Capabilities as an evaluative framework

Sen has proposed that capabilities can provide the “right kind of information” (Sen 2010, p233) to evaluate the justice of institutional arrangements. The capability approach proposed by Sen has been interpreted and applied in many different ways. The question that I am asking in this chapter is - can capabilities be used to evaluate the justice of arrangements determining the burdens and benefits of antibiotics? resistant microbes in an institutional context? The capabilities list that I will consider in this chapter is that of Martha Nussbaum specifically as described in ‘Frontiers of Justice’ (FJ) (2006). I do not intend to try to develop a justification for the particular elements that Nussbaum includes in her list. Many others have developed similar lists (see overview in Alkire 2005, Chapter 2). I start from the position that we have a list and that it is broadly agreed and accepted.

The context under consideration in this chapter is a healthcare institution, where (on any day) 40% of patients are receiving antibiotics and an additional 5-10% undergoing treatment for Healthcare Associated Infection (HCAI) (Health Protection Agency 2012b). Many of the HCAI are directly or indirectly associated with the use of antibiotics. In the healthcare context choices can impact on individual (patient) capabilities and can also (and often do) lead to an uneven distribution of burdens and benefits. Patients may not be able to advocate for

themselves. Nussbaum’s theory is designed to take account of disability and provides an account of the ‘goods’ wanted by all at all times, including those times during which individuals cannot advocate for themselves. Nussbaum’s capabilities entail positive entitlements, which are required by all (patients) even under conditions of dependency. Negative rights (or entitlements) are insufficient. Capabilities entitlements are universal and

cross over spatial and temporal boundaries (so entitlements don’t stop at the gates of healthcare institutions), and we all are share responsibility for assuring these entitlements (Nussbaum 2004, p13). It is increasingly apparent that health involves complex social and environmental interactions (Venkatapuran 2011; Wolff & De-Shalit 2007). There is

considerable empirical evidence that the spread of antibiotic resistant bacteria and associated diseases is a function of many interactions including nutritional status, education,

empowerment, housing conditions and social position. In many cases these interactions are two-way for example between health and nutrition, or health and education, or health and social position. In practice it is unlikely that an individual could be healthy without a sufficiency of many if not all of the ten dimensions of capability. Capabilities may be incommensurable but capabilities still interact with each other in contributing to a state of wellbeing.

3.2.1 The burden of antibiotic resistance

For Nussbaum and Sen a capability is a “substantial freedom he or she enjoys to lead the kind of life he or she has reason to value” (Sen 1999), resources and preferences only give a partial conception of how well off someone is. Resources and preferences are a substantial

component of health economic evaluations. Graves et al. (2010) overview the use of

economic measures to determine the cost of infections acquired in hospital and emphasise the large proportion of costs attributable to bed days lost. Graves et al. acknowledge the technical difficulties with accurately measuring bed days lost. There are also difficulties with valuing ‘public goods’ such as the control of the spread of antibiotic (treatment) resistant agents of

associated with an emerging problem such as new forms of antibiotic resistance. Even if we can measure these costs there remain substantial difficulties with health economic evaluations related to infection, for example the valuation of societal consequences such as loss of

confidence in healthcare institutions, or the fear, blame and shame which characterise the public response to treatment resistant infection such as might be caused by Meticillin-resistant

Staphylococcus aureus (MRSA).

3.2.2 The prevalence of infection

Currently in many countries the point prevalence of infections with antibiotic resistant microbes is measured and reported (see for example recent UK reports by Smythe et al. 2006 & Health Protection Agency 2012b). The Society for Healthcare Epidemiology of America & Healthcare Infection Control Practices Advisory Committee (HICPAC) have proposed

metrics for monitoring multidrug (antibiotic) resistant organisms in healthcare settings. These metrics are designed “to monitor Multi-Drug Resistant Organisms (MDROs) and the

infections they cause” (Cohen et al. 2008). These metrics measure the number of patients with infections, the proportions of particular types of microbe that are antibiotic resistant, the rates of specific types of infection, and the rates of colonisation with specific groups of agents of infection.

Measures of prevalence may identify two different hospitals to have similar rates of infection with antibiotic resistant microbes but we should recognise that the impact on patients in each hospital may be very different. Restrictions on individual capabilities, the distribution of burdens and benefits, the impact on other aspects of healthcare, and the social consequences

of infection are not well-captured by rates or prevalence, unless those measures can be translated into the experience of individual patients. The proportion of a population with a particular problem (in this case infection with antibiotic resistant microbes) does not tell us the impact of that problem on an individual. Infectious disease and the actions taken to control antibiotic resistance may or may not impact on the functional status of sufferers, may have shorter or longer term effects, may be treatable or untreatable, may be more or less associated with social stigmatisation, and can vary in the consequent economic consequences. None of these aspects of infection with antibiotic resistant bacteria are accurately captured by measures of prevalence, numbers, proportions, or rates of colonisation or infection.