The PRONE score: an algorithm for predicting doctors' risks of formal patient complaints using routinely collected administrative data.
Approach to Improving Safety
Setting of Care
Past studies have found a correlation between patient complaints and patient safety problems. Researchers sought to identify physicians at highest risk for a second patient complaint using routinely collected administrative data. They developed a risk prediction model which predicted future complaints with reasonable accuracy. Factors such as procedural specialty, male gender, and time since prior complaint were associated with a subsequent patient complaint. Application of this model has the potential to allow real-time identification of physicians at risk for further patient complaints and possible litigation. Actions to reduce future litigation risk—such as directed education, referral to a regulatory agency, or notification of the risk of future complaints—could be appropriately targeted based on this prediction model. A related editorial urges prompt and rigorous investigation of patient complaints.