Measuring the effectiveness of medical interventions faces three epistemological challenges: the choice of good measuring instruments, the use of appropriate analytic measures, and the use of a reliable method of extrapolating measures from an experimental context to a more general context. In practice each of these challenges contributes to overestimating the effectiveness of medical interventions. These challenges suggest the need for corrective normative principles. The instruments employed in clinical research should measure patient-relevant and disease-specific parameters, and should not be sensitive (...) to parameters that are only indirectly relevant. Effectiveness always should be measured and reported in absolute terms (using measures such as 'absolute risk reduction'), and only sometimes should effectiveness also be measured and reported in relative terms (using measures such as 'relative risk reduction')-employment of relative measures promotes an informal fallacy akin to the base-rate fallacy, which can be exploited to exaggerate claims of effectiveness. Finally, extrapolating from research settings to clinical settings should more rigorously take into account possible ways in which the intervention in question can fail to be effective in a target population. (shrink)

This article is a mutual introduction of the science of well-being to philosophy of science and an explanation of how the two disciplines can benefit each other. In the process, I argue that the science of well-being is not helpfully viewed as a social or a natural, but rather as a mixed, science. Hence, its methodology will have to attend to its specific features. I discuss two of its methodological problems: justifying the role of values, and validating measures. I suggest (...) that tackling them calls for developing mid-level rather than high theories of well-being. (shrink)

The philosophy of measurement studies the conceptual, ontological, epistemic, and technological conditions that make measurement possible and reliable. A new wave of philosophical scholarship has emerged in the last decade that emphasizes the material and historical dimensions of measurement and the relationships between measurement and theoretical modeling. This essay surveys these developments and contrasts them with earlier work on the semantics of quantity terms and the representational character of measurement. The conclusions highlight four characteristics of the emerging research program in (...) philosophy of measurement: it is epistemological, coherentist, practice oriented, and model based. (shrink)

This article develops a model-based account of the standardization of physical measurement, taking the contemporary standardization of time as its central case study. To standardize the measurement of a quantity, I argue, is to legislate the mode of application of a quantity concept to a collection of exemplary artefacts. Legislation involves an iterative exchange between top-down adjustments to theoretical and statistical models regulating the application of a concept, and bottom-up adjustments to material artefacts in light of remaining gaps. The model-based (...) account clarifies the cognitive role of ad hoc corrections, arbitrary rules, and seemingly circular inferences involved in contemporary timekeeping, and explains the stability of networks of standards better than its conventionalist and constructivist counterparts. 1 Introduction2 Making Time Universal2.1 Stability and accuracy2.2 Multiple realizability2.3 The challenges of synchronicity2.4 Divergent standards2.5 The leap second3 The Two Faces of Stability3.1 An explanatory challenge3.2 Conventionalist explanations3.3 Constructivist explanations4 Models and Standardization4.1 A third alternative4.2 Stability reconceived4.3 Legislative freedom4.4 Discovering gaps4.5 Nature and society entangled4.6 Remark on scope5 Conclusions. (shrink)

Engagement with the historical and theoretical underpinnings of measuring quality of life (QoL) and patient‐reported outcomes (PROs) in healthcare is important. Ideas and values that shape such practices—and in the endgame, people's lives—might otherwise remain unexamined, be taken for granted or even essentialized. Our aim is to explicate and theoretically discuss the philosophical tenets underlying the practices of QoL assessment and PRO measurement in relation to the notion of person‐centredness. First, we engage with the late‐modern history of the concept of (...) QoL and the act of assessing and measuring it. Working with the historical method of genealogy, we describe the development of both QoL assessments and PRO measures (PROMs) within healthcare by accounting for the contextual conditions for their possibility. In this way, the historical and philosophical underpinnings of these measurement practices are highlighted. We move on to analyse theoretical and philosophical underpinnings regarding the use of PROMs and QoL assessments in clinical practice, as demonstrated in review studies thereof. Finally, we offer a critical analysis regarding the state of theory in the literature and conclude that, although improved person‐centredness is an implied driver of QoL assessments and PROMs in clinical practice, enhanced theoretical underpinning of the development of QoL assessments is called for. (shrink)

Measurement outcomes are frequently used as evidence in favor of or against medical and surgical interventions, health policies, and system designs. Indeed, in the medical and health services research literature, outcomes are the currency of policy debate and decision making. Yet in the philosophy of science and philosophy of medicine, the measures used in evidence-based medicine (EBM) are rarely discussed. Rather, the focus here is almost exclusively on study design and hierarchies of evidence. This concentration on the methodology of study (...) design has meant that for practical purposes the measures used in randomized controlled trials, observational studies, audits, and so forth, appear as a “black box.” Yet as I argue in the first part of this article, an engagement with measurement can improve our understanding of EBM and the quality of our evidence. In the second part of the article, I develop such an engagement with one aspect of measurement, namely, the validity of patient-reported outcome measures. Here, I illustrate some of the complexity that is required to improve the validity of these measures and hence the validity of our study outcomes, that is, evidence. The concentration in philosophy of science on study design over measurement methodology perhaps reveals the interest that many philosophers of medicine have in causation, but there is more to the production of high-quality scientific evidence than securing the causal inference. (shrink)

Since the 1970’s epidemiological measures focusing on “health-related quality of life” or simply “quality of life” have figured increasingly as endpoints in clinical trials. Before the 1970’s these measures were known, generically, as performance measures or health status measures. Relabeled as “quality of life measures” they were first used in cancer trials. In the early 2000’s they were relabeled again as “patient-reported outcome measures” or PROMs, in their service to the FDA to support drug labeling claims. To the limited degree (...) that the philosophical literature addresses these measures, it tends to associate them with two major theories of well-being: subjective well-being and the capabilities approach. In this paper, I argue that philosophers ought to treat quality of life measures/proms as a distinct from these theories. I argue that quality of life/proms serve healthcare as vehicles for patient-centered care and this has important consequences for how we theorize these measures. To this end, two requirements set them apart from measures of subjective well-being and the capabilities approach: quality of life/proms need to be patient-directed and inclusive. (shrink)

Patient-reported outcomes are increasingly used as dependent variables in studies regarding the effectiveness of clinical interventions. But patient-reported outcome measures (PROMs) do not provide intuitively meaningful data. For instance, it is not clear what a five point increase or decrease on a particular scale signifies. Establishing ‘interpretability’ involves making changes in outcomes meaningful. Attempts to interpret PROMs have led to the development of methods for identifying a minimum important difference (MID). In this paper, however, I draw on Charles Taylor’s distinction (...) between weak and strong evaluations to suggest that identifying a MID, specifically, a MID that uses a patient-reported reference group, may not provide an adequate interpretation of these measures. Moreover, I argue that the difficulty with interpreting these measures is tied to a larger problem concerning their validity. If researchers wish to interpret PROMs, they may first need to know more about the constructs they attempt to measure, namely, quality of life. (shrink)

Quality improvement mechanisms increasingly use outcome measures to evaluate health care providers. This move toward outcome measures is a radical departure from the traditional focus on process measures. More radical still is the proposal to shift from relatively simple and proximal measures of outcome, such as mortality, to complex outcomes, such as quality of life. While the practical, scientific, and ethical issues associated with the use of outcomes such as mortality and morbidity to compare health care providers have been well (...) rehearsed, the specific concerns associated with the use of quality of life measures in quality of care research have received little attention. As with much research on quality of life there is a tendency to assume that the disadvantages are outweighed by the general virtue of “listening” to patients. In this paper we disagree with this assumption and argue that quality of life is a process, not an outcome. (shrink)

This article develops a model-based account of the standardization of physical measurement, taking the contemporary standardization of time as its central case-study. To standardize the measurement of a quantity, I argue, is to legislate the mode of application of a quantity-concept to a collection of exemplary artefacts. Legislation involves an iterative exchange between top-down adjustments to theoretical and statistical models regulating the application of a concept, and bottom-up adjustments to material artefacts in light of remaining gaps. The model-based account clarifies (...) the cognitive role of ad hoc corrections, arbitrary rules and seemingly circular inferences involved in contemporary timekeeping, and explains the stability of networks of standards better than its conventionalist and constructivist counterparts. (shrink)

There has been much philosophical interest regarding the ‘hierarchy of evidence’ used to determine which study designs are of most value for reporting on questions of effectiveness, prognosis, and so on. There has been much less philosophical interest in the choice of outcome measures with which the results of, say, an RCT or a cohort study are presented. In this paper, we examine the FDA’s recently published guidelines for assessing the psychometric adequacy of patient-reported outcome measures. We focus on their (...) recommendations for demonstrating content validity and also for how researchers should weigh up the sum of psychometric evidence when choosing these measures. We argue that questions regarding judgment and understanding meaning of these measures should play a more central role in determining their adequacy. (shrink)

I examine the dynamics of measure development using two case studies: temperature, and health-related quality of life. I argue, following Bas van Fraassen and Leah McClimans that in each case these dynamics have a hermeneutic structure. Measure development is plagued by epistemic circularity, as is the task of interpreting a text, and similar strategies can be used in both measure development and hermeneutics to overcome that circularity. I show that Hans Georg Gadamer’s philosophical hermeneutics in particular are an effective lens (...) through which to examine the development of the temperature standard as described by Hasok Chang. Despite similar grounding in hermeneutics, I note an important difference between measure development for temperature and for health-related quality of life. Namely, while the meaning of temperature can be standardized, the meaning of health-related quality of life cannot. This standardization of meaning for the temperature concept represents a limit to the analogy with hermeneutics. Finally, I argue that the indeterminacy we find in health-related quality of life measurement is a result not only of analogy with the hermeneutic task, but of full-fledged participation in it. (shrink)

Psychotherapy research is known for its pursuit of evidence-based treatment. Psychotherapeutic efficacy is assessed by calculation of aggregated differences between pre treatment- and post treatment symptom levels. As this ‘gold standard methodology’ is regarded as ‘procedurally objective’, the efficacy number that results from the procedure is taken as a valid indicator of treatment efficacy. However, I argue that the assumption of procedural objectivity is not justified, as the methodology is build upon a problematic numerical basis. I use an empirical case (...) study to show how measurement problems practically occur in the first step of data collection, i.e. in individual symptom measurement. These problems have been discussed and acknowledged for decades, but still measurement is regarded as the best epistemic means to gain evidence on psychotherapeutic efficacy. Therefore, I show how initial measurement problems are overlooked in the remainder of the methodological procedure, which harms the ‘evidence-base’ of psychotherapeutic EBT. Via this applied analysis, I exhibit concerns that are increasingly raised in the literature in an empirical way, to emphasize the need for a non-idealized consideration of the ‘gold standard methodology’ as a means towards its clinical end. (shrink)

Machine Learning (ML) is on the rise in medicine, promising improved diagnostic, therapeutic and prognostic clinical tools. While these technological innovations are bound to transform health care, they also bring new ethical concerns to the forefront. One particularly elusive challenge regards discriminatory algorithmic judgements based on biases inherent in the training data. A common line of reasoning distinguishes between justified differential treatments that mirror true disparities between socially salient groups, and unjustified biases which do not, leading to misdiagnosis and erroneous (...) treatment. In the curation of training data this strategy runs into severe problems though, since distinguishing between the two can be next to impossible. We thus plead for a pragmatist dealing with algorithmic bias in healthcare environments. By recurring to a recent reformulation of William James’s pragmatist understanding of truth, we recommend that, instead of aiming at a supposedly objective truth, outcome-based therapeutic usefulness should serve as the guiding principle for assessing ML applications in medicine. (shrink)

The aim of this study was to explore patients’ experiences of using the Integrated Palliative care Outcome Scale (IPOS) during specialized palliative home care. The study adopted a qualitative approach with an interpretive descriptive design. Interviews were performed with 10 patients, of whom a majority were diagnosed with incurable cancer. Our findings suggest that the use of IPOS as a basis for conversation promotes safe care by making the patients feel confident that the care provided was adapted to them which (...) gives them a sense of safety. IPOS facilitated discussions between patients and nurses about care needs. The patients believed that using IPOS enabled reflection on their well‐being and life situation. In conclusion, the study finds that using IPOS is beneficial and provide ways to enable person‐centered care and with advantage could be used in specialized palliative home care. The results may help overcome barriers and facilitate the use of patient‐reported outcome measures (PROMs). To enable the use of PROMs such as IPOS in palliative home care, nurses need education and opportunities to develop routines that enable patients’ voice to be heard and thereby compose a basis for care. (shrink)

The use of quality of life (QOL) outcomes in clinical trials is increasing as a number of practical, ethical, methodological, and regulatory reasons for their use have become apparent. It is important, then, that QOL measurements and differences between QOL scores be readily interpretable. We study interpretation in two contexts: when determining QOL and when basing decisions on QOL differences. We consider both clinical situations involving individual patients and research contexts, e.g., randomized clinical trials, involving groups of patients. We note (...) the ethical importance of such understanding: proper interpretation and communication facilitate health care decision making. Communication that facilitates interpretation is of moral significance since better communication can attenuate ethical problems and inform choices. Much of what is communication worthy about QOL assessments is determined by the particular QOL instrument used in the assessment and how it is administered. In practice, these choices will be driven by the purpose of the assessment, but, it is argued, to maximize understanding, we should combine the information garnered from traditional standardized QOL instruments, from individualized QOL assessments, and from a recently proposed dialogic paradigm, where QOL is determined by shared conversation regarding the interpretation of texts. And, while some studies can surely succeed using abbreviated methods of administration (e.g., postal surveys may suffice for certain purposes), we will focus on methods of administration involving interviewer–respondent interaction. We suggest that during the QOL elicitation process, interviewer and respondent should engage in a two-way conversation in order to achieve a shared understanding of the “answers” to QOL “questions” and, finally, to reach a shared interpretation of the individual’s QOL. (shrink)