Minimizing diagnostic error: the importance of follow-up and feedback.

An open-loop system (also called a “nonfeedback controlled” system) is one that makes decisions based solely on preprogrammed criteria and the preexisting model of the system. This approach does not use feedback to calibrate its output or determine if the desired goal is achieved. Because open-loop systems do not observe the output of the processes they are controlling, they cannot engage in learning. They are unable to correct any errors they make or compensate for any disturbances to the process. A commonly cited example of the open-loop system is a lawn sprinkler that goes on automatically at a certain hour each day, regardless of whether it is raining or the grass is already flooded. To an unacceptably large extent, clinical diagnosis is an open-loop system. Typically, clinicians learn about their diagnostic successes or failures in various ad hoc ways (e.g., a knock on the door from a server with a malpractice subpoena; a medical resident learning, upon bumping into a surgical resident in the hospital hallway that a patient he/she cared for has been readmitted; a radiologist accidentally stumbling upon an earlier chest x-ray of a patient with lung cancer and noticing a nodule that had been overlooked). Physicians lack systematic methods for calibrating diagnostic decisions based on feedback from their outcomes. Worse yet, organizations have no way to learn about the thousands of collective diagnostic decisions that are made each day— information that could allow them to both improve overall performance as well as better hear the voices of the patients living with the outcomes.