Using web technology to support population-based diabetes care

J Diabetes Sci Technol. 2011 May 1;5(3):523-34. doi: 10.1177/193229681100500307.

Abstract

Background: Managed clinical networks have been used to coordinate chronic disease management across geographical regions in the United Kingdom. Our objective was to review how clinical networks and multidisciplinary team-working can be supported by Web-based information technology while clinical requirements continually change.

Methods: A Web-based population information system was developed and implemented in November 2000. The system incorporates local guidelines and shared clinical information based upon a national dataset for multispecialty use. Automated data linkages were developed to link to the master index database, biochemistry, eye screening, and general practice systems and hospital diabetes clinics. Web-based data collection forms were developed where computer systems did not exist. The experience over the first 10 years (to October 2010) was reviewed.

Results: The number of people with diabetes in Tayside increased from 9694 (2.5% prevalence) in 2001 to 18,355 (4.6%) in 2010. The user base remained stable (~400 users), showing a high level of clinical utility was maintained. Automated processes support a single point of data entry with 10,350 clinical messages containing 40,463 data items sent to external systems during year 10. The system supported quality improvement of diabetes care; for example, foot risk recording increased from 36% in 2007 to 73.3% in 2010.

Conclusions: Shared-care datasets can improve communication between health care service providers. Web-based technology can support clinical networks in providing comprehensive, seamless care across a geographical region for people with diabetes. While health care requirements evolve, technology can adapt, remain usable, and contribute significantly to quality improvement and working practice.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Access to Information
  • Automation
  • Data Collection
  • Diabetes Mellitus / therapy*
  • Electronic Data Processing
  • Geography
  • Guidelines as Topic
  • Humans
  • Internet
  • Medical Informatics
  • Models, Organizational
  • Prevalence
  • Quality Control
  • Risk
  • Signal Processing, Computer-Assisted
  • Telemedicine / methods*
  • United Kingdom