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Background: Cardiovascular clinical trials depend on patient enrollment. Enrollment rates appear inadequate, but little is known about how frequently patients accept or decline offers of enrollment. The objective of this study was to assess trends and predictors of patient acceptance of offers to enroll in clinical trials for cardiovascular disease., Methods and Results: We utilized an established database containing all randomized, controlled trials (n=1224) in cardiovascular disease published between 2001 and 2012 in the 8 highest-impact general medical and cardiology journals. Studies were eligible if the number of patients approached and number of patients declining enrollment could be ascertained from published materials. All studies were screened for eligibility. Each eligible study was reviewed by 3 co-authors. All discrepancies were resolved by the group. The main outcome was acceptance rate, defined as the number of patients enrolled divided by the number patients who were eligible and approached. Only 21.7% (n=266) of studies provided information sufficient to assess patient enrollment and refusals. The median acceptance rate across trials was 83.2%. Significant predictors of higher enrollment included: enrollment in the acute setting (P=0.031); geographical region (P<0.001 for group); and trial sponsorship (P=0.006 for group)., Conclusions: Rates of reporting data sufficient to calculate acceptance rates are low. This compromises the ability to identify drivers of low enrollment and assess trial generalizability. However, the high rates of acceptance observed suggest that factors other than patients' decisions may be the primary drivers of declining rates of trial enrollment., (© 2016 The Authors. Published on behalf of the American Heart Association, Inc., by Wiley Blackwell.)

Objective: The purpose of this investigation was to assess workflow for medical imaging studies, specifically comparing liver and knee MRI examinations by use of the Lean Six Sigma methodologic framework. The hypothesis tested was that the Lean Six Sigma framework can be used to quantify MRI workflow and to identify sources of inefficiency to target for sequence and protocol improvement., Subjects and Methods: Audio-video interleave streams representing individual acquisitions were obtained with graphic user interface screen capture software in the examinations of 10 outpatients undergoing MRI of the liver and 10 outpatients undergoing MRI of the knee. With Lean Six Sigma methods, the audio-video streams were dissected into value-added time (true image data acquisition periods), business value-added time (time spent that provides no direct patient benefit but is requisite in the current system), and non-value-added time (scanner inactivity while awaiting manual input)., Results: For overall MRI table time, value-added time was 43.5% (range, 39.7-48.3%) of the time for liver examinations and 89.9% (range, 87.4-93.6%) for knee examinations. Business value-added time was 16.3% of the table time for the liver and 4.3% of the table time for the knee examinations. Non-value-added time was 40.2% of the overall table time for the liver and 5.8% for the knee examinations., Conclusion: Liver MRI examinations consume statistically significantly more non-value-added and business value-added times than do knee examinations, primarily because of respiratory command management and contrast administration. Workflow analyses and accepted inefficiency reduction frameworks can be applied with use of a graphic user interface screen capture program.