Prioritizing examination-centered over patient-centered dose reduction: a hazard of institutional "benchmarking".

ABSTRACT

OBJECTIVE: The purpose of this article is to evaluate whether examination-specific radiation dose metrics reliably measure an institution's success in reducing cancer risks. MATERIALS AND METHODS: We projected health benefits from dose-reduction programs in a hypothetical institution that sought to decrease exposures from abdominopelvic CT. Using modeling techniques to project radiation-induced cancer risks and tertiary center data to inform the institution's abdominopelvic CT age distribution, we compared a program in which effective doses were reduced equally (from 10 to 7 mSv) across all scans with programs in which dose reduction was age dependent. For each program, we projected lethal cancers averted, life expectancy gained, and average institutional dose achieved. Markov Chain Monte Carlo methods were used to estimate uncertainty in projections. RESULTS: The analysis's age distribution drew from 20,979 CT scans; 39% were from patients 65 years old and older. To illustrate trends yielded, if all patients in the hypothetical institution underwent 7-mSv (instead of 10-mSv) scans, we projected the maximum number of lethal cancers averted to be seven per 100,000 patients, and maximum life expectancy gained to be 0.26 days per patient, when averaged over the institution's population. When restricting dose reduction (from 10 to 7 mSv) to patients younger than 65 years, benefits were slightly lower (five lethal cancers averted per 100,000 patients and 0.22 days per patient gained); however, the average institutional dose was substantially higher (8.2 mSv). Although dose reduction in patients 65 years old and older accounted for only 16% of possible institutional life expectancy gains, this patient group contributed disproportionately (39%) to the institution's average dose. CONCLUSION: Institutional examination-specific dose metrics can be misleading, because the least-benefited patients may contribute disproportionately toward "improved" averages.