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BackgroundLow back pain (LBP) was the fifth most common reason for an emergency department (ED) visit in 2020-2021 in Australia, with >145,000 presentations. A total of one-third of these patients were subsequently admitted to the hospital. The admitted patient care accounts for half of the total health care expenditure on LBP in Australia. ObjectiveThe primary aim of the Back@Home study is to assess the effectiveness of a virtual hospital model of care to reduce the length of admission in people presenting to ED with musculoskeletal LBP. A secondary aim is to evaluate the acceptability and feasibility of the virtual hospital and our implementation strategy. We will also investigate rates of traditional hospital admission from the ED, representations and readmissions to the traditional hospital, demonstrate noninferiority of patient-reported outcomes, and assess cost-effectiveness of the new model. MethodsThis is a hybrid effectiveness-implementation type-I study. To evaluate effectiveness, we plan to conduct an interrupted time-series study at 3 metropolitan hospitals in Sydney, New South Wales, Australia. Eligible patients will include those aged 16 years or older with a primary diagnosis of musculoskeletal LBP presenting to the ED. The implementation strategy includes clinician education using multimedia resources, staff champions, and an “audit and feedback” process. The implementation of “Back@Home” will be evaluated over 12 months and compared to a 48-month preimplementation period using monthly time-series trends in the average length of hospital stay as the primary outcome. We will construct a plot of the observed and expected lines of trend based on the preimplementation period. Linear segmented regression will identify changes in the level and slope of fitted lines, indicating immediate effects of the intervention, as well as effects over time. The data will be fully anonymized, with informed consent collected for patient-reported outcomes. ResultsAs of December 6, 2023, a total of 108 patients have been cared for through Back@Home. A total of 6 patients have completed semistructured interviews regarding their experience of virtual hospital care for nonserious back pain. All outcomes will be evaluated at 6 months (August 2023) and 12 months post implementation (February 2024). ConclusionsThis study will serve to inform ongoing care delivery and implementation strategies of a novel model of care. If found to be effective, it may be adopted by other health districts, adapting the model to their unique local contexts. International Registered Report Identifier (IRRID)PRR1-10.2196/50146

BackgroundAlternate “hospital avoidance” models of care are required to manage the increasing demand for acute inpatient beds. There is currently a knowledge gap regarding the perspectives of hospital clinicians on barriers and facilitators to a transition to virtual care for low back pain. We plan to implement a virtual hospital model of care called “Back@Home” and use qualitative interviews with stakeholders to develop and refine the model. ObjectiveWe aim to explore clinicians’ perspectives on a virtual hospital model of care for back pain (Back@Home) and identify barriers to and enablers of successful implementation of this model of care. MethodsWe conducted semistructured interviews with 19 purposively sampled clinicians involved in the delivery of acute back pain care at 3 metropolitan hospitals. Interview data were analyzed using the Theoretical Domains Framework. ResultsA total of 10 Theoretical Domains Framework domains were identified as important in understanding barriers and enablers to implementing virtual hospital care for musculoskeletal back pain. Key barriers to virtual hospital care included patient access to videoconferencing and reliable internet, language barriers, and difficulty building rapport. Barriers to avoiding admission included patient expectations, social isolation, comorbidities, and medicolegal concerns. Conversely, enablers of implementing a virtual hospital model of care included increased health care resource efficiency, clinician familiarity with telehealth, as well as a perceived reduction in overmedicalization and infection risk. ConclusionsThe successful implementation of Back@Home relies on key stakeholder buy-in. Addressing barriers to implementation and building on enablers is crucial to clinicians’ adoption of this model of care. Based on clinicians’ input, the Back@Home model of care will incorporate the loan of internet-enabled devices, health care interpreters, and written resources translated into community languages to facilitate more equitable access to care for marginalized groups.