Patient and Staff Experience of Remote Patient Monitoring-What to Measure and How: Systematic Review

BACKGROUND

Patient and staff experience is a vital factor to consider in the evaluation of remote patient monitoring (RPM) interventions. However, no comprehensive overview of available RPM patient and staff experience-measuring methods and tools exists.

OBJECTIVE

This review aimed at obtaining a comprehensive set of experience constructs and corresponding measuring instruments used in contemporary RPM research and at proposing an initial set of guidelines for improving methodological standardization in this domain.

METHODS

Full-text papers reporting on instances of patient or staff experience measuring in RPM interventions, written in English, and published after January 1, 2011, were considered for eligibility. By "RPM interventions," we referred to interventions including sensor-based patient monitoring used for clinical decision-making; papers reporting on other kinds of interventions were therefore excluded. Papers describing primary care interventions, involving participants under 18 years of age, or focusing on attitudes or technologies rather than specific interventions were also excluded. We searched 2 electronic databases, Medline (PubMed) and EMBASE, on February 12, 2021.We explored and structured the obtained corpus of data through correspondence analysis, a multivariate statistical technique.

RESULTS

In total, 158 papers were included, covering RPM interventions in a variety of domains. From these studies, we reported 546 experience-measuring instances in RPM, covering the use of 160 unique experience-measuring instruments to measure 120 unique experience constructs. We found that the research landscape has seen a sizeable growth in the past decade, that it is affected by a relative lack of focus on the experience of staff, and that the overall corpus of collected experience measures can be organized in 4 main categories (service system related, care related, usage and adherence related, and health outcome related). In the light of the collected findings, we provided a set of 6 actionable recommendations to RPM patient and staff experience evaluators, in terms of both what to measure and how to measure it. Overall, we suggested that RPM researchers and practitioners include experience measuring as part of integrated, interdisciplinary data strategies for continuous RPM evaluation.

CONCLUSIONS

At present, there is a lack of consensus and standardization in the methods used to measure patient and staff experience in RPM, leading to a critical knowledge gap in our understanding of the impact of RPM interventions. This review offers targeted support for RPM experience evaluators by providing a structured, comprehensive overview of contemporary patient and staff experience measures and a set of practical guidelines for improving research quality and standardization in this domain.

From digital health to learning health systems: four approaches to using data for digital health design

Digital health technologies, powered by digital data, provide an opportunity to improve the efficacy and efficiency of health systems at large. However, little is known about different approaches to the use of data for digital health design, or about their possible relations to system-level dynamics. In this contribution, we identify four existing approaches to the use of data for digital health design, namely the silent, the overt, the data-enabled, and the convergent. After characterising the approaches, we provide real-life examples of each. Furthermore, we compare the approaches in terms of selected desirable characteristics of the design process, highlighting relative advantages and disadvantages. Finally, we reflect on the system-level relevance of the differentiation between the approaches and point towards future research directions. Overall, the contribution provides researchers and practitioners with a broad conceptual framework to examine data-related challenges and opportunities in digital health design.

Remote patient monitoring for perioperative care: a scoping review on workflow implications for clinical staff (Preprint)

Background

Remote patient monitoring (RPM) interventions are being increasingly implemented in health care environments, given their benefits for different stakeholders. However, the effects of these interventions on the workflow of clinical staff are not always considered in RPM research and practice.

Objective

This review explored how contemporary RPM interventions affect clinical staff and their workflows in perioperative settings.

Methods

We conducted a scoping review of recent articles reporting the impact of RPM interventions implemented in perioperative settings on clinical staff and their workflow. The databases accessed were Embase and PubMed. A qualitative analysis was performed to identify the main problems and advantages that RPM brings to staff, in addition to the approaches taken to evaluate the impact of those interventions. Different themes were identified in terms of the challenges of RPM for clinical staff as well as in terms of benefits, risk-reduction strategies, and methods for measuring the impact of these interventions on the workflow of clinical staff.

Results

A total of 1063 papers were found during the initial search, of which 21 (1.98%) met the inclusion criteria. Of the 21 included papers, 15 (71%) focused on evaluating new RPM systems, 4 (19%) focused on existing systems, and 2 (10%) were reviews.

Conclusions

The reviewed literature shows that the impact on staff work experience is a crucial factor to consider when developing and implementing RPM interventions in perioperative settings. However, we noticed both underdevelopment and lack of standardization in the methods for assessing the impact of these interventions on clinical staff and their workflow. On the basis of the reviewed literature, we recommend the development of more robust methods for evaluating the impact of RPM interventions on staff experience in perioperative care; the adoption of a stronger focus on transition management when introducing these interventions in clinical practice; and the inclusion of longer periods of assessment, including the evaluation of long-term goals.

Adrenocorticotropin induces heme oxygenase-1 expression in adrenal cells

Heme oxygenase (HO) catalyzes the first and rate-controlling step of heme catabolism into biliverdin, iron and carbon monoxide. Three isoforms of HO have been identified so far: the inducible HO-1 and the constitutive HO-2 and HO-3. Both HO-1 and HO-2 were expressed in zona fasciculata (ZF) adrenal cells and in a mouse adrenocortical cell line (Y1). HO-1 but not HO-2 expression was upregulated by adrenocorticotropic hormone (ACTH) and accumulation of HO-1 protein correlated with an increase in HO activity in Y1 cells. ACTH induced HO-1 expression in a time- and dose-dependent manner with a maximum after 5 h of treatment and a threshold concentration of 0.1 mIU/ml. Actinomycin D and cycloheximide completely blocked the effect of ACTH on HO-1 mRNA expression whereas mRNA stability was not affected by ACTH. Permeable analogs of cAMP mimicked the effect of ACTH on HO-1 expression and ACTH induction was prevented by the protein kinase A (PKA) inhibitor H89. Steroid production was significantly increased when both HO-1 and HO-2 activities were inhibited by Sn-protoporphyrin IX (SnPPIX). The lipid peroxidation and increase in carbonyl content triggered by hydrogen peroxide was prevented by treatment of Y1 cells with bilirubin and ACTH.