Physicians, clinics, and neighborhoods: multiple levels of influence on colorectal cancer screening.

BACKGROUND: We (i) described variability in colorectal cancer (CRC) test use across multiple levels, including physician, clinic, and neighborhood; and (ii) compared the performance of novel cross-classified models versus traditional hierarchical models.
METHODS: We examined multilevel variation in CRC test use among patients not up-to-date with screening in a large, urban safety net health system (2011-2012). Outcomes included: (i) fecal occult blood test (FOBT) or (ii) colonoscopy and were ascertained using claims data during a 1-year follow-up. We compared Bayesian (i) cross-classified four-level logistic models nesting patients within separate, nonoverlapping "levels" (physicians, clinics, and census tracts) versus (ii) three hierarchical two-level models using deviance information criterion. Models were adjusted for covariates (patient sociodemographic factors, driving time to clinic, and census tract poverty rate).
RESULTS: Of 3,195 patients, 157 (4.9%) completed FOBT and 292 (9.1%) completed colonoscopy during the study year. Patients attended 19 clinics, saw 177 physicians, and resided in 332 census tracts. Significant variability was observed across all levels in both hierarchical and cross-classified models that was unexplained by measured covariates. For colonoscopy, variance was similar across all levels. For FOBT, physicians, followed by clinics, demonstrated the largest variability. Model fit using cross-classified models was superior or similar to 2-level hierarchical models.
CONCLUSIONS: Significant and substantial variability was observed across neighborhood, physician, and clinic levels in CRC test use, suggesting the importance of factors at each of these levels on CRC testing. IMPACT: Future multilevel research and intervention should consider the simultaneous influences of multiple levels, including clinic, physician, and neighborhood. ©2014 American Association for Cancer Research.

RCT Entities:   Population Interventions Outcomes