The curse of endogeneity in the clinical literature

Endogeneity is everywhere. There is always a reason to assume that there is some endogeneity in a model; sometimes it can’t be totally eliminated and we must just reduce it to acceptable levels. Health economists produce research that often is relevant for both economics and clinical journals, but often the requirements of these two types of journal differ by quite a lot. One way they differ is that the clinical literature and biostatisticians don’t generally care about endogeneity, which is probably the exact opposite opinion of economics and econometricians. When it comes to making policy decisions, not being aware of the effects of endogeneity may have disastrous consequences. Here’s an example why.

Patient and procedure volume has been shown to be inversely correlated with clinical outcomes such as mortality. This suggests that big hospitals are good. But, what about causality? Is there any? And, if so, in which direction does it run?

The hypothesis that volume causes better outcomes is called ‘practice makes perfect’ (PMP). This could be due either to ‘learning by doing’ or ‘scale economies’. If PMP were the case then we could identify if a learning by doing mechanism was responsible either by looking at the effects of lagged volume, or by seeing if a clinician who had been at a high volume hospital ‘took’ his skills with him. The competing hypothesis is ‘selective referral’ (SR). Hospitals which have superior outcomes attract more patients which consequently boosts their volume.

In the case of a possibly simultaneous mechanism like this we resort to instrumental variables. A common instrument for volume in this case exploits the exogenous preference of individuals to go to their nearest hospital. The instrument could then be, at the patient level, the nearest hospital, or at the hospital level, the size of the catchment level.

In the clinical literature this issue of the direction of causality has often been ignored. The association of volume and positive clinical effects in some areas of medicine has led to calls for centralisation of healthcare services. This implicitly assumes that the PMP hypothesis is true, or at least plays a stronger role that SR. But what if the volume-outcome effect is driven more by SR than PMP? Then the sickest patients will all be sent to the new large hospitals which will not cause any effect to outcomes and may even have a negative effect by increasing burden on staff, inefficient use of resources, and making patients travel further among other things.

For many areas of medicine a causal link has been demonstrated between volume and outcome, and it may be shown that both PMP and SR play a role. But this is just a demonstration of the problems of ignoring endogeneity. Causal inference is demonstrated for many healthcare interventions through a randomised experiment – something which health economics could do with more of – but often it is unethical or impractical to perform such an experiment. If we do rely on observational research then economists and econometricians should be trying to communicate these issues.

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