatric patient dosages diverge from adults due to disparities in body surface area, total body water, and extracellular fluid per kilogram of body weight. The dosing regimen considers the variations in pharmacokinetics and pharmacology across distinct age groups, encompassing preterm newborns, infants, young children, older children, and adolescents. Calculation of pediatric patient doses is predicated on determining body surface area, which exhibits a superior correlation with the child's...
1.0K

You might also read

Related Articles

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

Sort by
Same author

Reply to: Reassessing the evidence linking clinical leadership to AI deployment outcomes.

NPJ digital medicine·2026
Same author

A real-world feasibility evaluation of LLM-based clinical prediction: emergency department return visit admission across two academic medical centers.

Research square·2026
Same author

Outcomes of 72-hour emergency department return visits requiring hospital admission in older adults: a nationally representative analysis.

BMC geriatrics·2026
Same author

An Artificial Intelligence-Enabled Cardiopulmonary Resuscitation Instructor.

JAMA internal medicine·2026
Same author

Implementation of a clinical decision support tool for postpartum depression: protocol for a prospective randomised clinical trial.

BMJ open·2026
Same author

A qualitative interview study investigating patient, health professional, and developer perspectives on real-world implementation of patient-centered AI systems.

NPJ digital medicine·2026

Related Experiment Video

Updated: May 1, 2026

Implementation of Non-invasive Point of Care Transient Elastography for Evaluation of Liver Disease in Pediatric Populations with Cystic Fibrosis
05:56

Implementation of Non-invasive Point of Care Transient Elastography for Evaluation of Liver Disease in Pediatric Populations with Cystic Fibrosis

Published on: August 29, 2025

705

Paving the COWpath: data-driven design of pediatric order sets.

Yiye Zhang1, Rema Padman2, James E Levin3

  • 1School of Information Systems Management, H John Heinz III College, Carnegie Mellon University, Pittsburgh, Pennsylvania, USA.

Journal of the American Medical Informatics Association : JAMIA
|March 29, 2014
PubMed
Summary

This study introduces data-driven methods to automate the creation of computerized provider order entry (CPOE) order sets, significantly reducing physical and cognitive workload for clinicians by 14-52%. These optimized order sets improve efficiency and patient safety.

Keywords:
CPOECognitive WorkloadOrder SetUsability

More Related Videos

Author Spotlight: Improving Radiation Therapy Access with Radiation Planning Assistant
05:18

Author Spotlight: Improving Radiation Therapy Access with Radiation Planning Assistant

Published on: October 6, 2023

2.1K
Development and Implementation of a Multi-Disciplinary Technology Enhanced Care Pathway for Youth and Adults with Concussion
08:13

Development and Implementation of a Multi-Disciplinary Technology Enhanced Care Pathway for Youth and Adults with Concussion

Published on: January 20, 2019

6.4K

Related Experiment Videos

Last Updated: May 1, 2026

Implementation of Non-invasive Point of Care Transient Elastography for Evaluation of Liver Disease in Pediatric Populations with Cystic Fibrosis
05:56

Implementation of Non-invasive Point of Care Transient Elastography for Evaluation of Liver Disease in Pediatric Populations with Cystic Fibrosis

Published on: August 29, 2025

705
Author Spotlight: Improving Radiation Therapy Access with Radiation Planning Assistant
05:18

Author Spotlight: Improving Radiation Therapy Access with Radiation Planning Assistant

Published on: October 6, 2023

2.1K
Development and Implementation of a Multi-Disciplinary Technology Enhanced Care Pathway for Youth and Adults with Concussion
08:13

Development and Implementation of a Multi-Disciplinary Technology Enhanced Care Pathway for Youth and Adults with Concussion

Published on: January 20, 2019

6.4K

Area of Science:

  • Health Informatics
  • Human-Computer Interaction
  • Clinical Decision Support

Background:

  • Computerized provider order entry (CPOE) systems are essential in modern healthcare.
  • Order sets within CPOE systems can impose significant physical and cognitive burdens on users.
  • Existing order set design may not align with user preferences or optimize clinical workflows.

Purpose of the Study:

  • To develop and validate data-driven approaches for automating the construction of order sets.
  • To minimize the physical and cognitive workload associated with using order sets.
  • To create order sets that closely match user preferences and clinical workflows.

Main Methods:

  • Developed optimization-based models incorporating clustering techniques.
  • Utilized physical and cognitive click cost criteria for model development.
  • Learned from historical user actions to identify relevant items and group them by similarity and timing.
  • Evaluated methods using 47,099 orders for asthma, appendectomy, and pneumonia management.

Main Results:

  • The novel approach reduced physical and cognitive workload by 14-52% compared to existing order sets.
  • The developed order sets demonstrated adaptability to variations in clinical conditions.
  • The methods successfully identified relevant items and grouped them based on usage patterns.

Conclusions:

  • Data-driven methods offer a promising strategy for generating generalizable, condition-based, and up-to-date order sets.
  • Optimizing order set generation using cognitive cost criteria can enhance ordering efficiency and reduce variations.
  • This approach has the potential to improve patient safety by designing features based on human factors best practices.