Reducing Imaging Utilization in Primary Care Through Implementation of a Peer Comparison Dashboard.

BACKGROUND: High clinical variation has been linked to decreased quality of care, increased costs, and decreased patient satisfaction. We present the implementation and analysis of a peer comparison intervention to reduce clinical variation within a large primary care network. OBJECTIVE: Evaluate existing variation in radiology ordering within a primary care network and determine whether peer comparison feedback reduces variation or changes practice patterns. DESIGN: Radiology ordering data was analyzed to evaluate baseline variation in imaging rates. A utilization dashboard was shared monthly with providers for a year, and imaging rates pre- and post-intervention were retrospectively analyzed. PARTICIPANTS: Providers within the primary care network spanning 1,358,644 outpatient encounters and 159 providers over a 3-year period. INTERVENTIONS: The inclusion of radiology utilization data as part of a provider's monthly quality and productivity dashboards. This information allows providers to compare their practice patterns with those of their colleagues. MAIN MEASURES: We measured provider imaging rates, stratified by modality, as well as order variation over time. KEY RESULTS: We observed significant variation in imaging rates among providers in the network, with the top decile ordering an average of 4.2 times more than the lowest decile in the two years prior to intervention. Provider experience and training were not significantly associated with imaging utilization. In the first year after sharing utilization data with providers, we saw a 17.3% decrease in median imaging rate (p < 0.001) and a 21.4% reduction in provider variation between top and bottom deciles. Median ordering rate for more costly cross-sectional imaging, including CT, MRI, and nuclear medicine studies, decreased by 30.4% (p < 0.001), 20.2% (p = 0.008), and 41.8% (p = 0.002), respectively. CONCLUSIONS: Peer comparison feedback can shape provider imaging behavior even in the absence of targets or financial incentives. Peer comparison is a low-touch, low-cost intervention for influencing provider ordering and may have applicability in other clinical areas.

Estimating the cost of no-shows and evaluating the effects of mitigation strategies.

OBJECTIVE: To measure the cost of nonattendance ("no-shows") and benefit of overbooking and interventions to reduce no-shows for an outpatient endoscopy suite. METHODS: We used a discrete-event simulation model to determine improved overbooking scheduling policies and examine the effect of no-shows on procedure utilization and expected net gain, defined as the difference in expected revenue based on Centers for Medicare & Medicaid Services reimbursement rates and variable costs based on the sum of patient waiting time and provider and staff overtime. No-show rates were estimated from historical attendance (18% on average, with a sensitivity range of 12%-24%). We then evaluated the effectiveness of scheduling additional patients and the effect of no-show reduction interventions on the expected net gain. RESULTS: The base schedule booked 24 patients per day. The daily expected net gain with perfect attendance is $4433.32. The daily loss attributed to the base case no-show rate of 18% is $725.42 (16.4% of net gain), ranging from $472.14 to $1019.29 (10.7%-23.0% of net gain). Implementing no-show interventions reduced net loss by $166.61 to $463.09 (3.8%-10.5% of net gain). The overbooking policy of 9 additional patients per day resulted in no loss in expected net gain when compared with the reference scenario. CONCLUSIONS: No-shows can significantly decrease the expected net gain of outpatient procedure centers. Overbooking can help mitigate the impact of no-shows on a suite's expected net gain and has a lower expected cost of implementation to the provider than intervention strategies.