Sır, Mustafa Y.

Abstract Background Each training program has its own internal policies and restrictions, which must be considered while developing trainee schedules. Designing these schedules is complex and time consuming, and the final schedules often contain undesirable aspects for trainees. Objective We developed a decision-support system (DSS) to optimally schedule daily assignments and monthly rotations for trainees. The proposed DSS aims to 1) reduce the schedule development time, 2) maximize trainee preferences for desired rotations and vacation times, and 3) ensure adaptability of the DSS across multiple graduate medical programs through a flexible design and intuitive graphical user interface. Methods Using mixed-integer linear programming, we developed a scheduling model that 1) maximized trainees’ preferences on specific rotations and vacation times and 2) ensured fairness by assigning equal numbers of vacation days and a balanced schedule of difficult versus easy rotations among trainees. The model was successfully implemented in the Mayo Clinic Division of Pulmonary and Critical Care for the academic year 2018–2019. Results Using the DSS, it took only a few minutes to produce a schedule versus several days of preparation time required by the manual process. Compared with the manually developed schedule, the DSS schedule satisfied 11% more rotation preferences and improved fairness by 19%. All trainees met duty hours in the DSS schedule compared with 83% in the manually developed schedule. Conclusion The proposed DSS can dramatically reduce the schedule preparation time, accommodate more of trainees’ preferences, and improve fairness in assigning rotations.

Abstract Background We aimed to determine if patient symptoms and computed tomography enterography (CTE) and magnetic resonance enterography (MRE) imaging findings can be used to predict near-term risk of surgery in patients with small bowel Crohn’s disease (CD). Methods CD patients with small bowel strictures undergoing serial CTE or MRE were retrospectively identified. Strictures were defined by luminal narrowing, bowel wall thickening, and unequivocal proximal small bowel dilation. Harvey-Bradshaw index (HBI) was recorded. Stricture observations and measurements were performed on baseline CTE or MRE and compared to with prior and subsequent scans. Patients were divided into those who underwent surgery within 2 years and those who did not. LASSO (least absolute shrinkage and selection operator) regression models were trained and validated using 5-fold cross-validation. Results Eighty-five patients (43.7 ± 15.3 years of age at baseline scan, majority male [57.6%]) had 137 small bowel strictures. Surgery was performed in 26 patients within 2 years from baseline CTE or MRE. In univariate analysis of patients with prior exams, development of stricture on the baseline exam was associated with near-term surgery (P = .006). A mathematical model using baseline features predicting surgery within 2 years included an HBI of 5 to 7 (odds ratio [OR], 1.7 × 105; P = .057), an HBI of 8 to 16 (OR, 3.1 × 105; P = .054), anastomotic stricture (OR, 0.002; P = .091), bowel wall thickness (OR, 4.7; P = .064), penetrating behavior (OR, 3.1 × 103; P = .096), and newly developed stricture (OR: 7.2 × 107; P = .062). This model demonstrated sensitivity of 67% and specificity of 73% (area under the curve, 0.62). Conclusions CTE or MRE imaging findings in combination with HBI can potentially predict which patients will require surgery within 2 years.

AbstractBackgroundHospitals face the challenge of managing demand for limited computed tomography (CT) resources from multiple patient types while ensuring timely access.MethodsA discrete event simulation model was created to evaluate CT access time for emergency department (ED) patients at a large academic medical center with six unique CT machines that serve unscheduled emergency, semi‐scheduled inpatient, and scheduled outpatient demand. Three operational interventions were tested: adding additional patient transporters, using an alternative creatinine lab, and adding a registered nurse dedicated to monitoring CT patients in the ED.ResultsAll interventions improved access times. Adding one or two transporters improved ED access times by up to 9.8 minutes (Mann‐Whitney (MW) CI: [−11.0,−8.7]) and 10.3 minutes (MW CI [−11.5, −9.2]). The alternative creatinine and RN interventions provided 3‐minute (MW CI: [−4.0, −2.0]) and 8.5‐minute (MW CI: [−9.7, −8.3]) improvements.ConclusionsAdding one transporter provided the greatest combination of reduced delay and ability to implement. The projected simulation improvements have been realized in practice.

AbstractPurposeTo prospectively assess acute differences in patient‐reported outcomes in bowel and urinary domains between intensity‐modulated radiotherapy (IMRT) and proton beam therapy (PBT) for prostate cancer.Methods and MaterialsBowel function (BF), urinary irritative/obstructive symptoms (UO), and urinary incontinence (UI) domains of EPIC‐26 were collected in patients with T1‐T2 prostate cancer receiving IMRT or PBT at a tertiary cancer center (2015‐2018). Mean changes in domain scores were analyzed from pretreatment to the end of and 3 months post‐radiotherapy for each modality. A clinically meaningful change was defined as a score change >50% of the baseline standard deviation.ResultsA total of 157 patients receiving IMRT and 105 receiving PBT were included. There were no baseline differences in domain scores between cohorts. At the end of radiotherapy, there was significant and clinically meaningful worsening of BF and UO scores for patients receiving either modality. In the BF domain, the IMRT cohort experienced greater decrement (−13.0 vs −6.7, P < .01), and had a higher proportion of patients with clinically meaningful reduction (58.4% vs 39.5%, P = .01), compared to PBT. At 3 months post‐radiotherapy, the IMRT group had significant and clinically meaningful worsening of BF (−9.3, P < .001), whereas the change in BF score of the PBT cohort was no longer significant or clinically meaningful (−1.2, P = .25). There were no significant or clinically meaningful changes in UO or UI 3 months post‐radiotherapy.ConclusionsPBT had less acute decrement in BF than IMRT following radiotherapy. There was no difference between the two modalities in UO and UI.

Abstract Real-time location systems (RTLS) such as radio frequency identification (RFID) have been shown to improve safety, save cost, and increase patient satisfaction in a healthcare setting especially in the emergency department (ED). Hospital administrators have realized the potential of these applications for improved workflow and operations and are positively adopting it despite the substantial implementation costs of such technologies. Our group has reported several studies with RFID data in the ED showing the relationship between RFID determined patient contact times and length of stay (LOS). In this study, we use ED RFID data to determine the relationship between the total LOS in ED to the overall patient satisfaction obtained from a survey report. ED survey results from 35 questions were obtained from patients after discharge. An observational cohort study was performed in the ED using RFID data from Jan 1 – Dec 31, 2017 matched with the ED survey participants. A total of 2595 survey data was used for logistic regression analysis with the RFID data. Results show that higher treatment LOS influenced overall patient satisfaction negatively. The results provide new insights into designing ideal patient-care team interactions to reduce overall LOS while providing optimal ED care, thereby improving patient satisfaction.

305 Background: Toxicity due to radiotherapy (RT) may differ in patients (pts) with prostate cancer who receive intensity-modulated radiotherapy (IMRT) or proton beam therapy (PBT). Methods: Patient-reported bowel function (BF), urinary incontinence (UI), and urinary irritative/obstructive symptoms (UO) domains of the Expanded Prostate Index Composite Questionnaire (EPIC-26) were prospectively collected in pts with localized prostate cancer receiving either IMRT (n=157) or PBT (n=105) to the prostate +/- proximal seminal vesicles for clinical stage T1-T2 N0 prostate cancer at a single tertiary cancer center between 2015 and 2018. Changes in domain scores were analyzed from pretreatment to the end of RT and 3 months post-RT, assessing the acute effects of each modality. A clinically relevant change was defined as a score change that exceeded 50% of the standard deviation of a baseline value. Results: At baseline there was no difference in the scores of BF, UI, and UO domains between IMRT and PBT cohorts. At the end of RT, pts treated with either modality had a statistically significant and clinically relevant worsening of BF and UO compared to baseline. Pts treated with IMRT experienced a significantly greater decrement in BF compared to the PBT cohort (-13 vs -9, p<0.01), including significantly more IMRT pts having a clinically relevant deterioration in BF compared to PBT pts (58% vs 40%, p=0.01). Though there was a statistically significant deterioration in UI in the IMRT cohort (-4, p<0.001), this did not reach the predefined threshold for clinical relevance. Three months following RT, the IMRT group continued to have statistically significant and clinically relevant worsening of BF (-9, p<0.001), whereas the change in BF domain score of the PBT cohort was no longer statistically significant or clinically relevant compared to baseline (-1, p=0.25). There were no statistically significant or clinically relevant changes in UO or UI in either cohort at three months when compared to baseline. Conclusions: Pts who received IMRT or PBT reported unique patterns of toxicity, and pts treated with IMRT had worse decrement in BF immediately after and three months following RT, compared to those treated with PBT.

Emergency Department (ED) is a complex care delivery environment in a hospital that provides time sensitive urgent and lifesaving care [1]. Emergency medicine is an unscheduled practice and therefore providers experience extreme fluctuations in their workload. ED crowding is a major concern that affects the efficacy of the ED workflow, which often is challenged by long wait times, overuse of observation units, patients either leaving without being seen by a provider and non-availability of inpatient beds to accommodate patients after diagnosis [2]. Evaluating ED workflow is a challenging task due to its chaotic nature, with some success using time-motion studies and novel capacity management tools are nowadays becoming common in ED to address workflow related issues [3]. Several studies reveal that Electronic Medical Record (EMR) adoption has not resulted in significant ED workflow improvements nor reduced the cost of ED operations. Since raw EMR data does not offer operational and clinical decision making insights, advanced EMR data analytics are often sought to derive actionable intelligence from EMR data that can provide insights to improve ED workflow. Improving ED workflow has been an important topic of research because of its great potential to optimize the urgent care needed for the patients and at the same time save time and cost. Radio Frequency Identification Device (RFID) is a wireless automatic identification and data capture technology device that has the potential for improving safety, preventing errors, saving costs, and increasing security and therefore improving overall organizational performance. RFID technology use in healthcare has opened a new space in healthcare informatics research that provides novel data to identify workflow process pitfalls and provide new directions [4]. The potential advantages of RFID adoption in healthcare and especially in ED has been well recognized to save costs and improve care delivery [5]. However, the large upfront infrastructure costs, need for an integrated health information technology (HIT), advanced analytical tools for big data analysis emerging from RFID and skilled data scientists to tackle the data to derive actionable intelligence discourage many hospitals from adoption RFID technology despite its potential advantages. Our recent pilot study on the RFID data analytics demonstrated the feasibility of quantifying and analyzing two novel variables such as ‘patient alone’ time defined as the total time a patient spends alone without interaction with a health care staff in the ED and ‘provider time’ defined as the total time a patient spends interacting with any health care staff [6]. The study motivated a more comprehensive big data analytics of RFID data which can provide better insights into optimizing ED workflow which can improve the quality of care in the ED and also reduce cost. In this work, the authors attempt to describe the RFID adoption in the ED at the Saint Mary’s Hospital at Mayo Clinic, in Rochester, MN, a level one trauma center both for children and adults as a step towards optimizing ED workflow.

Common approaches to emergency department (ED) staffing are to optimize shifts based on historical patient volume or arrival patterns. The former is problematic because historical patient volumes are based on the volumes during existing shifts. Therefore, optimizing shifts based on these volumes can replicate the inefficiencies in these shifts. The latter approach ignores queueing effects. To address the shortcomings of these commonly used approaches, we use classification and regression trees to identify thresholds for patient-to-staff ratios, which split the patient subpopulations into two groups that have different empirical cumulative distribution functions (ecdfs) for patients’ lengths of stay in the ED; one has an extended length and the other has a shorter length. We apply these thresholds and ecdfs to historical patient volumes to calculate an ideal patient volume. After accounting for arrival patterns of ED patients, ideal patient volumes represent the load on the entire ED if patient-to-staff ratios are always kept under the identified thresholds. We then use a mixed-integer programming model to minimize understaffing with respect to the ideal patient volumes. The ED at Mayo Clinic Saint Marys Hospital in Rochester, Minnesota, a trauma center for both adults and pediatrics, implemented the new shift templates in the fourth quarter of 2015. The templates resulted in statistically significant improvements in several patient-centered metrics. In particular, the median length of stay, door-to-provider time, and door-to-bed time decreased by 11, 2.7, and 3 minutes, respectively, despite a six percent increase in patient volume.