Iribarren SJ, Cato K, Falzon L, Stone PW, et al.
PloS one. Date of publication 2017 Feb 2;volume 12(2):e0170581.
1. PLoS One. 2017 Feb 2;12(2):e0170581. doi: 10.1371/journal.pone.0170581.
eCollection 2017.
What is the economic evidence for mHealth? A systematic review of economic
evaluations of mHealth solutions.
Iribarren SJ(1), Cato K(2)(3), Falzon L(4), Stone PW(2)(5).
Author information:
(1)University of Washington, Department of Biobehavioral Nursing and Health
Informatics, School of Nursing, Seattle, Washington, United States of America.
(2)Columbia University, School of Nursing, New York, New York, United States of
America.
(3)Office of Nursing Research, EBP and Innovation, New York-Presbyterian
Hospital, New York, New York, United States of America.
(4)Center for Behavioral Cardiovascular Health, Department of Medicine, Columbia
University Medical Center, New York-Presbyterian Hospital, New York, New York,
United States of America.
(5)Columbia University, School of Nursing, Center for Health Policy, New York,
New York, United States of America.
BACKGROUND: Mobile health (mHealth) is often reputed to be cost-effective or
cost-saving. Despite optimism, the strength of the evidence supporting this
assertion has been limited. In this systematic review the body of evidence
related to economic evaluations of mHealth interventions is assessed and
summarized.
METHODS: Seven electronic bibliographic databases, grey literature, and relevant
references were searched. Eligibility criteria included original articles,
comparison of costs and consequences of interventions (one categorized as a
primary mHealth intervention or mHealth intervention as a component of other
interventions), health and economic outcomes and published in English. Full
economic evaluations were appraised using the Consolidated Health Economic
Evaluation Reporting Standards (CHEERS) checklist and The PRISMA guidelines were
followed.
RESULTS: Searches identified 5902 results, of which 318 were examined at full
text, and 39 were included in this review. The 39 studies spanned 19 countries,
most of which were conducted in upper and upper-middle income countries (34,
87.2%). Primary mHealth interventions (35, 89.7%), behavior change communication
type interventions (e.g., improve attendance rates, medication adherence) (27,
69.2%), and short messaging system (SMS) as the mHealth function (e.g., used to
send reminders, information, provide support, conduct surveys or collect data)
(22, 56.4%) were most frequent; the most frequent disease or condition focuses
were outpatient clinic attendance, cardiovascular disease, and diabetes. The
average percent of CHEERS checklist items reported was 79.6% (range 47.62-100,
STD 14.18) and the top quartile reported 91.3-100%. In 29 studies (74.3%),
researchers reported that the mHealth intervention was cost-effective,
economically beneficial, or cost saving at base case.
CONCLUSIONS: Findings highlight a growing body of economic evidence for mHealth
interventions. Although all studies included a comparison of intervention
effectiveness of a health-related outcome and reported economic data, many did
not report all recommended economic outcome items and were lacking in
comprehensive analysis. The identified economic evaluations varied by disease or
condition focus, economic outcome measurements, perspectives, and were
distributed unevenly geographically, limiting formal meta-analysis. Further
research is needed in low and low-middle income countries and to understand the
impact of different mHealth types. Following established economic reporting
guidelines will improve this body of research.
DOI: 10.1371/journal.pone.0170581
PMCID: PMC5289471
PMID: 28152012 [Indexed for MEDLINE]
Conflict of interest statement: The authors declare no competing interests exist.
