Estimating risk when zero events have been observed

Assessing the risk of complications or adverse events following an intervention presents challenges when they have not yet occurred. Suppose, for instance, a chronic shortage of cardiac telemetry beds has prompted a hospital to implement a new policy that places low-risk patients admitted to ‘rule out myocardial infarction’ in regular ward beds (ie, with no telemetry). After 6 months and the admission of 100 such patients, no cardiac arrests or other untoward events have occurred. This absence of harm (ie, zero adverse events) indicates a low risk, but clearly we cannot infer a risk of zero on the basis of only 100 patients. But, what can we say about the true underlying risk?