Incentives, Informational Blind-Spots and the Emergence of Drug Resistance
February 18, 2009
By Prashant Yadav, Professor of Supply Chain Management, MIT-Zaragoza International Logistics Program
Drug resistance is threatening our ability and the resources required to treat infectious diseases in developing countries. Countering drug resistance involves complex tradeoffs between a number of activities¹. In order to formulate robust and effective strategies against resistance emergence, we need a clear understanding of the incentives of all health system actors and how these incentives interact to drive (socially-optimal²or not) behavior.
The DRWG recently commissioned a study to better understand how incentive structures might cause resistance. Findings confirmed the hypothesis that many actors across the supply chain deviate from making socially-optimal decisions. We identified three possible explanations for these deviations:
· Actors sometimes lack the necessary knowledge and information to make socially-optimal choices (informational blind-spots)
· Actors can often negatively affect others by their decisions (incentive misalignments arising from failure to internalize all costs)
· Short-term choices are not always consistent with long-term socially-optimal outcomes (incentive misalignments arising from faulty future vs. current reward discounting)
An example of the latter is when actors are rewarded as a result of good immediate outcomes (e.g. providing prompt treatment or ensuring lower stock outs of drugs) rather than for good (socially desirable) long-term decisions (e.g. educating patients and the general community about the importance of infection control and preventive methods or maintaining an assortment of drugs that may lead to decreased resistance). In these cases, different rewards or incentives may be found to encourage the socially-optimal choices.
A more challenging example stems from the lack of incentives for manufacturers to discover and develop drugs for neglected diseases and how these incentives affect resistance emergence. Manufacturers of innovative drugs, vaccines and to some extent diagnostic technologies are dependent upon a decision-model which is driven primarily by immediate market opportunities and estimated risks of technology failure. Using this model, higher risks of failure combined with a small market size have deterred companies from developing new classes of anti-infective products. Somehow, the potential market must be expanded or the risk of failure reduced – or both – before new anti-infective product development will become sufficiently attractive to manufacturers.
Large generic manufacturers have recently started moving into the pharmaceutical innovation business – perhaps with their eyes on larger mark