Smartphone Cardiac Rehabilitation, Assisted Self-Management Versus Usual Care: Protocol for a Multicenter Randomized Controlled Trial to Compare Effects and Costs Among People With Coronary Heart Disease

Jonathan Charles Rawstorn, Kylie Ball, Brian Oldenburg, Clara K Chow, Sarah A McNaughton, Karen Elaine Lamb, Lan Gao, Marj Moodie, John Amerena, Voltaire Nadurata, Christopher Neil, Stuart Cameron, Ralph Maddison, Jonathan Charles Rawstorn, Kylie Ball, Brian Oldenburg, Clara K Chow, Sarah A McNaughton, Karen Elaine Lamb, Lan Gao, Marj Moodie, John Amerena, Voltaire Nadurata, Christopher Neil, Stuart Cameron, Ralph Maddison

Abstract

Background: Alternative evidence-based cardiac rehabilitation (CR) delivery models that overcome significant barriers to access and delivery are needed to address persistent low utilization. Models utilizing contemporary digital technologies could significantly improve reach and fidelity as complementary alternatives to traditional center-based programs.

Objective: The aim of this study is to compare the effects and costs of the innovative Smartphone Cardiac Rehabilitation, Assisted self-Management (SCRAM) intervention with usual care CR.

Methods: In this investigator-, assessor-, and statistician-blinded parallel 2-arm randomized controlled trial, 220 adults (18+ years) with coronary heart disease are being recruited from 3 hospitals in metropolitan and regional Victoria, Australia. Participants are randomized (1:1) to receive advice to engage with usual care CR or the SCRAM intervention. SCRAM is a 24-week dual-phase intervention that includes 12 weeks of real-time remote exercise supervision and coaching from exercise physiologists, which is followed by 12 weeks of data-driven nonreal-time remote coaching via telephone. Both intervention phases include evidence- and theory-based multifactorial behavior change support delivered via smartphone push notifications. Outcomes assessed at baseline, 12 weeks, and 24 weeks include maximal aerobic exercise capacity (primary outcome at 24 weeks), modifiable cardiovascular risk factors, exercise adherence, secondary prevention self-management behaviors, health-related quality of life, and adverse events. Economic and process evaluations will determine cost-effectiveness and participant perceptions of the treatment arms, respectively.

Results: The trial was funded in November 2017 and received ethical approval in June 2018. Recruitment began in November 2018. As of September 2019, 54 participants have been randomized into the trial.

Conclusions: The innovative multiphase SCRAM intervention delivers real-time remote exercise supervision and evidence-based self-management behavioral support to participants, regardless of their geographic proximity to traditional center-based CR facilities. Our trial will provide unique and valuable information about effects of SCRAM on outcomes associated with cardiac and all-cause mortality, as well as acceptability and cost-effectiveness. These findings will be important to inform health care providers about the potential for innovative program delivery models, such as SCRAM, to be implemented at scale, as a complement to existing CR programs. The inclusion of a cohort comprising metropolitan-, regional-, and rural-dwelling participants will help to understand the role of this delivery model across health care contexts with diverse needs.

Trial registration: Australian New Zealand Clinical Trials Registry (ACTRN): 12618001458224; anzctr.org.au/Trial/Registration/TrialReview.aspx?id=374508.

International registered report identifier (irrid): DERR1-10.2196/15022.

Keywords: behavioral medicine; coronary artery disease; costs and cost analysis; exercise; health services accessibility; mHealth; myocardial ischemia; telemedicine; telerehabilitation.

Conflict of interest statement

Conflicts of Interest: The SCRAM platform and intervention content build on work initiated at the University of Auckland’s National Institute for Health Innovation. The software and intervention content were developed by Deakin University’s Institute for Physical Activity and Nutrition—led by RM, JCR, and SC—in conjunction with cardiac rehabilitation specialists and exercise scientists. We declare no further financial or competing interests.

©Jonathan Charles Rawstorn, Kylie Ball, Brian Oldenburg, Clara K Chow, Sarah A McNaughton, Karen Elaine Lamb, Lan Gao, Marj Moodie, John Amerena, Voltaire Nadurata, Christopher Neil, Stuart Cameron, Ralph Maddison. Originally published in JMIR Research Protocols (http://www.researchprotocols.org), 27.01.2020.

Figures

Figure 1
Figure 1
Consolidated Standards of Reporting Trials design schematic. CR: cardiac rehabilitation; SCRAM: Smartphone Cardiac Rehabilitation, Assisted self-Management.
Figure 2
Figure 2
Smartphone Cardiac Rehabilitation, Assisted self-Management mobile health platform components.

References

    1. Piepoli MF, Corrà U, Adamopoulos S, Benzer W, Bjarnason-Wehrens B, Cupples M, Dendale P, Doherty P, Gaita D, Höfer S, McGee H, Mendes M, Niebauer J, Pogosova N, Garcia-Porrero E, Rauch B, Schmid JP, Giannuzzi P. Secondary prevention in the clinical management of patients with cardiovascular diseases. Core components, standards and outcome measures for referral and delivery: a policy statement from the cardiac rehabilitation section of the European Association for Cardiovascular Prevention & Rehabilitation. Endorsed by the Committee for Practice Guidelines of the European Society of Cardiology. Eur J Prev Cardiol. 2014 Jun;21(6):664–81. doi: 10.1177/2047487312449597.2047487312449597
    1. Cowie A, Buckley J, Doherty P, Furze G, Hayward J, Hinton S, Jones J, Speck L, Dalal H, Mills J, British Association for Cardiovascular Prevention and Rehabilitation (BACPR) Standards and core components for cardiovascular disease prevention and rehabilitation. Heart. 2019 Apr;105(7):510–5. doi: 10.1136/heartjnl-2018-314206. heartjnl-2018-314206
    1. Woodruffe S, Neubeck L, Clark RA, Gray K, Ferry C, Finan J, Sanderson S, Briffa TG. Australian Cardiovascular Health and Rehabilitation Association (ACRA) core components of cardiovascular disease secondary prevention and cardiac rehabilitation 2014. Heart Lung Circ. 2015 May;24(5):430–41. doi: 10.1016/j.hlc.2014.12.008.S1443-9506(14)00822-1
    1. Balady GJ, Williams MA, Ades PA, Bittner V, Comoss P, Foody JA, Franklin B, Sanderson B, Southard D, American Heart Association Exercise‚ Cardiac Rehabilitation‚Prevention Committee. Council on Clinical Cardiology. Councils on Cardiovascular Nursing‚ Epidemiology and Prevention‚Nutrition‚ Physical Activity‚Metabolism. American Association of Cardiovascular and Pulmonary Rehabilitation Core components of cardiac rehabilitation/secondary prevention programs: 2007 update: a scientific statement from the American Heart Association Exercise, Cardiac Rehabilitation, and Prevention Committee, the Council on Clinical Cardiology; the Councils on Cardiovascular Nursing, Epidemiology and Prevention, and Nutrition, Physical Activity, and Metabolism; and the American Association of Cardiovascular and Pulmonary Rehabilitation. J Cardiopulm Rehabil Prev. 2007;27(3):121–9. doi: 10.1097/01.HCR.0000270696.01635.aa.01273116-200705000-00001
    1. Suaya JA, Shepard DS, Normand ST, Ades PA, Prottas J, Stason WB. Use of cardiac rehabilitation by Medicare beneficiaries after myocardial infarction or coronary bypass surgery. Circulation. 2007 Oct 9;116(15):1653–62. doi: 10.1161/CIRCULATIONAHA.107.701466.CIRCULATIONAHA.107.701466
    1. Neubeck L, Freedman SB, Clark AM, Briffa T, Bauman A, Redfern J. Participating in cardiac rehabilitation: a systematic review and meta-synthesis of qualitative data. Eur J Prev Cardiol. 2012 Jun;19(3):494–503. doi: 10.1177/1741826711409326.
    1. Inglis SC, Clark RA, McAlister FA, Ball J, Lewinter C, Cullington D, Stewart S, Cleland JG. Structured telephone support or telemonitoring programmes for patients with chronic heart failure. Cochrane Database Syst Rev. 2010 Aug 4;(8):CD007228. doi: 10.1002/14651858.CD007228.pub2.
    1. Jones M, Jolly K, Raftery J, Lip GY, Greenfield S, BRUM Steering Committee 'DNA' may not mean 'did not participate': a qualitative study of reasons for non-adherence at home- and centre-based cardiac rehabilitation. Fam Pract. 2007 Sep;24(4):343–57. doi: 10.1093/fampra/cmm021.cmm021
    1. Worringham C, Rojek A, Stewart I. Development and feasibility of a smartphone, ECG and GPS based system for remotely monitoring exercise in cardiac rehabilitation. PLoS One. 2011 Feb 9;6(2):e14669. doi: 10.1371/journal.pone.0014669.
    1. Maddison R, Rawstorn JC, Stewart RA, Benatar J, Whittaker R, Rolleston A, Jiang Y, Gao L, Moodie M, Warren I, Meads A, Gant N. Effects and costs of real-time cardiac telerehabilitation: randomised controlled non-inferiority trial. Heart. 2019 Jan;105(2):122–9. doi: 10.1136/heartjnl-2018-313189. heartjnl-2018-313189
    1. Marchionni N, Fattirolli F, Fumagalli S, Oldridge N, del Lungo F, Morosi L, Burgisser C, Masotti G. Improved exercise tolerance and quality of life with cardiac rehabilitation of older patients after myocardial infarction: results of a randomized, controlled trial. Circulation. 2003 May 6;107(17):2201–6. doi: 10.1161/01.CIR.0000066322.21016.4A.01.CIR.0000066322.21016.4A
    1. Anderson L, Sharp G, Norton R, Dalal H, Dean S, Jolly K, Cowie A, Zawada A, Taylor RS. Home-based versus centre-based cardiac rehabilitation. Cochrane Database Syst Rev. 2017 Jun 30;6:CD007130. doi: 10.1002/14651858.CD007130.pub4.
    1. Jin K, Khonsari S, Gallagher R, Gallagher P, Clark AM, Freedman B, Briffa T, Bauman A, Redfern J, Neubeck L. Telehealth interventions for the secondary prevention of coronary heart disease: a systematic review and meta-analysis. Eur J Cardiovasc Nurs. 2019 Apr;18(4):260–71. doi: 10.1177/1474515119826510.
    1. Rawstorn JC, Gant N, Direito A, Beckmann C, Maddison R. Telehealth exercise-based cardiac rehabilitation: a systematic review and meta-analysis. Heart. 2016 Aug 1;102(15):1183–92. doi: 10.1136/heartjnl-2015-308966.heartjnl-2015-308966
    1. Rawstorn JC, Gant N, Meads A, Warren I, Maddison R. Remotely delivered exercise-based cardiac rehabilitation: design and content development of a novel mHealth platform. JMIR Mhealth Uhealth. 2016 Jun 24;4(2):e57. doi: 10.2196/mhealth.5501. v4i2e57
    1. Rawstorn JC, Gant N, Rolleston A, Whittaker R, Stewart R, Benatar J, Warren I, Meads A, Jiang Y, Maddison R. End users want alternative intervention delivery models: usability and acceptability of the REMOTE-CR exercise-based cardiac telerehabilitation program. Arch Phys Med Rehabil. 2018 Nov;99(11):2373–7. doi: 10.1016/j.apmr.2018.06.027.S0003-9993(18)30919-5
    1. Blair J, Corrigall H, Angus N, Thompson D, Leslie S. Home versus hospital-based cardiac rehabilitation: a systematic review. Rural Remote Health. 2011;11(2):1532. 1532
    1. Frederix I, Solmi F, Piepoli MF, Dendale P. Cardiac telerehabilitation: a novel cost-efficient care delivery strategy that can induce long-term health benefits. Eur J Prev Cardiol. 2017 Nov;24(16):1708–17. doi: 10.1177/2047487317732274.
    1. Kraal JJ, van den Akker-Van Marle ME, Abu-Hanna A, Stut W, Peek N, Kemps HM. Clinical and cost-effectiveness of home-based cardiac rehabilitation compared to conventional, centre-based cardiac rehabilitation: Results of the FIT@Home study. Eur J Prev Cardiol. 2017 Aug;24(12):1260–73. doi: 10.1177/2047487317710803.
    1. Turk-Adawi K, Sarrafzadegan N, Grace SL. Global availability of cardiac rehabilitation. Nat Rev Cardiol. 2014 Oct;11(10):586–96. doi: 10.1038/nrcardio.2014.98. nrcardio.2014.98
    1. Brown TM, Hernandez AF, Bittner V, Cannon CP, Ellrodt G, Liang L, Peterson ED, Piña IL, Safford MM, Fonarow GC, American Heart Association Get With The Guidelines Investigators Predictors of cardiac rehabilitation referral in coronary artery disease patients: findings from the American Heart Association's Get With The Guidelines Program. J Am Coll Cardiol. 2009 Aug 4;54(6):515–21. doi: 10.1016/j.jacc.2009.02.080. S0735-1097(09)01639-8
    1. Chan A, Tetzlaff J, Altman D, Laupacis A, Gøtzsche PC, Krleža-Jerić K, Hróbjartsson A, Mann H, Dickersin K, Berlin J, Doré CJ, Parulekar W, Summerskill W, Groves T, Schulz K, Sox H, Rockhold F, Rennie D, Moher D. SPIRIT 2013 statement: defining standard protocol items for clinical trials. Ann Intern Med. 2013 Feb 5;158(3):200–7. doi: 10.7326/0003-4819-158-3-201302050-00583. 1556168
    1. Eysenbach G, CONSORT-EHEALTH Group CONSORT-EHEALTH: improving and standardizing evaluation reports of Web-based and mobile health interventions. J Med Internet Res. 2011 Dec 31;13(4):e126. doi: 10.2196/jmir.1923. v13i4e126
    1. Hoffmann TC, Glasziou PP, Boutron I, Milne R, Perera R, Moher D, Altman DG, Barbour V, Macdonald H, Johnston M, Lamb SE, Dixon-Woods M, McCulloch P, Wyatt JC, Chan A, Michie S. Better reporting of interventions: template for intervention description and replication (TIDieR) checklist and guide. Br Med J. 2014 Mar 7;348:g1687. doi: 10.1136/bmj.g1687.
    1. Schulz KF, Altman DG, Moher D, CONSORT Group CONSORT 2010 statement: updated guidelines for reporting parallel group randomised trials. Br Med J. 2010 Mar 23;340:c332. doi: 10.1136/bmj.c332.
    1. National Heart Foundation of Australia. 2016. [2019-03-13]. Australian Heart Maps .
    1. Hamilton S, Mills B, McRae S, Thompson S. Evidence to service gap: cardiac rehabilitation and secondary prevention in rural and remote Western Australia. BMC Health Serv Res. 2018 Jan 30;18(1):64. doi: 10.1186/s12913-018-2873-8. 10.1186/s12913-018-2873-8
    1. Jackson A, Higgins R, Murphy B, Rogerson M, Le Grande MR. Cardiac rehabilitation in Australia: a brief survey of program characteristics. Heart Lung Circ. 2018 Dec;27(12):1415–20. doi: 10.1016/j.hlc.2017.08.024.S1443-9506(17)31402-6
    1. Carr L, Bartee R, Dorozynski C, Broomfield J, Smith M, Smith D. Internet-delivered behavior change program increases physical activity and improves cardiometabolic disease risk factors in sedentary adults: results of a randomized controlled trial. Prev Med. 2008 May;46(5):431–8. doi: 10.1016/j.ypmed.2007.12.005.S0091-7435(07)00503-8
    1. Pescatello LS, Arena R, Riebe D, Thompson PD, editors. ACSM's Guidelines For Exercise Testing And Prescription. Ninth Edition. Philadelphia: Wolters Kluwer/Lippincott Williams & Wilkins; 2014.
    1. Bandura A. Self-efficacy: toward a unifying theory of behavioral change. Psychol Rev. 1977;84(2):191–215. doi: 10.1037//0033-295x.84.2.191.
    1. Deci E, Ryan RM. Intrinsic Motivation And Self-determination In Human Behavior. New York: Plenum Press; 1985.
    1. Leventhal H, Meyer D, Nerenz DR. The common sense representation of illness danger. In: Rachman SJ, editor. Contributions to Medical Psychology: Volume 2. NY, USA: Pergamon; 1980. pp. 7–30.
    1. Michie S, Richardson M, Johnston M, Abraham C, Francis J, Hardeman W, Eccles MP, Cane J, Wood CE. The behavior change technique taxonomy (v1) of 93 hierarchically clustered techniques: building an international consensus for the reporting of behavior change interventions. Ann Behav Med. 2013 Aug;46(1):81–95. doi: 10.1007/s12160-013-9486-6.
    1. Katch H, Mead H. The role of self-efficacy in cardiovascular disease self-management: a review of effective programs. Patient Intell. 2010;2:33–44. doi: 10.2147/pi.s12624.
    1. Lee L, Arthur A, Avis M. Using self-efficacy theory to develop interventions that help older people overcome psychological barriers to physical activity: a discussion paper. Int J Nurs Stud. 2008 Nov;45(11):1690–9. doi: 10.1016/j.ijnurstu.2008.02.012.S0020-7489(08)00059-X
    1. Maddison R, Pfaeffli L, Stewart R, Kerr A, Jiang Y, Rawstorn JC, Carter K, Whittaker R. The HEART Mobile Phone Trial: the partial mediating effects of self-efficacy on physical activity among cardiac patients. Front Public Health. 2014;2:56. doi: 10.3389/fpubh.2014.00056. doi: 10.3389/fpubh.2014.00056.
    1. Teixeira PJ, Carraça EV, Markland D, Silva MN, Ryan RM. Exercise, physical activity, and self-determination theory: a systematic review. Int J Behav Nutr Phys Act. 2012 Jun 22;9:78. doi: 10.1186/1479-5868-9-78. 1479-5868-9-78
    1. Maddison R, Pfaeffli L, Whittaker R, Stewart R, Kerr A, Jiang Y, Kira G, Leung W, Dalleck L, Carter K, Rawstorn JC. A mobile phone intervention increases physical activity in people with cardiovascular disease: results from the HEART randomized controlled trial. Eur J Prev Cardiol. 2015 Jun;22(6):701–9. doi: 10.1177/2047487314535076.2047487314535076
    1. Pfaeffli Dale L, Whittaker R, Jiang Y, Stewart R, Rolleston A, Maddison R. Text message and internet support for coronary heart disease self-management: results from the Text4Heart randomized controlled trial. J Med Internet Res. 2015 Oct 21;17(10):e237. doi: 10.2196/jmir.4944. v17i10e237
    1. Kayser L, Karnoe A, Furstrand D, Batterham R, Christensen KB, Elsworth G, Osborne RH. A multidimensional tool based on the eHealth literacy framework: development and initial validity testing of the eHealth literacy questionnaire (eHLQ) J Med Internet Res. 2018 Feb 12;20(2):e36. doi: 10.2196/jmir.8371. v20i2e36
    1. Godin G, Shephard RJ. Godin leisure-time exercise questionnaire. Med Sci Sports Exerc. 1997;29(6):36–8. doi: 10.1097/00005768-199706001-00009.
    1. Park Y, Dodd K, Kipnis V, Thompson F, Potischman N, Schoeller D, Baer D, Midthune D, Troiano R, Bowles H, Subar A. Comparison of self-reported dietary intakes from the Automated Self-Administered 24-h recall, 4-d food records, and food-frequency questionnaires against recovery biomarkers. Am J Clin Nutr. 2018 Jan 1;107(1):80–93. doi: 10.1093/ajcn/nqx002. 4825200
    1. National Health and Medical Research Council . Australian Dietary Guidelines. Canberra: National Health and Medical Research Council; 2013.
    1. Livingstone KM, McNaughton SA. Diet quality is associated with obesity and hypertension in Australian adults: a cross sectional study. BMC Public Health. 2016 Oct 1;16(1):1037. doi: 10.1186/s12889-016-3714-5. 10.1186/s12889-016-3714-5
    1. Subar AF, Kirkpatrick SI, Mittl B, Zimmerman TP, Thompson FE, Bingley C, Willis G, Islam NG, Baranowski T, McNutt S, Potischman N. The Automated Self-Administered 24-hour dietary recall (ASA24): a resource for researchers, clinicians, and educators from the National Cancer Institute. J Acad Nutr Diet. 2012 Aug;112(8):1134–7. doi: 10.1016/j.jand.2012.04.016. S2212-2672(12)00589-8
    1. Bush K, Kivlahan DR, McDonell MB, Fihn SD, Bradley KA. The AUDIT alcohol consumption questions (AUDIT-C): an effective brief screening test for problem drinking. Ambulatory Care Quality Improvement Project (ACQUIP). Alcohol Use Disorders Identification Test. Arch Intern Med. 1998 Sep 14;158(16):1789–95. doi: 10.1001/archinte.158.16.1789.
    1. Morisky DE, Green LW, Levine DM. Concurrent and predictive validity of a self-reported measure of medication adherence. Med Care. 1986 Jan;24(1):67–74. doi: 10.1097/00005650-198601000-00007.
    1. Maxwell A, Özmen M, Iezzi A, Richardson J. Deriving population norms for the AQoL-6D and AQoL-8D multi-attribute utility instruments from web-based data. Qual Life Res. 2016 Dec;25(12):3209–19. doi: 10.1007/s11136-016-1337-z.10.1007/s11136-016-1337-z
    1. Kavanagh T, Mertens DJ, Hamm LF, Beyene J, Kennedy J, Corey P, Shephard RJ. Peak oxygen intake and cardiac mortality in women referred for cardiac rehabilitation. J Am Coll Cardiol. 2003 Dec 17;42(12):2139–43. doi: 10.1016/j.jacc.2003.07.028.S0735109703013056
    1. Kavanagh T, Mertens DJ, Hamm LF, Beyene J, Kennedy J, Corey P, Shephard RJ. Prediction of long-term prognosis in 12 169 men referred for cardiac rehabilitation. Circulation. 2002 Aug 6;106(6):666–71. doi: 10.1161/01.cir.0000024413.15949.ed.
    1. Braun V, Clarke V. Using thematic analysis in psychology. Qual Res Psychol. 2006;3(2):77–101. doi: 10.1191/1478088706qp063oa.
    1. Harris PA, Taylor R, Minor BL, Elliott V, Fernandez M, O'Neal L, McLeod L, Delacqua G, Delacqua F, Kirby J, Duda SN, REDCap Consortium The REDCap consortium: Building an international community of software platform partners. J Biomed Inform. 2019 Jul;95:103208. doi: 10.1016/j.jbi.2019.103208.S1532-0464(19)30126-1
    1. Harris PA, Taylor R, Thielke R, Payne J, Gonzalez N, Conde JG. Research electronic data capture (REDCap)--a metadata-driven methodology and workflow process for providing translational research informatics support. J Biomed Inform. 2009 Apr;42(2):377–81. doi: 10.1016/j.jbi.2008.08.010. S1532-0464(08)00122-6
    1. National Health and Medical Research Council . Data Safety Monitoring Boards (DSMBs) Canberra: National Health and Medical Research Council; 2018.
    1. Richardson J, Iezzi A, Khan MA, Maxwell A. Validity and reliability of the Assessment of Quality of Life (AQoL)-8D multi-attribute utility instrument. Patient. 2014;7(1):85–96. doi: 10.1007/s40271-013-0036-x.
    1. Thornley S, Marshall R, Chan WC, Kerr A, Harrison J, Jackson G, Crengle S, Wright C, Wells S, Jackson R. Four out of ten patients are not taking statins regularly during the 12 months after an acute coronary event. Eur J Prev Cardiol. 2012 Jun;19(3):349–57. doi: 10.1177/1741826711403069.1741826711403069
    1. International Committee of Medical Journal Editors. 2017. [2018-10-16]. Recommendations for the Conduct, Reporting, Editing, and Publication of Scholarly work in Medical Journals
    1. Anderson L, Thompson D, Oldridge N, Zwisler A, Rees K, Martin N, Taylor RS. Exercise-based cardiac rehabilitation for coronary heart disease. Cochrane Database Syst Rev. 2016 Jan 5;(1):CD001800. doi: 10.1002/14651858.CD001800.pub3.
    1. Redfern J, Ellis ER, Briffa T, Freedman SB. High risk-factor level and low risk-factor knowledge in patients not accessing cardiac rehabilitation after acute coronary syndrome. Med J Aust. 2007 Jan 1;186(1):21–5.red10302_fm

Source: PubMed

3
Abonnieren