This scoping review mapped and synthesised original research that identified low-value care in hospital settings as part of multicomponent processes.

Scoping review.

Electronic databases (EMBASE, PubMed, CINAHL, PsycINFO and Cochrane CENTRAL) and grey literature were last searched 11 July and 3 June 2022, respectively, with no language or date restrictions.

We included original research targeting the identification and prioritisation of low-value care as part of a multicomponent process in hospital settings.

Screening was conducted in duplicate. Data were extracted by one of six authors and checked by another author. A framework synthesis was conducted using seven areas of focus for the review and an overuse framework.

Twenty-seven records were included (21 original studies, 4 abstracts and 2 reviews), originating from high-income countries. Benefit or value (11 records), risk or harm (10 records) were common concepts referred to in records that explicitly defined low-value care (25 records). Evidence of contextualisation including barriers and enablers of low-value care identification processes were identified (25 records). Common components of these processes included initial consensus, consultation, ranking exercise or list development (16 records), and reviews of evidence (16 records). Two records involved engagement of patients and three evaluated the outcomes of multicomponent processes. Five records referenced a theory, model or framework.

Gaps identified included applying systematic efforts to contextualise the identification of low-value care, involving people with lived experience of hospital care and initiatives in resource poor contexts. Insights were obtained regarding the theories, models and frameworks used to guide initiatives and ways in which the concept ‘low-value care’ had been used and reported. A priority for further research is evaluating the effect of initiatives that identify low-value care using contextualisation as part of multicomponent processes.

To understand and report on the direct-to-consumer virtual care industry in Canada, focusing on how companies collect, use and value patient data.

Qualitative study using situational analysis methodology.

Canadian for-profit virtual care industry.

18 individuals employed by or affiliated with the Canadian virtual care industry.

Semistructured interviews were conducted between October 2021 and January 2022 and publicly available documents on websites of commercial virtual care platforms were retrieved. Analysis was informed by situational analysis, a constructivist grounded theory methodology, with a continuous and iterative process of data collection and analysis; theoretical sampling and creation of theoretical concepts to explain findings.

Participants described how companies in the virtual care industry highly valued patient data. Companies used data collected as patients accessed virtual care platforms and registered for services to generate revenue, often by marketing other products and services. In some cases, virtual care companies were funded by pharmaceutical companies to analyse data collected when patients interacted with a healthcare provider and adjust care pathways with the goal of increasing uptake of a drug or vaccine. Participants described these business practices as expected and appropriate, but some were concerned about patient privacy, industry influence over care and risks to marginalised communities. They described how patients may have agreed to these uses of their data because of high levels of trust in the Canadian health system, problematic consent processes and a lack of other options for care.

Patients, healthcare providers and policy-makers should be aware that the direct-to-consumer virtual care industry in Canada highly values patient data and appears to view data as a revenue stream. The industry’s data handling practices of this sensitive information, in the context of providing a health service, have implications for patient privacy, autonomy and quality of care.

Physical inactivity is a risk factor for repeat cardiac events and all-cause mortality in coronary heart disease (CHD). Cardiac rehabilitation, a secondary prevention programme, aims to increase physical activity levels in this population from a reported low baseline. This trial will investigate the effectiveness and implementation of a very brief physical activity intervention, comparing different frequencies of physical activity measurement by cardiac rehabilitation clinicians. The Measure It! intervention (

This type 1 hybrid effectiveness–implementation study will use a two-arm multicentre assessor-blind randomised trial design. Insufficiently active (

The study has ethical approval (University of Canberra (ID 11836), Calvary Bruce Public Hospital (ID 14-2022) and the Greater Western Area (ID 2022/ETH01381) Human Research Ethics Committees). Results will be disseminated in multiple formats for consumer, public and clinical audiences.

ACTRN12622001187730p.

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.

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.

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.

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.