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Dounia Marbouh,1 Iman Khaleel,1 Khawla Al Shanqiti,1 Maryam Al Tamimi,1 Mecit Can Emre Simsekler,1,2 Samer Ellahham,3 Deniz Alibazoglu,3 Haluk Alibazoglu4 1Research Center of Digital Supply Chain and Operations, Department of Industrial and Systems Engineering, Khalifa University, Abu Dhabi, United Arab Emirates; 2School of Management, University College London, London, UK; 3Heart and Vascular Institute, Cleveland Clinic Abu Dhabi, Abu Dhabi, United Arab Emirates; 4Imaging Institute, Cleveland Clinic Abu Dhabi, Abu Dhabi, United Arab EmiratesCorrespondence: Mecit Can Emre SimseklerKhalifa University of Science and Technology, Department of Industrial and Systems Engineering, P.O. Box 127788, Abu Dhabi, United Arab EmiratesTel +9712 501 8410Fax +971 2 447 2442Email emre.simsekler@ku.ac.aePurpose: Patient no-shows are long-standing issues affecting resource utilization and posing risks to the quality of healthcare services. They also lead to loss of anticipated revenue, particularly in services where resources are expensive and in great demand.Methods: In order to address common reasons why patients miss appointments, this study reviews the current literature and investigates various tools and methods that have been implemented to mitigate such issues. Further, a case study is conducted to identify the rate of no-shows and underlying causes at a radiology department in one of the leading hospitals in the MENA region.Results: Our results show that the no-shows are high due to multiple factors, such as patient behavior, patients’ financial situation, environmental factors and scheduling policy.Conclusion: In conclusion, we generate a list of recommendations that can help in reducing the rate of patient no-shows, such as patient education, application of dynamic scheduling policies and effective appointment reminder systems to patients.Keywords: quality, no-shows, overbooking, resource utilization, scheduling policy, patient appointment, predictive analytics

Background: Planar and single-photon emission computed tomography (SPECT) nuclear imaging techniques with bone seeking radiotracers have been increasingly adopted for diagnosis of ATTR cardiac amyloidosis. However, inherent limitations of these techniques due to lack of anatomical landmarks have been recognized, with consequent high numbers of equivocal or false positive cases. SPECT/computed tomography (CT) fusion imaging offers a significant advantage to overcome these limitations by substantially reducing inaccurate interpretations. The authors present the results of a 3-year imaging quality improvement project that focused on reducing the high number of equivocal studies that were noted in the first two years of the amyloidosis program, comparing SPECT only to SPECT/CT fusion technique., Methods: A retrospective, systematic analysis of 176 patient records was performed to test the premise that SPECT/CT fusion imaging has the potential to reduce equivocal and false positive results., Results: Of a total of 176 patients, 35 equivocal (19.8%), 32 (18.18%) strongly suggestive, and 109 (61.93%) not suggestive cases were identified. Recognizing that this was not consistent with the international data, the authors set out on a comprehensive quality assessment project to reduce the number of equivocal and false positive cases. In patients who initially underwent SPECT only (Group A; n = 78), the addition of SPECT/CT fusion resulted in the net reclassification of 73% of cases: 100% of equivocal cases (n = 35) were reclassified to not suggestive (n = 34) or strongly suggestive (n = 1). 73% of strongly suggestive cases (n = 30) were reclassified to not suggestive (n = 22) while 8 strongly suggestive cases were confirmed as true positives. 13 not suggestive cases remained negative after SPECT/CT fusion. In cases where SPECT/CT fusion was utilized from the beginning (Group B; n = 98), there were no reclassification of any of the cases when these cases were reprocessed as a control group., Conclusion: Addition of SPECT/CT imaging reduces the false positive or equivocal studies and increases the diagnostic accuracy of the test. All false positive and equivocal studies were eliminated using the fusion technique. Utilizing the fusion imaging technique increases the spatial resolution, with the ability to localize myocardial uptake and accurately differentiate from blood pool, which is a major source of error., (© 2023. The Author(s).)

Answer ALS is a biological and clinical resource of patient-derived, induced pluripotent stem (iPS) cell lines, multi-omic data derived from iPS neurons and longitudinal clinical and smartphone data from over 1,000 patients with ALS. This resource provides population-level biological and clinical data that may be employed to identify clinical-molecular-biochemical subtypes of amyotrophic lateral sclerosis (ALS). A unique smartphone-based system was employed to collect deep clinical data, including fine motor activity, speech, breathing and linguistics/cognition. The iPS spinal neurons were blood derived from each patient and these cells underwent multi-omic analytics including whole-genome sequencing, RNA transcriptomics, ATAC-sequencing and proteomics. The intent of these data is for the generation of integrated clinical and biological signatures using bioinformatics, statistics and computational biology to establish patterns that may lead to a better understanding of the underlying mechanisms of disease, including subgroup identification. A web portal for open-source sharing of all data was developed for widespread community-based data analytics., (© 2022. The Author(s).)