Evaluating the Economic Impact of Palliative and End-of-Life Care Interventions on Intensive Care Unit Utilization and Costs from the Hospital and Healthcare System Perspective.

Purpose of report: Understanding the impact of palliative care interventions on intensive care unit (ICU) costs and utilization is critical for demonstrating the value of palliative care. Performing these economic assessments, however, can be challenging. The purpose of this special report is to highlight and discuss important considerations when assessing ICU utilization and costs from the hospital perspective, with the goal of providing recommendations on methods to consider for future analyses. FINDINGS: ICU length of stay (LOS) and associated costs of care are common and important outcome measures, but must be analyzed properly to yield valid conclusions. There is significant variation in costs by day of stay in the ICU with only modest differences between an ICU day at the end of a stay and the first day on the acute care floor; this variation must be appropriately accounted for analytically. Furthermore, reporting direct variable costs, in addition to total ICU costs, is needed to understand short-term and long-term impact of a reduction in LOS. Importantly, incentives for the hospital to realize savings vary depending on reimbursement policies. SUMMARY: ICU utilization and costs are common outcomes in studies evaluating palliative care interventions. Accurate estimation and interpretation are key to understanding the economic implications of palliative care interventions

Infant lung function tests as endpoints in the ISIS multicenter clinical trial in cystic fibrosis

BACKGROUND: The Infant Study of Inhaled Saline (ISIS) in CF was the first multicenter clinical trial to utilize infant pulmonary function tests (iPFTs) as an endpoint. METHODS: Secondary analysis of ISIS data was conducted in order to assess feasibility of iPFT measures and their associations with respiratory symptoms. Standard deviations were calculated to aid in power calculations for future clinical trials. RESULTS: Seventy-three participants enrolled, 70 returned for the final visit; 62 (89%) and 45 (64%) had acceptable paired functional residual capacity (FRC) and raised volume measurements, respectively. Mean baseline FEV0.5, FEF75 and FRC z-scores were 0.3 (SD: 1.2), -0.2 (SD: 2.0), and 1.8 (SD: 2.0). CONCLUSIONS: iPFTs are not appropriate primary endpoints for multicenter clinical trials due to challenges of obtaining acceptable data and near-normal average raised volume measurements. Raised volume measures have potential to serve as secondary endpoints in future clinical CF trials

Infant lung function tests as endpoints in the ISIS multicenter clinical trial in cystic fibrosis

The Infant Study of Inhaled Saline (ISIS) in CF was the first multicenter clinical trial to utilize infant pulmonary function tests (iPFTs) as an endpoint

Association of lung function, chest radiographs and clinical features in infants with cystic fibrosis

The optimal strategy for monitoring cystic fibrosis (CF) lung disease in infancy remains unclear

Lack of Fit in Self Modeling Regression: Application to Pulse Waveforms

Self modeling regression (SEMOR) is an approach for modeling sets of observed curves that have a common shape (or sequence of features) but have variability in the amplitude (y-axis) and/or timing (x-axis) of the features across curves. SEMOR assumes the x and y axes for each observed curve can be separately transformed in a parametric manner so that the features across curves are aligned with the common shape, usually represented by non-parametric function. We show that when the common shape is modeled with a regression spline and the transformational parameters are modeled as random with the traditional distribution (normal with mean zero), the SEMOR model may surprisingly suffer from lack of fit and the variance components may be over-estimated. A random effects distribution that restricts the predicted random transformational parameters to have mean zero or the inclusion of a fixed transformational parameter improves estimation. Our work is motivated by arterial pulse pressure waveform data where one of the variance components is a novel measure of short-term variability in blood pressure.

Lack of Fit in Self Modeling Regression: Application to Pulse Waveforms*

Self modeling regression (SEMOR) is an approach for modeling sets of observed curves that have a common shape (or sequence of features) but have variability in the amplitude (y-axis) and/or timing (x-axis) of the features across curves. SEMOR assumes the x and y axes for each observed curve can be separately transformed in a parametric manner so that the features across curves are aligned with the common shape, usually represented by non-parametric function. We show that when the common shape is modeled with a regression spline and the transformational parameters are modeled as random with the traditional distribution (normal with mean zero), the SEMOR model may surprisingly suffer from lack of fit and the variance components may be over-estimated. A random effects distribution that restricts the predicted random transformational parameters to have mean zero or the inclusion of a fixed transformational parameter improves estimation. Our work is motivated by arterial pulse pressure waveform data where one of the variance components is a novel measure of short-term variability in blood pressure

Adjusting for confounding by cluster using generalized linear mixed models

We show how to use generalized linear mixed models to adjust for confounding by cluster of the effect of a within-cluster covariate. We derive estimators for both a cluster-specific causal effect and a population-averaged causal effect.Model-based standardization Conditional likelihood Misspecified mixing distribution Prediction of random effects Causal inference

Endpoints for Clinical Trials in Young Children with Cystic Fibrosis

The availability of sensitive, reproducible, and feasible outcome measures for quantifying lung disease in children with cystic fibrosis (CF) younger than 6 years is critical to the conduct of clinical trials in this important population. Historically, identifying and quantifying the presence of lung disease in very young children with CF was hampered by a lack of reproducible measures of lung function or lung pathology. Over the past 10 years, significant progress has led to physiologic, anatomic, and bronchoscopic measures that may serve as endpoints for future intervention trials. These endpoints include infant and preschool lung function testing, computed tomography of the chest, and bronchoalveolar lavage markers of inflammation and infection. Much progress has occurred in standardizing lung function testing, which is essential for multicenter collaboration. Pulmonary exacerbation has the potential to serve as a clinical endpoint; however, there is currently no standardized definition in children with CF younger than 6 years. Further development of these outcomes measures will enable clinical trials in the youngest CF population with the objective of improving long-term prognosis