Materials and Methods: Sensitivity and scenario analyses were overlaid on an existing validated modeling tool in Excel. Sensitivity analysis calculates revenue fluctuation related to dynamic adjustment of discrete variables such as patient and provider mix. In scenario analysis, we project three possible scenarios -Optimistic, Base, Cautious -by changing multiple variables simultaneously. Base case assumes the status quo. Optimistic case projects modest gains in level of care, provider mix, documentation, and collection rates, while the Cautious case projects unfavorable trends. Results: Sensitivity analysis demonstrates that significant gains in hypothetical revenue can be attained specifically by increasing patient volume, attending physician instead of advanced practitioner staffing of visits, physician compliance with billing, and institutional collection rate. The Base case scenario projects $1.7M in charges with $293K in hypothetical revenues. The Optimistic case assumes modest gains in provider mix (30% increase in attending staffing for complex patients), increased attending compliance with documentation (50% increase), and a 5% gain in collection rate, resulting in $2.2M in charges with $483K in revenues. The Cautious case assumes shrinking patient volume (15% decrease in volume), lower acuity of care (25% decrease in high level visits), poor provider mix (i.e. 10% decrease in attending staffing), no improvement in documentation, and a 5% reduction in collection rate, resulting in $1.3M in charges and $188K in revenues. Conclusion: Strategic application of widely used corporate financial modeling can identify key opportunities to maximize revenue from an IR inpatient service. Sensitivity and scenario analyses demonstrate a wide range of potential revenues that may be achieved by an inpatient IR clinical service. Close attention and active management of key variables may result in significant implications for the financial health of an IR division.
Objective The objective of this study was to assess the impact of preprocedural time-out on workflow and patient safety in computed tomography (CT)–guided procedures. Methods In this institutional review board–approved, Health Insurance Portability and Accountability Act–compliant study, preprocedure time-out was assessed by an independent observer in CT-guided procedures performed from January 16, 2018, to May 15, 2018. Anonymous survey of 302 radiology team members involved in image-guided procedures about preprocedure time-out was performed using REDCap. Results Preprocedure time-out for 100 CT-guided procedures (biopsies, drainages, ablations) was observed. Procedures were recruited per observer availability and thus were nonconsecutive and nonrandom. Preprocedure time-out was performed in 100 procedures (100%). Median duration was 60 seconds (interquartile range, 60–71 seconds). Scripted checklist was followed in 52 cases (52/100, 52%). Omissions from the preprocedure time-out were identified in 40 cases (40/100, 40%) and were much more frequent when scripted checklist was not used (30/48 [63%] vs 10/52 [19%], P < 0.005). One case (1/100, 1%) was postponed due to abnormal coagulation parameters discovered during the time-out. Three cases (3/100, 3%) were delayed by 3 minutes to address other safety issues. In additional 14 cases (14/100, 14%), safety issues were raised during the time-out, which were resolved in less than 30 seconds. A total of 137 (45%) of 302 survey responses from 54 radiologists (39%), 55 technologists (40%), and 28 nurses (20%) were received. Forty-eight respondents (48/137, 35%) encountered a procedure that was cancelled or delayed as a result of information identified during time-out. Ninety-six percent (131/137) of respondents stated that time-out improves teamwork, 98% (134/137) stated that it enhances communication between the team members, and 93% (127/137) stated that it identifies and resolves problems and ambiguities. Conclusions Scripted preprocedure time-out for CT-guided procedures takes approximately 1 minute to execute and detects safety issues in 18% of cases.
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