Exploring the factors that influence the decision to adopt and engage with an integrated assistive telehealth and telecare service in Cambridgeshire, UK: a nested qualitative study of patient ‘users’ and ‘non-users’

BackgroundThere is a political drive in the UK to use assistive technologies such as telehealth and telecare as an innovative and efficient approach to healthcare delivery. However, the success of implementation of such services remains dependent on the ability to engage the wider population to adopt these services. It has been widely acknowledged that low acceptance of technology, forms a key barrier to adoption although findings been mixed. Further, it remains unclear what, if any barriers exist between patients and how these compare to those who have declined or withdrawn from using these technologies. This research aims to address this gap focusing on the UK based Cambridgeshire Community Services Assistive Telehealth and Telecare service, an integrated model of telehealth and telecare.MethodsQualitative semi-structured interviews were conducted between 1st February 2014 and 1st December 2014, to explore the views and experiences of ‘users’ and ‘non-users’ using this service. ‘Users’ were defined as patients who used the service (N = 28) with ‘non-users’ defined as either referred patients who had declined the service before allocation (N = 3) or had withdrawn after using the ATT service (N = 9). Data were analysed using the Framework Method.ResultsThis study revealed that there are a range of barriers and facilitators that impact on the decision to adopt and continue to engage with this type of service. Having a positive attitude and a perceived need that could be met by the ATT equipment were influential factors in the decision to adopt and engage in using the service. Engagement of the service centred on ‘usability’, ‘usefulness of equipment’, and ‘threat to identity and independence’.ConclusionsThe paper described the influential role of referrers in decision-making and the need to engage with such agencies on a strategic level. The findings also revealed that reassurance from the onset was paramount to continued engagement, particularly in older patients who appeared to have more negative feelings towards technology. In addition, there is a clear need for continued product development and innovation to not only increase usability and functionality of equipment but also to motivate other sections of the population who could benefit from such services. Uncovering these factors has important policy implications in how services can improve access and patient support through the application of assistive technology which could in turn reduce unnecessary cost and burden on overstretched health services.

[1]  M. Mandelstam Community care practice and the law , 1995 .

[2]  Eddy Karnieli,et al.  A model of the willingness to use telemedicine for routine and specialized care , 2003, Journal of telemedicine and telecare.

[3]  Marilyn McGee-Lennon,et al.  A stakeholder‐centred exploration of the current barriers to the uptake of home care technology in the UK , 2011 .

[4]  C. Armitage,et al.  Home Telehealth Uptake and Continued Use Among Heart Failure and Chronic Obstructive Pulmonary Disease Patients: a Systematic Review , 2014, Annals of behavioral medicine : a publication of the Society of Behavioral Medicine.

[5]  P. Bower,et al.  A comprehensive evaluation of the impact of telemonitoring in patients with long-term conditions and social care needs: protocol for the whole systems demonstrator cluster randomised trial , 2011, BMC health services research.

[6]  Stuart M. Speedie,et al.  Factors influencing health information technology adoption in Thailand's community health centers: Applying the UTAUT model , 2009, Int. J. Medical Informatics.

[7]  David Barrett,et al.  Examining perspectives on telecare: factors influencing adoption, implementation, and usage , 2014 .

[8]  Joanna Smith,et al.  Qualitative data analysis: the framework approach. , 2011, Nurse researcher.

[9]  N. Goodwin,et al.  Sustaining innovation in telehealth and telecare: WSDAN briefing paper , 2010 .

[10]  Peter Millward,et al.  The 'grey digital divide': Perception, exclusion and barriers of access to the Internet for older people , 2003, First Monday.

[11]  Christer Carlsson,et al.  Adoption of Mobile Devices/Services — Searching for Answers with the UTAUT , 2006, Proceedings of the 39th Annual Hawaii International Conference on System Sciences (HICSS'06).

[12]  N. Gale,et al.  Using the framework method for the analysis of qualitative data in multi-disciplinary health research , 2013, BMC Medical Research Methodology.

[13]  C. McCreadie,et al.  The acceptability of assistive technology to older people , 2005, Ageing and Society.

[14]  Megs Okoye Whole System Demonstrator programme - Headline findings December 2011 , 2011 .

[15]  Gordon B. Davis,et al.  User Acceptance of Information Technology: Toward a Unified View , 2003, MIS Q..

[16]  J. Pick,et al.  Understanding Global Digital Inequality: The Impact of Government, Investment in Business and Technology, and Socioeconomic Factors on Technology Utilization , 2009, 2009 42nd Hawaii International Conference on System Sciences.

[17]  Kenneth J. Turner,et al.  Advances in telecare over the past 10 years , 2013 .

[18]  Michael Mackert Expanding the theoretical foundations of telemedicine , 2006, Journal of telemedicine and telecare.

[19]  G. Munchus,et al.  The role of information technology in enhancing patient satisfaction , 2001 .

[20]  A. Comas-Herrera,et al.  Care for older people Projected expenditure to 2022 on social care and continuing health care for England's older population , 2012 .

[21]  J. Kirscht The Health Belief Model and Illness Behavior , 1974 .

[22]  F. Rabiee Focus-group interview and data analysis , 2004, Proceedings of the Nutrition Society.

[23]  Karen Cimon,et al.  Home telehealth for chronic obstructive pulmonary disease: a systematic review and meta-analysis , 2010, Journal of telemedicine and telecare.

[24]  Kate McMillan,et al.  A cross-sectional survey and service evaluation of simple telehealth in primary care: what do patients think? , 2012, BMJ Open.

[25]  M. Becker,et al.  Health Belief Model and Personal Health Behavior , 1976 .

[26]  Trisha Greenhalgh,et al.  Technology as system innovation: a key informant interview study of the application of the diffusion of innovation model to telecare , 2014, Disability and rehabilitation. Assistive technology.

[27]  Caroline Sanders,et al.  What influences withdrawal because of rejection of telehealth - the whole systems demonstrator evaluation , 2013 .

[28]  G. Hartvigsen,et al.  Home telecare technologies for the elderly , 2008, Journal of telemedicine and telecare.

[29]  F. Mair,et al.  Integrating telecare for chronic disease management in the community: What needs to be done? , 2011, BMC health services research.

[30]  I. Rosenstock Historical Origins of the Health Belief Model , 1974 .

[31]  S. Kegeles HEALTH BELIEF MODEL AND PERSONAL HEALTH BEHAVIOR , 1980 .

[32]  I. Rosenstock Why people use health services. , 1966, The Milbank Memorial Fund quarterly.

[33]  J. Wardle,et al.  Attitudes towards HPV testing: a qualitative study of beliefs among Indian, Pakistani, African-Caribbean and white British women in the UK , 2003, British Journal of Cancer.

[34]  D DavisFred Perceived usefulness, perceived ease of use, and user acceptance of information technology , 1989 .

[35]  Peter A. Todd,et al.  Assessing IT usage: the role of prior experience , 1995 .

[36]  C E Lipscomb,et al.  Medical Subject Headings (MeSH). , 2000, Bulletin of the Medical Library Association.

[37]  Martin Knapp,et al.  Exploring barriers to participation and adoption of telehealth and telecare within the Whole System Demonstrator trial: a qualitative study , 2012, BMC Health Services Research.

[38]  Peter Caputi,et al.  Issues in predicting and explaining usage behaviors with the technology acceptance model and the theory of planned behavior when usage is mandatory , 2000, ICIS.

[39]  Willingness to use telemedicine for psychiatric care. , 2004, Telemedicine journal and e-health : the official journal of the American Telemedicine Association.

[41]  Nick Goodwin,et al.  The State of Telehealth and Telecare in the UK: Prospects for Integrated Care , 2010 .

[42]  Tugrul U. Daim,et al.  Health Information Service Adoption: Case of Telemedicine , 2009, 2009 42nd Hawaii International Conference on System Sciences.

[43]  J. Ritchie,et al.  Qualitative Research Practice: A Guide for Social Science Students and Researchers , 2013 .

[44]  Icek Ajzen,et al.  From Intentions to Actions: A Theory of Planned Behavior , 1985 .

[45]  S. Korupp,et al.  Causes and Trends of the Digital Divide , 2005 .

[46]  L. Spencer,et al.  Qualitative data analysis for applied policy research , 2002 .

[47]  H. L. Hsieh,et al.  An Empirical Study to Explore the Adoption of Telehealth: Health Belief Model Perspective , 2013 .