Such outcomes are difficult to interpret at the individual-provider level simply because of the fact that low-frequency events in a small sample size will produce unreliable estimates of provider performance. For this rea- son, certain measures are appropriately applied only to larger aggregated provider groupings where sample sizes are larger. These principles have substantial implications for PCI out- comes because the rates of major complications, such as death Table 5. Preferred Attributes of Models Used for Publicly Reported Outcomes 1. Clear and explicit definition of an appropriate patient sample 2. Clinical coherence of model variables 3. Sufficient high-quality and timely data 4. Designation of an appropriate reference time before which covariates are derived and after which outcomes are derived 5. Use of an appropriate outcome and a standardized period of outcome assessment 6. Application of an analytical approach that takes into account the multilevel organization of data 7. Disclosure of the methods used to compare outcomes, including disclosure of performance or risk-adjustment methodology in derivation and validation samples Reprinted with permission from Krumholz et al.20 and the need for emergency coronary artery bypass surgery, have decreased significantly in recent years. Death is perhaps the most important and least ambiguous out- come measure. Proper risk adjustment is and will remain a mandatory cornerstone of mortality monitoring for PCI. However, the writing committee also recognized that even the best risk-adjustment model cannot correct for potentially unmea- sured confounders, and most risk-adjustment models perform less well at the extremes of risk. This requires a careful design of outcome measures to avoid the unintended consequence of either penalizing facilities or clinicians who take on more difficult cases or rewarding those who avoid certain high-risk patients requiring treatment. 