Ebru Bish

ABSTRACT We propose a novel analytic approach for the comparative statics analysis of multiproduct multiresource newsvendor networks under responsive pricing. Our approach involves exploiting the properties of the primal mathematical programming formulation and of the dual variables and linking those properties to the concept of convex orders and to properties of the underlying demand function. The use of convex orders allows us to establish our main results without restriction to a specific demand distribution. A major strength of our approach is that it is "scalable," i.e., it applies to newsvendor networks with any number of "nonindependent" (i.e., demand or resource sharing) products and resources, without an exponential increase in effort as problem size increases. This is unlike the current approaches commonly used in the operations management literature, which typically involve a parametric analysis of the recourse problem, followed by the use of Jacobians and the implicit function theorem. Providing a rigorous framework for comparative statics analysis, which can be applied to other problems that are not amenable to traditional parametric analysis, is our main contribution. We demonstrate this approach on the optimal capacity decision problem in multiproduct newsvendor networks under responsive pricing, formulated as a two-stage stochastic programming problem with recourse: The firm determines the resource capacities ex ante, in the first stage, when demand intercepts are uncertain, and makes the pricing and production decisions ex post, in the second stage, when demand intercepts (e.g., market conditions) are fully observed. This particular problem and its variants are well studied in the operations management literature. A comparative statics analysis is integral to the study of the capacity investment decision, as it allows answers to important questions such as the following: "Does the firm acquire more or less of the different resources available as demand uncertainty increases? Does the firm benefit from an increase in demand uncertainty?" Using our proposed approach, we establish comparative statics results on how the newsvendor's expected profit and optimal capacity decision change with demand risk in multiproduct multiresource newsvendor networks. We also extend our analysis to the study of demand dependence in two-product networks.

Health care during hospitalization has become more complex. With this complexity comes additional patient risk that may lead to patient safety events. These risks usually occur infrequently, but when they do, they can be catastrophic for patients. Common approaches for analyzing serious or sentinel events in health care include root cause analysis (RCA), which is retrospective in nature and has a number of limitations. Hospitals are also required to prospectively perform a failure modes and effects analysis (FMEA) annually on one high risk event. The FMEA process is also not without its own limitations. This paper describes an approach to prospectively analyze potential serious and sentinel events by using a tool known as socio-technical probabilistic risk assessment (ST-PRA). This tool, used in several other industries, has seen some moderate success in health care for analyzing risks related to blood transfusions, medication errors, and infections. The major benefits of this tool,...

Babesia microti causes transfusion-transmitted babesiosis (TTB); currently, blood donor screening assays are unlicensed but used investigationally. We developed a decision tree model assessing the comparative- and cost-effectiveness of B. microti blood donation screening strategies in endemic areas compared to the status quo (question regarding a history of babesiosis), including testing by: 1) universal antibody (Ab), 2) universal polymerase chain reaction (PCR), 3) universal Ab/PCR, and 4) recipient risk-targeted Ab/PCR. The model predicted the number of TTB cases, complicated TTB cases, cases averted, and quality-adjusted life years (QALYs). Economic outcomes included each strategy's per-donation cost, waste (number of infection-free units incorrectly discarded), and waste index (number wasted units/number true positives). Sensitivity analyses examined uncertainty in transmission probabilities, prevalence rates, and other key model inputs. Universal PCR in four endemic states would prevent 24 to 31 TTB cases/100,000 units transfused (pht) at an incremental cost-effectiveness ratio (ICER) of $26,000 to $44,000/QALY (transmission probability dependent) and waste index of zero. Universal Ab/PCR would prevent 33 to 42 TTB cases pht at an ICER of $54,000 to $83,000/QALY and waste index of 0.05. The questionnaire is most wasteful (99.62 units wasted pht; 208.62 waste index), followed by the risk-targeted strategy (76.27 units wasted pht; 0.68 waste index). The model predicted zero cases of TTB or complicated TTB with universal Ab/PCR (versus [33, 42] and [13, 18] pht, respectively [no screening]). Results are highly sensitive to transmission probabilities. Universal PCR in endemic states is an effective blood donation screening strategy at a threshold of $50,000/QALY. Using a higher cost-effectiveness ratio, universal Ab/PCR is the most effective strategy.

To understand how structural and process elements may affect the risk for surgical site infections (SSIs) in the ambulatory surgery center (ASC) environment, the researchers employed a tool known as socio-technical probabilistic risk assessment (ST-PRA). ST-PRA is particularly helpful for estimating risks in outcomes that are very rare, such as the risk of SSI in ASCs. Study objectives were to (1) identify the risk factors associated with SSIs resulting from procedures performed at ASCs and (2) design an intervention to mitigate the likelihood of SSIs for the most common risk factors that were identified by the ST-PRA for a particular surgical procedure. ST-PRA was used to study the SSI risk in the ASC setting. Both quantitative and qualitative data sources were utilized, and sensitivity analysis was performed to ensure the robustness of the results. The event entitled "fail to protect the patient effectively" accounted for 51.9% of SSIs in the ambulatory care setting. Critical components of this event included several failure risk points related to skin preparation, antibiotic administration, staff training, proper response to glove punctures during surgery, and adherence to surgical preparation rules related to the wearing of jewelry, watches, and artificial nails. Assuming a 75% reduction in noncompliance on any combination of 2 of these 5 components, the risk for an SSI decreased from 0.0044 to between 0.0027 and 0.0035. An intervention that targeted the 5 major components of the major risk point was proposed, and its implications were discussed.

The Socio-Technical Probabilistic Risk Assessment, a proactive risk assessment tool imported from high-risk industries, was used to identify risks for surgical site infections (SSIs) associated with the ambulatory surgery center setting and to guide improvement efforts. This study had 2 primary objectives: (1) to identify the critical risk factors associated with SSIs resulting from procedures performed at ambulatory surgery centers and (2) to design an intervention to mitigate the probability of SSI for the highest risk factors identified. Inputs included quantitative and qualitative data sources from the evidence-based literature and from health care providers. The Socio-Technical Probabilistic Risk Assessment ranked the failure points (events) on the basis of their contribution to an SSI. The event, entitled "Failure to protect the patient effectively," which included several failure points, was the most critical unique event with the highest contribution to SSI risk. A total of 51.87% of SSIs in this setting were caused by this failure. Consequently, we proposed an intervention aimed at all 5 major components of this failure. The intervention targets improvements in skin preparation; proper administration of antibiotics; staff training in infection control principles, including practices for the prevention of glove punctures; and procedures to ensure the removal of watches, jewelry, and artificial nails.

... Ebru K. Bish† Ana Muriel* Stephan Biller§ ... both products, we investigate the performance of various simple capacity allocation policies.For each i,j G { 1,2 } , let X ij denote the quantity of producti allocated to plant j in the flexible system under allocation policyA, and letic = { 1,2 ...

ABSTRACT We consider a firm that uses two perishable resources to satisfy two demand types. Resources are flexible such that each resource can be used to satisfy either demand type. Resources are also indivisible such that the entire resource must be allocated to the same demand type. This type of resource flexibility can be found in different applications such as movie theater complexes, cruise lines, and airlines. In our model, customers arrive according to independent Poisson processes, but the arrival rates are uncertain. Thus, the manager can learn about customer arrival rates from earlier demand figures and potentially increase the sales by postponing the resource allocation decision. We consider two settings, and derive the optimal resource allocation policy for one setting and develop a heuristic policy for the other. Our analysis provides managerial insights into the effectiveness of different resource allocation mechanisms for flexible and indivisible resources.