Jenn Lee CHIA
Senior Lecturer - Digital Health Information Management, La Trobe University
CHIA 673
The increasing advancement of digital health flows on to affect digital literacy skills and user adoption across many healthcare workers. A recent study[1] involving focus groups of nursing and allied health participants identified a significant gap between the rapid inception of digital technologies and healthcare workforce capabilities. Morris et al.[1] interpret healthcare worker digital capabilities as the effective utilisation of digital technologies to achieve better services and patient care. The authors describe successful digital technology adoption as healthcare workers literally thriving in a digital world[1]. The findings of the study[1] revealed nursing staff identifying digital capabilities at an intermediate level (from three levels – formative, intermediate, and proficient) while allied health professionals self-rated at a consolidated level (from four levels – foundation, consolidation, expert, and leader). The sample size of 23 participants pertained to healthcare workers sampled across eight private/public health services across Victoria. Examining generational responses to digital health will contribute towards intelligent strategy, harnessing the greatest potential of the technology and simultaneously serves to strengthen multidisciplinary relationships through closer engagement using techniques such as upwards/reverse mentoring techniques.
Reinbeck & Fitzsimons[2] draw upon the literature to describe four generation types: traditionalists, baby boomers, generation X and generation Y. Traditionalists refer to the generation that has lived through the Great Depression and World War II events and tend to be very hard-working, private, disciplined, and prefer a military style of management. Baby boomers are described as the post-war generation that lived through an era of significant social change including the civil rights movement. This generation prefers team styles of management that are positive, goal-focussed, and confident. Generation X is characterised by their preference for independence and working autonomously. They tend to be critical thinkers and possess clear goals. Survival through economic downturns such as recessions has meant that they take a conservative approach to economics. Generation Y or Millennials literally grew up with technology and in fairly peaceful times. They tend to be optimistic, require quick results, immediate gratification, and are known for their multitasking abilities.
Aydin & Kumru[3] describe a fifth generation type – generation Z or digital natives, characterised by their quick adaptation to new technologies. Cowey & Potts[4] identify a further subgroup of this generation type – secondary digital natives, or those born after 1990 – as they have been exposed to Web 2.0 throughout their entire development. These authors[4] highlight the change in digital health models, from earlier static and read-only approaches to the current participatory suite of digital solutions. This second generation of digital natives utilise a significant proportion of healthcare solutions quite autonomously, such as self-monitoring devices and self-service booking for online appointments[4]. The characteristics of this generation include busy lifestyles and utilising the mobility of technology on-the-go during travel time, changing locations, and varying hours of the day[4].
The presence of a generation gap has been identified by many authors[1-5]. Generation gaps refer to differences in values, perceptions, practices, and approaches in the context of healthcare as a consumer, worker, government agent, vendor, and other stakeholders. Can we borrow the ALDI slogan of “Good, different” to ameliorate the stigmatising image of difference meaning conflict or antagonism? Reinbeck & Fitzsimmons[2] suggest that reverse mentoring offers a powerful, effective strategy to link generations, as well as leveraging relationships and subsequent skill sets. Reinbeck & Fitzsimmons[2, p.12] define reverse mentoring as “an initiative that pairs a younger staff member with a more experienced staff member to share the younger employee’s expertise.” Goldsack & Zanetti[6] further propose three strategies for digital healthcare transformation to be successful – big tent thinking, which focuses on the incorporation of new technical skills within the more traditional clinical disciplines; the integration of clinical and technical skills within educational curricula, healthcare corporations, and professional organisations; and a complete commitment to diversity.
The author suggests applying the concept of ‘big tent thinking’ to each of the generations and extrapolating unique professional attributes and skills that can be harnessed and utilised using a multigenerational approach. One such strategy is the concept of reverse mentoring enabling the younger generation to teach the experienced generation some of the new digital technology solutions. In return, the traditionalist generation could mentor the new generation in sharing their experience and corporate knowledge.
The integration of skills could be interpreted as the intentional embedding of content that relates to each successive generation into the education curricula for each health discipline to promote better understanding, wider acceptance, and appreciation for each generation’s unique sets of attributes, skills and knowledge.
A focus on diversity requires deliberately creating social environments of multigenerational interactions to enable the lived experience to strengthen these relationships and effectively foster rather than divide workforce generations.
An additional strategy is proposed – utilising digital health solutions through a multigenerational lens assures comprehensive and inclusive testing and evaluation of these health technologies and a more powerful voice to push back against technology vendors promoting their products without sufficient understanding of its application to the business.
Unless deliberate measures to unify the present and future generations are taken, the health workforce will continue to fall victim to the already fragmented, siloed, and disparate components of the healthcare system that will disempower and disillusion healthcare workers, and inhibit successful growth and performance at the individual, service, and organisational level. Harnessing the power and expertise of each generation together, however, will generate a stronger voice and agent for change to achieve better health outcomes with the help of digital health technology.
References
- Morris, ME, Brusco, NK, Jones, J, et al. 2023, The widening gap between the digital capability of the care workforce and technology-enabled healthcare delivery: A nursing and allied health analysis, Healthcare, vol. 11, no. 7, pp. 1-12. Available from: https://www.mdpi.com/2227-9032/11/7/994
- Reinbeck, DM & Fitzsimons, V 2014, Bridging nursing’s digital generation gap, Nursing Management, vol. 45, no. 4, pp. 12–14. Available at: https://journals.lww.com/nursingmanagement/citation/2014/04000/bridging_nursing_s_digital_generation_gap.3.aspx
- Aydin, G & Kumru, S 2022, Paving the way for increased e-health record use: Elaborating intentions of Gen-Z, Health Systems, 2022, pp. 1–18. Available at: https://www.tandfonline.com/doi/full/10.1080/20476965.2022.2129471
- Cowey, AE & Potts, HWW 2018, What can we learn from second generation digital natives? A qualitative study of undergraduates’ views of digital health at one London university, Digital Health, vol. 4, pp. 1-13. Available at: https://pubmed.ncbi.nlm.nih.gov/30046453/
- Papp-Zipernovszky, O, Horvath, MD, Schulz, PJ, et al. 2021, Generation Gaps in digital health literacy and their impact on health information seeking behavior and health empowerment in Hungary, Frontiers in Public Health, vol. 9, no. 635943, pp. 1-12. Available at: https://pubmed.ncbi.nlm.nih.gov/34055714/
- Goldsack, J & Zanetti, CA 2020, Defining and developing the workforce needed for success in the digital era of medicine, Digital Biomarkers, vol. 4, no. Suppl 1, pp. 136-142. Available at: https://pubmed.ncbi.nlm.nih.gov/33442586/