Asking the right questions and using the right analytics can lead to major knowledge breakthroughs. However, it is often difficult to know which questions are the right questions.
Steve D. Levitt and Stephen J. Dubner, the authors of Freakonomics, would argue that you should not focus on asking one specific question based on what is known, but instead ask a variety of questions and use the right analytics to discover hidden connections between seemingly unconnected variables. They reason that you will hit a number of dead ends and a number of questions won’t have clear answers, but some will be extremely revealing and meaningful.
The analytic approach they write about is based in economics with five major principles:
“Incentives are the cornerstone of modern life.”
“The conventional wisdom is often wrong.”
“Dramatic effects often have distant, even subtle causes.”
““Experts” – from criminologist to real-estate agents – use their informational advantage to serve their own agenda.”
“Knowing what to measure and how to measure it makes a complicated world much less so.”
Their book analyzes the drop in violent crime in the 1990s and cheating in sumo wrestling, among various other topics. One large subject area that was mostly absent from the book was healthcare.
I believe that their approach could be very revealing when applied to healthcare quality improvement, or the relative lack thereof. Deep reliance on expert opinion rather than objective data, misaligned incentives that don’t support quality goals and limited ability to measure and understand the measurements of quality outcomes must play a role in the state of quality improvement. It would be fascinating to see the authors of the book explore this issue. With a robust health information system in place, many questions could be asked and efficiently answered, potentially revealing meaningful hidden connections to quality improvement in the healthcare setting.