A Qualitative Study on Patient Perceptions Towards mHealth Technology Among High Risk, Chronic Disease Patients
MetadataShow full item record
CitationMartinez, Phillip Rico. 2015. A Qualitative Study on Patient Perceptions Towards mHealth Technology Among High Risk, Chronic Disease Patients. Doctoral dissertation, Harvard Medical School.
AbstractBackground: For over 17 years, the Prevention and Access to Care and Treatment (PACT) Project has actively developed a Community Health Worker model for care of chronically ill, high risk patients. Given the high burden of chronic disease and associated rising health expenditures, mHealth technology has emerged as a promising low cost, high efficacy intervention for delivery of patient-centered care and as a tool for self-management of chronic disease
Objective: Attitudes and perceptions regarding mHealth accessibility and utility among adult patients with chronic disease will be assessed. Information regarding desired mHealth applications as well as facilitators and barriers to utilization are collected and presented as a tool for informing potential mHealth design.
Methods: This qualitative study consisted of 4 focus groups with target population (chronic disease, low SES) stratified by age >55 y.o (n=8 and 5) and <55 y.o. (n=7 and n=7) using a semi-structured focus group guide. Transcripts of each focus group were subsequently analyzed for key themes using qualitative data analysis software and grounded theory methodology.
Results: Analysis of key themes reveal a largely positive reception towards mHealth technology with perceived benefits of improving communication with provider teams, reporting live patient data and as an aid for daily self-management of chronic conditions. Participants expressed a strong preference for individualized, patient- centered mHealth interventions while confidentiality emerged as the largest mHealth concern.
Conclusions: mHealth technology is an accessible intervention for health care self- management. Given the need for long-term prospective outcome data for mHealth intervention among high risk chronic disease patients, findings from this study may be to used to inform potential mHealth design in order to optimally assess mHealth outcomes with future prospective studies.
Citable link to this pagehttp://nrs.harvard.edu/urn-3:HUL.InstRepos:17295915