The Impact of Virtual Reality on Anxiety and Pain During US-Guided Breast Biopsies: A Randomized Controlled Clinical Trial.

OBJECTIVE: To investigate the efficacy of immersive virtual reality (VR) in combination with standard local anesthetic for mitigating anxiety and pain during US-guided breast biopsies compared to local anesthetic alone. METHODS: Patients scheduled for US-guided biopsy were invited to participate. Eligible patients were females 18 years of age or older. Patients were randomized to VR or control group at a 1:1 ratio. Patients in the VR group underwent biopsy with the addition of a VR experience and patients in the control group underwent usual biopsy. Patient-perceived levels of anxiety and pain were collected before and after biopsy via the State-Trait Anxiety Inventory (STAI) and Visual Analog Scale (VAS). Physiological data were captured during biopsy using a clinically validated wristband. Differences in anxiety, pain, and physiologic data were compared between the VR and control group. RESULTS: Sixty patients were enrolled. After excluding 2 patients with VR device malfunction, there were 29 patients in the VR and 29 patients in the control group for analysis. The VR group had reduced anxiety compared to the control group based on postintervention STAI (P <.001) and VAS (P = .036). The VR group did not have lower pain based on postintervention VAS (P = .555). Physiological measures showed higher RR intervals and decreased skin conductance levels, which are associated with lower anxiety levels in the VR group. CONCLUSION: Use of VR in addition to standard local anesthetic for US-guided breast biopsies was associated with reduced patient anxiety. Virtual reality may be a useful tool to improve the patient biopsy experience.

Risk-adjusted policies to minimise perioperative staffing shortages during a pandemic: An agent-based simulation study.

Healthcare workers' (HCWs) safety and availability to care for patients are critical during a pandemic such as the one caused by severe acute respiratory syndrome coronavirus 2. Among providers of different specialities, it is critical to protect those working in hospital settings with a high risk of infection. Using an agent-based simulation model, various staffing policies were developed and simulated for 90 days using data from the largest health systems in South Carolina. The model considers staffing policies that include geographic segregation, interpersonal contact limits, and a combination of factors, including the patient census, transmission rates, vaccination status of providers, hospital capacity, incubation time, quarantine period, and interactions between patients and providers. Comparing the existing practices to various risk-adjusted staffing policies, model predictions show that restricted teaming and rotating schedules significantly (p-value <0.01) reduced weekly HCW unavailability and the number of infected HCWs by 22% and 38%, respectively, when the vaccination rates among HCWs were lower (<75%). However, as the vaccination rate increases, the benefits of risk-adjusted policies diminish; and when 90% of HCWs were vaccinated, there were no significant (p-value = 0.09) benefits. Although these simulated outcomes are specific to one health system, our findings can be generalised to other health systems with multiple locations.