Joel Goh

Robust Optimization Made Easy with ROME

We introduce ROME, an algebraic modeling toolbox for a class of robust optimization problems. ROME serves as an intermediate layer between the modeler and optimization solver engines, allowing modelers to express robust optimization problems in a mathematically meaningful way. In this paper, we discuss how ROME can be used to model (1) a service-constrained robust inventory management problem, (2) a project-crashing problem, and (3) a robust portfolio optimization problem. Through these modeling examples, we highlight the key features of ROME that allow it to expedite the modeling and subsequent numerical analysis of robust optimization problems. ROME is freely distributed for academic use at http://www.robustopt.com.

The Relationship Between Workplace Stressors and Mortality and Health Costs in the United States

Even though epidemiological evidence links specific workplace stressors to health outcomes, the aggregate contribution of these factors to overall mortality and health spending in the United States is not known. In this paper, we build a model to estimate the excess mortality and incremental health expenditures associated with exposure to the following 10 workplace stressors: unemployment, lack of health insurance, exposure to shift work, long working hours, job insecurity, work–family conflict, low job control, high job demands, low social support at work, and low organizational justice. Our model uses input parameters obtained from publicly accessible data sources. We estimated health spending from the Medical Expenditure Panel Survey and joint probabilities of workplace exposures from the General Social Survey, and we conducted a meta-analysis of the epidemiological literature to estimate the relative risks of poor health outcomes associated with exposure to these stressors. The model was designed to overcome limitations with using inputs from multiple data sources. Specifically, the model separately derives optimistic and conservative estimates of the effect of multiple workplace exposures on health, and uses optimization to calculate upper and lower bounds around each estimate, which accounts for the correlation between exposures. We find that more than 120,000 deaths per year and approximately 5%–8% of annual healthcare costs are associated with and may be attributable to how U.S. companies manage their work forces. Our results suggest that more attention should be paid to management practices as important contributors to health outcomes and costs in the United States. This paper was accepted by Dimitris Bertsimas, optimization .

Genetic optimization of photonic bandgap structures

We investigate the use of a Genetic Algorithm (GA) to design a set of photonic crystals (PCs) in one and two dimensions. Our flexible design methodology allows us to optimize PC structures for specific objectives. In this paper, we report the results of several such GA-based PC optimizations. We show that the GA performs well even in very complex design spaces, and therefore has great potential as a robust design tool in a range of PC applications.

The Business Case for Investing in Physician Well-being

Importance Widespread burnout among physicians has been recognized for more than 2 decades. Extensive evidence indicates that physician burnout has important personal and professional consequences. Observations A lack of awareness regarding the economic costs of physician burnout and uncertainty regarding what organizations can do to address the problem have been barriers to many organizations taking action. Although there is a strong moral and ethical case for organizations to address physician burnout, financial principles (eg, return on investment) can also be applied to determine the economic cost of burnout and guide appropriate investment to address the problem. The business case to address physician burnout is multifaceted and includes costs associated with turnover, lost revenue associated with decreased productivity, as well as financial risk and threats to the organization’s long-term viability due to the relationship between burnout and lower quality of care, decreased patient satisfaction, and problems with patient safety. Nearly all US health care organizations have used similar evidence to justify their investments in safety and quality. Herein, we provide conservative formulas based on readily available organizational characteristics to determine the financial return on organizational investments to reduce physician burnout. A model outlining the steps of the typical organization’s journey to address this issue is presented. Critical ingredients to making progress include prioritization by leadership, physician involvement, organizational science/learning, metrics, structured interventions, open communication, and promoting culture change at the work unit, leader, and organization level. Conclusions and Relevance Understanding the business case to reduce burnout and promote engagement as well as overcoming the misperception that nothing meaningful can be done are key steps for organizations to begin to take action. Evidence suggests that improvement is possible, investment is justified, and return on investment measurable. Addressing this issue is not only the organization’s ethical responsibility, it is also the fiscally responsible one.

Total Cost Control in Project Management via Satisficing

We consider projects with uncertain activity times and the possibility of expediting, or crashing, them. Activity times come from a partially specified distribution within a family of distributions. This family is described by one or more of the following details about the uncertainties: support, mean, and covariance. We allow correlation between past and future activity time performance across activities. Our objective considers total completion time penalty plus crashing and overhead costs. We develop a robust optimization model that uses a conditional value-at-risk satisficing measure. We develop linear and piecewise-linear decision rules for activity start time and crashing decisions. These rules are designed to perform robustly against all possible scenarios of activity time uncertainty, when implemented in either static or rolling horizon mode. We compare our procedures against the previously available Program Evaluation and Review Technique and Monte Carlo simulation procedures. Our computational studies show that, relative to previous approaches, our crashing policies provide both a higher level of performance, i.e., higher success rates and lower budget overruns, and substantial robustness to activity time distributions. The relative advantages and information requirements of the static and rolling horizon implementations are discussed. This paper was accepted by Dimitris Bertsimas, optimization.

Workplace stressors & health outcomes: Health policy for the workplace

Extensive research focuses on the causes of workplace-induced stress. However, policy efforts to tackle the ever-increasing health costs and poor health outcomes in the United States have largely ignored the health effects of psychosocial workplace stressors such as high job demands, economic insecurity, and long work hours. Using meta-analysis, we summarize 228 studies assessing the effects of ten workplace stressors on four health outcomes. We find that job insecurity increases the odds of reporting poor health by about 50%, high job demands raise the odds of having a physician-diagnosed illness by 35%, and long work hours increase mortality by almost 20%. Therefore, policies designed to reduce health costs and improve health outcomes should account for the health effects of the workplace environment.

Evidence of Strategic Behavior in Medicare Claims Reporting

Recent Medicare legislation has been directed at improving patient care quality by penalizing providers for hospital-acquired infections (HAIs). However, asymmetric information prevents Medicare from directly monitoring HAI rates. Thus, these policies assume that providers correctly distinguish HAIs from present-on-admission (POA) infections in claims data despite opposing financial incentives. In particular, these policies may be undermined if providers engage in upcoding, a practice where HAIs are mis-reported (possibly unintentionally) to increase reimbursement or avoid financial penalties. Identifying upcoding behavior from claims data is challenging due to unobservable confounders. Our approach leverages state-level variations in adverse event reporting regulations and instrumental variable techniques to discover contradictions between HAI and POA reporting rates that are strongly suggestive of upcoding. We estimate that there are over 10,000 upcoded infections a year, resulting in an added cost burden of

Active Postmarketing Drug Surveillance for Multiple Adverse Events

200 million. Our findings suggest that, contrary to widely-held beliefs, increasing financial penalties alone may not reduce HAI incidence and may even exacerbate the problem. We make several policy recommendations based on our results, including a new measure for targeted HAI auditing and suggestions for effective adverse event reporting systems.Recent Medicare legislation has been directed at improving patient care quality by penalizing providers for hospital-acquired infections (HAIs). However, asymmetric information prevents Medicare from directly monitoring HAI rates. Thus, these policies assume that providers correctly distinguish HAIs from present-on-admission (POA) infections in claims data despite opposing financial incentives. In particular, these policies may be undermined if providers engage in upcoding, a practice where HAIs are mis-reported (possibly unintentionally) to increase reimbursement or avoid financial penalties. Identifying upcoding behavior from claims data is challenging due to unobservable confounders. Our approach leverages state-level variations in adverse event reporting regulations and instrumental variable techniques to discover contradictions between HAI and POA reporting rates that are strongly suggestive of upcoding. We estimate that there are over 10,000 upcoded infections a year, resulting in an added cost burden of

Data Uncertainty in Markov Chains: Application to Cost-Effectiveness Analyses of Medical Innovations

200 million. Our findings suggest that, contrary to widely-held beliefs, increasing financial penalties alone may not reduce HAI incidence and may even exacerbate the problem. We make several policy recommendations based on our results, including a new measure for targeted HAI auditing and suggestions for effective adverse event reporting systems.

Evidence of Upcoding in Pay-for-Performance Programs

Postmarketing drug surveillance is the process of monitoring the adverse events of pharmaceutical or medical devices after they are approved by the appropriate regulatory authorities. Historically, such surveillance was based on voluntary reports by medical practitioners, but with the widespread adoption of electronic medical records and comprehensive patient databases, surveillance systems that utilize such data are of considerable interest. Unfortunately, existing methods for analyzing the data in such systems ignore the open-ended exploratory nature of such systems that requires the assessment of multiple possible adverse events. In this article, we propose a method, SEQMEDS, that assesses the effect of a single drug on multiple adverse events by analyzing data that accumulate sequentially and explicitly captures interdependencies among the multiple events. The method continuously monitors a vector-valued test-statistic derived from the cumulative number of adverse events. It flags a potential adverse ...