Development stage of novel digital health interventions for postoperative monitoring: protocol of a systematic review

Abstract

IntroductionThe postoperative period represents a time where patients are at a high-risk of morbidity, which warrants effective surveillance. While digital health interventions (DHIs) for postoperative monitoring are promising, a coordinated, standardized and evidence-based approach regarding their implementation and evaluation is currently lacking. This study aimed to identify DHIs implemented and evaluated in postoperative care to highlight research gaps and assess the readiness for routine implementation.MethodsA systematic review will be conducted in accordance with Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines to identify studies describing the implementation and evaluation of DHIs for postoperative monitoring published since 2000 (PROSPERO ID: CRD42021264289). This will encompass the Embase, Cumulative Index to Nursing and Allied Health Literature, Cochrane Library, Web of Science and ClinicalTrials.gov databases, and manual search of bibliographies for relevant studies and gray literature. Methodological reporting quality will be evaluated using the Idea, Development, Exploration, Assessment and Long-term Follow-up (IDEAL) reporting guideline relevant to the IDEAL stage of the study, and risk of bias will be assessed using the Grading of Recommendations, Assessment, Development and Evaluations (GRADE) framework. Data will be extracted according to the WHO framework for monitoring and evaluating DHIs, and a narrative synthesis will be performed.DiscussionThis review will assess the readiness for implementation of DHIs for routine postoperative monitoring and will include studies describing best practice from service changes already being piloted out of necessity during the COVID-19 pandemic. This will identify interventions with sufficient evidence to progress to the next IDEAL stage, and promote standardized and comprehensive evaluation of future implementational studies.

Dynamic Prediction of Patient Outcomes in the Intensive Care Unit: A Scoping Review of the State-of-the-Art

“…Scoping reviews can be used to identify emerging patterns in the literature for potentially extremely large research domains such as “digital technologies for postoperative care”, for example. 12 This mode of investigation is particularly useful for researching emerging technology innovations, where identifying broad trends is key as is the case for this study.…”

Artificial intelligence in surgery

“…As innovations proliferate toward the goal of remote postoperative monitoring, including mobile technologies 24 , sensors 149 , wearables 23 and hospital-at-home services, we have identified the key limitations to advancement to be the lack of routine large-scale implementation efforts, collaborations and comprehensive innovation evaluations in line with the IDEAL (idea, development, exploration, assessment and long-term follow-up) framework 154 .…”

“…AI in surgery is a rapidly developing and promising avenue for innovation; the realization of this potential will be underpinned by increased collaboration 154 , robust randomized trial evidence 55 , the exploration of novel use cases 164 and the development of a digitally minded surgical infrastructure to enable this technological transformation. The role of AI in surgery is set to expand dramatically and, with correct oversight, its ultimate promise is to effectively improve both patient and operator outcomes, reduce patient morbidity and mortality and enhance the delivery of surgery globally.…”

Patient-Centred, Technology-Based Interventions for High Treatment Burden: An Overview of the State of the Art

“…We here present an overview of the state of the art in technologies specifically developed for patients with high treatment burden, based on a recent scoping review that we have conducted in this domain [6]. Scoping reviews can be particularly useful to identify emerging patterns in the literature or mapping multi-dimensional and potentially loosely defined concepts such as 'eHealth', 'ePrescribing', 'optimisation' or potentially extremely large research domains such as 'digital technology' and 'postoperative monitoring' for example [7][8][9]. This mode of investigation is particularly useful for researching emerging technology innovations, where identifying broad trends is key but absolute recall is not essential, as opposed to systematic reviews aiming to underpin the development of policies or clinical guidelines for example [10].…”