Severity as a moral qualifier of malady.

The overarching aim of this article is to scrutinize how severity can work as a qualifier for the moral impetus of malady. While there is agreement that malady is of negative value, there is disagreement about precisely how this is so. Nevertheless, alleviating disease, injury, and associated suffering is almost universally considered good. Furthermore, the strength of a diseased person's moral claims for our attention and efforts will inevitably vary. This article starts by reflecting on what kind of moral impetus malady incites. We then analyze how severity may qualify this impetus. We do so by discussing the relationship between severity and need, well-being and disvalue, death, urgency, rule of rescue, and distributive justice. We then summarize our thoughts about severity as a moral qualifier. We conclude that severity is, and should continue to be seen, as a morally significant concept that deserves continued attention in the future.

Cycle-network expansion plan in Oslo: Modeling cost-effectiveness analysis and health equity impact.

Physical inactivity is the leading cause of non-communicable diseases, and further research on the cost-effectiveness of interventions that target inactivity is warranted. Socioeconomic status is vital in this process. We aim to evaluate the cost-effectiveness of a cycle-network expansion plan in Oslo compared to the status quo by income quintiles. We applied a Markov model using a public payer perspective. Health outcomes were measured by quality-adjusted life years (QALYs) gained from the prevention of coronary heart disease, stroke, type 2 diabetes, and cancer. We measured equity impact by the concentration index and social welfare using the achievement index. We conducted sensitivity analyses. The intervention was generally more costly and more effective than the status quo. Incremental cost per QALY falls with income quintile, ranging from $10,098 in the richest quintile to $23,053 per QALY gained in the poorest quintile. The base-case intervention increased health inequality. However, a scenario targeting low-income quintiles reduced inequality and increased social welfare. In conclusion, the cycle-network expansion is likely to be cost-effective, but with equity concerns. If decision makers care about health inequalities, the disadvantaged groups could be targeted to produce more equitable and socially desirable outcomes instead of a uniform intervention across income quintiles.

A Markov chain method for counting and modelling migraine attacks.

To ensure reproducibility in research quantifying episodic migraine attacks, and identifying attack onset, a sound theoretical model of a migraine attack, paired with a uniform standard for counting them, is necessary. Many studies report on migraine frequencies-e.g. the fraction of migraine-days of the observed days-without paying attention to the number of discrete attacks. Furthermore, patients' diaries frequently contain single, migraine-free days between migraine-days, and we argue here that such 'migraine-locked days' should routinely be interpreted as part of a single attack. We tested a simple Markov model of migraine attacks on headache diary data and estimated transition probabilities by mapping each day of each diary to a unique Markov state. We explored the validity of imputing migraine days on migraine-locked entries, and estimated the effect of imputation on observed migraine frequencies. Diaries from our patients demonstrated significant clustering of migraine days. The proposed Markov chain model was shown to approximate the progression of observed migraine attacks satisfactorily, and imputing on migraine-locked days was consistent with the conceptual model for the progression of migraine attacks. Hence, we provide an easy method for quantifying the number and duration of migraine attacks, enabling researchers to procure data of high inter-study validity.

Severity as a Priority Setting Criterion: Setting a Challenging Research Agenda.

Priority setting in health care is ubiquitous and health authorities are increasingly recognising the need for priority setting guidelines to ensure efficient, fair, and equitable resource allocation. While cost-effectiveness concerns seem to dominate many policies, the tension between utilitarian and deontological concerns is salient to many, and various severity criteria appear to fill this gap. Severity, then, must be subjected to rigorous ethical and philosophical analysis. Here we first give a brief history of the path to today's severity criteria in Norway and Sweden. The Scandinavian perspective on severity might be conducive to the international discussion, given its long-standing use as a priority setting criterion, despite having reached rather different conclusions so far. We then argue that severity can be viewed as a multidimensional concept, drawing on accounts of need, urgency, fairness, duty to save lives, and human dignity. Such concerns will often be relative to local mores, and the weighting placed on the various dimensions cannot be expected to be fixed. Thirdly, we present what we think are the most pertinent questions to answer about severity in order to facilitate decision making in the coming years of increased scarcity, and to further the understanding of underlying assumptions and values that go into these decisions. We conclude that severity is poorly understood, and that the topic needs substantial further inquiry; thus we hope this article may set a challenging and important research agenda.

Identifying menstrual migraine- improving the diagnostic criteria using a statistical method.

OBJECTIVE: To develop a robust statistical tool for the diagnosis of menstrually related migraine. BACKGROUND: The International Classification of Headache Disorders (ICHD) has diagnostic criteria for menstrual migraine within the appendix. These include the requirement for menstrual attacks to occur within a 5-day window in at least [Formula: see text] menstrual cycles ([Formula: see text]-criterion). While this criterion has been shown to be sensitive, it is not specific. Yet in some circumstances, for example to establish the underlying pathophysiology of menstrual attacks, specificity is also important, to ensure that only women in whom the relationship between migraine and menstruation is more than a chance occurrence are recruited. METHODS: Using a simple mathematical model, a Markov chain, to model migraine attacks we developed a statistical criterion to diagnose menstrual migraine (sMM). We then analysed a data set of migraine diaries using both the [Formula: see text]-criterion and the sMM. RESULTS: sMM was superior to the [Formula: see text]-criterion for varying numbers of menstrual cycles and increased in accuracy with more cycle data. In contrast, the [Formula: see text]-criterion showed maximum sensitivity only for three cycles, although specificity increased with more cycle data. CONCLUSIONS: While the ICHD [Formula: see text]-criterion is a simple screening tool for menstrual migraine, the sMM provides a more specific diagnosis and can be applied irrespective of the number of menstrual cycles recorded. It is particularly useful for clinical trials of menstrual migraine where a chance association between migraine and menstruation must be excluded.

Choice Defines Value: A Predictive Modeling Competition in Health Preference Research.

OBJECTIVE: To identify which specifications and approaches to model selection better predict health preferences, the International Academy of Health Preference Research (IAHPR) hosted a predictive modeling competition including 18 teams from around the world. METHODS: In April 2016, an exploratory survey was fielded: 4074 US respondents completed 20 out of 1560 paired comparisons by choosing between two health descriptions (e.g., longer life span vs. better health). The exploratory data were distributed to all teams. By July, eight teams had submitted their predictions for 1600 additional pairs and described their analytical approach. After these predictions had been posted online, a confirmatory survey was fielded (4148 additional respondents). RESULTS: The victorious team, "Discreetly Charming Econometricians," led by Michal Jakubczyk, achieved the smallest χ2, 4391.54 (a predefined criterion). Its primary scientific findings were that different models performed better with different pairs, that the value of life span is not constant proportional, and that logit models have poor predictive validity in health valuation. CONCLUSIONS: The results demonstrated the diversity and potential of new analytical approaches in health preference research and highlighted the importance of predictive validity in health valuation.

The disvalue of death in the global burden of disease.

In the Global Burden of Disease study, disease burden is measured as disability-adjusted life years (DALYs). The paramount assumption of the DALY is that it makes sense to aggregate years lived with disability (YLDs) and years of life lost (YLLs). However, this is not smooth sailing. Whereas morbidity (YLD) is something that happens to an individual, loss of life itself (YLL) occurs when that individual's life has ended. YLLs quantify something that involves no experience and does not take place among living individuals. This casts doubt on whether the YLL is an individual burden at all. If not, then YLDs and YLLs are incommensurable. There are at least three responses to this problem, only one of which is tenable: a counterfactual account of harm. Taking this strategy necessitates a re-examination of how we count YLLs, particularly at the beginning of life.