Literature DB >> 29947136

Evaluation of clinical decision support systems for diabetes care: An overview of current evidence.

Pengli Jia1,2, Pujing Zhao1, Jingjing Chen3, Mingming Zhang1.   

Abstract

BACKGROUND: Systematic reviews (SRs) have shown that clinical decision support systems (CDSSs) have the potential to improve diabetes care. However, methods of measuring and presenting outcomes are varied, and conclusions have been inconsistent. In addition, the reporting and methodological quality in this field is unknown, which could affect the integrity and accuracy of research. Therefore, it is difficult to confirm whether CDSSs are effective in improving diabetes care.
OBJECTIVE: To comprehensively evaluate the effects of CDSS on diabetes care and to examine the methodological and reporting qualities.
METHODS: We searched PubMed, EMBASE, and Cochrane Library from their inception to February 2017. Systematic reviews investigating the effects of CDSS on diabetes care were included. Outcomes were determined in advance and assessed separately for process of care and patient outcomes. Methodological and reporting qualities were assessed by AMSTAR and PRISMA, respectively.
RESULTS: Seventeen SRs, consisting of 222 unique randomized controlled trials and 102 nonrandomized controlled trials, were included. Evidence that CDDS significantly impacted patient outcomes was found in 32 of 102 unique studies of the 15 SRs that examined this effect (31%). A significant impact of CDSS on process of care was found in 117 out of 143 unique studies of the 11 SRs that examined this effect (82%). Ratings for overall scores of AMSTAR resulted in a mean score of 6.5 with a range of scores from 3.5 to 10.0. Reporting quality related to methodological domains was particularly incomplete.
CONCLUSIONS: Clinical decision support systems improved the quality of diabetes care by inconsistently improving process of care or patient outcomes. There is evidence that CDSS for providing alerts, reminders, or feedback to participants were most likely to impact diabetes care. Poor reporting of methodological domains, together with qualitative or narrative methods to combine findings, may limit the confidence in research evidence.
© 2018 John Wiley & Sons, Ltd.

Entities:  

Keywords:  clinical decision support system; diabetes care; methodological quality; reporting quality

Mesh:

Year:  2018        PMID: 29947136     DOI: 10.1111/jep.12968

Source DB:  PubMed          Journal:  J Eval Clin Pract        ISSN: 1356-1294            Impact factor:   2.431


  7 in total

1.  Impact of a Novel Diabetes Support System on a Cohort of Individuals With Type 1 Diabetes Treated With Multiple Daily Injections: A Multicenter Randomized Study.

Authors:  Alessandro Bisio; Stacey Anderson; Lisa Norlander; Grenye O'Malley; Jessica Robic; Selassie Ogyaadu; Liana Hsu; Camilla Levister; Laya Ekhlaspour; David W Lam; Carol Levy; Bruce Buckingham; Marc D Breton
Journal:  Diabetes Care       Date:  2022-01-01       Impact factor: 17.152

2.  Clinical Decision Support for Diabetes Care in the Hospital: A Time for Change Toward Improvement of Management and Outcomes.

Authors:  Ariana R Pichardo-Lowden
Journal:  J Diabetes Sci Technol       Date:  2021-01-07

Review 3.  Continuous Glucose Monitoring Sensors for Diabetes Management: A Review of Technologies and Applications.

Authors:  Giacomo Cappon; Martina Vettoretti; Giovanni Sparacino; Andrea Facchinetti
Journal:  Diabetes Metab J       Date:  2019-08       Impact factor: 5.376

4.  Development and Implementation of a Decision Support System to Improve Control of Hypertension and Diabetes in a Resource-Constrained Area in Brazil: Mixed Methods Study.

Authors:  Milena Soriano Marcolino; João Antonio Queiroz Oliveira; Christiane Corrêa Rodrigues Cimini; Junia Xavier Maia; Vânia Soares Oliveira Almeida Pinto; Thábata Queiroz Vivas Sá; Kaique Amancio; Lissandra Coelho; Leonardo Bonisson Ribeiro; Clareci Silva Cardoso; Antonio Luiz Ribeiro
Journal:  J Med Internet Res       Date:  2021-01-11       Impact factor: 5.428

5.  Clinical decision support to improve management of diabetes and dysglycemia in the hospital: a path to optimizing practice and outcomes.

Authors:  Ariana Pichardo-Lowden; Guillermo Umpierrez; Erik B Lehman; Matthew D Bolton; Christopher J DeFlitch; Vernon M Chinchilli; Paul M Haidet
Journal:  BMJ Open Diabetes Res Care       Date:  2021-01

6.  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

7.  Mobile Clinical Decision Support System for the Management of Diabetic Patients With Kidney Complications in UK Primary Care Settings: Mixed Methods Feasibility Study.

Authors:  Hala Ibrahim Alhodaib; Christina Antza; Joht Singh Chandan; Wasim Hanif; Sailesh Sankaranarayanan; Sunjay Paul; Paul Sutcliffe; Krishnarajah Nirantharakumar
Journal:  JMIR Diabetes       Date:  2020-11-18
  7 in total

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