Opportunities in mHealth

Real World Evidence: Mobile Health (mHealth)

Section 2

Opportunities in mHealth


Christopher E. Knoepke, PhD, MSW

Jennifer D. Portz, PhD, MSW

Sheana Bull, PhD, MPH

Lisa Sandy, MPH

Thomas Glorioso, MS

Joy Wachtal, MPH

Phat Luong, MS

Adrian Hernandez, MD

Michael Ho, MD, PhD


Contributing Editor

Karen Staman, MS


Digital health is a broad, inclusive term referring to the use of digital technology to improve health services, health research, or health outcomes. Mobile health (mHealth) is a type of digital health that uses wireless mobile devices, i.e., mobile phones, tablets, and laptops, to deliver health-related interventions.

mHealth offers unique opportunities to improve health service delivery, implement public health interventions, facilitate healthy behaviors, and ultimately improve health outcomes. People increasingly use mobile technology regardless of age, socioeconomic class, and primary language (Hunsaker and Hargittai 2018). Using familiar mobile devices that people are already using can increase the reach and access of health interventions to diverse populations. mHealth can provide health tools to people with lower-socioeconomic status (SES) who may not have access to more expensive technologies or in-person health care. mHealth can approach sensitive health topics, such as mental health, unintended pregnancy, death and dying, that people may not feel comfortable discussing. This approach allows people with the flexibility to engage in health services and interventions at convenient locations and times based on their individual needs.

Common mHealth applications for health providers include mobile applications for medical education and tips to providers when deciding upon or prescribing medications for patients, as well as collecting patient-reported outcomes with mobile screening tools and intake assessments. On the patient side, mHealth services are offered by healthcare systems via mobile applications, web-based platforms, patient portal apps, and text messaging to encourage chronic disease self-management, appointment attendance, and adherence to medical regimens. These mHealth services are often, yet not always, linked to electronic health record systems.

Currently, there are over 318,000 health-related, commercially available mobile applications (Institute for Health Informatics 2015; Research 2 Guidance). These applications, initiated by industry, health systems, clinicians, and researchers, offer tools for diet, exercise, medication, health education, disease specific information, monitoring features, and games. The applications target a wide variety of health concerns ranging from pregnancy, infant well-being, sexual health, fitness, to chronic disease and end-of-life care  (Flores Mateo et al. 2015; Fedele et al. 2017; Hanlon et al. 2017; Gyselaers et al. 2019; Portz et al. 2020). While some apps are designed to help individual patients, others target caregivers, and some are created for large-scale public health campaigns (e.g., smoking cessation, suicide prevention, breastfeeding).

Evidence suggests that mHealth interventions likely improve antecedents to health behavior, including self-efficacy, disease-specific knowledge, health literacy and numeracy, and motivation (Hamine et al. 2015; McKay et al. 2018; Aromatario et al. 2019). However, very little is known about the effectiveness of mHealth in improving health and health services (Free et al. 2010). Adoption rates of mobile apps are high, but use declines over time (Tang et al. 2016). Little is known about mHealth engagement and the associations between engagement on health behaviors and outcomes. There are also barriers to mHealth implementation including interoperability with electronic health record systems, regulations and security issues, and clinical provider and workflow concerns (Bradbury et al. 2014).





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Aromatario O, Van Hoye A, Vuillemin A, et al. 2019. How do mobile health applications support behaviour changes? A scoping review of mobile health applications relating to physical activity and eating behaviours. Public Health. 175:8–18. doi:10.1016/j.puhe.2019.06.011. PMID: 31374453.

Bradbury K, Watts S, Arden-Close E, Yardley L, Lewith G. 2014. Developing digital interventions: a methodological guide. Evid-Based Complement Altern Med ECAM. 2014:561320. doi:10.1155/2014/561320.

Fedele DA, Cushing CC, Fritz A, Amaro CM, Ortega A. 2017. Mobile health interventions for improving health outcomes in youth: a meta-analysis. JAMA Pediatr. 171(5):461–469. doi:10.1001/jamapediatrics.2017.0042.

Flores Mateo G, Granado-Font E, Ferré-Grau C, Montaña-Carreras X. 2015. Mobile phone apps to promote weight loss and increase physical activity: a systematic review and meta-analysis. J Med Internet Res. 17(11):e253. doi:10.2196/jmir.4836. PMID: 24648848.

Free C, Phillips G, Felix L, Galli L, Patel V, Edwards P. 2010. The effectiveness of M-health technologies for improving health and health services: a systematic review protocol. BMC Res Notes. 3(1):250. doi:10.1186/1756-0500-3-250. PMID: 20925916.

Gyselaers W, Lanssens D, Perry H, Khalil A. 2019. Mobile health applications for prenatal assessment and monitoring. Curr Pharm Des. 25(5):615–623. doi:10.2174/1381612825666190320140659. PMID: 30894100.

Hamine S, Gerth-Guyette E, Faulx D, Green BB, Ginsburg AS. 2015. Impact of mHealth chronic disease management on treatment adherence and patient outcomes: a systematic review. J Med Internet Res. 17(2):e52. doi:10.2196/jmir.3951. PMID: 25803266.


Hanlon P, Daines L, Campbell C, McKinstry B, Weller D, Pinnock H. 2017. Telehealth interventions to support self-management of long-term conditions: a systematic metareview of diabetes, heart failure, asthma, chronic obstructive pulmonary disease, and cancer. J Med Internet Res. 19(5):e172. doi:10.2196/jmir.6688. PMID: 28526671.

Hunsaker A, Hargittai E. 2018. A review of Internet use among older adults. New Media Soc. 20(10):3937–3954. doi:10.1177/1461444818787348.

Institute for Health Informatics. 2015. IMS Institute Patient Adoption of MHealth Report. https://www.iqvia.com/-/media/iqvia/pdfs/institute-reports/patient-adoption-of-mhealth.pdf. Accessed March 9, 2020.

McKay FH, Cheng C, Wright A, Shill J, Stephens H, Uccellini M. 2018. Evaluating mobile phone applications for health behaviour change: a systematic review. J Telemed Telecare. 24(1):22–30. doi:10.1177/1357633X16673538. PMID: 27760883.

Portz JD, Elsbernd K, Plys E, et al. 2020. Elements of social convoy theory in mobile health for palliative care: scoping review. JMIR MHealth UHealth. 8(1):e16060. doi:10.2196/16060. PMID: 31904581.

Research 2 Guidance. 325,000 mobile health apps available in 2017 – Android now the leading mHealth platform. https://research2guidance.com/325000-mobile-health-apps-available-in-2017/. Accessed March 9, 2020.

Tang C, Lorenzi N, Harle CA, Zhou X, Chen Y. 2016. Interactive systems for patient-centered care to enhance patient engagement. J Am Med Inform Assoc JAMIA. 23(1):2–4. doi:10.1093/jamia/ocv198. PMID: 26912537.

Version History

Published March 16, 2020


Knoepke CE, Portz JD, Bull S, et al. Real World Evidence: Mobile Health (mHealth): Opportunities in mHealth. In: Rethinking Clinical Trials: A Living Textbook of Pragmatic Clinical Trials. Bethesda, MD: NIH Health Care Systems Research Collaboratory. Available at: https://rethinkingclinicaltrials.org/chapters/conduct/real-world-evidence-mobile-health-mhealth/opportunities-in-mhealth/. Updated March 26, 2020. DOI: 10.28929/122.