Do clinical decision support tools improve quality of care outcomes in the primary prevention of cardiovascular disease: A systematic review and meta-analysis.

Blood glucose Blood pressure Cardiovascular disease Clinical decision support tool Lipid levels Meta-analysis Primary prevention

Journal

American journal of preventive cardiology
ISSN: 2666-6677
Titre abrégé: Am J Prev Cardiol
Pays: Netherlands
ID NLM: 101769122

Informations de publication

Date de publication:
Dec 2024
Historique:
received: 12 05 2024
revised: 20 08 2024
accepted: 05 09 2024
medline: 17 10 2024
pubmed: 17 10 2024
entrez: 17 10 2024
Statut: epublish

Résumé

To assess the effectiveness of Clinical Decision Support Tools (CDSTs) in enhancing the quality of care outcomes in primary cardiovascular disease (CVD) prevention. A systematic review was undertaken in accordance with PRISMA guidelines, and included searches in Ovid Medline, Ovid Embase, CINAHL, and Scopus. Eligible studies were randomized controlled trials of CDSTs comprising digital notifications in electronic health systems (EHS/EHR) in various primary healthcare settings, published post-2013, in patients with CVD risks and without established CVD. Two reviewers independently assessed risk of bias using the Cochrane RoB-2 tool. Attainment of clinical targets was analysed using a Restricted Maximum Likelihood random effects meta-analysis. Other relevant outcomes were narratively synthesised due to heterogeneity of studies and outcome metrics. Meta-analysis revealed CDSTs showed improvement in systolic (Mean Standardised Difference (MSD)=0.39, 95 %CI=-0.31, -1.10) and diastolic blood pressure target achievement (MSD=0.34, 95 %CI=-0.24, -0.92), but had no significant impact on lipid (MSD=0.01; 95 %CI=-0.10, 0.11) or glucose target attainment (MSD=-0.19, 95 %CI=-0.66, 0.28). The CDSTs with active prompts increased statin initiation and improved patients' adherence to clinical appointments but had minimal effect on other medications and on enhancing adherence to medication. CDSTs were found to be effective in improving blood pressure clinical target attainments. However, the presence of multi-layered barriers affecting the uptake, longer-term use and active engagement from both clinicians and patients may hinder the full potential for achieving other quality of care outcomes. The study aimed to evaluate how Clinical Decision Support Tools (CDSTs) impact the quality of care for primary cardiovascular disease (CVD) management. CDSTs are tools designed to support healthcare professionals in delivering the best possible care to patients by providing timely and relevant information at the point of care (ie. digital notifications in electronic health systems). Although CDST are designed to improve the quality of healthcare outcomes, the current evidence of their effectiveness is inconsistent. Therefore, we conducted a systematic review with meta-analysis, to quantify the effectiveness of CDSTs. The eligibility criteria targeted patients with CVD risk factors, but without diagnosed CVD. The meta-analysis found that CDSTs showed improvement in systolic and diastolic blood pressure target achievement but did not significantly impact lipid or glucose target attainment. Specifically, CDSTs showed effectiveness in increasing statin prescribing but not antihypertensives or antidiabetics prescribing. Interventions with CDSTs aimed at increasing screening programmes were effective for patients with kidney diseases and high-risk patients, but not for patients with diabetes or teenage patients with hypertension. Alerts were effective in improving patients' adherence to clinical appointments but not in medication adherence. This study suggests CDSTs are effective in enhancing a limited number of quality of care outcomes in primary CVD prevention, but there is need for future research to explore the mechanisms and context of multiple barriers that may hinder the full potential for cardiovascular health outcomes to be achieved.

Identifiants

pubmed: 39416379
doi: 10.1016/j.ajpc.2024.100855
pii: S2666-6677(24)00223-X
pmc: PMC11481602
doi:

Types de publication

Journal Article

Langues

eng

Pagination

100855

Informations de copyright

© 2024 The Authors. Published by Elsevier B.V.

Déclaration de conflit d'intérêts

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Auteurs

Iva Buzancic (I)

Faculty of Pharmacy and Biochemistry, University of Zagreb, A. Kovacica 1, Zagreb, Croatia.
City Pharmacies Zagreb, Ulica kralja Drzislava 6, Zagreb, Croatia.

Harvey Jia Wei Koh (HJW)

School of Public Health and Preventive Medicine, Monash University, 553 St Kilda Road, Alfred Precinct, Melbourne, VIC. 3004, Australia.

Caroline Trin (C)

School of Public Health and Preventive Medicine, Monash University, 553 St Kilda Road, Alfred Precinct, Melbourne, VIC. 3004, Australia.

Caitlin Nash (C)

School of Public Health and Preventive Medicine, Monash University, 553 St Kilda Road, Alfred Precinct, Melbourne, VIC. 3004, Australia.

Maja Ortner Hadziabdic (M)

Faculty of Pharmacy and Biochemistry, University of Zagreb, A. Kovacica 1, Zagreb, Croatia.

Dora Belec (D)

Faculty of Pharmacy and Biochemistry, University of Zagreb, A. Kovacica 1, Zagreb, Croatia.

Sophia Zoungas (S)

School of Public Health and Preventive Medicine, Monash University, 553 St Kilda Road, Alfred Precinct, Melbourne, VIC. 3004, Australia.

Ella Zomer (E)

School of Public Health and Preventive Medicine, Monash University, 553 St Kilda Road, Alfred Precinct, Melbourne, VIC. 3004, Australia.

Lachlan Dalli (L)

Stroke and Ageing Research, School of Clinical Sciences at Monash Health, Monash University, Level 2, 631 Blackburn Road, Clayton, VIC, 3168, Australia.

Zanfina Ademi (Z)

School of Public Health and Preventive Medicine, Monash University, 553 St Kilda Road, Alfred Precinct, Melbourne, VIC. 3004, Australia.
Health Economics and Policy Evaluation Research Group, Centre for Medicine Use and Safety, Faculty of Pharmacy and Pharmaceutical Sciences, Level 1, 407 Royal Parade, Parkville, VIC, 3052, Australia.
Department of Neuroscience, Central Clinical School, Monash University, Melbourne VIC 3004, Australia.
School of Pharmacy, Faculty of Health Sciences, Kuopio Campus, University of Eastern Finland, Kuopio, Finland.

Bryan Chua (B)

School of Public Health and Preventive Medicine, Monash University, 553 St Kilda Road, Alfred Precinct, Melbourne, VIC. 3004, Australia.

Stella Talic (S)

School of Public Health and Preventive Medicine, Monash University, 553 St Kilda Road, Alfred Precinct, Melbourne, VIC. 3004, Australia.

Classifications MeSH