We’re marking the last assessments of the academic year – just in time to start teaching the next set of students. We’re ready to put new names to new faces and to work on creating relationships that help everyone to learn. But as ‘examiners’ rather than ‘teachers’, we try to set aside such relationships and knowledge of individuals, e.g. marking scripts without names and using candidate numbers in discussion. As a teacher, I find it really helpful to work with candidate numbers when it comes to assessment. If I know the author of a script, I also know details of the background. One person may have attended every session, while another did not. A third may be a mature student who is struggling to fund their degree. A fourth may have suffered from a family crisis the previous term. This knowledge makes it harder to mark fairly and assess the submitted work.
Higher education is perhaps unusual in conflating the roles of examiner and teacher, but the possible value of ‘ignorance’ of wider criteria has purchase in other sectors, particularly health. The idea of blinding clinicians to particular information is familiar in research, where those testing treatments may be kept deliberately ignorant of whether participants are receiving an active intervention or a placebo. It is argued that this strategy helps reduce the play of conscious and unconscious bias in evaluating new treatments. Might such ignorance be useful for other groups in healthcare, such as those involved in rationing healthcare?
Work published more than a decade ago showed doctors drawing on knowledge of age, lifestyle, class and ethnicity in what has been called implicit rationing – generally around decisions about who to treat next (Hughes and Griffiths 1996). Such considerations were not the only ones – doctors also invoked clinical or technical factors – but ‘social’ judgements did come into play, just as they appeared to do in wider public debates about deservingness.
Difficulties involved in rationing healthcare in the clinic have encouraged a growing emphasis on explicit approaches to prioritisation in the UK. For example the National Institute for Health and Clinical Excellence (NICE) draws on quantitative data on both clinical effectiveness and cost effectiveness to make recommendations about treatments that are good value for money for the NHS in England and Wales. Guideline authors are asked to consider the benefits expected across a group of patients. Indeed the Citizens Council has explicitly asked NICE not to refer to people’s age or social role when producing guidance.
At a local level, appeals against decisions by primary care trusts are currently dealt with as Individual Funding Requests, which have to be grounded in the ‘exceptionality’ of specific patients. The difficulty of this process is that it has reduced anonymity: panels may not be ‘blind’ to (or ignorant of) the gender, age, occupation and family status of applicants.
It is not yet apparent how questions of prioritisation will be addressed in the reorganised NHS emerging in the next few months. As Professor Albert Weale at UCL noted in a fascinating summer school on Social Values and Clinical Commissioning last week, Clinical Commissioning Groups (CCGs) are only starting to create systems to manage the difficult aspects of budgeting. Though it seems likely that some kind of appeal process will continue, there is uncertainty about how CCGs will balance different priorities at a local level.
One question then is when and how information on individual patients will be brought into CCG discussions or local appeals. Sociologists like Linsey McGoey have discussed ‘strategic ignorance’ as a resource for large corporations who use it to deflect critiques and deny responsibility (see McGoey 2012). These issues clearly become much more significant in a health system undergoing major reorganisation and facing cuts. Does ignorance or blind decision making have value in health prioritisation debates as well as in research? If so, what kinds of ignorance should we insist on for those responsible for rationing? Gender, age, occupation and family status might all be candidates.