Decision Support for Diabetes in Scotland: Implementation and Evaluation of a Clinical Decision Support System

Nicholas Conway (Lead / Corresponding author), Karen A. Adamson, Scott G. Cunningham, Alistair Emslie Smith, Peter Nyberg, Blair H. Smith, Ann Wales, Deborah J. Wake

Research output: Contribution to journalArticlepeer-review

3 Citations (Scopus)
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Abstract

Background: Automated clinical decision support systems (CDSS) are associated with improvements in health care delivery to those with long-term conditions, including diabetes. A CDSS was introduced to two Scottish regions (combined diabetes population ~30 000) via a national diabetes electronic health record. This study aims to describe users' reactions to the CDSS and to quantify impact on clinical processes and outcomes over two improvement cycles: December 2013 to February 2014 and August 2014 to November 2014.

Methods: Feedback was sought via patient questionnaires, health care professional (HCP) focus groups, and questionnaires. Multivariable regression was used to analyze HCP SCI-Diabetes usage (with respect to CDSS message presence/absence) and case-control comparison of clinical processes/outcomes. Cases were patients whose HCP received a CDSS messages during the study period. Closely matched controls were selected from regions outside the study, following similar clinical practice (without CDSS). Clinical process measures were screening rates for diabetes-related complications. Clinical outcomes included HbA1c at 1 year.

Results: The CDSS had no adverse impact on consultations. HCPs were generally positive toward CDSS and used it within normal clinical workflow. CDSS messages were generated for 5692 cases, matched to 10 667 controls. Following clinic, the probability of patients being appropriately screened for complications more than doubled for most measures. Mean HbA1c improved in cases and controls but more so in cases (-2.3 mmol/mol [-0.2%] versus -1.1 [-0.1%], P = .003).

Discussions and Conclusions: The CDSS was well received; associated with improved efficiencies in working practices; and large improvements in guideline adherence. These evidence-based, early interventions can significantly reduce costly and devastating complications.

Original languageEnglish
Pages (from-to)381-388
Number of pages8
JournalJournal of Diabetes Science and Technology
Volume12
Issue number2
Early online date14 Sep 2017
DOIs
Publication statusPublished - 1 Mar 2018

Keywords

  • Decision support systems
  • Clinical
  • Diabetes mellitus
  • Guideline adherence
  • Process assessment (health care)
  • process assessment (health care)
  • clinical
  • guideline adherence
  • diabetes mellitus
  • decision support systems

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