On value-judgements and ethics in health technology assessment

The widespread application of technology in health care has imposed a broad range of challenges. The field of health technology assessment (HTA) is developed in order to face some of these challenges. However, this strategy has not been as successful as one could hope. One of the reasons for this is that social and ethical considerations have not been integrated in the HTA process. Nowadays however, such considerations have been included in many HTAs. Still, the conclusions and recommendations of the HTAs are not followed. The reason for this may be that the methods for integrating ethics for HTA are not sufficiently developed, or that they are not adequate. This article presents a supplementary approach to the ethical inquiry in HTA. It is argued that a value analysis is crucial in order to address the ethical issues of health care technology in a fruitful way and to make viable decisions about such technology.

Conflicting strategic objectives in hospital design

This paper presents a multigoal linear programming model designed to analyse the impact of different strategic objectives in the planning of hospitals. The paper argues that it is necessary to adopt an overall point-of-view in planning; that it is necessary to consider the interactions between the hospital, other social and health institutions and the community at large in order to attain an efficient plan. A simplified cost-benefit analysis is suggested, and it is demonstrated that the opportunity costs of lost working days may be more important than both capital and operating costs from a social point of view.     

Employment transitions for clubhouse members

Using a longitudinal dataset which followed 2195 individuals employed in 3379 separate job placements over a four-year period, this paper explores movement between the employment supports, [Transitional (TE), Supported (SE), and Independent Employment (IE)], offered by clubhouses. Sixty-four percent of employed members held only one job (N=1395) and 36% held multiple jobs during the study (N=791). Patterns of movement were consistent for transitions between the first and second job and subsequent transitions. Forty-six percent of individuals holding multiple jobs moved from one employment type to another. When movement occurred clubhouse members were significantly more likely to move from employment types offering more supports to those that offer less supports.     

A decision support methodology for strategic planning in maritime transportation

This paper presents a decision support methodology for strategic planning in tramp and industrial shipping. The proposed methodology combines simulation and optimization, where a Monte Carlo simulation framework is built around an optimization-based decision support system for short-term routing and scheduling. The simulation proceeds by considering a series of short-term routing and scheduling problems using a rolling horizon principle where information is revealed as time goes by. The approach is flexible in the sense that it can easily be configured to provide decision support for a wide range of strategic planning problems, such as fleet size and mix problems, analysis of long-term contracts and contract terms. The methodology is tested on a real case for a major Norwegian shipping company. The methodology provided valuable decision support on important strategic planning problems for the shipping company.     

Iterative bias reduction: a comparative study

Multivariate nonparametric smoothers, such as kernel based smoothers and thin plate splines smoothers, are adversely impacted by the sparseness of data in high dimension, also known as the curse of dimensionality. Adaptive smoothers, that can exploit the underlying smoothness of the regression function, may partially mitigate this effect. This paper presents a comparative simulation study of a novel adaptive smoother (IBR) with competing multivariate smoothers available as package or function within the R language and environment for statistical computing. Comparison between the methods are made on simulated datasets of moderate size, from 50 to 200 observations, with two, five or 10 potential explanatory variables, and on a real dataset. The results show that the good asymptotic properties of IBR are complemented by a very good behavior on moderate sized datasets, results which are similar to those obtained with Duchon low rank splines.     

Constructions of ‘the ageless’ asylum seekers: An analysis of how age is understood among professionals working within the norwegian immigration authorities

This article explores how professionals within the Norwegian immigration authorities conceptualise age when doing non-medical age assessments. By using social constructivism, which challenges an ethnocentric quantifying understanding of age, we delve into how socially constructed perceptions of childhood and adulthood manifest in assessment practices and the implications of these. By examining how applicants’ physical appearance, body language and life experience are used as an assessment basis, we argue that the ways age is conceptualised relate to Western ideas and ideals while overlooking other social and cultural backgrounds in which age is embedded.     

Against the De Minimis Principle

According to the class of de minimis decision principles, risks can be ignored (or at least treated very differently from other risks) if the risk is sufficiently small. In this article, we argue that a de minimis threshold has no place in a normative theory of decision making, because the application of the principle will either recommend ignoring risks that should not be ignored (e.g., the sure death of a person) or it cannot be used by ordinary bounded and information-constrained agents.     

Principal stratum strategy: Potential role in drug development

A randomized trial allows estimation of the causal effect of an intervention compared to a control in the overall population and in subpopulations defined by baseline characteristics. Often, however, clinical questions also arise regarding the treatment effect in subpopulations of patients, which would experience clinical or disease related events post-randomization. Events that occur after treatment initiation and potentially affect the interpretation or the existence of the measurements are called intercurrent events in the ICH E9(R1) guideline. If the intercurrent event is a consequence of treatment, randomization alone is no longer sufficient to meaningfully estimate the treatment effect. Analyses comparing the subgroups of patients without the intercurrent events for intervention and control will not estimate a causal effect. This is well known, but post-hoc analyses of this kind are commonly performed in drug development. An alternative approach is the principal stratum strategy, which classifies subjects according to their potential occurrence of an intercurrent event on both study arms. We illustrate with examples that questions formulated through principal strata occur naturally in drug development and argue that approaching these questions with the ICH E9(R1) estimand framework has the potential to lead to more transparent assumptions as well as more adequate analyses and conclusions. In addition, we provide an overview of assumptions required for estimation of effects in principal strata. Most of these assumptions are unverifiable and should hence be based on solid scientific understanding. Sensitivity analyses are needed to assess robustness of conclusions.     

Estimation of seroprevalence, rape, and homelessness in the United States using a social network approach

The authors have developed and tested scale-up methods, based on a simple social network theory, to estimate the size of hard-to-count subpopulations. The authors asked a nationally representative sample of respondents how many people they knew in a list of 32 subpopulations, including 29 subpopulations of known size and 3 of unknown size. Using these responses, the authors produced an effectively unbiased maximum likelihood estimate of the number of people each respondent knows. These estimates were then used to back-estimate the size of the three populations of unknown size. Maximum likelihood values and 95% confidence intervals are found for seroprevalence, 800,000 +/- 43,000; for homeless, 526,000 +/- 35,000; and for women raped in the last 12 months, 194,000 +/- 21,000. The estimate for seroprevalence agrees strikingly with medical estimates, the homeless estimate is well within the published estimates, and the authors' estimate lies in the middle of the published range for rape victims.