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 Experiment Videos

Computer Rx: more harm than good?

R Wall1

  • 1Faculty of Medicine, University of Manitoba, Winnipeg, Canada.

Journal of Medical Systems
|December 1, 1991
PubMed
Summary
This summary is machine-generated.

Selecting clinical information systems (CIS) requires evidence-based evaluation. A technology assessment framework helps decision-makers choose effective CIS, avoiding costly, underperforming systems for better patient care quality and efficiency.

Related Concept Videos

You might also read

Related Articles

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

Sort by
Same author

Towards a regulation of food advertising?

The Proceedings of the Nutrition Society·2022
Same author

Dung beetle community assemblages in a southern African landscape: niche overlap between domestic and wild herbivore dung.

Bulletin of entomological research·2021
Same author

Climate and the seasonal abundance of the tick Dermacentor reticulatus.

Medical and veterinary entomology·2021
Same author

Fleas infesting cats and dogs in Great Britain: spatial distribution of infestation risk and its relation to treatment.

Medical and veterinary entomology·2020
Same author

Nutritional requirements for reproduction and survival in the blowfly Lucilia sericata.

Medical and veterinary entomology·2019
Same author

Ecological and geographical speciation in <i>Lucilia</i> <i>bufonivora</i>: The evolution of amphibian obligate parasitism.

International journal for parasitology. Parasites and wildlife·2019
Same journal

Starmate: A Lightweight AI Assistant for Autism Caregivers Developed and Evaluated Through a User-Centered Mixed-Methods Framework.

Journal of medical systems·2026
Same journal

Predicting the Predictor: Unresolved Validity Threats in LLM-Based ASA Classification.

Journal of medical systems·2026
Same journal

Development and Internal Validation of a Vectorcardiography-Augmented Model for 12-Month Major Adverse Cardiovascular Events in Chronic Heart Failure.

Journal of medical systems·2026
Same journal

Development and Validation of an Automated Acute Kidney Injury E-Alert System Integrated with Clinical Decision Support for Hospitalized Patients.

Journal of medical systems·2026
Same journal

Calibration of Self-Reported Confidence and Accuracy of Large Language Models in Medical Question Answering.

Journal of medical systems·2026
Same journal

Throughput Benchmarking and Throughput Variance Analysis to Evaluate the Efficiency of an Outpatient Endoscopy Unit.

Journal of medical systems·2026
See all related articles

Area of Science:

  • Health Informatics
  • Health Services Research
  • Technology Assessment

Background:

  • Clinical Information Systems (CIS) are vital health technologies for improving healthcare performance.
  • Informed selection of CIS is crucial, as many adopted systems fail to enhance patient care quality or efficiency.
  • Lack of evidence-based evaluation contributes to the adoption of ineffective CIS.

Purpose of the Study:

  • To present a technology assessment framework for evaluating alternative CIS.
  • To guide decision-makers in selecting CIS that demonstrably improve healthcare quality and efficiency.
  • To prevent the adoption of non-beneficial CIS, often termed 'white elephants'.

Main Methods:

  • Discusses a technology assessment framework tailored for CIS evaluation.

Related Experiment Videos

  • Leverages existing methodologies for assessing diagnostic and therapeutic technologies.
  • Emphasizes the role of researchers in providing evidence for decision-makers at each framework stage.
  • Main Results:

    • The framework provides a structured approach to evaluating CIS.
    • It enables decision-makers to utilize scientific evidence for informed system selection.
    • Rigorous pre-implementation evaluation is key to successful CIS adoption.

    Conclusions:

    • Evidence-based technology assessment is essential for effective CIS selection.
    • The proposed framework supports informed decision-making in healthcare technology adoption.
    • Implementing this framework can lead to improved patient care and operational efficiency.