Comparing efficiency of health systems across industrialized countries: a panel analysis.

BackgroundRankings from the World Health Organization (WHO) place the US health care system as one of the least efficient among Organization for Economic Cooperation and Development (OECD) countries. Researchers have questioned this, noting simplistic or inappropriate methodologies, poor measurement choice, and poor control variables. Our objective is to re-visit this question by using newer modeling techniques and a large panel of OECD data.MethodsWe primarily use the OECD Health Data for 25 OECD countries. We compare results from stochastic frontier analysis (SFA) and fixed effects models. We estimate total life expectancy as well as life expectancy at age 60. We explore a combination of control variables reflecting health care resources, health behaviors, and economic and environmental factors.ResultsThe US never ranks higher than fifth out of all 36 models, but is also never the very last ranked country though it was close in several models. The SFA estimation approach produces the most consistent lead country, but the remaining countries did not maintain a steady rank.DiscussionOur study sheds light on the fragility of health system rankings by using a large panel and applying the latest efficiency modeling techniques. The rankings are not robust to different statistical approaches, nor to variable inclusion decisions.ConclusionsFuture international comparisons should employ a range of methodologies to generate a more nuanced portrait of health care system efficiency

Fast and flexible inference of joint distributions from their marginals

Copyright 2019 by the author(s). Across the social sciences and elsewhere, practitioners frequently have to reason about relationships between random variables, despite lacking joint observations of the variables. This is sometimes called an "ecological" inference; given samples from the marginal distributions of the variables, one attempts to infer their joint distribution. The problem is inherently ill-posed, yet only a few models have been proposed for bringing prior information into the problem, often relying on restrictive or unrealistic assumptions and lacking a unified approach. In this paper, we treat the inference problem generally and propose a unified class of models that encompasses some of those previously proposed while including many new ones. Previous work has relied on either relaxation or approximate inference via MCMC, with the latter known to mix prohibitively slowly for this type of problem. Here we instead give a single exact inference algorithm that works for the entire model class via an efficient fixed point iteration called Dykstra's method. We investigate empirically both the computational cost of our algorithm and the accuracy of the new models on real datasets, showing favorable performance in both cases and illustrating the impact of increased flexibility in modeling enabled by this work

Critical loads for soil in Norway, Nordmoen

We evaluate the critical load for soil and water at Nordmoen using the dynamic model Magic, the static PROFILE model, and the empirical method as suggested by the mapping handbook. Nordmoen is located about 60 km N of Oslo on thick deposits of glaciofluvial sands, and receives moderate (for Norway) levels of acid deposition (53 meqSO4/m²/yr). At Nordmoen both acid deposition and forestry practices have caused soil acidification. MOGIC indicates that the "tolerable" load is 0 meq SO4/m²/yr under the conditions that the CA/AL molar ratio in soil solution be above 1 or 0.5. The estimate assumes that forestry practices will continue for the next 50 years. The empirical method for waters gives a critical load estimate of 126 meq SO4/m²/yr. Nordmoen is thus a site in Norway at which the soil and forest are more sensitive than surface waters. These results can be used to determinate under which circumstances forest will be more sensitive than fish, and thus provide a basis for mapping critical load

Maps of critical loads and exceedance for sulfur and nitrogen to forest soils in Norway

We use the dynamic MAGIC model to calculate critical loads of sulfur and nitrogen for forest soils in Norway. Inputs include the soil surveydata of NIJOS and NISK, the atmospheric deposition data of NILU, the forest productivity data of NIJOS, and the surface water chemistry of NIVA. Two scenarios for future sulfur deposition are used with two scenarios of nitrogen retention in catchments. The magnitude and patterns of calculated nitrogen critical loads and exceedance differ substantially depending on the scenario chosen for sulfur deposition and nitrogen retention. In worst case critical loads for N are low and exceed in southernmost Norway. In the best case critical loads for N are high and not exceeded. More information on the processes controlling N retention in forested ecosystems is of outmost importance for the specification of nitrogen critical loads

Convection-permitting ensembles : Challenges related to their design and use

Challenges related to the design and use of a convection-permitting ensemble (CPEPS) are discussed. In particular the scale-dependent predictability of precipitation and the use of a CPEPS as well as its potential added value over global ensemble prediction systems (EPS) are investigated. Forecasts of precipitation from the operational CPEPS in Finland, Norway and Sweden (MEPS) are used for the investigations. It is found that predictability for scales smaller than similar to 60 km is lost rapidly within the first 6 h of the forecast with the smallest predictable scale growing more slowly to similar to 100 km over the following 18-24 h. However, there is large case-to-case variability and the ensemble perturbations fail to become fully saturated, especially in winter, suggesting a weakness in the design of the ensemble. The added value of CPEPS over deterministic forecasts and coarser resolution EPSs is discussed with summary statistics and case-studies. It is shown that the added value varies between seasons and lead times. For precipitation there is an added value for both severe precipitation events and for precipitation/no precipitation decisions. The added value is higher in summer compared to winter and for shorter lead times compared to longer lead times

Map of critical loads (sulphur) for coniferous forest soils in Norway

Maps of critical loads of acidity and exceedance (sulphur) for coniferous forest soils in Norway have been compiled using the dynamic MAGIC model based on the soil survey data of NIJOS and NISK, the atmospheric deposition data of NILU, the forest productivity data of NIJOS, and the surface water chemistry data base of NIVA. The criterion used was that the Ca/Al molar ratio in soil solution should not fall beneath 1.0 in the uppermost 50 cm of soil. Scenarios were run 50 years into the future under the assumptions that nitrogen deposition and nitrogen retention are unchanged relative to the present. The results show that the critical load for soils is higher than the critical load for water (i.e soils are less sensitive). Critical loads for soils are exceeded by present-day sulphur deposition in many squares in southernmost Norway. There are indications that crown density of spruce stands in these squares in also lower than in nearby squares in which the critical load is not exceeded.Norwegian Directorate for Nature Management (DN