Industrial Engineering & Operations Research Masters Theses Collection

The Process by which Physicians Extract Information from Electronic Progress Notes During Handoffs

Amster, Brian D. — Fri, 23 Nov 2012 07:02:26 PST

A handoff requires that the responsibility for patient patient’s care is transferred from one healthcare professional to another. The goals of this research were to identify, evaluate, and use analytical methods to describe how physicians (n=10) extracted information from electronic progress notes, one important source of information used during handoffs. Participants also verbally summarized the notes as they would during handoffs. Six methods were used to analyze how participants read progress notes, each uniquely contributing to our understanding of physicians’ visual attention patterns during this process. The participants focused their visual attention on the Impression and Plan section of the progress notes in that over 60% of the participants’ total time was spent reading that section. Physicians could miss an error or critical piece of information if the information is not located in the Impression and Plan. The importance given by the participants to the Impression and Plan section was confirmed in that the majority of participants’ verbal handoff content focused primarily on information that could be found in the Impression and Plan. Participants relied on the Medication Profile section quite heavily if it was present in the progress note.

We determined that if the participant was currently reading in one section (s)he most likely would transition his/her visual attention to the physically closest section in the note, meaning the format of progress notes may dictate how notes are read. We determined what the most likely paths were through the progress notes, which could be a first step in reordering of the progress note for evaluation in future studies.

Participants’ responses to debriefing questions suggested that they were aware of their reliance on the Impression and Plan, but that they thought the way they read notes is context-specific, depending on factors such as their use of the note and the reputation of the author of the note. These findings suggest a need for more research that evaluates how different note structures and content affect how physicians and other health providers extract and use information in varied clinical contexts.

Optimizing the Safety Stock Inventory Cost Under Target Service Level Constraints

Shivsharan, Chetan T. — Thu, 23 Aug 2012 05:44:50 PDT

The level of customer satisfaction largely depends on manufacturer’s ability to respond to customer orders with promptness. The swiftness with which the manufacturers are able to meet customer demand is measured by the service level. There are two service level measures typically used. The first one is type 1 service level which denotes the probability of not stocking out over a planning period. The other is fill rate which denotes the proportion of demand satisfied with the existing inventory. We review the rich and diverse literature available on inventory cost optimization under these service level constraints. Subsequently two optimization models are developed for the two different types of service level measures. The goal is to determine the safety stock values for all products in a multi product inventory required to achieve aggregate type 1 and type 2 service levels at the minimum inventory cost. For both the models we also maintain a minimum threshold for individual type 1 and type 2 service level for every product. The models are solved using Lagrangian relaxation techniques.

The models are computationally solved in Microsoft Excel. We then carry out discrete event simulation to validate the results and to test the performance of the models. To provide the decision makers with an idea of variability in the service levels and the related risks associated with it on an immediate finite horizon planning scale we also carry out simulation for a time span of one, two and four years.

The results obtained show desired type 1 and type 2 service levels for products with under both infinite and finite planning horizons.

Development of a Cost Minimizing Strategy to Mitigate Bird Mortalities in a Wind Farm

Singh, Karamvir — Thu, 23 Aug 2012 05:33:02 PDT

Wind is the second largest renewable energy source after solar. It is one of the fastest growing sources of electricity in the world and currently of wind energy is installed in the United States and an additional is under construction (Office of Energy and Environment Affairs, 2011). For the growth of wind electricity, one of the most prominent environmental concerns relates to the death of birds, bats and other avian species resulting from collision with turbine blades.

This thesis develops a model that provides the optimal strategy of turning the turbines off in a wind farm for certain periods to mitigate bird mortalities. We first create a single turbine optimization model for each hour on each day of a single month. We maximize the expected revenue generation and limit the expected bird mortalities to a certain level to solve for the dates and times for which the turbine should be turned off. The optimization problem is found to be part of common class of problems called Knapsack problems and through experiments we conclude that a linear programming (LP) relaxation of the problem provides a near-optimal solution. We extend the single-turbine model to a multiple-turbine model applicable to a wind farm. In this case, we solve for the percentage of wind turbines that should be turned off to limit the expected bird mortalities to a certain level. Finally, we carry out an uncertainty analysis and estimate probability distributions over the outcome of optimal strategy of turning the turbine off.

We consider the Cape Wind project as a case study and limit the analysis to only one species of endangered birds called the common loon. We find that in order to save an expected number of 10 such birds in the month of March; we need to turn the turbine off for a total of 23 hours spread over specific dates and times. The average cost per bird was found to be $171.

The Economic Impacts of Technical Change in Carbon Capture

Rasmussen, Peter G. — Thu, 12 Apr 2012 01:14:57 PDT

There is a general consensus in the literature that carbon capture and storage (CCS), a technology that controls CO₂ emissions from fossil fuel power plants, figures to be a critical technology to reduce CO₂ emissions to CO₂ concentration stabilization levels prescribed in the literature. We completed three projects that advance the understanding of how technical change in carbon capture affects both near-future costs of CCS and the economy in the long term. First, we conducted a literature review of near-future capture cost estimates in order to get an idea of how expensive carbon capture will be in the near-future. The literature indicates that pre-combustion capture is the least expensive carbon capture technology because its combustion process best facilitates carbon capture. Second, we explored the limits of incremental technical change in each near-future capture technology using a performance-cost model. The results of the sensitivity analysis showed that pre-combustion capture could be the least expensive capture technology after incremental technical change has occurred. Third, we used an integrated assessment model (IAM) to investigate how rapid incremental and breakthrough technical change in carbon capture could impact the electric energy market, total CO₂ abatement cost and CO₂ price over time. We modeled breakthrough technical change using data from a paper in the literature that provides cost and performance estimates for a radical carbon capture technology still in the early stages of research and development (R&D) (Baker, Chon, & Keisler, 2009). CCS dominates electricity market share over time given a chemical looping breakthrough.

Dynamic Capacity Allocation in Primary Care with Physician Flexibility

Biehl, Sebastian S. — Thu, 12 Apr 2012 01:12:50 PDT

Key performance measures for PC performance are timeliness and continuity. Whereas the first refers to the ability to obtain an appointment as soon as possible, the latter warrants a patient being able to see a familiar physician. In this context one has to consider the two types of appointments - same-day and prescheduled. The former is characterized by an urgent need of the patient to see a physician, the latter embodies non-urgent follow-up visits or regular appointments due to a chronic comorbidity. How should requests for appointments be assigned in order to deliver on the conflicting key metrics? What impact does the presence and the location of prescheduled appointments have in this context? How does the capacity allocation between prescheduled and same-day demand influence the decision making in the clinic? Using a stochastic dynamic program to model the dynamics of practice, we explore various ways of managing the inherent flexibility of physicians to see each others’ patients. Patients are calling in for same-day appointments. Thus, assignment decisions have to be made dynamically in real time under uncertainty of future demand and in presence of prescheduled appointment slots. The study consists of three parts: first, we examine the impact of the location of prescheduled appointments on the performance of the clinic. Second, we use our structural insights gained in the first part in order to derive implementable heuristic assignment policies. Third, we evaluate the performance of the heuristics in comparison to the optimal solution gained in the stochastic dynamic program and derive implications for the practice of primary care.

Reverse Logistics Network Design for Electric Vehicle Batteries

Schnellenpfeil, Tilman — Thu, 12 Apr 2012 01:10:06 PDT

As the interest in value recovery of used products increases, industries such as the automotive industry are starting to rethink their product policy. In this thesis we analyze a reverse logistics network for electric vehicle batteries. We develop a cost model that includes the major factors driving the costs in the handling and remanufacturing of failed electric vehicle batteries. Also, we capture the value of time in terms of value decay of returned batteries in the network over time.

Using this model we study alternative reverse logistics network designs and identify under what conditions each of them would be optimal.

First, we develop a mathematical formulation to describe the network we take into focus. Second, we run a computational study and compare different scenario settings to gain insights about the performance of different network configurations and how it is affected by the various factors: returns volume, how it changes over time, repair capability, decay rate and transportation costs.

The results of the study highlight the fact that the network has to adjust its structure over time to reduce costs. Due to the increasing volume certain configurations appear to be more cost-effective at some point in time. Any changes need to be made under consideration of the continuous growth of the demands on the reverse logistics network to prepare for the next optimal configuration.

In this thesis we present appropriate network adjustments to optimize the performance in terms of costs.

Using Discrete Event Simulation to Evaluate the Impact of Adding a Fast Track Section to a Crowded Emergency Department

Jin, Yan — Thu, 12 Apr 2012 01:09:21 PDT

The implementation of a fast track section is a commonly used strategy to improve patient flow in emergency departments (EDs). A fast track section reserves resources (beds, doctors and nurses) for lower acuity patients, and is thus aimed to reduce the wait time and length of stay of these patients. We use a discrete event simulation to investigate the impact of adding a fast track section to an emergency department. We quantify the effect of introducing a fast track on length of stay and waiting time to bed for low and high acuity patients in a crowded ED and compare it to an ED without fast track (Combined ED). We simulate a crowded ED by increasing the patient arrival rate, changing the acuity mix and increasing the time taken for admitted patients in the ED to obtain an inpatient bed (boarding time).

We demonstrate that, when compared to a Combined ED with the same number of resources, the introduction of a fast track reduces the wait time to bed for lower acuity patients. However, this comes at the cost of increased waiting time for some higher acuity patients, which is unacceptable in practice. In investigating the solutions to this problem, we find that changing patient prioritization is the most effective way of reducing wait times under crowding. This change in priority does not require the addition of beds, doctors and nurses, and is therefore a cost-effective approach. Finally, we discuss the implications of our results for emergency departments.

Methods to Study Nurses’ Visual Scanning Patterns during the Medication Administration Process

He, Ze — Wed, 24 Aug 2011 09:57:39 PDT

Quality of care is important in health care systems, and reducing medication errors is an effective approach to improve health care quality because medication errors are not rare and can cause adverse patient outcomes. Current researchers have adopted contextual, macro level methods to study the medication administration process, but the association between cognitive factors and nurses’ abilities to identify medication errors during this process remains unclear. In this research, I tested whether methods for analyzing visual scanning patterns are applicable to the study of health care processes, specifically how nurses complete the medication administration process.

The data used in this study was collected during three experiments wherein nurse participants wore an eye tracking device to record their eye movements while they performed a medication administration process, with some trials containing an embedded patient identification error. The three experiments included:

Nurses administering medications in a simulated setting
Nurses using barcoding technology to administer medication in a simulated setting
Nurses using barcoding technology to administer medication in a real clinical setting

I focused on four types of visual scanning patterns when analyzing the eye tracking data: 1) nurses’ eye fixation distributions, 2) nurses’ maximum consecutive eye fixations, 3) nurses’ eye gaze transition ratios, and 4) nurses’ two gaze scanpaths. By using the aforementioned methods, I was able to distinguish visual scanning patterns between groups of nurses who identified and did not identify a patient identity error, assessed how barcode technology influenced nurses’ visual scanning patterns, and assessed how nurses’ visual scanning patterns differed in simulated and real clinical environments. These findings may have implications for the design of medication administration protocols, nurse training, and technology design.

The Effect of External Distractions on Novice and Experienced Drivers' Anticipation of Hazards and Vehicle Control

Divekar, Gautam — Wed, 24 Aug 2011 09:54:17 PDT

Out-of-vehicle distractions were identified as contributing factors to about 29.4 % of all crashes that were reported between the years 1995 to 1999 (Stutts J. K., 2005; Stutts J. R., 2001).These crash statistics are from a decade ago. With the increase of cars, pedestrians, shops,vendors, billboards and signs over the last decade it can be safely assumed that the driving environment is more complex now and has greater potential for external driver distraction. Given this, it is important to know the effects of out-of-vehicle distraction on drivers’ ability to drive safely in their presence. With this in mind, a driving simulator study was conducted that compared younger novice and older experienced drivers on their ability to maintain their attention on the forward roadway, anticipate potential hazards and maintain vehicle control while performing an out-of-vehicle tasks. The results of the experiment indicate that both age groups took equally long glances away from the forward roadway at the out-of-vehicle task and that these long glances away from the forward roadway had a negative effects on the hazard anticipation performance of both age groups. In addition, these long glances away from the forward roadway did have a significantly negative impact on the lane maintainence ability of younger drivers as compared to their experienced counterparts but these long glances away from the forward roadway did not seem to affect the speed maintainence abilities of either group. No matter what the vehicle measures indicate, it is clear that both age groups are at elevated risk of crashing when they are attending to tasks that are outside the vehicle.

Electric Power Market Modeling with Multi-Agent Reinforcement Learning

Miksis, Nathanael K. — Fri, 05 Nov 2010 09:15:15 PDT

Agent-based modeling (ABM) is a relatively new tool for use in electric power market research. At heart are software agents representing real-world stakeholders in the industry: utilities, power producers, system operators, and regulators. Agents interact in an environment modeled after the real-world market and underlying physical infrastructure of modern power systems. Robust simulation laboratories will allow interested parties to stress test regulatory changes with agents motivated and able to exploit any weaknesses, before making these changes in the real world. Eventually ABM may help develop better understandings of electric market economic dynamics, clarifying both delineations and practical implications of market power.

The research presented here builds upon work done in collateral fields of machine learning and computational economics, as well as academic and industry literature on electric power systems. We build a simplified transmission model with agents having learning capabilities, in order to explore agent performance under several plausible scenarios. The model omits significant features of modern electric power markets, but is able to demonstrate successful convergence to stable profit-maximizing equilibria of adaptive agents competing in a quantity-based, available capacity model.