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Digital Health Intervention as an Adjunct to Cardiac Rehabilitation Reduces Cardiovascular Risk Factors and Rehospitalizations

  • R. Jay Widmer
  • Thomas G. Allison
  • Lilach O. Lerman
  • Amir LermanEmail author
Article

Abstract

Cardiac rehabilitation (CR) following myocardial infarction is vastly underused. As such, the aim of this study was to test a digital health intervention (DHI) as an adjunct to CR. Patients undergoing standard Mayo Clinic CR were recruited prior to CR (n = 25) or after 3 months CR (n = 17). Changes in risk factors and rehospitalizations plus emergency department (ED) visits were assessed after 3 months. Patients assigned to DHI during CR had significant reductions in weight (−4.0 ± 5.2 kg, P = .001), blood pressure (−10.8 ± 13.5 mmHg, P = .0009), and the group using DHI after 3 months of CR had significant reductions in weight (−2.5 ± 3.8 kg, P = .04) and systolic BP (−12.6 ± 12.4 mmHg, P = .001) compared to the control groups. Both DHI groups also displayed significant reductions in rehospitalizations/ED visits (−37.9 %, P = 0.01 and −28 %, P = .04, respectively). This study suggests that a guideline-driven DHI CR program can augment secondary prevention strategies during usual CR by improving risk factors for repeat events.

Keywords

Digital health Mobile health Cardiovascular disease Cardiac rehabilitation Secondary prevention Online Health Monitoring 

Notes

Acknowledgments

The authors thank the Binational Industrial Research and Development (BIRD) Foundation for their financial support. We also extend appreciation to Arturo Weschler, MD and Healarium Inc. an e-Health company, Dallas TX for their assistance in data de-identification and gathering. The sponsors and granting institutions had no impact on the results or preparation of the manuscript.

Compliance with Ethical Standards

Funding

This study was funded by Binational Industrial Research and Development (BIRD) Foundation #1303. This publication was also made possible by CTSA Grant Number UL1 TR000135 from the National Center for Advancing Translational Sciences (NCATS), a component of the National Institutes of Health (NIH). Its contents are solely the responsibility of the authors and do not necessarily represent the official view of NIH.

Conflict of Interest

The authors declare that they have no conflict of interest.

Ethical Approval

All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki Declaration and its later amendments or comparable ethical standards.

Informed Consent

Informed consent was obtained from all individual participants included in the study.

References

  1. 1.
    Roger, V., Go, A. S., Lloyd-Jones, D. M., Benjamin, E. J., Berry, J. D., Borden, W. B., Bravata, D. M., Dai, S., Ford, E. S., Fox, C. S., Fullerton, H. J., Gillespie, C., Hailpern, S. M., Heit, J. A., Howard, V. J., Kissela, B. M., Kittner, S. J., Lackland, D. T., Lichtman, J. H., Lisabeth, L. D., Makuc, D. M., Marcus, G. M., Marelli, A., Matchar, D. B., Moy, C. S., Mozaffarian, D., Mussolino, M. E., Nichol, G., Paynter, N. P., Soliman, E. Z., Sorlie, P. D., Sotoodehnia, N., Turan, T. N., Virani, S. S., Wong, N. D., Woo, D., Turner, M. B., & American Heart Association Statistics Committee and Stroke Statistics Subcommittee. (2012). Executive summary: heart disease and stroke statistics--2012 update: a report from the American Heart Associatio. Circulation, 125(1), 188–197.PubMedCrossRefGoogle Scholar
  2. 2.
    Rosamond, W., Flegal, K., Furie, K., et al. (2008). Heart disease and stroke statistics—2008 update: a report from the American Heart Association Statistics Committee and Stroke Statistics Subcommittee, Circulation. Circulation, 117, e25–e146.PubMedCrossRefGoogle Scholar
  3. 3.
    Yusef, S., et al. (2004). Effects of potentially modifiable risk factors associated with myocardial infarction in 52 countries (the INTERHEART study): case controlled study. Lancet, 342, 937–952.CrossRefGoogle Scholar
  4. 4.
    Go, A., Mozaffarian, D., Roger, V. L., Benjamin, E. J., Berry, J. D., Borden, W. B., Bravata, D. M., Dai, S., Ford, E. S., Fox, C. S., Franco, S., Fullerton, H. J., Gillespie, C., Hailpern, S. M., Heit, J. A., Howard, V. J., Huffman, M. D., Kissela, B. M., Kittner, S. J., Lackland, D. T., Lichtman, J. H., Lisabeth, L. D., Magid, D., Marcus, G. M., Marelli, A., Matchar, D. B., McGuire, D. K., Mohler, E. R., Moy, C. S., Mussolino, M. E., Nichol, G., Paynter, N. P., Schreiner, P. J., Sorlie, P. D., Stein, J., Turan, T. N., Virani, S. S., Wong, N. D., Woo, D., & Turner, M. B. (2013). American Heart Association Statistics Committee and Stroke Statistics Subcommittee., Executive summary: heart disease and stroke statistics–2013 update: a report from the American Heart Association. Circulation, 127(1), 143–152.PubMedCrossRefGoogle Scholar
  5. 5.
    Pfuntner, A., Wier, L. M., & Steiner, C. (2013). Costs for Hospital Stays in the United States, 2010. HCUP Statistical Brief #146. Rockville: Agency for Healthcare Research and Quality.Google Scholar
  6. 6.
    Likosky, D., Zhou, W., Malenka, D. J., Borden, W. B., Nallamothu, B. K., & Skinner, J. S. (2013). Growth in medicare expenditures for patients with acute myocardial infarction: a comparison of 1998 through 1999 and 2008. JAMA Internal Medicine, 173, 2055–2061.PubMedCentralPubMedCrossRefGoogle Scholar
  7. 7.
    Dunlay, S., Weston, S. A., Killian, J. M., Bell, M. R., Jaffe, A. S., & Roger, V. L. (2012). Thirty-day rehospitalizations after acute myocardial infarction: a cohort study. Annals of Internal Medicine, 157(1), 11–18.PubMedCentralPubMedCrossRefGoogle Scholar
  8. 8.
    Maddox, T., Reid, K. J., Rumsfeld, J. S., & Spertus, J. A. (2007). One-year health status outcomes of unstable angina versus myocardial infarction: a prospective, observational cohort study of ACS survivors. BMC Cardiovascular Disorders, 7, 28.PubMedCentralPubMedCrossRefGoogle Scholar
  9. 9.
    Khumri, T., Reid, K. J., Kosiborod, M., Spertus, J. A., & Main, M. L. (2009). Usefulness of left ventricular diastolic dysfunction as a predictor of one-year rehospitalization in survivors of acute myocardial infarction. American Journal of Cardiology, 103(1), 17–21.PubMedCrossRefGoogle Scholar
  10. 10.
    Balducci, S., for the Italian Diabetes Exercise Study, Investigators, et al. (2010). Effect of an intensive exercise intervention strategy on modifiable cardiovascular risk factors in subjects with type 2 diabetes mellitus: a randomized controlled trial: the italian diabetes and exercise study (IDES). Archives of Internal Medicine, 170(20), 1794–1803.PubMedCrossRefGoogle Scholar
  11. 11.
    Goel, K., Lennon, R. J., Tilbury, R. T., Squires, R. W., & Thomas, R. J. (2011). Impact of cardiac rehabilitation on mortality and cardiovascular events after percutaneous coronary intervention in the community. Circulation, 123(21), 2344–2352.PubMedCrossRefGoogle Scholar
  12. 12.
    Schroeder, S. (2007). Shattuck Lecture. We can do better–improving the health of the American people. New England Journal of Medicine, 357(12), 1221–1228.PubMedCrossRefGoogle Scholar
  13. 13.
    Suaya, J., Shepard, D. S., Normand, S. L., Ades, P. A., Prottas, J., & Stason, W. B. (2007). Use of cardiac rehabilitation by Medicare beneficiaries after myocardial infarction or coronary bypass surgery. Circulation, 116(15), 1653–1662.PubMedCrossRefGoogle Scholar
  14. 14.
    Brown, T., Hernandez, A. F., Bittner, V., Cannon, C. P., Ellrodt, G., Liang, L., Peterson, E. D., Piña, I. L., Safford, M. M., & Fonarow, G. C. (2009). Predictors of cardiac rehabilitation referral in coronary artery disease patients: findings from the American Heart Association’s get with the guidelines program. Journal of the American College of Cardiology, 54(6), 515–521.PubMedCentralPubMedCrossRefGoogle Scholar
  15. 15.
    Cooper, A. (2002). Factors associated with cardiac rehabilitation attendance: a systematic review of the literature. Clinical Rehabilitation, 16(5), 541–552.PubMedCrossRefGoogle Scholar
  16. 16.
    Corra, U., et al. (2010). Secondary prevention through cardiac rehabilitation: physical activity counselling and exercise training. European Heart Journal, 31, 1967–1974. doi: 10.1093/eurheartj/ehq236.PubMedCrossRefGoogle Scholar
  17. 17.
    Mattila, E., et al. (2008). Mobile diary for wellness management—results on usage and usability in two user studies. IEEE Transactions on Information Technology in Biomedicine, 12(4), 501–512.PubMedCrossRefGoogle Scholar
  18. 18.
    McAlister, F., Lawson, F. M., Teo, K. K., & Armstrong, P. W. (2001). Randomised trials of secondary prevention programmes in coronary heart disease: systematic review. British Medical Journal, 323(7319), 957–962.PubMedCentralPubMedCrossRefGoogle Scholar
  19. 19.
    McKellar, S., et al. (2008). Development of the diet habits questionnaire for use in cardiac rehabilitation. Australian Journal of Primary Health, 14(3), 43–47.Google Scholar
  20. 20.
    Scott, I., Lindsay, K. A., & Harden, H. E. (2003). Utilisation of outpatient cardiac rehabilitation in Queensland. Medical Journal of Australia, 179(7), 332–333.Google Scholar
  21. 21.
    Teo, K., Lear, S., Islam, S., Mony, P., Dehghan, M., Li, W., Rosengren, A., Lopez-Jaramillo, P., Diaz, R., Oliveira, G., Miskan, M., Rangarajan, S., Iqbal, R., Ilow, R., Puone, T., Bahonar, A., Gulec, S., Darwish, E. A., Lanas, F., Vijaykumar, K., Rahmarn, O., Chifamba, J., Hou, Y., Li, N., Yusuf, S., & PURE Investigators. (2013). Prevalence of a healthy lifestyle among individuals with cardiovascular disease in high-, middle- and low-income countries: The Prospective Urban Rural Epidemiology (PURE) study. JAMA, 309(15), 1613–1621.PubMedCrossRefGoogle Scholar
  22. 22.
    Hawn, C. (2009). Take two aspirin and tweet me in the morning: how twitter, facebook, and other social media are reshaping health care. Health Affairs, 28(2), 361–368.PubMedCrossRefGoogle Scholar
  23. 23.
    Lefebvre, R. (2007). The new technology: the consumer as participant rather than target audience. Social Marketing Quarterly, 13, 31–42.CrossRefGoogle Scholar
  24. 24.
    Freeman, B., & Chapman, S. (2012). Measuring interactivity on tobacco control websites. Journal of Health Communication, 17, 857–865.PubMedCrossRefGoogle Scholar
  25. 25.
    Beatty, A., Fukuoka, Y., & Whooley, M. A. (2013). Using mobile technology for cardiac rehabilitation: a review and framework for development and evaluation. Journal of the American Heart Association, 2(6), e000568.PubMedCentralPubMedCrossRefGoogle Scholar
  26. 26.
    Widmer, R., Allison, T. G., Keane, B., Dallas, A., Lerman, L. O., & Lerman, A. (2014). Using an online, personalized program reduces cardiovascular risk factor profiles in a motivated, adherent population of participants. American Heart Journal, 167(1), 93–100.PubMedCrossRefGoogle Scholar
  27. 27.
    Clark, M., Warren, B. A., Hagen, P. T., Johnson, B. D., Jenkins, S. M., Werneburg, B. L., & Olsen, K. D. (2011). Stress level, health behaviors, and quality of life in employees joining a wellness center. American Journal of Health Promotion, 26(1), 21–25.PubMedCrossRefGoogle Scholar
  28. 28.
    Van Weel, C. (1993). Functional status in primary care: COOP/WONCA charts. Disability and Rehabilitation, 15, 96–101.PubMedCrossRefGoogle Scholar
  29. 29.
    Glanz, K., & Bishop, D. B. (2010). The role of behavioral science theory in development and implementation of public health interventions. Annual Review of Public Health, 31, 399–418.PubMedCrossRefGoogle Scholar
  30. 30.
    Balady, G., Ades, P. A., Bittner, V. A., Franklin, B. A., Gordon, N. F., Thomas, R. J., Tomaselli, G. F., & Yancy, C. W. (2011). Referral, enrollment, and delivery of cardiac rehabilitation/secondary prevention programs at clinical centers and beyond: a presidential advisory from the American Heart Association. Circulation, 124, 2951–2960.PubMedCrossRefGoogle Scholar
  31. 31.
    Thomas, R., King, M., Lui, K., Oldridge, N., Piña, I. L., & Spertus, J. (2010). AACVPR/ACCF/AHA 2010 update: performance measures on cardiac rehabilitation for referral to cardiac rehabilitation/secondary prevention services: a report of the American Association of Cardiovascular and Pulmonary Rehabilitation and the American College of Cardiology Foundation/American Heart Association Task Force on Performance Measures (Writing Committee to Develop Clinical Performance Measures for Cardiac Rehabilitation). Circulation, 122(13), 1342–1350.PubMedCrossRefGoogle Scholar
  32. 32.
    Smith, A., Smartphone ownership 2013. http://pewinternet.org/Reports/2013/Smartphone-Ownership-2013.aspx. 2013.
  33. 33.
    Zickuhr, K., & Madden, M. (2012). Older adults and internet use. Pew Internet & American Life Project http://www.pewinternet.org//media//Files/Reports/2012/PIP_Older_adults_and_internet_use.pdf.
  34. 34.
    Fox, S., Duggan, M. (2012). Pew Research Center’s Internet & American Life Project. http://pewinternet.org/Reports/2012/Mobile-Health.aspx.
  35. 35.
    Arrigo, I., Brunner-LaRocca, H., Lefkovits, M., Pfisterer, M., & Hoffmann, A. (2008). Comparative outcome one year after formal cardiac rehabilitation: the effects of a randomized intervention to improve exercise adherence. European Journal of Cardiovascular Prevention and Rehabilitation, 15(3), 306–311.PubMedCrossRefGoogle Scholar
  36. 36.
    Willich, S., Müller-Nordhorn, J., Kulig, M., Binting, S., Gohlke, H., Hahmann, H., Bestehorn, K., Krobot, K., Völler, H., & PIN Study Group. (2001). Cardiac risk factors, medication, and recurrent clinical events after acute coronary disease; a prospective cohort study. European Heart Journal, 22(4), 307–313.PubMedCrossRefGoogle Scholar
  37. 37.
    Shah, N., Dunlay, S. M., Ting, H. H., Montori, V. M., Thomas, R. J., Wagie, A. E., & Roger, V. L. (2009). Long-term medication adherence after myocardial infarction: experience of a community. American Journal of Medicine, 122(10), e7–e13.PubMedCrossRefGoogle Scholar
  38. 38.
    Hansen, D., Dendale, P., Raskin, A., Schoonis, A., Berger, J., Vlassak, I., & Meeusen, R. (2010). Long-term effect of rehabilitation in coronary artery disease patients: randomized clinical trial of the impact of exercise volume. Clinical Rehabilitation, 24(4), 319–327.PubMedCrossRefGoogle Scholar
  39. 39.
    Gore, J., Peterson, E., Amin, A., Anderson, F. A., Jr., Dasta, J. F., Levy, P. D., O’Neil, B. J., Sung, G. Y., Varon, J., Wyman, A., Granger, C. B., & STAT Investigators. (2010). Predictors of 90-day readmission among patients with acute severe hypertension. The cross-sectional observational Studying the Treatment of Acute hyperTension (STAT) study. American Heart Journal, 160(3), 521–527.PubMedCrossRefGoogle Scholar
  40. 40.
    Dunlay, S., Pack, Q. R., Thomas, R. J., Killian, J. M., & Roger, V. L. (2014). Participation in cardiac rehabilitation, readmissions, and death after acute myocardial infarction. American Journal of Medicine, 127(6), 538–546.PubMedCentralPubMedCrossRefGoogle Scholar
  41. 41.
    Rodgers, W., Murray, T. C., Selzler, A. M., & Norman, P. (2013). Development and impact of exercise self-efficacy types during and after cardiac rehabilitation. Rehabilitation Psychology, 58(2), 178–184.PubMedCrossRefGoogle Scholar
  42. 42.
    Webb, T., Joseph, J., Yardley, L., & Michie, S. (2010). Using the internet to promote health behavior change: a systematic review and meta-analysis of the impact of theoretical basis, use of behavior change techniques, and mode of delivery on efficacy. Journal of Medical Internet Research, 12, e4.PubMedCentralPubMedCrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media New York 2015

Authors and Affiliations

  • R. Jay Widmer
    • 1
  • Thomas G. Allison
    • 1
  • Lilach O. Lerman
    • 2
  • Amir Lerman
    • 1
    Email author
  1. 1.Division of Cardiovascular Diseases, Department of Internal MedicineMayo Clinic and College of MedicineRochesterUSA
  2. 2.Division of Nephrology and Hypertension, Department of Internal MedicineMayo Clinic and College of MedicineRochesterUSA

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