John Harris has made many seminal contributions to bioethics. Two of these are in the ethics of resource allocation. Firstly, he proposed the “fair innings argument” which was the first sufficientarian approach to distributive justice. Resources should be provided to ensure people have a fair innings—when Harris first wrote this, around 70 years of life, but perhaps now 80. Secondly, Harris famously advanced the egalitarian position in response to utilitarian approaches to allocation (such as maximizing Quality Adjusted Life Years [QALYs]) that what people want is the greatest chance of the longest, best quality life for themselves, and justice requires treating these claims equally. Harris thus proposed both sufficientarian and egalitarian approaches. This chapter compares these approaches with utilitarian and contractualist approaches and provides a methodology for deciding among these (Collective Reflective Equilibrium). This methodology is applied to the allocation of ventilators in the pandemic (as an example) and an ethical algorithm for their deployment created. This paper describes the concept of algorithmic bioethics as a way of addressing pluralism of values and context specificity of moral judgment and policy, and addressing complex ethics.

The normative principle that every individual is equally entitled to continued life is a subject of debate in ethics, health economics and policy. We reconsider this principle in the context of setting priorities for healthcare interventions. When applied without restriction, the principle overlooks quality of life concerns entirely. However, we contend that it remains ethically relevant in certain situations, particularly when patients suffer from conditions unrelated to the therapeutic areas and treatments under consideration. Thus, we defend the principle while also emphasizing the need for its application within tight limits.

Meeting healthcare needs is a matter of social justice. Healthcare needs are virtually limitless; however, resources, such as money, for meeting those needs, are limited. How then should we (just and caring citizens and policymakers in such a society) decide which needs must be met as a matter of justice with those limited resources? One reasonable response would be that we should use cost effectiveness as our primary criterion for making those choices. This article argues instead that cost-effectiveness considerations must be constrained by considerations of healthcare justice. The goal of this article will be to provide a preliminary account of how we might distinguish just from unjust or insufficiently just applications of cost-effectiveness analysis to some healthcare rationing problems; specifically, problems related to extraordinarily expensive targeted cancer therapies. Unconstrained compassionate appeals for resources for the medically least well-off cancer patients will be neither just nor cost effective.

The growing interest in analyzing the cost-effectiveness of interventions presents a challenge to anyone involved in dementia research. Although not yet often expressed as a formal requirement, drug authorities and budget holders also wish to have information on cost effectiveness. Clinical outcomes must therefore be combined with outcomes suitable for cost effectiveness analysis. However, issues about cost effectiveness are seldom included in empirical clinical trials, but are more often analyzed using modeling approaches. Clinical researchers and economists need to bridge these areas of potential conflict when long-term cost effectiveness is being considered. Randomized clinical trials (RCTs), observational studies, register data and economic models all have their advant-ages and drawbacks, and in making statements about cost effectiveness it is necessary to make a comprehensive judgment based on several methodological approaches. RCTs with a duration of at least 12 months should include assess-ments of resource utilization, and outcomes should offer a link to population-based cohort studies to discuss generalizability (e.g. a cognitive measure avail-able both in trials and cohort studies, such as the Mini-mental State Examination (MMSE), staging instruments, quality of life instruments) of the costs, while also serving as one source of modeling. Both dementia-specific and generic quality of life instruments are required. Models are necessary but must be transparent so that the assumptions on which the models are built can be critically analyzed.

Objectives: In quality-adjusted life-years (QALY) models, it is customary to weigh life-years with quality of life via multiplication. As a consequence, for positive health states a longer duration has more QALYs than a shorter duration (i.e., longer is better). However, we have found that for poor health states, many prefer to live only a limited amount of time (i.e., longer is worse). Such preferences are said to be maximum endurable time (MET). In the present contribution, the following questions are asked: a) How low does the utility have to be in order for a MET to arise? and b) Do MET preferences occur when patients judge hypothetical health states?

Methods and Results: We reanalyzed data from 176 students for the hypothetical health states of “living with migraines” and “living with metastasized cancer.” For utilities smaller than 0.7 (ranging from 0 to 1), the MET preference rate was larger than 50%. High MET preference rates were also found in two new studies on migraine and esophageal cancer patients, who evaluated hypothetical health states related to their disease.

Conclusions: We discuss the interpretation of the MET preferences and the preference reversal phenomenon. Standard QALY models imply that longer is better. However, we find that more often, longer is worse for poorly evaluated health states. Consider the following question: are 3 years with a weight of 0.3 equally as valuable as 1 year with a weight of 0.9? Our results suggest that the 3-year period may be less valuable because for poor health, many will prefer a 1-year over a 3-year period.

This paper considers the question of what ought to be valued in the context of measuring the outcomes of healthcare interventions. The answer is discrete health states in the case of the quality-adjusted life-year (QALY) model and an entire health profile in the case of the healthy-years equivalent (HYE) approach. How well the weighted average of values attached to the former approximates the overall value attached to the latter depends on the validity of the assumptions of the QALY model. The paper considers some of the empirical literature relating to them. One of the most important assumptions, which from the limited evidence available appears not to hold, is additive separability. However, it is argued that violation of this assumption does not in itself invalidate the QALY approach, since in some circumstances it might be more appropriate to elicit the value of a health state independently of the states that succeed it. Investigation into this issue is identified as one of the key areas where future research efforts should be directed.