M. Eric Johnson

Information security and privacy in healthcare: current state of research

Information security and privacy in the healthcare sector is an issue of growing importance. The adoption of digital patient records, increased regulation, provider consolidation and the increasing need for information exchange between patients, providers and payers, all point towards the need for better information security. We critically survey the literature on information security and privacy in healthcare, published in information systems journals as well as many other related disciplines including health informatics, public health, law, medicine, the trade press and industry reports. In this paper, we provide a holistic view of the recent research and suggest new areas of interest to the information systems community.

Postponement Strategies for Channel Derivatives

The value of postponing product differentiation until final distribution for manufacturers who market a family of product derivatives through multiple channels is examined. A model is developed of a supply chain that distributes many short‐lived products through different channels. Using the model, we find the postponement is particularly valuable for managing short‐life products. Postponement increases distribution service levels while reducing costs and order fulfillment risk. Postponement is particularly valuable when there are many derivative products and forecast error is high. Trade‐off curves are presented, that allow managers to evaluate the benefits of investing in postponement strategies.

Data Hemorrhages in the Health-Care Sector

Confidential data hemorrhaging from health-care providers pose financial risks to firms and medical risks to patients. We examine the consequences of data hemorrhages including privacy violations, medical fraud, financial identity theft, and medical identity theft. We also examine the types and sources of data hemorrhages, focusing on inadvertent disclosures. Through an analysis of leaked files, we examine data hemorrhages stemming from inadvertent disclosures on internet-based file sharing networks. We characterize the security risk for a group of health-care organizations using a direct analysis of leaked files. These files contained highly sensitive medical and personal information that could be maliciously exploited by criminals seeking to commit medical and financial identity theft. We also present evidence of the threat by examining user-issued searches. Our analysis demonstrates both the substantial threat and vulnerability for the health-care sector and the unique complexity exhibited by the US health-care system.

Expressions for item fill rates in periodic inventory systems

We examine the problem of estimating the item fill rate in a periodic inventory system. We show that the traditional expressions for line item fill rate, found in many operations management textbooks, perform well for high fill rates (above 90%), but they consistently underestimate the true fill rate. The problem of underestimation becomes significant as the fill rate falls below 90% and is greatly amplified in cases with very low fill rates (below 50%). We review other more accurate expressions for fill rate, discussing their relative merits. We then develop an exact fill rate expression that is robust for both high and low fill rates. We compare the new expression to others found in the literature via an extensive set of simulation experiments using data that reflect actual inventory systems found at Hewlett-Packard. We also examine the robustness of the expressions to violations in the underlying assumptions. Finally, we develop an alternative fill rate expression that is robust for cases of high demand variability where product returns are allowed.

Stochastic Modeling for Automated Material Handling System Design and Control

Material handling systems (MHSs) are micro-transportation systems that share many of the same challenges in design and operation as their larger-scale transportation counterparts. However, because of the automation technology employed in material handling, such systems also present many new challenges. Over the past decade, progress in automation technology has led to the replacement of many non-automated MHSs with automated systems. Use of an automated MHS can lead to significantly lower overall material handling cost, and thus overall production cost. However, the installation cost of such a system can be significant, and an MHS that does not function properly can lead to significant losses in productivity and profits. Analysis of design and control problems for such systems must take into account the fact that MHSs typically operate in a stochastic environment, with stochastic demands for material handling, flexibility in vehicle routing, variable processing times and other random elements. This paper reviews research on design and control of automated MHSs, with emphasis on analytical models that incorporate stochastic elements. We focus on models of automated storage and retrieval systems and automated guided vehicle systems. In addition to evaluating the existing literature, we describe areas where further research is needed.

Medication administration quality and health information technology: a national study of US hospitals

OBJECTIVE To determine whether the use of computerized physician order entry (CPOE) and electronic medication administration records (eMAR) is associated with better quality of medication administration at medium-to-large acute-care hospitals. DATA/STUDY SETTING: A retrospective cross-sectional analysis of data from three sources: CPOE/eMAR usage from HIMSS Analytics (2010), medication quality scores from CMS Hospital Compare (2010), and hospital characteristics from CMS Acute Inpatient Prospective Payment System (2009). The analysis focused on 11 quality indicators (January-December 2009) at 2603 medium-to-large (≥ 100 beds), non-federal acute-care hospitals measuring proportion of eligible patients given (or prescribed) recommended medications for conditions, including acute myocardial infarction, heart failure, and pneumonia, and surgical care improvement. Using technology adoption by 2008 as reference, hospitals were coded: (1) eMAR-only adopters (n=986); (2) CPOE-only adopters (n=115); and (3) adopters of both technologies (n=804); with non-adopters of both technologies as reference group (n=698). Hospitals were also coded for duration of use in 2-year increments since technology adoption. Hospital characteristics, historical measure-specific patient volume, and propensity scores for technology adoption were used to control for confounding factors. The analysis was performed using a generalized linear model (logit link and binomial family). PRINCIPAL FINDINGS Relative to non-adopters of both eMAR and CPOE, the odds of adherence to all measures (except one) were higher by 14-29% for eMAR-only hospitals and by 13-38% for hospitals with both technologies, translating to a marginal increase of 0.4-2.0 percentage points. Further, each additional 2 years of technology use was associated with 6-15% higher odds of compliance on all medication measures for eMAR-only hospitals and users of both technologies. CONCLUSIONS Implementation and duration of use of health information technologies are associated with improved adherence to medication guidelines at US hospitals. The benefits are evident for adoption of eMAR systems alone and in combination with CPOE.

Implementing Setup Optimization on the Shop Floor

We develop a model and solution algorithm for sequencing production on a flexible assembly line. The model incorporates the practical considerations of printed circuit board PCB assembly where the goal is to reduce the time spent in setup. We discuss the practical implementation problems of integrating optimization software on the shop floor-both from an operations research and systems perspective. We describe Hewlett-Packards successful use of the software and the limitations of production sequencing in PCB assembly.

The impact of sorting strategies on automated sortation system performance

Abstract In this paper, we develop an analytical model of an order sortation system used in automated distribution centers. In such systems, groups of orders are delivered to a recirculating conveyor system where they are sorted into shipping lanes for final preparation and loaded onto waiting trucks. We develop a model of the sorting process, which incorporates the stochastic elements of these systems, to determine the relative merits of two common categories of sorting strategies found in industry: fixed priority schemes and the next available rule. Fixed priority schemes include such popular rules as “sort the largest (or smallest) orders first”. We show that in systems with little lane blocking, a rule which assigns the next available order to a shipping lane will outperform any fixed priority scheme in terms of sorting time and system throughput while in systems with significant lane blocking, the sorting rule has little impact.

Performance Analysis of Split-Case Sorting Systems

Split-case sorting systems are used in many retail supply chains where items must be distributed in less-than-case quantities, such as orders shipped directly to customers by catalogers and e-tailers or shipments made in less-than-case quantities from a distribution center to a retail store. These systems are particularly effective in order-packing systems where the same item is needed for multiple orders. Items are inducted into a circular sorting conveyor system one unit at a time and then delivered to an order-packing bin designated for a particular customer or retail store. We develop analytical performance models that incorporate the stochastic operating conditions faced by these systems. Our model allows system designers to predict the sorting capacity for different system configurations. More importantly, we use the model to develop insight into the system design and operation.

Supply Chain Management: Technology, Globalization, and Policy at a Crossroads

Supply chain management is an important application area for INFORMS, with many opportunities for our community to contribute models and insight. The seemingly relentless forces of globalization and technology continually present us with new supply chain challenges and opportunities for further progress. Over the past decade, researchers and practitioners have developed many models and methods that have influenced supply chain practices. However, as managers and management scientists have embraced these new approaches for improving supply chain competitiveness, these initiatives have slipped into the middle of many important corporate and public debates.