A COVID-19 Recovery Strategy Based on the Health System Capacity Modeling. Implications on Citizen Self-management

Versión preprint depositada sin articulo publicado dada la actualidad del tema. *Solicitud de los autoresConfinement ends, and recovery phase should be accurate planned. Health System (HS) capacity, specially ICUs and plants capacity and availability, will remain the key stone in this new Covid-19 pandemic life cycle phase. Until massive vaccination programs will be a real option (vaccine developed, world wield production capacity and effective and efficient administration process), date that will mark recovery phase end, important decisions should be taken. Not only by authorities. Citizen self-management and organizations self-management will be crucial. This means: citizen and organizations day a day decision in order to control their own risks (infecting others and being infected). This paper proposes a management tool that is based on a ICUs and plants capacity model. Principal outputs of this tool are, by sequential order and by last best data available: (i) ICUs and plants saturation estimation data (according to incoming rate of patients), (ii) with this results new local and temporal confinement measure can be planned and also a dynamic analysis can be done to estimate maximum Ro saturation scenarios, and finally (iii) provide citizen with clear and accurate data allow them adapting their behavior to authorities’ previous recommendations. One common objective: to accelerate as much as possible socioeconomic normalization with a strict control over HS relapses risk

Survivor-complier effects in the presence of selection on treatment, with application to a study of prompt ICU admission

Pre-treatment selection or censoring (`selection on treatment') can occur when two treatment levels are compared ignoring the third option of neither treatment, in `censoring by death' settings where treatment is only defined for those who survive long enough to receive it, or in general in studies where the treatment is only defined for a subset of the population. Unfortunately, the standard instrumental variable (IV) estimand is not defined in the presence of such selection, so we consider estimating a new survivor-complier causal effect. Although this effect is generally not identified under standard IV assumptions, it is possible to construct sharp bounds. We derive these bounds and give a corresponding data-driven sensitivity analysis, along with nonparametric yet efficient estimation methods. Importantly, our approach allows for high-dimensional confounding adjustment, and valid inference even after employing machine learning. Incorporating covariates can tighten bounds dramatically, especially when they are strong predictors of the selection process. We apply the methods in a UK cohort study of critical care patients to examine the mortality effects of prompt admission to the intensive care unit, using ICU bed availability as an instrument

Cost-effectiveness of Implementing Low-Tidal Volume Ventilation in Patients With Acute Lung Injury

Background: Despite widespread guidelines recommending the use of lung-protective ventilation (LPV) in patients with acute lung injury (ALI), many patients do not receive this lifesaving therapy. We sought to estimate the incremental clinical and economic outcomes associated with LPV and determined the maximum cost of a hypothetical intervention to improve adherence with LPV that remained cost-effective. Methods: Adopting a societal perspective, we developed a theoretical decision model to determine the cost-effectiveness of LPV compared to non-LPV care. Model inputs were derived from the literature and a large population-based cohort of patients with ALI. Cost-effectiveness was determined as the cost per life saved and the cost per quality-adjusted life-years (QALYs) gained. Results: Application of LPV resulted in an increase in QALYs gained by 15% (4.21 years for non-LPV vs 4.83 years for LPV), and an increase in lifetime costs of $7,233 per patient with ALI ($99,588 for non-LPV vs $106,821 for LPV). The incremental cost-effectiveness ratios for LPV were$22,566 per life saved at hospital discharge and $11,690 per QALY gained. The maximum, cost-effective, per patient investment in a hypothetical program to improve LPV adherence from 50 to 90$9,482. Results were robust to a wide range of economic and patient parameter assumptions. Conclusions: Even a costly intervention to improve adherence with low-tidal volume ventilation in patients with ALI reduces death and is cost-effective by current societal standards.NIH F32HL090220.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/84154/1/Cooke - CEA LPV.pd

Developing minimum clinical standards for physiotherapy in South African ICUs: A qualitative study

Rationale, aims, and objectives: Physiotherapists are integral members of the intensive care unit (ICU) team. Clinicians working in ICU are dependent on their own experience when making decisions regarding individual patient management thus resulting in variation in clinical practice. No formalized clinical practice guidelines or standards exist for the educational profile or scope of practice requirements for ICU physiotherapy. This study explored perceptions of physiotherapists on minimum clinical standards that ICU physiotherapists should adhere to for delivering safe, effective physiotherapy services to critically ill patients. Method: Experienced physiotherapists offering a service to South African ICUs were purposively sampled. Three focus group sessions were held in different parts of the country to ensure national participation. Each was audio recorded. The stimulus question posed was “What is the minimum standard of clinical practice needed by physiotherapists to ensure safe and independent practice in South African ICUs?” Three categories were explored, namely, knowledge, skill, and attributes. Themes and subthemes were developed using the codes identified. An inductive approach to data analysis was used to perform conventional content analysis. Results: Twenty-five physiotherapists participated in 1 of 3 focus group sessions. Mean years of ICU experience was 10.8 years (±7.0; range, 3-33). Three themes emerged from the data namely, integrated medical knowledge, multidisciplinary teamwork, and physiotherapy practice. Integrated medical knowledge related to anatomy and physiology, conditions that patients present with in ICU, the ICU environment, pathology and pathophysiology, and pharmacology. Multidisciplinary teamwork encompassed elements related to communication, continuous professional development, cultural sensitivity, documentation, ethics, professionalism, safety in ICU, and technology. Components related to physiotherapy practice included clinical reasoning, handling skills, interventions, and patient care. Conclusions: The information obtained will be used to inform the development of a list of standards to be presented to the wider national physiotherapy and ICU communities for further consensus-building activities

Snakebite: An Exploratory Cost-Effectiveness Analysis of Adjunct Treatment Strategies.

The cost-effectiveness of the standard of care for snakebite treatment, antivenom, and supportive care has been established in various settings. In this study, based on data from South Indian private health-care providers, we address an additional question: "For what cost and effectiveness values would adding adjunct-based treatment strategies to the standard of care for venomous snakebites be cost-effective?" We modeled the cost and performance of potential interventions (e.g., pharmacologic or preventive) used adjunctively with antivenom and supportive care for the treatment of snakebite. Because these potential interventions are theoretical, we used a threshold cost-effectiveness approach to explore this forward-looking concept. We examined economic parameters at which these interventions could be cost-effective or even cost saving. A threshold analysis was used to examine the addition of new interventions to the standard of care. Incremental cost-effectiveness ratios were used to compare treatment strategies. One-way, scenario, and probabilistic sensitivity analyses were conducted to analyze parameter uncertainty and define cost and effectiveness thresholds. Our results suggest that even a 3% reduction in severe cases due to an adjunct strategy is likely to reduce the cost of overall treatment and have the greatest impact on cost-effectiveness. In this model, for example, an investment of $10 of intervention that reduces the incidence of severe cases by 3$75 per individual. These findings illustrate the striking degree to which an adjunct intervention could improve patient outcomes and be cost-effective or even cost saving