Implementing digital health for real: what factors affect participation

Thanks to healthier lifestyles, nutrition and education, we are getting older and older. Digital aids such as apps and wearables also help. Siobhan O’Connor of  Edinburgh University examines what helps or hinders their everyday use.

In Switzerland and across Europe, populations are living longer thanks to good public health and education systems. However, older adults can have complex care needs as their physical health declines. Lifestyles changes in the latter half of the 20th century such as diets high in sugar and fat, a lack of exercise and unhealthy habits such as smoking, binge drinking and recreational drug use are increasing the numbers of people with long-term chronic conditions such as asthma, diabetes and heart disease. These problems are placing huge burdens on patients, families, professionals and health systems worldwide.

A wide range of mobile, online and sensor technologies are available to the public to support healthy lifestyles and for patients to manage their disease. Lots of research has looked at how well different types of hardware and software work with patients, carers and people who want to stay healthy. However, many people do not use these electronic tools outside of taking part in research as they can experience barriers that prevent them from engaging in technology for their health. A review of the literature on this subject was published in 2016 and can be read for free here.

The review identified many aspects, which we summarised into three themes, that help or hinder patients and the public when engaging and enrolling in all types of digital health interventions. It included technologies such as telehealth, mobile apps, online health services, social media, wearable devices like pedometers and patient accessible electronic health records.

  • The first theme from the literature review is around personal agency (choice and control) and motivation as people have difference preferences towards technology for their health. For example, some people are more motivated to look after their health and like the flexibility that technology offers to access health information and services.
  • The second area is personal life and values which includes how busy someone’s life is and what competing priorities they have. It also covers the skills and equipment needed to use digital health products and services and how much people value the privacy and security of their health data.
  • The third reason why patients and the public participate in digital health or not is the engagement and recruitment approach that is used. This can include direct support from family and friends, advice from a trusted source such as a peer or colleague, endorsement by a health professional (e.g. doctor or nurse), and strategies used to promote awareness and understanding of the technology. The strategies could be a mixture of advertising in print media (newspapers or magazines), electronic media (TV or radio) or online media (email, social media, websites).
  • The fourth and final theme highlighted in the literature review is the quality of the digital health intervention. Whether patients and the public had a positive or negative perception of the quality of the digital information or virtual interaction that could occur when using the technology influenced their decision to participate or not in it. For example, some people had experienced abusive language on social media or did not think interacting virtually with a healthcare professional would be as good as meeting them in person. How easy it was to sign up to and register for a technology was another aspect of quality that people considered before they began using it.

From these themes the literature review created a Digital Health Engagement Model (DIEGO) to summarise the complexity of participating in digital health (see Figure 1). Using this model could help researchers, clinicians, companies and policy makers understand the dynamics of implementing digital health products and services in the real-world and what barriers and facilitators patients and the public experience in the process. Further research is underway to extend and refine the initial DIEGO model and use it to develop a valid and reliable eHealth readiness assessment tool. This could help improve how digital health is implemented in the future.

Figure 1: Digital Health Engagement Model (DIEGO) (O’Connor et al, 2016)

 


Reference

  • O’Connor, S., Hanlon, P., O’Donnell, C.A., Garcia, S., Glanville, J. & Mair, F. S. (2016). Understanding factors affecting patient and public engagement and recruitment to digital health: a systematic review of qualitative studies. BMC Medical Informatics and Decision Making 16:120.
  • https://bmcmedinformdecismak.biomedcentral.com/articles/10.1186/s12911-016-0359-3

AUTOR/AUTORIN: Siobhan O'Connor

Siobhan O'Conno ist Dozentin an der School of Health and Social Care, Edinburgh Napier University, UK und Gastdozentin an der University of Pennsylvania School of Nursing, USA. Sie hat einen multidisziplinären Hintergrund mit den Abschlüssen B.Sc. Business Information Systems und B.Sc. Nursing.

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