Here is a disturbing fact: The USA has had a little more than a million deaths from COVID-19, many of them unnecessary because of weak countermeasures – but since 1999, it has also had a million deaths from drug overdoses. Many of these are also unnecessary, because they involve drugs treating insomnia, anxiety, and in some cases pain. The drugs (benzodiazepines and opioids) can create dependence and are dangerous in high doses, so it is the doctor’s (physician’s) responsibility to check need and dosage. They often fail to do so, with deadly consequences for the patient.
Finding out why this happens was the task of Victoria (Shu)Zhang, Aharon Cohen Mohliver, and Marissa King in research published in Administrative Science Quarterly. To get to the core of the problem, the researchers made two important innovations. The first innovation was to look carefully at how doctors are connected to each other through their patient sharing. Patient sharing means that the same patients see more than one doctor and implies that the doctors can communicate and learn from each other. Through their network of patient-sharing peer doctors, they can learn how to follow good practice, or they can learn how to deviate from it.
The second innovation was to distinguish deviant (illegal) over-prescription from marginal over-prescription. Marginal over-prescription is when the doctor prescribes too much according to good practice, but not so much that it clearly violates legal limits. This is a liminal (borderline) practice, and accounts for more over-prescription than deviant over-prescription. Much more: 56 percent is liminal, as opposed to 9 percent deviant. The rest is by doctors who cannot be easily classified as either deviant or liminal.
So how do doctors learn from their network? The answers are disturbing. Any kind of over-prescribing in the network (liminal or deviant) encourages any kind of over-prescribing by the doctor (liminal or deviant). Network misconduct promotes physician misconduct. So what distinguishes between doctors engaging in one or the other of these types of over-prescribing? It turns out that doctors with a central position (many connected peers) or a cohesive position (connected peers are connected to each other) were more likely to engage in deviant, criminal over-prescription. Looser connected network positions encouraged liminal over-prescription.
What about doctors being more or less honest? We often think of people as being different in integrity and willingness to violate norms and break laws. We may even imagine that people differ in their tendencies to build networks depending on who they are. Part of the strength of this research is how carefully the researchers examined this explanation, finding that the network had strong effects even when accounting for many alternative explanations.
Which is not to say that doctor differences don’t exist. In fact, high workloads led to much more liminal over-prescription but only a minor increase in deviant over-prescription. Illegal prescription was mostly related to age – young doctors or doctors near retirement age were more likely to do it.
These are disturbing answers because they show that laws and norms are not enough. Laws regulate deviant/illegal over-prescription, but that accounts for a minority of the dangerous prescription. Norms are learnt, but findings on network effects show that the physicians learn liminal over-prescription just as well as normative best practice. And here is the most worrying part of the research, which I did not write until now. The patient-sharing networks the researchers measured were not captured through shared prescription of benzodiazepines or any other mental health drug—only regular drugs. This research shows that networks not organized around misconduct can produce misconduct learning.
Zhang, Victoria (Shu), Aharon Cohen Mohliver, and MarissaKing. 2022. Where Is All the Deviance? Liminal Prescribing and the SocialNetworks Underlying the Prescription Drug Crisis. Administrative Science Quarterly, forthcoming.
This blog is devoted to discussions of how events in the news illustrate organizational research and can be explained by organizational theory. It is only updated when I have time to spare.