Original article
Digital Health Interventions for the Prevention of Cardiovascular Disease: A Systematic Review and Meta-analysis

https://doi.org/10.1016/j.mayocp.2014.12.026Get rights and content

Abstract

Objective

To assess the potential benefit of digital health interventions (DHIs) on cardiovascular disease (CVD) outcomes (CVD events, all-cause mortality, hospitalizations) and risk factors compared with non-DHIs.

Patients and Methods

We conducted a systematic search of PubMed, MEDLINE, EMBASE, Web of Science, Ovid, CINHAL, ERIC, PsychINFO, Cochrane, and Cochrane Central Register of Controlled Trials for articles published from January 1, 1990, through January 21, 2014. Included studies examined any element of DHI (telemedicine, Web-based strategies, e-mail, mobile phones, mobile applications, text messaging, and monitoring sensors) and CVD outcomes or risk factors. Two reviewers independently evaluated study quality utilizing a modified version of the Cochrane Collaboration risk assessment tool. Authors extracted CVD outcomes and risk factors for CVD such as weight, body mass index, blood pressure, and lipid levels from 51 full-text articles that met validity and inclusion criteria.

Results

Digital health interventions significantly reduced CVD outcomes (relative risk, 0.61; 95% CI, 0.46-0.80; P<.001; I2=22%). Concomitant reductions in weight (−2.77 lb [95% CI, −4.49 to −1.05 lb]; P<.002; I2=97%) and body mass index (−0.17 kg/m2 [95% CI, −0.32 kg/m2 to −0.01 kg/m2]; P=.03; I2=97%) but not blood pressure (−1.18 mm Hg [95% CI, −2.93 mm Hg to 0.57 mm Hg]; P=.19; I2=100%) were found in these DHI trials compared with usual care. In the 6 studies reporting Framingham risk score, 10-year risk percentages were also significantly improved (−1.24%; 95% CI, −1.73% to −0.76%; P<.001; I2=94%). Results were limited by heterogeneity not fully explained by study population (primary or secondary prevention) or DHI modality.

Conclusion

Overall, these aggregations of data provide evidence that DHIs can reduce CVD outcomes and have a positive impact on risk factors for CVD.

Section snippets

Data Sources and Searches

This systematic review was conducted in accordance with PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines.14 We included all RCTs and observational/cohort studies published between January 1, 1990, and January 21, 2014, that examined any element of DHI (telemedicine, Web-based strategies, e-mail, mobile phones, mobile applications, text messaging, and monitoring sensors) and impact on CVD. We intentionally and broadly included any studies of adult patients

Results

Fifty-one studies met criteria for full-text review and were included in the systematic review, with 9 studies providing analyzable CVD outcome data. A summary of studies reporting CVD outcomes is presented in the Table.20, 21, 22, 23, 24, 25, 26, 27, 28 Risk of bias among studies reporting CVD outcomes was predominantly low apart from a consistent lack of participant blinding (Figure 2) with a funnel plot included (Supplemental Figure 2, available online at http://www.mayoclinicproceedings.org

Discussion

This systematic review and meta-analysis reveals that DHI has a beneficial effect on CVD risk factors and outcomes. Applying an inclusive definition of DHI broadly applied to studies ranging from 2 to 36 months, we found a CVD morbidity and all-cause mortality benefit for secondary CVD prevention and HF groups, with primary prevention populations having benefit with regard to weight loss, BMI, SBP, total cholesterol, and LDL cholesterol. However, there was no clear benefit of DHI in primary

Conclusion

The data synthesized and analyzed in this systematic review show a net benefit of DHI on overall CVD outcomes (CVD events, hospitalizations, and all-cause mortality) compared with usual care. These gains are largely driven by improvements in CVD outcomes among higher-risk populations such as patients with HF or those targeting secondary CVD prevention. Digital health interventions were also associated with improvement in risk factors for CVD in primary prevention studies, suggesting the

Acknowledgments

There was no direct role of the funding agencies in this study or article. The views expressed are those of the authors and do not necessarily reflect those of the National Institutes of Health. All authors contributed to the work.

We thank the Clinial and Translational Science program of Mayo Clinic including the faculty and staff of course CTSC 5740 (Dr M. Hassan Murad, Dr Victor Montori, and Ms Jesse Welsh) for their guidance. We greatly appreciate the 28 authors who responded to our request

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    Grant support: This work was supported by funding from the BIRD Foundation, by National Institutes of Health grants HL-92954 and AG-31750, and by the Mayo Foundation.

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