As the Department of Health Policy & Management at the Harvard School of Public Health explains it:

We make decisions everyday, usually without much thought about how we make them. An intuitive, personal approach works fairly well when we’re deciding whether we’re going to have eggs or cereal for breakfast, but we may very well overlook important considerations and possibilities when it comes to more complex decisions.

 

This is particularly true of the complex decisions often required of policy makers, questions such as how to determine the best prevention and treatment policy for HIV-infected individuals in the United States or sub-Saharan Africa, or the best use of drugs or technologies to prevent or treat heart disease in the United States or India. How can a health-care payer decide which of the expensive but effective cancer therapies available should be offered to patients if funds are finite? What is the best global policy to control tuberculosis, taking into account the interests of individual patients and the larger community, and considering costs of treatment, risks of multi-drug resistance, and short-term and long-term outcomes? Should drugs be stockpiled in preparation for a possible influenza pandemic, and what early warning signs should trigger precautionary measures, such as school closings or quarantines? What is the best policy of water disinfection, recognizing the benefits of reducing the incidence of waterborne diseases, the risks of exposure to heavy metals, and economic costs of chlorination and demineralization?

 

For these kinds of questions—high-impact questions that involve uncertainty, risk, several possible perspectives, and multiple competing objectives—we may try using rules of thumb or panels of experts, but even these approaches can easily bypass optimal choices. Merely keeping all the variables in mind is beyond human capacity; analyzing them effectively is even more unmanageable.

Decision science steps into the breach by providing structure and guidance for systematic thinking about these kinds of questions. Based on logical principles, and informed by what we know about the limitations of human judgment and decision-making in complex situations, it allows logical and consistent analysis of the tough, complex decisions often faced by public health providers.