RT Journal Article
SR Electronic
T1 How digital health translational research is prioritised: a qualitative stakeholder-driven approach to decision support evaluation
JF BMJ Open
JO BMJ Open
FD British Medical Journal Publishing Group
SP e075009
DO 10.1136/bmjopen-2023-075009
VO 13
IS 11
A1 Bamgboje-Ayodele, Adeola
A1 McPhail, Steven M
A1 Brain, David
A1 Taggart, Richard
A1 Burger, Mitchell
A1 Bruce, Lenert
A1 Holtby, Caroline
A1 Pradhan, Malcolm
A1 Simpson, Mark
A1 Shaw, Tim J
A1 Baysari, Melissa T
YR 2023
UL http://bmjopen.bmj.com/content/13/11/e075009.abstract
AB Objectives Digital health is now routinely being applied in clinical care, and with a variety of clinician-facing systems available, healthcare organisations are increasingly required to make decisions about technology implementation and evaluation. However, few studies have examined how digital health research is prioritised, particularly research focused on clinician-facing decision support systems. This study aimed to identify criteria for prioritising digital health research, examine how these differ from criteria for prioritising traditional health research and determine priority decision support use cases for a collaborative implementation research programme.Methods Drawing on an interpretive listening model for priority setting and a stakeholder-driven approach, our prioritisation process involved stakeholder identification, eliciting decision support use case priorities from stakeholders, generating initial use case priorities and finalising preferred use cases based on consultations. In this qualitative study, online focus group session(s) were held with stakeholders, audiorecorded, transcribed and analysed thematically.Results Fifteen participants attended the online priority setting sessions. Criteria for prioritising digital health research fell into three themes, namely: public health benefit, health system-level factors and research process and feasibility. We identified criteria unique to digital health research as the availability of suitable governance frameworks, candidate technology’s alignment with other technologies in use,and the possibility of data-driven insights from health technology data. The final selected use cases were remote monitoring of patients with pulmonary conditions, sepsis detection and automated breast screening.Conclusion The criteria for determining digital health research priority areas are more nuanced than that of traditional health condition focused research and can neither be viewed solely through a clinical lens nor technological lens. As digital health research relies heavily on health technology implementation, digital health prioritisation criteria comprised enablers of successful technology implementation. Our prioritisation process could be applied to other settings and collaborative projects where research institutions partner with healthcare delivery organisations.Data are available on reasonable request. The data that support the findings of this study are available on request from the corresponding author. The data are not publicly available due to privacy or ethical restrictions.