Literature DB >> 28905658

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

Nicholas Conway1,2, Karen A Adamson3, Scott G Cunningham2, Alistair Emslie Smith2, Peter Nyberg4, Blair H Smith2, Ann Wales5, Deborah J Wake1,2.   

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). DISCUSSION 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.

Entities:  

Keywords:  clinical; decision support systems; diabetes mellitus; guideline adherence; process assessment (health care)

Mesh:

Year:  2017        PMID: 28905658      PMCID: PMC5851216          DOI: 10.1177/1932296817729489

Source DB:  PubMed          Journal:  J Diabetes Sci Technol        ISSN: 1932-2968


  18 in total

1.  The quality of health care delivered to adults in the United States.

Authors:  Elizabeth A McGlynn; Steven M Asch; John Adams; Joan Keesey; Jennifer Hicks; Alison DeCristofaro; Eve A Kerr
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Review 2.  Effects of computerized clinical decision support systems on practitioner performance and patient outcomes: a systematic review.

Authors:  Amit X Garg; Neill K J Adhikari; Heather McDonald; M Patricia Rosas-Arellano; P J Devereaux; Joseph Beyene; Justina Sam; R Brian Haynes
Journal:  JAMA       Date:  2005-03-09       Impact factor: 56.272

3.  Estimating the current and future costs of Type 1 and Type 2 diabetes in the UK, including direct health costs and indirect societal and productivity costs.

Authors:  N Hex; C Bartlett; D Wright; M Taylor; D Varley
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4.  Using web technology to support population-based diabetes care.

Authors:  Scott Cunningham; Ritchie McAlpine; Graham Leese; Geraldine Brennan; Frank Sullivan; Alan Connacher; Annalu Waller; Douglas Ir Boyle; Stephen Greene; Elaine Wilson; Alistair Emslie-Smith; Andrew D Morris
Journal:  J Diabetes Sci Technol       Date:  2011-05-01

5.  Diabetic retinopathy: more patients, less laser: a longitudinal population-based study in Tayside, Scotland.

Authors:  James H Vallance; Peter J Wilson; Graham P Leese; Ritchie McAlpine; Caroline J MacEwen; John D Ellis
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6.  Estimating the impact of better management of glycaemic control in adults with Type 1 and Type 2 diabetes on the number of clinical complications and the associated financial benefit.

Authors:  M Baxter; R Hudson; J Mahon; C Bartlett; Y Samyshkin; D Alexiou; N Hex
Journal:  Diabet Med       Date:  2016-04-15       Impact factor: 4.359

7.  Current guidelines have limited applicability to patients with comorbid conditions: a systematic analysis of evidence-based guidelines.

Authors:  Marjolein Lugtenberg; Jako S Burgers; Carolyn Clancy; Gert P Westert; Eric C Schneider
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8.  Patient-specific computer-based decision support in primary healthcare--a randomized trial.

Authors:  Tiina Kortteisto; Jani Raitanen; Jorma Komulainen; Ilkka Kunnamo; Marjukka Mäkelä; Pekka Rissanen; Minna Kaila
Journal:  Implement Sci       Date:  2014-01-20       Impact factor: 7.327

9.  Implementing an evidence-based computerized decision support system linked to electronic health records to improve care for cancer patients: the ONCO-CODES study protocol for a randomized controlled trial.

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Journal:  Implement Sci       Date:  2016-11-25       Impact factor: 7.327

10.  Polypharmacy in chronic diseases-Reduction of Inappropriate Medication and Adverse drug events in older populations by electronic Decision Support (PRIMA-eDS): study protocol for a randomized controlled trial.

Authors:  Andreas Sönnichsen; Ulrike S Trampisch; Anja Rieckert; Giuliano Piccoliori; Anna Vögele; Maria Flamm; Tim Johansson; Aneez Esmail; David Reeves; Christin Löffler; Jennifer Höck; Renate Klaassen-Mielke; Hans Joachim Trampisch; Ilkka Kunnamo
Journal:  Trials       Date:  2016-01-29       Impact factor: 2.279

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  4 in total

1.  Clinician Perceptions of a Computerized Decision Support System for Pediatric Type 2 Diabetes Screening.

Authors:  Hala K El Mikati; Lisa Yazel-Smith; Randall W Grout; Stephen M Downs; Aaron E Carroll; Tamara S Hannon
Journal:  Appl Clin Inform       Date:  2020-05-13       Impact factor: 2.342

2.  Emergency Department Clinician Perspectives on the Data Availability to Implement Clinical Decision Support Tools for Five Clinical Practice Guidelines.

Authors:  Brian J Douthit; Rachel L Richesson
Journal:  AMIA Jt Summits Transl Sci Proc       Date:  2018-05-18

Review 3.  Barriers and enablers to implementing and using clinical decision support systems for chronic diseases: a qualitative systematic review and meta-aggregation.

Authors:  Winnie Chen; Claire Maree O'Bryan; Gillian Gorham; Kirsten Howard; Bhavya Balasubramanya; Patrick Coffey; Asanga Abeyaratne; Alan Cass
Journal:  Implement Sci Commun       Date:  2022-07-28

4.  Design, effectiveness, and economic outcomes of contemporary chronic disease clinical decision support systems: a systematic review and meta-analysis.

Authors:  Winnie Chen; Kirsten Howard; Gillian Gorham; Claire Maree O'Bryan; Patrick Coffey; Bhavya Balasubramanya; Asanga Abeyaratne; Alan Cass
Journal:  J Am Med Inform Assoc       Date:  2022-09-12       Impact factor: 7.942

  4 in total

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