Does the epistemology of digital information herald the end of general practice?
This paper eventually became ‘The Gatekeeper goes Digital’ published in the Christmas edition of the BMJ 2016.
General practitioners mediate the boundary between the expert and the lay. Over the last 30 years the information revolution has changed the nature of this boundary: patients are much better informed whilst the falling cost of information has led directly to the codification of much practice via evidence based medicine. Whilst these changes affect all branches of medicine the digital revolution poses particular questions about the foundations of general practice.
The epistemology of knowledge is profoundly affected by the medium which carries it. Books are written on paper and therefore have a beginning, middle and end. The age of the book necessarily involved leaving stuff out which reinforced the role of experts who curated and mediated knowledge for the rest of us. By contrast knowledge viewed via the web has no ‘end’. There is no paper’s edge, no limit to where your clicks can take you. In this process we have moved from ‘filter out’ to ‘filter forward’. Knowledge curated by experts into a defining canon has given way to a flatter knowledge landscape accessible to anyone [i]
Given that for every ‘fact’ there is now another equal and opposite ‘fact’ just a click away, this world can be very confusing and people still need help to navigate it. However it is not clear that such guides need to be doctors. Not only are doctors very expensive, the web is creating new forms of meta-knowledge that simply did not exist 20 years ago – for example knowing what ‘people like me’ chose when faced with similar choices. Who would you choose to guide you through a complex care pathway – your GP? local consultant? Specialist nurse? or what people with the same problem attending the Mayo clinic decided to do? Probably all of the above, but whatever your choice, generalist claims to mediate between the known and the unknown now have to be argued against multiple legitimate contenders. Given the ease of finding information what is the justification for a profession that makes a fetish of not knowing the detailed stuff?
A world where all knowledge is just a click away also greatly extends the range of things that a generalist might reasonably be expected to know. ‘We are witnessing a steady increase in agents’ [i.e. GP’s] responsibilities. The more any bit of information is just a click away, the less we shall be forgiven for not checking it.’[ii] In a digital world common knowledge is becoming more common.
The challenge of having to know much more is one reason why we are seeing the rise of knowledge-handling intermediaries like NICE and care pathways. These help all clinicians but are especially important to generalists who otherwise have to live out their lives in the Badlands where both uncertainty and lawyers roam. But precisely to the extent that the regime of discipline exercised by NICE and its familiars gets bigger so the role of the generalist is diminished.
To sum all this up: in a world of flat, low-friction, digital information, the value of being a professional generalist is falling whilst the risks are rising.
But what about referral? Surely GPs’ ability to know what to refer and – just as importantly – that sometimes the unknown is not worth knowing (‘I don’t know what it is, but it isn’t serious’) will always be valuable. At its heart skilled referral rest on the relationship between prevalence and predictive values and here the epistemology of digital knowledge may, in time, further weaken the GP role.
Being a good referrer depends on identifying symptom complexes that have a high predictive value of being associated with serious disease. Predictive value in turns depends on the prevalence of disease in the population you are used to dealing with. For GPs this population has historically been those turning up in surgery. The prevalence of disease in this population is significantly lower than the prevalence in the population presenting to hospital consultants. Let those same patients you decided not to refer in the morning get to see a specialist in the afternoon and watch those false positives (and costs) rack up as the higher prevalence of serious disease in hospital populations increases the predictive value of the presenting symptoms[iii]. Since this is why healthcare systems with effective primary care gatekeepers are more cost effective than those without[iv] you might assume that GPs will always have a role.
But big data means that at least in theory the population from which the system derives predictive values can be matched to each individual. Suppose that you see a 33 year old man presenting with rectal bleeding of <2 weeks duration but no red flags. Thirty years ago management would have been based on clinical judgement derived from seeing many such symptom complexes in your low prevalence general practice population. Today your judgement might have been replaced by a local guideline derived from largely hospital-based research tempered by budgetary constraints. But what if the NHS routinely logged all symptom complexes against all outcomes for every one of the million people it sees each working day? What if in time, we added in people’s genomic predispositions? At this point we would know the prevalence (and hence predictive values) of symptom complexes within ever more closely defined populations. Now the conversation becomes ‘the chance of this pattern of rectal bleeding being associated with serious disease in people like you (i.e. all the white males aged 30-35 who presented with similar short duration rectal bleeding in the NHS in the last 2 years) is <X%. Here are some treatment plans. Let’s talk about what which ones suit you’
The story of general practice over the last 30 years is one where the predictive value of symptom complexes ceased to be physician-based (those presenting to general practitioners as opposed to those presenting to hospital clinicians) and came to be determined by the care pathway regime mandated in your health economy. Typically these place-based regimes wrongly assume that prevalence does not affect predictive value, that rectal bleeding presenting in a GP’s surgery in the morning ‘means the same’ (i.e. has the same predictive value) if the same patient with the same rectal bleeding presents to a consultant surgeon in the afternoon. This inability of place-based protocols to interpret clinical data in the light of accurate estimates of prevalence may in turn be one explanation for why the productivity of health systems worldwide has remained stubbornly low.
Over the next 10 years it should be possible to free ourselves from the tyranny of ‘non-prevalence-based’ pathways by constructing predictive values based on the prevalence of the patient’s symptom complex in populations that ever more closely match ‘people like you’ – in this case all white 33 year old men with rectal bleeding of <2 weeks presenting in England over the last 2 years.
Seventy years ago general practice began trying to systematically improve diagnosis by coding encounters in disease registers[v]. Thirty years ago the falling cost of collating research allowed us to move to evidence based care protocols. Today the epistemology of web-based information mean GPs add less and less value as either diagnosticians or guides to treatment. Tomorrow ever-more finely grained predictive values are likely to inform and in time replace all expert-based referral decisions. Along the way general practice will have completed a historic journey: starting from the heuristics of clinical judgement, moving through the one-size fits all tyranny of evidence-based (but not prevalence-based) pathways and finally arriving at a personalised diagnostic predictions mediated by the complex information systems and membranes of the emerging digital world. At which point the generalist medical practitioner may – at most – be a helpful discussant.
The changing epistemology of medical knowledge does not render all aspects of a generalist role redundant – there’s always that ‘Let’s discuss what suits you’ to execute skilfully – but exploring these present and future ontological threats is important since they are how disruptive change midwifes the real revolutions in medical practice. Along the way they cast new light on why so many practitioners feel their job is changing in ways that go beyond financial pressures or the constraints of whatever national or local regime of healthcare they may practice under.
Thanks to Kate Billingham, Margaret McCartney, Amar Rughani and Val Iles for comments and suggestions to this and subsequent drafts.
[i] Weinberger D ‘Too Big to Know. Rethinking knowledge now facts aren’t facts, experts are everywhere and the smartest person in the room is the room’ Basic Books, New York. 2012
[ii] The Fourth Revolution. How the infosphere is reshaping human reality. Floridi L. Oxford University Press 2014
[iii] The Gatekeeper and the Wizard: a fairly tale. BMJ 1989; 298: 172-3
[iv] Starfield B Primary care and health. A cross-national comparison. JAMA 1991; 266:2268-9
[v] Hodgkin K Towards Earlier Diagnosis, Livingstone, 1962