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

Measuring clinical performance using routinely collected clinical data.

D R Prytherch1, J S Briggs, P C Weaver

  • 1University of Portsmouth, Portsmouth, UK. dave.prytherch@port.ac.uk

Medical Informatics and the Internet in Medicine
|December 13, 2005
PubMed
Summary
This summary is machine-generated.

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

Observational study of the relationship between nurse staffing levels and compliance with mandatory nutritional assessments in hospital.

Journal of human nutrition and dietetics : the official journal of the British Dietetic Association·2021
Same author

Vital signs and other observations used to detect deterioration in pregnant women: an analysis of vital sign charts in consultant-led UK maternity units.

International journal of obstetric anesthesia·2017
Same author

Heap leach cyanide irrigation and risk to wildlife: Ramifications for the international cyanide management code.

Ecotoxicology and environmental safety·2017
Same author

Comparison of the National Early Warning Score in non-elective medical and surgical patients.

The British journal of surgery·2016
Same author

Introduction of an electronic physiological early warning system: effects on mortality and length of stay.

British journal of anaesthesia·2015
Same author

'Errors' and omissions in paper-based early warning scores: the association with changes in vital signs--a database analysis.

BMJ open·2015
Same journal

Patients' perceptions of Internet usage and their opportunity to obtain health information.

Medical informatics and the Internet in medicine·2007
Same journal

Assisting the transition from hospital to home for children with major congenital heart disease by telemedicine: a feasibility study and initial results.

Medical informatics and the Internet in medicine·2007
Same journal

Digital pens and pain diaries in palliative home health care: professional caregivers' experiences.

Medical informatics and the Internet in medicine·2007
Same journal

Readability and cultural sensitivity of web-based patient decision aids for cancer screening and treatment: a systematic review.

Medical informatics and the Internet in medicine·2007
Same journal

ICT-based health information services for elderly people: past experiences, current trends, and future strategies.

Medical informatics and the Internet in medicine·2007
Same journal

Obtrusiveness of information-based assistive technologies as perceived by older adults in residential care facilities: a secondary analysis.

Medical informatics and the Internet in medicine·2007
See all related articles

Hospital performance can be predicted using simple patient data like age and blood tests. This approach offers a meaningful, case-mix-adjusted metric for clinical performance management, enhancing patient safety and care quality.

Area of Science:

  • Healthcare quality improvement
  • Clinical informatics
  • Patient safety research

Background:

  • Public concern regarding hospital performance has increased following high-profile incidents in pediatric cardiac surgery.
  • The Kennedy report emphasized the need for meaningful, case-mix-adjusted hospital performance measures using routine clinical data.

Purpose of the Study:

  • To determine if in-hospital mortality can be predicted using readily available, routine clinical data.
  • To develop a practical risk model for evidence-based clinical performance management.

Main Methods:

  • Utilized simple, routinely collected patient data including age, mode of admission, sex, and routine blood test results.
  • Data was sourced from existing hospital core IT systems, requiring no additional clinical burden.

Related Experiment Videos

Main Results:

  • Successfully predicted in-hospital mortality using basic demographic and routine laboratory data.
  • Identified key predictors such as age, admission type, sex, and blood test results.

Conclusions:

  • A feasible and meaningful metric for hospital performance can be derived from simple, routinely collected clinical data.
  • This risk model supports evidence-based clinical performance management and is logistically viable for national application.