mHealth Technology and Nurse Health Coaching to Improve Health in Diabetes: Protocol for a Randomized Controlled Trial

Sheridan Miyamoto, Madan Dharmar, Sarina Fazio, Yajarayma Tang-Feldman, Heather M Young, Sheridan Miyamoto, Madan Dharmar, Sarina Fazio, Yajarayma Tang-Feldman, Heather M Young

Abstract

Background: Chronic diseases, including diabetes mellitus, are the leading cause of mortality and disability in the United States. Current solutions focus primarily on diagnosis and pharmacological treatment, yet there is increasing evidence that patient-centered models of care are more successful in improving and addressing chronic disease outcomes.

Objective: The objective of this clinical trial is to evaluate the impact of a mobile health (mHealth) enabled nurse health coaching intervention on self-efficacy among adults with type-2 diabetes mellitus.

Methods: A randomized controlled trial was conducted at an academic health system in Northern California. A total of 300 participants with type-2 diabetes were scheduled to be enrolled through three primary care clinics. Participants were randomized to either usual care or intervention. All participants received training on use of the health system patient portal. Participants in the intervention arm received six scheduled health-coaching telephone calls with a registered nurse and were provided with an activity tracker and mobile application that integrated data into the electronic health record (EHR) to track their daily activity and health behavior decisions. All participants completed a baseline survey and follow-up surveys at 3 and 9 months. Primary and secondary outcomes include diabetes self-efficacy, hemoglobin A1c (HbA1c), and quality of life measures.

Results: Data collection for this trial, funded by the Patient-Centered Outcomes Research Institute, will be completed by December 2017. Results from the trial will be available mid-2018.

Conclusions: This protocol details a patient-centered intervention using nurse health coaching, mHealth technologies, and integration of patient-generated data into the EHR. The aim of the intervention is to enhance self-efficacy and health outcomes by providing participants with a mechanism to track daily activity by offering coaching support to set reasonable and attainable health goals, and by creating a complete feedback loop by bringing patient-generated data into the EHR.

Trial registration: ClinicalTrials.gov NCT02672176; https://ichgcp.net/clinical-trials-registry/NCT02672176 (Archived by WebCite at http://www.webcitation.org/6xEQXe1M5).

Keywords: electronic health record; health coaching; mobile health; motivational interviewing; patient engagement; patient generated health data; person-centered outcomes research; randomized controlled trial; study protocol; type 2 diabetes mellitus.

Conflict of interest statement

Conflicts of Interest: None declared.

©Sheridan Miyamoto, Madan Dharmar, Sarina Fazio, Yajarayma Tang-Feldman, Heather M Young. Originally published in JMIR Research Protocols (http://www.researchprotocols.org), 15.02.2018.

Figures

Figure 1
Figure 1
Changing the conversation about health. PGHD: patient-generated health data.
Figure 2
Figure 2
Diagram of Patient and Provider Engagement and Empowerment through Technology (P2E2T2) patient enrollment, randomization, intervention, and timeline. EHR: electronic health record; PCP: primary care provider.

References

    1. Narayan KMV, Boyle JP, Geiss LS, Saaddine JB, Thompson TJ. Impact of recent increase in incidence on future diabetes burden: US, 2005-2050. Diabetes Care. 2006 Sep;29(9):2114–6. doi: 10.2337/dc06-1136.
    1. Deshpande AD, Harris-Hayes M, Schootman M. Epidemiology of diabetes and diabetes-related complications. Phys Ther. 2008 Nov;88(11):1254–64. doi: 10.2522/ptj.20080020.
    1. Lago R, Singh P, Nesto R. Diabetes and hypertension. Nat Clin Pract Endocrinol Metab. 2007 Oct;3(10):667. doi: 10.1038/ncpendmet0638.
    1. Bohannon N. Coronary artery disease and diabetes. Postgrad Med. 1999 Feb;105(2):66–8, 71. doi: 10.3810/pgm.1999.02.533.
    1. Icks A, Trautner C, Haastert B, Berger M, Giani G. Blindness Due to Diabetes: Population-based Age- and Sex-specific Incidence Rates. Diabet. Med. 1997 Jul;14(7):571–575. doi: 10.1002/(SICI)1096-9136(199707)14:7<571::AID-DIA384>;2-Y.
    1. Johnson R, Segal M, Sautin Y, Nakagawa Takahiko, Feig Daniel I, Kang Duk-Hee, Gersch Michael S, Benner Steven, Sánchez-Lozada Laura G. Potential role of sugar (fructose) in the epidemic of hypertension, obesity and the metabolic syndrome, diabetes, kidney disease, and cardiovascular disease. Am J Clin Nutr. 2007 Oct;86(4):899–906.
    1. American Association of Diabetes Ed AADE Guidelines for the Practice of Diabetes Self-Management Education and Training (DSME/T) Diabetes Educ. 2009 Nov 24;35(3_suppl):85S–107S. doi: 10.1177/0145721709352436.
    1. Norris S, Engelgau M, Narayan K. Effectiveness of self-management training in type 2 diabetes: a systematic review of randomized controlled trials. Diabetes Care. 2001 Mar;24(3):561–87.
    1. Renders C, Valk G, Griffin S, Wagner E, Eijk J, Assendelft W. Interventions to improve the management of diabetes mellitus in primary care, outpatient and community settings. Cochrane Database Syst Rev. 2001;(1):CD001481. doi: 10.1002/14651858.CD001481.
    1. Chen S, Creedy D, Lin H, Wollin J. Effects of motivational interviewing intervention on self-management, psychological and glycemic outcomes in type 2 diabetes: a randomized controlled trial. Int J Nurs Stud. 2012 Jun;49(6):637–44. doi: 10.1016/j.ijnurstu.2011.11.011.
    1. West D, DiLillo V, Bursac Z, Gore S, Greene P. Motivational interviewing improves weight loss in women with type 2 diabetes. Diabetes Care. 2007 May;30(5):1081–7. doi: 10.2337/dc06-1966.
    1. Thompson D, Chair S, Chan S, Astin F, Davidson P, Ski C. Motivational interviewing: a useful approach to improving cardiovascular health? J Clin Nurs. 2011 May;20(9-10):1236–44. doi: 10.1111/j.1365-2702.2010.03558.x.
    1. Miller W, Rollnick S, Ebooks C. Motivational interviewing: helping people change. 3rd ed. New York, NY: Guilford Press; 2013.
    1. Treasure J. Motivational interviewing. Adv. psychiatr. treat (Print) 2018 Jan 2;10(05):331–337. doi: 10.1192/apt.10.5.331.
    1. Young H, Miyamoto S, Ward D, Dharmar M, Tang-Feldman Y, Berglund L. Sustained effects of a nurse coaching intervention via telehealth to improve health behavior change in diabetes. Telemed J E Health. 2014 Sep;20(9):828–34. doi: 10.1089/tmj.2013.0326.
    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.
    1. Fitzgerald JT, Stansfield RB, Tang T, Oh M, Frohna A, Armbruster B, Gruppen L, Anderson R. Patient and provider perceptions of diabetes: measuring and evaluating differences. Patient Educ Couns. 2008 Jan;70(1):118–25. doi: 10.1016/j.pec.2007.09.005.
    1. Mercer SW, Maxwell M, Heaney D, Watt GC. The consultation and relational empathy (CARE) measure: development and preliminary validation and reliability of an empathy-based consultation process measure. Fam Pract. 2004 Dec;21(6):699–705. doi: 10.1093/fampra/cmh621.
    1. Agency for Healthcare Research and Quality. [2018-02-05]. CAHPS® Clinician & Group Survey 3 .
    1. Broderick JE, DeWitt EM, Rothrock N, Crane PK, Forrest CB. Advances in Patient-Reported Outcomes: The NIH PROMIS Measures. EGEMS (Wash DC) 2013;1(1):1015. doi: 10.13063/2327-9214.1015.
    1. Kroenke K, Spitzer RL, Williams JB. The PHQ-9: validity of a brief depression severity measure. J Gen Intern Med. 2001 Sep;16(9):606–13.
    1. Cohen S, Kessler R, Underwood L. Measuring stress: a guide for health and social scientists. New York: Oxford University Press; 1995. p. a.
    1. Horrigan J. Pew Research Center. 2016. [2018-02-05]. Digital readiness gaps

Source: PubMed

Спонсоры и соавторы

Заболевания

Медикаментозные вмешательства

Подписаться