The benefits (or detriments) of adapting to demand disruptions in a hospital pharmacy with supply chain disruptions.

Supply chain disruptions and demand disruptions make it challenging for hospital pharmacy managers to determine how much inventory to have on-hand. Having insufficient inventory leads to drug shortages, while having excess inventory leads to drug waste. To mitigate drug shortages and waste, hospital pharmacy managers can implement inventory policies that account for supply chain disruptions and adapt these inventory policies over time to respond to demand disruptions. Demand disruptions were prevalent during the Covid-19 pandemic. However, it remains unclear how a drug's shortage-waste weighting (i.e., concern for shortages versus concern for waste) as well as the duration of and time between supply chain disruptions influence the benefits (or detriments) of adapting to demand disruptions. We develop an adaptive inventory system (i.e., inventory policies change over time) and conduct an extensive numerical analysis using real-world demand data from the University of Michigan's Central Pharmacy to address this research question. For a fixed mean duration of and mean time between supply chain disruptions, we find a drug's shortage-waste weighting dictates the magnitude of the benefits (or detriments) of adaptive inventory policies. We create a ranking procedure that provides a way of discerning which drugs are of most concern and illustrates which policies to update given that a limited number of inventory policies can be updated. When applying our framework to over 300 drugs, we find a decision-maker needs to update a very small proportion of drugs (e.g., < 5 % ) at any point in time to get the greatest benefits of adaptive inventory policies.

Life and expectations post-kidney transplant: a qualitative analysis of patient responses.

BACKGROUND: The effect of a kidney transplant on a recipient extends beyond the restoration of kidney function. However, there is limited qualitative analysis of recipient perspectives on life following transplantation, particularly in the United States. To understand the full patient experience, it is necessary to understand recipient views on life adjustments after kidney transplantation, medical management, and quality of life. This could lead to improvements in recipient care and sense of well-being. METHODS: We conducted a paper-based survey from March 23 to October 1, 2015 of 476 kidney transplant recipients at the University of Michigan Health System in Ann Arbor, Michigan. We analyzed their open-ended responses using qualitative research methods. This is a companion analysis to a previous quantitative report on the closed-ended responses to that survey. RESULTS: Common themes relating to changes following transplantation included: improvements in quality of life, a return to normalcy, better health and more energy. Concerns included: duration of graft survival, fears about one day returning to dialysis or needing to undergo another kidney transplant, comorbidities, future quality of life, and the cost and quality of their healthcare. Many recipients were grateful for their transplant, but some were anxious about the burdens transplantation placed on their loved ones. CONCLUSIONS: While most recipients reported meaningful improvements in health and lifestyle after kidney transplantation, a minority of participants experienced declines in energy or health status. Worries about how long the transplant will function, future health, and cost and quality of healthcare are prevalent. Future research could study the effects of providing additional information, programs, and interventions following transplantation that target these concerns. This may better prepare and support kidney recipients and lead to improvements in the patient experience.

Incorporating nurse absenteeism into staffing with demand uncertainty.

Increased nurse-to-patient ratios are associated negatively with increased costs and positively with improved patient care and reduced nurse burnout rates. Thus, it is critical from a cost, patient safety, and nurse satisfaction perspective that nurses be utilized efficiently and effectively. To address this, we propose a stochastic programming formulation for nurse staffing that accounts for variability in the patient census and nurse absenteeism, day-to-day correlations among the patient census levels, and costs associated with three different classes of nursing personnel: unit, pool, and temporary nurses. The decisions to be made include: how many unit nurses to employ, how large a pool of cross-trained nurses to maintain, how to allocate the pool nurses on a daily basis, and how many temporary nurses to utilize daily. A genetic algorithm is developed to solve the resulting model. Preliminary results using data from a large university hospital suggest that the proposed model can save a four-unit pool hundreds of thousands of dollars annually as opposed to the crude heuristics the hospital currently employs.

Overcoming obstacles to resident-patient continuity of care.

OBJECTIVE: Because continuity of care (CC) is a necessary component of resident education, this analysis was done to understand what keeps CC between residents and patients low and how it can be most effectively improved. BACKGROUND: Many authors lament low CC between residents and patients, especially in the era of duty hour regulations. Some have tried lengthening rotations, some have tried increasing clinic attendance, and some have argued for various training models. Little detailed analysis has been done to identify root causes of low CC or ways to improve it. METHODS: Two months of charts were reviewed to estimate baseline CC on a vascular surgery rotation. Probability theory and engineering simulations were used to determine whether CC can be enhanced by (a) lengthening rotations, (b) altering observed logistical patterns, (c) using a "resident return" model where residents are able to see patients postoperatively even if moved to a different rotation, or (d) employing an apprenticeship model. RESULTS: Baseline analysis showed residents had 0% CC given 131 opportunities to do so. Probability analysis and the simulation outcomes suggest that rotation length plays a minor role in achieving CC. Logistical changes showed some improvement in CC, but not as much as using an apprenticeship rotation model. CONCLUSIONS: The limitations placed on CC by rotation duration are real, but lengthening the rotation does not meaningfully resolve the gap between acceptable CC levels and actual levels. Although CC can be enhanced with longer rotations if coupled with the use of the resident return model, the greater barrier to CC is the logistical patterns such as where residents spend time, how cases are assigned, and the lack of an alert system to inform residents about returning postoperative patients. The apprenticeship model enables residents to achieve CC closer to that of the faculty.

Comparison of patient and provider goals, expectations, and experiences following kidney transplantation.

OBJECTIVE: This study examined whether kidney transplant recipients' post-transplant goals and expectations align with those as perceived by their healthcare providers. METHODS: Post-transplant goals and expectations across four domains were assessed via a descriptive survey of healthcare providers (N=72) and kidney transplant recipients (N=476) at the University of Michigan from March 23 - October 1, 2015. Demographic and transplant-related data were collected via a retrospective review of medical records, and survey responses were compared using Chi-square tests, Wilcoxon two-sample tests, and logistic regression. RESULTS: Patients expressed higher quality of life (mean Neuro-QOL T-score 60.2 vs. 52.7), were less likely to report that they were currently experiencing complications (11% vs. 24%), and anticipated their transplants to last longer (median 25 vs. 15 years) and to live longer (median 80 vs. 71 years) than providers expected for their typical patient. However, provider perceptions of patients' future ability to feel well, perform daily activities and work were significantly higher than those expressed by patients (all p<0.05). CONCLUSION: Kidney transplant patient and provider expectations differ in significant ways. PRACTICE IMPLICATIONS: Identified areas of discordance may provide opportunities for patients and providers to better evaluate treatment option tradeoffs in post-transplant clinical interactions.

Design of a large network for radiological image data.

Radiological imaging is a rapidly growing business. The field is quickly evolving from films to electronic or digital imaging. By the year 2015, the amount of radiological image data that will have been generated in the U.S. alone is projected to be between 100 and 300 000 PB. (1 PB equals 2(50) B or about 10(15) B.) As the volume of radiological data increases, the need to transmit the data over long distances also increases. For example, radiologists in Chicago, India, or Israel, working in the same medical practice, may read images taken in Chicago. Globally distributed research requires that images be transmitted around the world. Radiologists and researchers want to be able to download files containing hundreds of megabytes in seconds. This service requirement suggests that multiple copies of images should be retained in globally distributed databases to minimize access and transmission delays. Key design issues for such a database include the location of the data repositories relative to the generating and retrieval (reading) sites and the number and location of the copies of the files that are generated. In this paper, we approximate the time to retrieve images stored in city j by a radiologist in city k at time period t. Next, we formulate a model designed to minimize the average retrieval time weighted over all demands. We briefly outline a nested Lagrangian relaxation approach to the problem. Computational results are then summarized. The paper ends with conclusion and directions for future research.

Computer Modeling to Evaluate the Impact of Technology Changes on Resident Procedural Volume.

BACKGROUND: As resident "index" procedures change in volume due to advances in technology or reliance on simulation, it may be difficult to ensure trainees meet case requirements. Training programs are in need of metrics to determine how many residents their institutional volume can support. OBJECTIVE: As a case study of how such metrics can be applied, we evaluated a case distribution simulation model to examine program-level mediastinoscopy and endobronchial ultrasound (EBUS) volumes needed to train thoracic surgery residents. METHODS: A computer model was created to simulate case distribution based on annual case volume, number of trainees, and rotation length. Single institutional case volume data (2011-2013) were applied, and 10 000 simulation years were run to predict the likelihood (95% confidence interval) of all residents (4 trainees) achieving board requirements for operative volume during a 2-year program. RESULTS: The mean annual mediastinoscopy volume was 43. In a simulation of pre-2012 board requirements (thoracic pathway, 25; cardiac pathway, 10), there was a 6% probability of all 4 residents meeting requirements. Under post-2012 requirements (thoracic, 15; cardiac, 10), however, the likelihood increased to 88%. When EBUS volume (mean 19 cases per year) was concurrently evaluated in the post-2012 era (thoracic, 10; cardiac, 0), the likelihood of all 4 residents meeting case requirements was only 23%. CONCLUSIONS: This model provides a metric to predict the probability of residents meeting case requirements in an era of changing volume by accounting for unpredictable and inequitable case distribution. It could be applied across operations, procedures, or disease diagnoses and may be particularly useful in developing resident curricula and schedules.

Achieving Accreditation Council for Graduate Medical Education duty hours compliance within advanced surgical training: a simulation-based feasibility assessment.

BACKGROUND: Certain operative cases occur unpredictably and/or have long operative times, creating a conflict between Accreditation Council for Graduate Medical Education (ACGME) rules and adequate training experience. METHODS: A ProModel-based simulation was developed based on historical data. Probabilistic distributions of operative time calculated and combined with an ACGME compliant call schedule. RESULTS: For the advanced surgical cases modeled (cardiothoracic transplants), 80-hour violations were 6.07% and the minimum number of days off was violated 22.50%. There was a 36% chance of failure to fulfill any (either heart or lung) minimum case requirement despite adequate volume. CONCLUSIONS: The variable nature of emergency cases inevitably leads to work hour violations under ACGME regulations. Unpredictable cases mandate higher operative volume to ensure achievement of adequate caseloads. Publically available simulation technology provides a valuable avenue to identify adequacy of case volumes for trainees in both the elective and emergency setting.

Improving Geographic Equity in Kidney Transplantation Using Alternative Kidney Sharing and Optimization Modeling.

The national demand for kidney transplantation far outweighs the supply of kidney organs. Currently, a patient's ability to receive a kidney transplant varies depending on where he or she seeks transplantation. This reality is in direct conflict with a federal mandate from the Department of Health and Human Services. We analyze current kidney allocation and develop an alternative kidney sharing strategy using a multiperiod linear optimization model, KSHARE. KSHARE aims to improve geographic equity in kidney transplantation while also respecting transplant system constraints and priorities. KSHARE is tested against actual 2000-2009 kidney allocation using Organ Procurement and Transplant Network data. Geographic equity is represented by minimizing the range in kidney transplant rates around local areas of the country. In 2009, less than 25% of standard criteria donor kidneys were allocated beyond the local area of procurement, and Donor Service Area kidney transplantation rates varied from 3.0% to 30.0%, for an overall range of 27.0%. Given optimal sharing of kidneys within 600 miles of procurement for 2000-2009, kidney transplant rates vary from 5.0% to 12.5% around the country for an overall kidney transplant range of 7.5%. Nationally sharing kidneys optimally between local areas only further decreases the transplant rate range by 1.7%. Enhancing the practice of sharing kidneys by the KSHARE model may increase geographic equity in kidney transplantation.

Estimating minimum program volume needed to train surgeons: when 4 × 15 really equals 90.

INTRODUCTION: Work-hour restrictions have decreased flexibility in scheduling and reduced exposure to certain operative cases. These restrictions may affect a resident's ability to meet certification requirements, particularly for rare, unscheduled cases (e.g., cardiothoracic transplants). We developed a computer-based simulation model using variables such as case volume and program size to demonstrate the influence of these factors on the likelihood of certifying a set of residents on rare cases. METHODS: We built a simulator to predict the probability of attaining certification for surgical residents, using cardiothoracic transplants as a test case. Inputs to the model included operating times, call schedules, and procurement travel times, as well as information on the distribution of times between transplants. RESULTS: We simulated 100 years of schedules using our current system parameters of an average of 33 heart and 31 lung transplants per year, and assuming an Accreditation Council for Graduate Medical Education-compliant daily-rotating call schedule. Despite having enough transplants to certify all residents for lungs if all opportunities were distributed equally among residents, the certification rate achieved when constrained by arrival time (and call schedules) and work restrictions was only 55%. Our calculations show that meeting minimum transplant-certification requirements for all residents would require at least 1.5 times the expected number of annual transplants. CONCLUSIONS: Our model enables analysis of a given program's ability to certify its residents based on program size and volume. These results could be used to design alternative scheduling paradigms to improve certification rates, without requiring reductions in certification requirements or program size.

Using optimization models to demonstrate the need for structural changes in training programs for surgical medical residents.

The primary goal of a residency program is to prepare trainees for unsupervised care. Duty hour restrictions imposed throughout the prior decade require that residents work significantly fewer hours. Moreover, various stakeholders (e.g. the hospital, mentors, other residents, educators, and patients) require them to prioritize very different activities, often conflicting with their learning goals. Surgical residents' learning goals include providing continuity throughout a patient's pre-, peri-, and post-operative care as well as achieving sufficient surgical experience levels in various procedure types and participating in various formal educational activities, among other things. To complicate matters, senior residents often compete with other residents for surgical experience. This paper features experiments using an optimization model and a real dataset. The experiments test the viability of achieving the above goals at a major academic center using existing models of delivering medical education and training to surgical residents. It develops a detailed multi-objective, two-stage stochastic optimization model with anticipatory capabilities solved over a rolling time horizon. A novel feature of the models is the incorporation of learning curve theory in the objection function. Using a deterministic version of the model, we identify bounds on the achievement of learning goals under existing training paradigms. The computational results highlight the structural problems in the current surgical resident educational system. These results further corroborate earlier findings and suggest an educational system redesign is necessary for surgical medical residents.