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01.12.2019 | Research article | Ausgabe 1/2019 Open Access

BMC Medical Informatics and Decision Making 1/2019

The effect of computerized decision support systems on cardiovascular risk factors: a systematic review and meta-analysis

Zeitschrift:
BMC Medical Informatics and Decision Making > Ausgabe 1/2019
Autoren:
T. Katrien J. Groenhof, Folkert W. Asselbergs, Rolf H. H. Groenwold, Diederick E. Grobbee, Frank L. J. Visseren, Michiel L. Bots, on behalf of the UCC-SMART study group
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Electronic supplementary material

The online version of this article (https://​doi.​org/​10.​1186/​s12911-019-0824-x) contains supplementary material, which is available to authorized users.

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Abstract

Background

Cardiovascular risk management (CVRM) is notoriously difficult because of multi-morbidity and the different phenotypes and severities of cardiovascular disease. Computerized decision support systems (CDSS) enable the clinician to integrate the latest scientific evidence and patient information into tailored strategies. The effect on cardiovascular risk factor management is yet to be confirmed.

Methods

We performed a systematic review and meta-analysis evaluating the effects of CDSS on CVRM, defined as the change in absolute values and attainment of treatment goals of systolic blood pressure (SBP), low density lipoprotein cholesterol (LDL-c) and HbA1c. Also, CDSS characteristics related to more effective CVRM were identified. Eligible articles were methodologically appraised using the Cochrane risk of bias tool. We calculated mean differences, relative risks, and if appropriate (I2 < 70%), pooled the results using a random-effects model.

Results

Of the 14,335 studies identified, 22 were included. Four studies reported on SBP, 3 on LDL-c, 10 on CVRM in patients with type II diabetes and 5 on guideline adherence. The CDSSs varied considerably in technical performance and content. Heterogeneity of results was such that quantitative pooling was often not appropriate. Among CVRM patients, the results tended towards a beneficial effect of CDSS, but only LDL-c target attainment in diabetes patients reached statistical significance. Prompting, integration into the electronical health record, patient empowerment, and medication support were related to more effective CVRM.

Conclusion

We did not find a clear clinical benefit from CDSS in cardiovascular risk factor levels and target attainment. Some features of CDSS seem more promising than others. However, the variability in CDSS characteristics and heterogeneity of the results – emphasizing the immaturity of this research area - limit stronger conclusions. Clinical relevance of CDSS in CVRM might additionally be sought in the improvement of shared decision making and patient empowerment.
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