@article{zhang_wu_denton_wilson_lobo_2019, title={Probabilistic sensitivity analysis on Markov models with uncertain transition probabilities: an application in evaluating treatment decisions for type 2 diabetes}, volume={22}, ISSN={1386-9620 1572-9389}, url={http://dx.doi.org/10.1007/S10729-017-9420-8}, DOI={10.1007/s10729-017-9420-8}, abstractNote={Markov models are commonly used for decision-making studies in many application domains; however, there are no widely adopted methods for performing sensitivity analysis on such models with uncertain transition probability matrices (TPMs). This article describes two simulation-based approaches for conducting probabilistic sensitivity analysis on a given discrete-time, finite-horizon, finite-state Markov model using TPMs that are sampled over a specified uncertainty set according to a relevant probability distribution. The first approach assumes no prior knowledge of the probability distribution, and each row of a TPM is independently sampled from the uniform distribution on the row's uncertainty set. The second approach involves random sampling from the (truncated) multivariate normal distribution of the TPM's maximum likelihood estimators for its rows subject to the condition that each row has nonnegative elements and sums to one. The two sampling methods are easily implemented and have reasonable computation times. A case study illustrates the application of these methods to a medical decision-making problem involving the evaluation of treatment guidelines for glycemic control of patients with type 2 diabetes, where natural variation in a patient's glycated hemoglobin (HbA1c) is modeled as a Markov chain, and the associated TPMs are subject to uncertainty.}, number={1}, journal={Health Care Management Science}, publisher={Springer Nature}, author={Zhang, Yuanhui and Wu, Haipeng and Denton, Brian T. and Wilson, James R. and Lobo, Jennifer M.}, year={2019}, month={Mar}, pages={34–52} }
 @article{mason_denton_shah_smith_2014, title={Optimizing the simultaneous management of blood pressure and cholesterol for type 2 diabetes patients}, volume={233}, ISSN={["1872-6860"]}, DOI={10.1016/j.ejor.2013.09.018}, abstractNote={We present a Markov decision process (MDP) model to determine the optimal timing of blood pressure and cholesterol medications. We study the use of our model for a high-risk population of patients with type 2 diabetes; however, the model and methods we present are applicable to the general population. We compare the optimal policies based on our MDP to published guidelines for initiation of blood pressure and cholesterol medications over the course of a patient’s lifetime. We also present a bicriteria analysis that illustrates the trade off between quality-adjusted life years and costs of treatment.}, number={3}, journal={EUROPEAN JOURNAL OF OPERATIONAL RESEARCH}, author={Mason, J. E. and Denton, B. T. and Shah, N. D. and Smith, S. A.}, year={2014}, month={Mar}, pages={727–738} }
 @article{erdogan_denton_2013, title={Dynamic Appointment Scheduling of a Stochastic Server with Uncertain Demand}, volume={25}, ISSN={["1526-5528"]}, DOI={10.1287/ijoc.1110.0482}, abstractNote={ We formulate and solve two new stochastic linear programming formulations of appointment scheduling problems that are motivated by the management of health services. We assume that service durations and the number of customers to be served on a particular day are uncertain. In the first model, customers may fail to show up for their appointments (“no-show”). This model is formulated as a two-stage stochastic linear program. In the second model, customers are scheduled dynamically, one at a time, as they request appointments. This model is formulated as a multistage stochastic linear program with stages defined by customer appointment requests. We analyze the structure of the models and adapt decomposition-based algorithms to solve the problems efficiently. We present numerical results that illustrate the impact of uncertainty on dynamic appointment scheduling, and we identify useful insights that can be applied in practice. We also present a case study based on real data for an outpatient procedure center. }, number={1}, journal={INFORMS JOURNAL ON COMPUTING}, author={Erdogan, S. Ayca and Denton, Brian}, year={2013}, pages={116–132} }
 @article{mason_denton_2012, title={A comparison of decision-maker perspectives for optimal cholesterol treatment}, volume={56}, ISSN={["2151-8556"]}, DOI={10.1147/jrd.2012.2201849}, abstractNote={Medical decisions often involve tradeoff among competing criteria. For example, patients with third-party health insurance are primarily concerned about maximizing their quality-adjusted lifespan, since the majority of the cost burden typically falls on the third-party payer. On the other hand, third-party payers are incented to minimize total healthcare-related costs. Therefore, third-party payers must weigh the short-term cost of treatment against the long-term benefits of avoiding more costly health outcomes associated with disease progression and adverse events. The goal of the societal perspective is to achieve a reasonable balance among these competing criteria of quality-adjusted lifespan and costs. Treatment of diabetes provides a good example of the need to apply multicriteria decision-making models to treatment decisions. Chronic diseases such as diabetes are associated with high medical costs and a large number of available treatment options. In this paper, we use a Markov decision process (MDP) to show how decision-maker perspectives can influence medical treatment decisions related to cardiovascular risk management in patients with type 2 diabetes. We compare optimal treatment decisions from three different perspectives: societal, patient, and third-party payer. We further formulate an inverse MDP model to estimate the implied monetary value of a year of life, from the societal perspective, according to current U.S. treatment guidelines.}, number={5}, journal={IBM JOURNAL OF RESEARCH AND DEVELOPMENT}, author={Mason, J. E. and Denton, B. T.}, year={2012} }
 @article{inman_zhang_shah_denton_2012, title={An examination of the dynamic changes in prostate-specific antigen occurring in a population-based cohort of men over time}, volume={110}, DOI={10.1111/j.1464-410x.2011.10925.x}, abstractNote={Study Type – Diagnosis (exploratory cohort)Level of Evidence 2bWhat's known on the subject? and What does the study add?A single serum PSA measurement is commonly used as a screening test to identify men with prostate cancer. A rise in PSA over time may identify men at increased risk of prostate cancer. Dynamic measures of PSA change (ex: PSA velocity, PSA doubling time) are frequently used to justify prostate biopsy in men.We demonstrate that the current serum PSA is the best predictor of future prostate cancer risk among commonly available clinical variables. We show that dynamic measures of PSA change do not improve upon PSA's ability to predict future prostate cancer. Our study suggests that dynamic measures of PSA change may not be useful in screening for prostate cancer.}, number={3}, journal={BJU International}, author={Inman, B. A. and Zhang, J. Y. and Shah, N. D. and Denton, B. T.}, year={2012}, pages={375–381} }
 @article{zhang_denton_balasubramanian_shah_inman_2012, title={Optimization of PSA Screening Policies: A Comparison of the Patient and Societal Perspectives}, volume={32}, ISSN={["1552-681X"]}, DOI={10.1177/0272989x11416513}, abstractNote={ Objective. To estimate the benefit of PSA-based screening for prostate cancer from the patient and societal perspectives. Method. A partially observable Markov decision process model was used to optimize PSA screening decisions. Age-specific prostate cancer incidence rates and the mortality rates from prostate cancer and competing causes were considered. The model trades off the potential benefit of early detection with the cost of screening and loss of patient quality of life due to screening and treatment. PSA testing and biopsy decisions are made based on the patient’s probability of having prostate cancer. Probabilities are inferred based on the patient’s complete PSA history using Bayesian updating. Data Sources. The results of all PSA tests and biopsies done in Olmsted County, Minnesota, from 1993 to 2005 (11,872 men and 50,589 PSA test results). Outcome Measures. Patients’ perspective: to maximize expected quality-adjusted life years (QALYs); societal perspective: to maximize the expected monetary value based on societal willingness to pay for QALYs and the cost of PSA testing, prostate biopsies, and treatment. Results. From the patient perspective, the optimal policy recommends stopping PSA testing and biopsy at age 76. From the societal perspective, the stopping age is 71. The expected incremental benefit of optimal screening over the traditional guideline of annual PSA screening with threshold 4.0 ng/mL for biopsy is estimated to be 0.165 QALYs per person from the patient perspective and 0.161 QALYs per person from the societal perspective. PSA screening based on traditional guidelines is found to be worse than no screening at all. Conclusions. PSA testing done with traditional guidelines underperforms and therefore underestimates the potential benefit of screening. Optimal screening guidelines differ significantly depending on the perspective of the decision maker. }, number={2}, journal={MEDICAL DECISION MAKING}, author={Zhang, Jingyu and Denton, Brian T. and Balasubramanian, Hari and Shah, Nilay D. and Inman, Brant A.}, year={2012}, pages={337–349} }
 @article{zhang_denton_balasubramanian_shah_inman_2012, title={Optimization of Prostate Biopsy Referral Decisions}, volume={14}, ISSN={["1526-5498"]}, DOI={10.1287/msom.1120.0388}, abstractNote={ Prostate cancer is the most common solid tumor in American men and is screened for using prostate-specific antigen (PSA) tests. We report on a nonstationary partially observable Markov decision process (POMDP) for prostate biopsy referral decisions. The core states are the patients' prostate cancer related health states, and PSA test results are the observations. Transition probabilities and rewards are inferred from the Mayo Clinic Radical Prostatectomy Registry and the medical literature. The objective of our model is to maximize expected quality-adjusted life years. We solve the POMDP model to obtain an age and belief (probability of having prostate cancer) dependent optimal biopsy referral policy. We also prove a number of structural properties including the existence of a control-limit type policy for the biopsy referral decision. Our empirical results demonstrate a nondecreasing belief threshold in age, and we provide sufficient conditions under which PSA screening should be discontinued for older patients. Finally, the benefits of screening under the optimal biopsy referral policy are estimated, and sensitivity analysis is used to prioritize the model parameters that would benefit from additional data collection. }, number={4}, journal={M&SOM-MANUFACTURING & SERVICE OPERATIONS MANAGEMENT}, author={Zhang, Jingyu and Denton, Brian T. and Balasubramanian, Hari and Shah, Nilay D. and Inman, Brant A.}, year={2012}, pages={529–547} }
 @article{mason_england_denton_smith_kurt_shah_2012, title={Optimizing Statin Treatment Decisions for Diabetes Patients in the Presence of Uncertain Future Adherence}, volume={32}, ISSN={["1552-681X"]}, DOI={10.1177/0272989x11404076}, abstractNote={Background. Statins are an important part of the treatment plan for patients with type 2 diabetes. However, patients who are prescribed statins often take less than the prescribed amount or stop taking the drug altogether. This suboptimal adherence may decrease the benefit of statin initiation. Objective. To estimate the influence of adherence on the optimal timing of statin initiation for patients with type 2 diabetes. Method. The authors use a Markov decision process (MDP) model to optimize the treatment decision for patients with type 2 diabetes. Their model incorporates a Markov model linking adherence to treatment effectiveness and long-term health outcomes. They determine the optimal time of statin initiation that minimizes expected costs and maximizes expected quality-adjusted life years (QALYs). Results. In the long run, approximately 25% of patients remain highly adherent to statins. Based on the MDP model, generic statins lower costs in men and result in a small increase in costs in women relative to no treatment. Patients are able to noticeably increase their expected QALYs by 0.5 to 2 years depending on the level of adherence. Conclusions. Adherence-improving interventions can increase expected QALYs by as much as 1.5 years. Given suboptimal adherence to statins, it is optimal to delay the start time for statins; however, changing the start time alone does not lead to significant changes in costs or QALYs.}, number={1}, journal={MEDICAL DECISION MAKING}, author={Mason, Jennifer E. and England, Darin A. and Denton, Brian T. and Smith, Steven A. and Kurt, Murat and Shah, Nilay D.}, year={2012}, pages={154–166} }
 @article{underwood_zhang_denton_shah_inman_2012, title={Simulation optimization of PSA-threshold based prostate cancer screening policies}, volume={15}, ISSN={["1572-9389"]}, DOI={10.1007/s10729-012-9195-x}, abstractNote={We describe a simulation optimization method to design PSA screening policies based on expected quality adjusted life years (QALYs). Our method integrates a simulation model in a genetic algorithm which uses a probabilistic method for selection of the best policy. We present computational results about the efficiency of our algorithm. The best policy generated by our algorithm is compared to previously recommended screening policies. Using the policies determined by our model, we present evidence that patients should be screened more aggressively but for a shorter length of time than previously published guidelines recommended.}, number={4}, journal={HEALTH CARE MANAGEMENT SCIENCE}, author={Underwood, Daniel J. and Zhang, Jingyu and Denton, Brian T. and Shah, Nilay D. and Inman, Brant A.}, year={2012}, month={Dec}, pages={293–309} }
 @article{gul_denton_fowler_huschka_2011, title={Bi-Criteria Scheduling of Surgical Services for an Outpatient Procedure Center}, volume={20}, ISSN={["1937-5956"]}, DOI={10.1111/j.1937-5956.2011.01232.x}, abstractNote={ Uncertainty in the duration of surgical procedures can cause long patient wait times, poor utilization of resources, and high overtime costs. We compare several heuristics for scheduling an Outpatient Procedure Center. First, a discrete event simulation model is used to evaluate how 12 different sequencing and patient appointment time‐setting heuristics perform with respect to the competing criteria of expected patient waiting time and expected surgical suite overtime for a single day compared with current practice. Second, a bi‐criteria genetic algorithm (GA) is used to determine if better solutions can be obtained for this single day scheduling problem. Third, we investigate the efficacy of the bi‐criteria GA when surgeries are allowed to be moved to other days. We present numerical experiments based on real data from a large health care provider. Our analysis provides insight into the best scheduling heuristics, and the trade‐off between patient and health care provider‐based criteria. Finally, we summarize several important managerial insights based on our findings. }, number={3}, journal={PRODUCTION AND OPERATIONS MANAGEMENT}, author={Gul, Serhat and Denton, Brian T. and Fowler, John W. and Huschka, Todd}, year={2011}, pages={406–417} }
 @article{batun_denton_huschka_schaefer_2011, title={Operating room pooling and parallel surgery processing under uncertainty}, volume={23}, DOI={10.1287/ijoc.1100.0396}, abstractNote={ Operating room (OR) scheduling is an important operational problem for most hospitals. In this study, we present a novel two-stage stochastic mixed-integer programming model to minimize total expected operating cost given that scheduling decisions are made before the resolution of uncertainty in surgery durations. We use this model to quantify the benefit of pooling ORs as a shared resource and to illustrate the impact of parallel surgery processing on surgery schedules. Decisions in our model include the number of ORs to open each day, the allocation of surgeries to ORs, the sequence of surgeries within each OR, and the start time for each surgeon. Realistic-sized instances of our model are difficult or impossible to solve with standard stochastic programming techniques. Therefore, we exploit several structural properties of the model to achieve computational advantages. Furthermore, we describe a novel set of widely applicable valid inequalities that make it possible to solve practical instances. Based on our results for different resource usage schemes, we conclude that the impact of parallel surgery processing and the benefit of OR pooling are significant. The latter may lead to total cost reductions between 21% and 59% on average. }, number={2}, journal={INFORMS Journal on Computing}, author={Batun, S. and Denton, B. T. and Huschka, T. R. and Schaefer, A. J.}, year={2011}, pages={220–237} }
 @article{berg_denton_nelson_balasubramanian_rahman_bailey_lindor_2010, title={A Discrete Event Simulation Model to Evaluate Operational Performance of a Colonoscopy Suite}, volume={30}, ISSN={["1552-681X"]}, DOI={10.1177/0272989x09345890}, abstractNote={ Background and Aims. Colorectal cancer, a leading cause of cancer death, is preventable with colonoscopic screening. Colonoscopy cost is high, and optimizing resource utilization for colonoscopy is important. This study’s aim is to evaluate resource allocation for optimal use of facilities for colonoscopy screening. Method. The authors used data from a computerized colonoscopy database to develop a discrete event simulation model of a colonoscopy suite. Operational configurations were compared by varying the number of endoscopists, procedure rooms, the patient arrival times, and procedure room turnaround time. Performance measures included the number of patients served during the clinic day and utilization of key resources. Further analysis included considering patient waiting time tradeoffs as well as the sensitivity of the system to procedure room turnaround time. Results. The maximum number of patients served is linearly related to the number of procedure rooms in the colonoscopy suite, with a fixed room to endoscopist ratio. Utilization of intake and recovery resources becomes more efficient as the number of procedure rooms increases, indicating the potential benefits of large colonoscopy suites. Procedure room turnaround time has a significant influence on patient throughput, procedure room utilization, and endoscopist utilization for varying ratios between 1:1 and 2:1 rooms per endoscopist. Finally, changes in the patient arrival schedule can reduce patient waiting time while not requiring a longer clinic day. Conclusions. Suite managers should keep a procedure room to endoscopist ratio between 1:1 and 2:1 while considering the utilization of related key resources as a decision factor as well. The sensitivity of the system to processes such as turnaround time should be evaluated before improvement efforts are made. }, number={3}, journal={MEDICAL DECISION MAKING}, author={Berg, Bjorn and Denton, Brian and Nelson, Heidi and Balasubramanian, Hari and Rahman, Ahmed and Bailey, Angela and Lindor, Keith}, year={2010}, pages={380–387} }
 @article{balasubramanian_banerjee_denton_naessens_stahl_2010, title={Improving Clinical Access and Continuity through Physician Panel Redesign}, volume={25}, ISSN={["1525-1497"]}, DOI={10.1007/s11606-010-1417-7}, abstractNote={Population growth, an aging population and the increasing prevalence of chronic disease are projected to increase demand for primary care services in the United States.Using systems engineering methods, to re-design physician patient panels targeting optimal access and continuity of care.We use computer simulation methods to design physician panels and model a practice's appointment system and capacity to provide clinical service. Baseline data were derived from a primary care group practice of 39 physicians with over 20,000 patients at the Mayo Clinic in Rochester, MN, for the years 2004-2006. Panel design specifically took into account panel size and case mix (based on age and gender).The primary outcome measures were patient waiting time and patient/clinician continuity. Continuity is defined as the inverse of the proportion of times patients are redirected to see a provider other than their primary care physician (PCP).The optimized panel design decreases waiting time by 44% and increases continuity by 40% over baseline. The new panel design provides shorter waiting time and higher continuity over a wide range of practice panel sizes.Redesigning primary care physician panels can improve access to and continuity of care for patients.}, number={10}, journal={JOURNAL OF GENERAL INTERNAL MEDICINE}, author={Balasubramanian, Hari and Banerjee, Ritesh and Denton, Brian and Naessens, James and Stahl, James}, year={2010}, month={Oct}, pages={1109–1115} }
 @article{denton_miller_balasubramanian_huschka_2010, title={Optimal Allocation of Surgery Blocks to Operating Rooms Under Uncertainty}, volume={58}, ISSN={["0030-364X"]}, DOI={10.1287/opre.1090.0791}, abstractNote={ The allocation of surgeries to operating rooms (ORs) is a challenging combinatorial optimization problem. There is also significant uncertainty in the duration of surgical procedures, which further complicates assignment decisions. In this paper, we present stochastic optimization models for the assignment of surgeries to ORs on a given day of surgery. The objective includes a fixed cost of opening ORs and a variable cost of overtime relative to a fixed length-of-day. We describe two types of models. The first is a two-stage stochastic linear program with binary decisions in the first stage and simple recourse in the second stage. The second is its robust counterpart, in which the objective is to minimize the maximum cost associated with an uncertainty set for surgery durations. We describe the mathematical models, bounds on the optimal solution, and solution methodologies, including an easy-to-implement heuristic. Numerical experiments based on real data from a large health-care provider are used to contrast the results for the two models and illustrate the potential for impact in practice. Based on our numerical experimentation, we find that a fast and easy-to-implement heuristic works fairly well, on average, across many instances. We also find that the robust method performs approximately as well as the heuristic, is much faster than solving the stochastic recourse model, and has the benefit of limiting the worst-case outcome of the recourse problem. }, number={4}, journal={OPERATIONS RESEARCH}, author={Denton, Brian T. and Miller, Andrew J. and Balasubramanian, Hari J. and Huschka, Todd R.}, year={2010}, pages={802–816} }
 @article{denton_2009, title={Analysis of current approach and methodology for improvements}, volume={39}, number={3}, journal={Interfaces}, author={Denton, B. T.}, year={2009}, pages={288–289} }
 @article{denton_winands_kok_timpe_2009, title={Case Study of a Batch-Production and Inventory System}, volume={39}, ISSN={["1526-551X"]}, DOI={10.1287/inte.1090.0431}, abstractNote={ The goal of “Practice Abstracts” is to present interesting, topical, and novel applications of operations research methodology to a wide range of industrial applications. “Practice Abstracts” are intended to provide Interfaces readers with short (2–4 page) descriptions of the most relevant aspects of operations research-based projects, in a form that is accessible to academics and practitioners in other organizations. Contributions should be sent for evaluation to the editor of “Practice Abstracts,” Brian T. Denton, Edward P. Fitts Department of Industrial and Systems Engineering, 376 Daniels Hall, North Carolina State University, 111 Lampe Drive, Campus Box 7906, Raleigh, North Carolina 27695 (bdenton@ncsu.edu). }, number={6}, journal={INTERFACES}, author={Denton, Brian T. and Winands, E. M. M. and Kok, A. G. and Timpe, C.}, year={2009}, pages={552–554} }
 @article{denton_2009, title={Comparison with historical data and impact}, volume={39}, number={3}, journal={Interfaces}, author={Denton, B. T.}, year={2009}, pages={289–290} }
 @article{denton_oostrum_houdenhoven_wagelmans_kazemier_2009, title={Implementing a Master Surgical Scheduling Approach in a Regional Hospital}, volume={39}, ISSN={["1526-551X"]}, DOI={10.1287/inte.1090.0433}, abstractNote={ The goal of “Practice Abstracts” is to present interesting, topical, and novel applications of operations research methodology to a wide range of industrial applications. “Practice Abstracts” are intended to provide Interfaces readers with short (2–4 page) descriptions of the most relevant aspects of operations research-based projects, in a form that is accessible to academics and practitioners in other organizations. Contributions should be sent for evaluation to the editor of “Practice Abstracts,” Brian T. Denton, Edward P. Fitts Department of Industrial and Systems Engineering, 376 Daniels Hall, North Carolina State University, 111 Lampe Drive, Campus Box 7906, Raleigh, North Carolina 27695 (bdenton@ncsu.edu). }, number={6}, journal={INTERFACES}, author={Denton, Brian T. and Oostrum, Jeroen M. and Houdenhoven, Mark and Wagelmans, Albert P. M. and Kazemier, Geert}, year={2009}, pages={549–551} }
 @article{denton_2009, title={Improving the utilization of catheterization labs at Scottsdale Healthcare}, volume={39}, number={3}, journal={Interfaces}, author={Denton, B. T.}, year={2009}, pages={288–288} }
 @article{denton_sodhi_2009, title={Introduction: 2008 Franz Edelman Award for Achievement in Operations Research and the Management Sciences}, volume={39}, ISSN={["0092-2102"]}, DOI={10.1287/inte.1080.0422}, abstractNote={ This special issue of Interfaces is devoted to the finalists of the 37th annual competition for the Franz Edelman Award for Achievement in Operations Research and the Management Sciences, the profession's prestigious award for the practice of operations research. Of the six entries, one demonstrates the benefits derived from OR/MS-based scheduling for the care of the elderly in Sweden. The second shows dramatic improvement in air traffic management with new weather-system-related policies in the United States. The third shows how to improve network configuration and routing of natural gas in Norway and neighboring countries. The fourth shows how to place contaminant sensors in water sources and its application in the United States. The fifth reflects productivity improvements in print shops and document manufacturing facilities, also in the United States. The final entry shows how OR/MS was used to construct a brand new timetable for the passenger railway system in The Netherlands to account for much higher demand on the system. }, number={1}, journal={INTERFACES}, author={Denton, Brian T. and Sodhi, ManMohan S.}, year={2009}, pages={2–5} }
 @article{denton_kurt_shah_bryant_smith_2009, title={Optimizing the Start Time of Statin Therapy for Patients with Diabetes}, volume={29}, ISSN={["0272-989X"]}, DOI={10.1177/0272989x08329462}, abstractNote={Background . Clinicians often use validated risk models to guide treatment decisions for cardiovascular risk reduction. The most common risk models for predicting cardiovascular risk are the UKPDS, Framingham, and Archimedes models. In this article, the authors propose a model to optimize the selection of patients for statin therapy of hypercholesterolemia, for patients with type 2 diabetes, using each of the risk models. For each model, they evaluate the role of age, gender, and metabolic state on the optimal start time for statins. Method . Using clinical data from the Mayo Clinic electronic medical record, the authors construct a Markov decision process model with health states composed of cardiovascular events and metabolic factors such as total cholesterol and high-density lipoproteins. They use it to evaluate the optimal start time of statin treatment for different combinations of cardiovascular risk models and patient attributes. Results . The authors find that treatment decisions depend on the cardiovascular risk model used and the age, gender, and metabolic state of the patient. Using the UKPDS risk model to estimate the probability of coronary heart disease and stroke events, they find that all white male patients should eventually start statin therapy; however, using Framingham and Archimedes models in place of UKPDS, they find that for male patients at lower risk, it is never optimal to initiate statins. For white female patients, the authors also find some patients for whom it is never optimal to initiate statins. Assuming that age 40 is the earliest possible start time, the authors find that the earliest optimal start times for UKPDS, Framingham, and Archimedes are 50, 46, and 40, respectively, for women. For men, the earliest optimal start times are 40, 40, and 40, respectively. Conclusions . In addition to age, gender, and metabolic state, the choice of cardiovascular risk model influences the apparent optimal time for starting statins in patients with diabetes.}, number={3}, journal={MEDICAL DECISION MAKING}, author={Denton, Brian T. and Kurt, Murat and Shah, Nilay D. and Bryant, Sandra C. and Smith, Steven A.}, year={2009}, month={May}, pages={351–367} }
 @article{denton_2009, title={Performance evaluation and parametric analysis of our recommendations}, volume={39}, number={3}, journal={Interfaces}, author={Denton, B. T.}, year={2009}, pages={289–289} }
 @article{denton_van saane_reid_2009, title={Practice Abstracts}, volume={39}, ISSN={["0092-2102"]}, DOI={10.1287/inte.1090.0434}, abstractNote={ The goal of “Practice Abstracts” is to present interesting, topical, and novel applications of operations research methodology to a wide range of industrial applications. “Practice Abstracts” are intended to provide Interfaces readers with short (2–4 page) descriptions of the most relevant aspects of operations research-based projects, in a form that is accessible to academics and practitioners in other organizations. Contributions should be sent for evaluation to the editor of “Practice Abstracts,” Brian T. Denton, Edward P. Fitts Department of Industrial and Systems Engineering, 376 Daniels Hall, North Carolina State University, 111 Lampe Drive, Campus Box 7906, Raleigh, North Carolina 27695, bdenton@ncsu.edu. }, number={4}, journal={INTERFACES}, author={Denton, Brian T. and Van Saane, Lex and Reid, Ian}, year={2009}, pages={373–374} }
 @article{gupta_denton_2008, title={Appointment scheduling in health care: Challenges and opportunities}, volume={40}, ISSN={["1545-8830"]}, DOI={10.1080/07408170802165880}, abstractNote={Appointment scheduling systems are used by primary and specialty care clinics to manage access to service providers, as well as by hospitals to schedule elective surgeries. Many factors affect the performance of appointment systems including arrival and service time variability, patient and provider preferences, available information technology and the experience level of the scheduling staff. In addition, a critical bottleneck lies in the application of Industrial Engineering and Operations Research (IE/OR) techniques. The most common types of health care delivery systems are described in this article with particular attention on the factors that make appointment scheduling challenging. For each environment relevant decisions ranging from a set of rules that guide schedulers to real-time responses to deviations from plans are described. A road map of the state of the art in the design of appointment management systems is provided and future opportunities for novel applications of IE/OR models are identified.}, number={9}, journal={IIE TRANSACTIONS}, author={Gupta, Diwakar and Denton, Brian}, year={2008}, pages={800–819} }
 @article{iser_denton_king_2008, title={HEURISTICS FOR BALANCING OPERATING ROOM AND POST-ANESTHESIA RESOURCES UNDER UNCERTAINTY}, ISBN={["978-1-4244-2707-9"]}, DOI={10.1109/wsc.2008.4736243}, abstractNote={The post-anesthesia care unit (PACU) is a shared resource in the hospital where patients recover from surgery. It is fed by a set of operating rooms (OR¿s) often spanning several surgical services. It is insufficient to determine the best surgery schedule for any single OR without considering available PACU capacity. We model this as a two-stage process where the first stage is surgery and the second, post-anesthesia recovery. An interesting aspect of the second-stage process is that it begins as soon as the first stage has concluded even if a PACU bed is not available. In this case, the OR continues to house the recovering patient until a PACU bed is available. We analyze the structure of the problem, evaluate several heuristics based on competing performance measures for surgical suite efficiency, and present results of numerical experiments and insights that can be derived from them.}, journal={2008 WINTER SIMULATION CONFERENCE, VOLS 1-5}, author={Iser, Jill H. and Denton, Brian T. and King, Russell E.}, year={2008}, pages={1601–1608} }
 @article{denton_sodhi_2008, title={Introduction: 2007 Franz Edelman Award for Achievement in Operations Research and the Management Sciences}, volume={38}, ISSN={["0092-2102"]}, DOI={10.1287/inte.1070.0338}, abstractNote={ This special issue of Interfaces is devoted to the finalists of the 36th annual competition for the Franz Edelman Award for Achievement in Operations Research and the Management Sciences, the profession's prestigious award for the practice of operations research. Brian Denton, chair of the competition, and ManMohan S. Sodhi, editor of this special issue, provide an overview of the competition and introduce the finalists. }, number={1}, journal={INTERFACES}, author={Denton, Brian and Sodhi, ManMohan S.}, year={2008}, pages={2–4} }
 @article{denton_2008, title={Simulation of a virtual campus at the Open University of Catalonia}, volume={38}, ISSN={["0092-2102"]}, DOI={10.1287/inte.1070.0321}, abstractNote={ The goal of “Practice Abstracts” is to present interesting, topical, and novel applications of operations research methodology to a wide range of industrial applications. “Practice Abstracts” are intended to provide Interfaces readers with short (2–4 pages) descriptions of the most relevant aspects of operations research-based projects, in a form that is accessible to academics and practitioners in other organizations. Contributions should be sent for evaluation to the editor of “Practice Abstracts,” Brian T. Denton, Edward P. Fitts Department of Industrial and Systems Engineering, North Carolina State University, 370 Daniels Hall, 111 Lampe Drive, Raleigh, North Carolina 27695-7906, bdenton@ncsu.edu. }, number={2}, journal={INTERFACES}, author={Denton, Brian T.}, year={2008}, pages={147–149} }
 @article{denton_2007, title={Practice Abstracts}, volume={37}, ISSN={["0092-2102"]}, DOI={10.1287/inte.1070.0315}, abstractNote={ The goal of “Practice Abstracts” is to present interesting, topical, and novel applications of operations research methodology to a wide range of industrial applications. “Practice Abstracts” are intended to provide Interfaces readers with short (2–4 page) descriptions of the most relevant aspects of operations-research–based projects, in a form that is accessible to academics and practitioners in other organizations. Contributions should be sent for evaluation to the editor of “Practice Abstracts,” Brian T. Denton, Edward P. Fitts Department of Industrial and Systems Engineering, 370 Daniels Hall, North Carolina State University, 111 Lampe Drive, Raleigh, North Carolina 27695-7906, bdenton@ncsu.edu. }, number={6}, journal={INTERFACES}, author={Denton, Brian T.}, year={2007}, pages={582–583} }