Estimating the value of repositioning timing to streamline pressure injury prevention efforts in nursing homes: A cost-effectiveness analysis of the 'TEAM-UP' clinical trial.

Pressure injury (PrI) prevention guidelines recommend 2-h repositioning intervals in healthcare settings, requiring significant nursing time investment. We analysed the cost-effectiveness of PrI prevention protocols with 2-, 3- and 4-h repositioning intervals in US nursing homes according to 'Turn Everyone and Move for Ulcer Prevention' (TEAM-UP) randomized controlled trial findings. Markov modelling compared 2-, 3- and 4-h repositioning intervals, controlling for other practice guidelines, to prevent PrIs in nursing home residents from a US health sector perspective over one year using TEAM-UP trial data for model structure, sampling and parameterization. Costs, captured in 2020 US dollars, and quality-adjusted life years (QALYs) were used to derive an incremental cost-effectiveness ratio and net monetary benefit (NMB) at $50 000/QALY-$150 000/QALY cost-effectiveness thresholds. Sensitivity analyses tested model uncertainty. Repositioning intervals between 3 and 4 h were cost-effective based on reduced costs at slightly lower QALYs than 2 h at a $50 000/QALY threshold, and the NMB of 4-h repositioning was also more efficient than at 3 h ($9610). Repositioning labour cost and prevention routines were among the most sensitive parameters. Sensitivity analyses demonstrated that 3- and 4-h intervals were cost-effective in over 65% of simulations at any cost-effectiveness threshold. Repositioning intervals of 3 to 4 h have potential to reduce nursing time costs without significant decrements in clinical benefits to nursing home residents. Clinical guidelines for PrI prevention should be updated to reflect TEAM-UP clinical and economic findings. Facilities can use cost-savings recuperated from nursing time to deploy to other patient safety priorities without seriously jeopardizing PrI safety.

A Cost-Utility Analysis of Remote Pulse-Oximetry Monitoring of Patients With COVID-19.

OBJECTIVES: Since 2020, COVID-19 has infected tens of millions and caused hundreds of thousands of fatalities in the United States. Infection waves lead to increased emergency department utilization and critical care admission for patients with respiratory distress. Although many individuals develop symptoms necessitating a ventilator, some patients with COVID-19 can remain at home to mitigate hospital overcrowding. Remote pulse-oximetry (pulse-ox) monitoring of moderately ill patients with COVID-19 can be used to monitor symptom escalation and trigger hospital visits, as needed. METHODS: We analyzed the cost-utility of remote pulse-ox monitoring using a Markov model with a 3-week time horizon and daily cycles from a US health sector perspective. Costs (US dollar 2020) and outcomes were derived from the University Hospitals' real-world evidence and published literature. Costs and quality-adjusted life-years (QALYs) were used to determine the incremental cost-effectiveness ratio at a cost-effectiveness threshold of $100 000 per QALY. We assessed model uncertainty using univariate and probabilistic sensitivity analyses. RESULTS: Model results demonstrated that remote monitoring dominates current standard care, by reducing costs ($11 472 saved) and improving outcomes (0.013 QALYs gained). There were 87% fewer hospitalizations and 77% fewer deaths among patients with access to remote pulse-ox monitoring. The incremental cost-effectiveness ratio was not sensitive to uncertainty ranges in the model. CONCLUSIONS: Patient with COVID-19 remote pulse-ox monitoring increases the specificity of those requiring follow-up care for escalating symptoms. We recommend remote monitoring adoption across health systems to economically manage COVID-19 volume surges, maintain patients' comfort, reduce community infection spread, and carefully monitor needs of multiple individuals from one location by trained experts.

Diagnosing newborns with suspected mitochondrial disorders: an economic evaluation comparing early exome sequencing to current typical care.

PURPOSE: To determine the value of early exome sequencing (eES) relative to the current typical care (TC) in the diagnosis of newborns with suspected severe mitochondrial disorders (MitD). METHODS: We used a decision tree-Markov hybrid to model neonatal intensive care unit (NICU)-related outcomes and costs, lifetime costs and quality-adjusted life-years among patients with MitD. Probabilities, costs, and utilities were populated using published literature, expert opinion, and the Pediatric Health Information System database. Incremental cost-effectiveness ratios (ICER) and net monetary benefits (NMB) were calculated from lifetime costs and quality-adjusted life-years for singleton and trio eES, and TC. Robustness was assessed using univariate and probabilistic sensitivity analyses (PSA). Scenario analyses were also conducted. RESULTS: Findings indicate trio eES is a cost-minimizing and cost-effective alternative to current TC. Diagnostic probabilities and NICU length-of-stay were the most sensitive model parameters. Base case analysis demonstrates trio eES has the highest incremental NMB, and PSA demonstrates trio eES had the highest likelihood of being cost-effective at a willingness-to-pay (WTP) of $200,000 relative to TC, singleton eES, and no ES. CONCLUSION: Trio and singleton eES are cost-effective and cost-minimizing alternatives to current TC in diagnosing newborns suspected of having a severe MitD.

A US Population Health Survey on the Impact of COVID-19 Using the EQ-5D-5L.

BACKGROUND: The COVID-19 pandemic has resulted in negative impacts on the economy, population health, and health-related quality-of-life (HRQoL). OBJECTIVE: To assess the impact of COVID-19 on US population HRQoL using the EQ-5D-5L. DESIGN: We surveyed respondents on physical and mental health, demographics, socioeconomics, brief medical history, current COVID-19 status, sleep, dietary, financial, and spending changes. Results were compared to online and face-to-face US population norms. Predictors of EQ-5D-5L utility were analyzed using both standard and post-lasso OLS regressions. Robustness of regression coefficients against unmeasured confounding was analyzed using the E-Value sensitivity analysis. SUBJECTS: Amazon MTurk workers (n=2776) in the USA. MAIN MEASURES: EQ-5D-5L utility and VAS scores by age group. KEY RESULTS: We received n=2746 responses. Subjects 18-24 years reported lower mean (SD) health utility (0.752 (0.281)) compared with both online (0.844 (0.184), p=0.001) and face-to-face norms (0.919 (0.127), p<0.001). Among ages 25-34, utility was worse compared to face-to-face norms only (0.825 (0.235) vs. 0.911 (0.111), p<0.001). For ages 35-64, utility was better during pandemic compared to online norms (0.845 (0.195) vs. 0.794 (0.247), p<0.001). At age 65+, utility values (0.827 (0.213)) were similar across all samples. VAS scores were worse for all age groups (p<0.005) except ages 45-54. Increasing age and income were correlated with increased utility, while being Asian, American Indian or Alaska Native, Hispanic, married, living alone, having history of chronic illness or self-reported depression, experiencing COVID-19-like symptoms, having a family member diagnosed with COVID-19, fear of COVID-19, being underweight, and living in California were associated with worse utility scores. Results were robust to unmeasured confounding. CONCLUSIONS: HRQoL decreased during the pandemic compared to US population norms, especially for ages 18-24. The mental health impact of COVID-19 is significant and falls primarily on younger adults whose health outcomes may have been overlooked based on policy initiatives to date.