By Dr Louise Rooney, Change Team, ARCH
The rapid and continual sophistication of computer science has led to the growing uptake of Information and Communication Technologies (ICT’s) across the entirety of the healthcare sector. In this age of ‘digitalisation’ it is inevitable that ICT’s will become a more integral part of both primary and secondary patient care. In conjunction with this digitalisation has been the centralisation of the ‘Patient Experience’ amidst healthcare research, policy and practice. Accordingly, the ways in which patients’ experience such technological advancements have not only become a ‘hot topic’ for the healthcare sector but for the IT industry alike. The Beryl Institute  defines Patient Experience as:
“the sum of all interactions, shaped by an organisation’s culture that influence patient perceptions across the continuum of care.”
There is a general consensus amongst scholars that Patient Experience is not simply a reflection of clinical outcomes but seeks to measure a complex psychological construct that is multifaceted, subjective and ambiguous . To complicate matters further, the concept is poorly defined and has numerous aliases which each have their own assortment of standardised psychometric tests (e.g. Patient Engagement, Health Related Quality of Life, Patient Reported Outcomes) Yet, despite the abundance of quantitative tools within this space, much uncertainty still exists as to how the construct should be measured, defined and explored.
Healthcare research is typically conducted within the realms of the ‘hard’ sciences (biology, chemistry, etc.) where scientific integrity is attained via quantifiability and objectivity. Whilst the ‘softer’ social sciences tend to be side-lined because of their willingness to explore subjective experience. As a result, Patient Experience data has traditionally been collected and analysed using quantitative methods. However, it appears that the medical community is becoming more open to qualitative data collection techniques. This is not only evidenced by the marked increase in studies that have employed qualitative tools to explore health related phenomenon (e.g. Interviewing, Photovoice, Patient Journey Diaries), but by the UK’s Medical Research Council recommendation for researchers to consider adopting mix-method designs when evaluating patient care .
The Middle Ground: Having your Cake and Eating It Too…
Historically, qualitative and quantitative methods have been pitted against each other in a long-standing epistemological debate concerning methodological superiority. However, over the past couple of decades scholars from a variety of disciplines have published extensively on the benefits of applying a pragmatic research approach which draws on both quantitative and qualitative mechanisms of investigation. They argue that adopting a mixed-methods design removes the “forced choice dichotomy” between quantitative and qualitative techniques and encourages the researcher to draw on a selection of tools as a means of generating multidimensional knowledge . They also point out that neither approach is immune to bias or confounds, both have their own set of strengths and weaknesses (see Figure 2 & 3); and when used collaboratively, qualitative and quantitative tools often work to counterbalance each other’s shortcomings . Adopting a pragmatic approach promotes scientific vigour whilst also providing a front row seat to the lived experiences of participants, allowing us as researchers ‘to have our cake and eat it too’.
Patient Experience is key when it comes to enhancing primary and secondary care, designing healthcare technology and innovation, and improving healthcare policy. Accordingly, it is imperative that the right techniques are utilised to capture the full picture when exploring this nebulous phenomenon. Given their versatility and scope, mixed-methods are by far the most appropriate research design for the job.
 The Beryl Institute (2017). Defining Patient Experience. Available at: http://www.theberylinstitute.org/?page=definingpatientexp [Accessed 1December, 2017].
 LaVela, S. L., & Gallan, A. (2014). Evaluation and measurement of patient experience. Patient Experience Journal 1(1), 28-36.
 Moore, G. F., Audrey, S., Barker, M., Bond, L., Bonell, C., Hardeman, W., … & Baird, J. (2015). Process evaluation of complex interventions: Medical Research Council guidance. bmj, 350, h1258.
 Feilzer Y. M. (2010). Doing mixed methods research pragmatically: Implications for the rediscovery of pragmatism as a research paradigm. Journal of mixed methods research, 4(1), 6-16.
 Creswell, J. W., & Tashakkori, A. (2007). Editorial: Differing perspectives on mixed methods research. Journal of Mixed Methods Research, 1(4), 303-308.