Collaboration, Interruptions, and Changeover Times: Workflow Model and Empirical Study of Hospitalist Charting

2020 ◽  
Vol 22 (4) ◽  
pp. 754-774 ◽  
Author(s):  
Itai Gurvich ◽  
Kevin J. O’Leary ◽  
Lu Wang ◽  
Jan A. Van Mieghem
Keyword(s):  
Task Switching ◽  
Processing Time ◽  
Hospital Medicine ◽  
Problem Definition ◽  
Workflow Model ◽  
Total Processing Time ◽  
Data Set ◽  
Changeover Times ◽  
Managerial Implications ◽  
The Empirical Analysis

Problem definition: Collaboration is important in services but may lead to interruptions. Professionals exercise discretion on when to preempt individual tasks to switch to collaborative tasks. Academic/practical relevance: Discretionary task switching can introduce changeover times when resuming the preempted task and, thus, can increase total processing time. Methodology: We analyze and quantify how collaboration, through interruptions and discretionary changeovers, affects total processing time. We introduce an episodal workflow model that captures the interruption and discretionary changeover dynamics—each switch and the episode of work it preempts—present in settings in which collaboration and multitasking is paramount. A simulation study provides evidence that changeover times are properly identified and estimated without bias. We then deploy the model in a field study of hospital medicine physicians: “hospitalists.” The hospitalist workflow includes visiting patients, consulting with other caregivers to guide patient diagnosis and treatment, and documenting in the patient’s medical chart. The empirical analysis uses a data set assembled from direct observation of hospitalist activity and pager-log data. Results: We estimate that a hospitalist incurs a total changeover time during documentation of five minutes per patient per day. Managerial implications: This estimate represents a significant 20% of the total processing time per patient: caring for 14 patients per day, our model estimates that a hospitalist spends more than one hour each day on changeovers. This provides evidence that task switching can causally lead to longer documentation time.

Incentivized Actions in Freemium Games

2020 ◽  
Author(s):  
Lifei Sheng ◽  
Christopher Thomas Ryan ◽  
Mahesh Nagarajan ◽  
Yuan Cheng ◽  
Chunyang Tong
Keyword(s):  
Operations Management ◽  
Sufficient Conditions ◽  
Problem Definition ◽  
Data Set ◽  
New Class ◽  
Recent Innovation ◽  
Markov Decision ◽  
Managerial Implications ◽  
Operational Issues ◽  
Data Driven Decisions

Problem definition: Games are the fastest-growing sector of the entertainment industry. Freemium games are the fastest-growing segment within games. The concept behind freemium is to attract large pools of players, many of whom will never spend money on the game. When game publishers cannot earn directly from the pockets of consumers, they employ other revenue-generating content, such as advertising. Players can become irritated by revenue-generating content. A recent innovation is to offer incentives for players to interact with such content, such as clicking an ad or watching a video. These are termed incentivized (incented) actions. We study the optimal deployment of incented actions. Academic/practical relevance: Removing or adding incented actions can essentially be done in real-time. Accordingly, the deployment of incented actions is a tactical, operational question for game designers. Methodology: We model the deployment problem as a Markov decision process (MDP). We study the performance of simple policies, as well as the structure of optimal policies. We use a proprietary data set to calibrate our MDP and derive insights. Results: Cannibalization—the degree to which incented actions distract players from making in-app purchases—is the key parameter for determining how to deploy incented actions. If cannibalization is sufficiently high, it is never optimal to offer incented actions. If cannibalization is sufficiently low, it is always optimal to offer. We find sufficient conditions for the optimality of threshold strategies that offer incented actions to low-engagement users and later remove them once a player is sufficiently engaged. Managerial implications: This research introduces operations management academics to a new class of operational issues in the games industry. Managers in the games industry can gain insights into when incentivized actions can be more or less effective. Game designers can use our MDP model to make data-driven decisions for deploying incented actions.

Beyond Related Experience: Upstream vs. Downstream Experience in Innovation Contest Platforms with Interdependent Problem Domains

2020 ◽  
Vol 22 (5) ◽  
pp. 1045-1065 ◽  
Author(s):  
Nirup Menon ◽  
Anant Mishra ◽  
Shun Ye
Keyword(s):  
Problem Solving ◽  
Software Development ◽  
Problem Definition ◽  
Problem Domain ◽  
Data Set ◽  
Job Rotation ◽  
Managerial Implications ◽  
Significant Performance ◽  
Innovation Contest ◽  
Output Information

Problem definition: Innovation contest platforms are often organized around specific fields and host contests that span a variety of interdependent problem domains. Whereas contestants may benefit from related experience in contests whose problem domains share an interdependency with the focal problem domain, it is unclear whether the benefits of related experience arise symmetrically from upstream experience (i.e., experience in problem domains that provide input information to the focal problem domain) and downstream experience (i.e., experience in problem domains that use output information from the focal problem domain) or differ among them. Academic/practical relevance: Given that innovation contest platforms serve to effectively match contest problem requirements with contestants’ skills, it is important to understand how a contestant’s prior experience on a platform contributes to her problem-solving performance. Our research provides a more granular examination of the benefits of related experience than what has been examined in prior studies on individual learning or innovation contests. Methodology: We collected detailed archival data from TopCoder, a leading innovation contest platform that hosts contests across multiple interdependent software development problem domains, from its launch in 2001 to September 2013. Our data set comprises detailed participation histories of 821 contestants in 3,274 contests across eight interdependent problem domains involving 8,985 observations. Results: Whereas a contestant’s related experience on the innovation contest platform is more positively associated with her focal contest performance compared with unrelated experience, the benefits of related experience arise only from downstream experience. That is, there are no significant performance benefits of upstream experience. Furthermore, the performance benefits of downstream experience are greater when the contest duration is shorter, highlighting its role in enabling more efficient search and problem solving in innovation contest platforms with interdependent problem domains. Managerial implications: Contrary to the notion of “hyperspecialization,” our findings suggest that contestants can reap benefits from diversifying their experience into downstream problem domains on innovation contest platforms. Furthermore, innovation contest platforms could facilitate such targeted diversification of contestant experience by developing more granular metrics of contestant experience across problem domains. Our findings also have implications for resource allocation and job rotation decisions in software development projects within firms.

The Effects of Multisiting on Productivity and Quality

2020 ◽  
Author(s):  
Diwas KC ◽  
Sokol Tushe
Keyword(s):  
Operations Management ◽  
Low Complexity ◽  
Cognitive Effort ◽  
Problem Definition ◽  
Negative Effects ◽  
Data Set ◽  
Managerial Implications ◽  
Potential Benefits ◽  
Frequent Site

Problem definition: In the modern workplace, it is increasingly common for workers to concurrently attend to tasks across multiple physical locations. However, frequent site switching can lead to increased setup and overhead costs. Specifically, workers expend significant time and cognitive effort getting reoriented with personnel, operating processes, tools, and resources whenever they switch sites. In this paper, we look at the productivity and quality implications of multisite work. Academic/practical relevance: Although multisite workplace deployment is increasingly common, its impact on people operations has not been examined in the operations management literature. We contribute to the literature by studying the effect of multisiting on individual worker productivity and quality of output. Methodology: To estimate the effect of multisite operations on performance, we turn to a setting where multisite worker assignment is common—that of physicians who have admitting privileges at multiple hospitals. We collected detailed data on individual physicians practicing in 83 hospitals between 1999 and 2010. Our extensive data set includes detailed operational and clinical factors associated with more than 950,000 patient encounters. Our empirical analysis takes the form of a panel, where we follow a given physician over time and link short-term multisiting to patient-level outcomes. Results: We find that multisiting negatively impacts productivity. Specifically, for each additional site at which a physician works, we observe a 2% increase in patient length of stay. For each site served, the likelihood of a patient developing a complication increases by 3%. Greater travel distance between sites and lack of focus at a given site explain the performance declines due to multisiting. In addition, we find that the performance declines resulting from multisite operation are reduced among low-complexity patients and among highly experienced physicians. Managerial implications: Multisite performance losses need to be traded off against the potential benefits. The negative effects of multisiting can be mitigated by limiting multisite deployment to simpler tasks and among highly experienced physicians. Managers can decrease switching costs of multisite work by standardizing workflows, processes, and tools across sites. In addition, the practice of multisite work can be limited to sites that are physically proximate to avoid the overhead costs associated with excessive travel.

Does Online Training Work in Retail?

2020 ◽  
Author(s):  
Marshall Fisher ◽  
Santiago Gallino ◽  
Serguei Netessine
Keyword(s):  
Causal Effect ◽  
Indirect Costs ◽  
Online Training ◽  
Problem Definition ◽  
Product Knowledge ◽  
Data Set ◽  
Sales Training ◽  
Training Methodology ◽  
Managerial Implications ◽  
The One

Problem definition: How much, if at all, does training in product features increase a sales associate’s sales productivity? Academic/practical relevance: A knowledgeable retail sales associate (SA) can explain the features of available product variants and give a customer sufficient confidence in the customer’s choice or suggest alternatives so that the customer becomes willing to purchase. Although it is plausible that increasing an SA’s product knowledge will increase sales, training is not without cost and turnover is high in retail, so most retailers provide little product-knowledge training. Methodology: We partner with two firms and collect data on more than 50,000 SAs who had access to training. We assemble a detailed data set of the training history and individual sales productivity over a two-year period. We conduct econometric analysis to quantify the causal effect of training on sales. Results: For SAs who engaged in training, the sales rate increases by 1.8% for every online module taken, which is a much higher benefit than the direct or indirect costs associated with this training. Brand-specific training has a larger effect on the focal brand; however, there is a positive effect on other brands the SA sells. We also assess how the training benefit varies depending on the SA’s tenure, sales rate prior to training, and number of modules taken. Managerial implications: We present evidence of a novel training mechanism that can be extremely attractive to retailers. Online training tools, such as the one we study, have two characteristics that should not be overlooked. First, it is the brands, not the retailers, that create, develop, and pay for the training content. Second, the incentives are such that SAs invest their own time, rather than time on the job, to train, and this makes the retailer’s investment in the training a profitable proposition.

Cell Block Optimization: A Comparative Study of Quality Variables in 4 Different Cell Block Methods

2021 ◽  
pp. 1-7
Author(s):  
Marsali Newman ◽  
Matthew Walsh ◽  
Rosemary Jeffrey ◽  
Richard Hiscock
Keyword(s):  
Comparative Study ◽  
Processing Time ◽  
Morphological Features ◽  
Cell Block ◽  
Total Processing Time ◽  
Block Methods ◽  
Molecular Studies ◽  
Agar Method ◽  
Md Anderson ◽  
Ancillary Studies

<b><i>Objective:</i></b> The cell block (CB) is an important adjunct to cytological preparations in diagnostic cytopathology. Optimizing cellular material in the CB is essential to the success of ancillary studies such as immunohistochemistry (IHC) and molecular studies (MS). Our aim was to identify which CB method was most suitable in a variety of specimen types and levels of cellularity. <b><i>Study Design:</i></b> We assessed 4 different CB methods, thrombin clot method (TCM), MD Anderson method (MDAM), gelatin foam method (GFM), and agar method (AM), with descriptive observations and ranking of the methods based on quantity of cells and morphological features. <b><i>Results:</i></b> TCM performed best in ranking for both quantity of cells and morphological features, followed by MDAM, GFM, and AM. Lack of adjuvant in the MDAM resulted in some unique morphological advantages which, however, also resulted in inconsistent performance. In low cellularity cases insufficient cells were frequently identified on slides from MDAM and AM CBs. Technique touch time was similar for all methods, with total processing time being shortest for TCM followed by MDAM, GFM, and AM. <b><i>Conclusions:</i></b> TCM was the most robust CB technique, retaining high scores for ranking of quantity and morphology in a variety of specimen cellularities and specimen types.

scholarly journals Designing optimizing procedures for task switching to ensure efficiency in the hospital laboratory

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Young-Jin Kim ◽  
Garam Kim ◽  
Sangil Kim ◽  
Dawoon Jung ◽  
Minwoo Park
Keyword(s):  
Task Switching ◽  
Compliance Rate ◽  
Turnaround Time ◽  
Optimal Time ◽  
Work Efficiency ◽  
Work Quality ◽  
Time Optimization ◽  
Sample Classification ◽  
Multiple Tasks ◽  
Changeover Times

AbstractThis study aims to improve the efficiency of task switching in hospital laboratories. In a laboratory, several medical technicians perform multiple tasks. Technicians are not aware of the marginal amount of time it takes to switch between tasks, and this accumulation of lost minutes can cause the technician to worry more about the remaining working time than work quality. They rush through their remaining tasks, thereby rendering their work less efficient. For time optimization, we identified work changeover times to help maintain the work quality in the laboratory while reducing the number of task switching instances. We used the turnaround time (TAT) compliance rate of emergency room samples as an indicator to evaluate laboratory performance and the number of task switching instances as an index of the task performer perspective (TPP). We experimented with a monitoring system that populates the time for sample classification according to the optimal time for task switching. Through the proposed methodology, we successfully reduced not only the instances of task switching by 10% but also the TAT non-compliance rate from 4.97 to 2.66%. Consequently, the introduction of new methodology has greatly increased work efficiency.

Partial Completion as a Nonprofit Strategy

2021 ◽  
Author(s):  
Can Zhang ◽  
Atalay Atasu ◽  
Karthik Ramachandran
Keyword(s):  
Nonprofit Organizations ◽  
Service Provision ◽  
Problem Definition ◽  
Product Service ◽  
Service Portfolio ◽  
Wide Range ◽  
Partial Completion ◽  
Innovative Solution ◽  
Managerial Implications ◽  
Level 3

Problem definition: Faced with the challenge of serving beneficiaries with heterogeneous needs and under budget constraints, some nonprofit organizations (NPOs) have adopted an innovative solution: providing partially complete products or services to beneficiaries. We seek to understand what drives an NPO’s choice of partial completion as a design strategy and how it interacts with the level of variety offered in the NPO’s product or service portfolio. Academic/practical relevance: Although partial product or service provision has been observed in the nonprofit operations, there is limited understanding of when it is an appropriate strategy—a void that we seek to fill in this paper. Methodology: We synthesize the practices of two NPOs operating in different contexts to develop a stylized analytical model to study an NPO’s product/service completion and variety choices. Results: We identify when and to what extent partial completion is optimal for an NPO. We also characterize a budget allocation structure for an NPO between product/service variety and completion. Our analysis sheds light on how beneficiary characteristics (e.g., heterogeneity of their needs, capability to self-complete) and NPO objectives (e.g., total-benefit maximization versus fairness) affect the optimal levels of variety and completion. Managerial implications: We provide three key observations. (1) Partial completion is not a compromise solution to budget limitations but can be an optimal strategy for NPOs under a wide range of circumstances, even in the presence of ample resources. (2) Partial provision is particularly valuable when beneficiary needs are highly heterogeneous, or beneficiaries have high self-completion capabilities. A higher self-completion capability generally implies a lower optimal completion level; however, it may lead to either a higher or a lower optimal variety level. (3) Although providing incomplete products may appear to burden beneficiaries, a lower completion level can be optimal when fairness is factored into an NPO’s objective or when beneficiary capabilities are more heterogeneous.

The Effects of Patent Extension and Take-Back Regulation on Green Pharmacy

2021 ◽  
Author(s):  
Tianqin Shi ◽  
Nicholas C. Petruzzi ◽  
Dilip Chhajed
Keyword(s):  
Pharmaceutical Industry ◽  
Social Welfare ◽  
Technical Information ◽  
Problem Definition ◽  
Theoretic Model ◽  
Innovative Company ◽  
Take Back ◽  
Starting Point ◽  
European Environmental Agency ◽  
Managerial Implications

Problem definition: The eco-toxicity arising from unused pharmaceuticals has regulators advocating the benign design concept of “green pharmacy,” but high research and development expenses can be prohibitive. We therefore examine the impacts of two regulatory mechanisms, patent extension and take-back regulation, on inducing drug manufacturers to go green. Academic/practical relevance: One incentive suggested by the European Environmental Agency is a patent extension for a company that redesigns its already patented pharmaceutical to be more environmentally friendly. This incentive can encourage both the development of degradable drugs and the disclosure of technical information. Yet, it is unclear how effective the extension would be in inducing green pharmacy and in maximizing social welfare. Methodology: We develop a game-theoretic model in which an innovative company collects monopoly profits for a patented pharmaceutical but faces competition from a generic rival after the patent expires. A social-welfare-maximizing regulator is the Stackelberg leader. The regulator leads by offering a patent extension to the innovative company while also imposing take-back regulation on the pharmaceutical industry. Then the two-profit maximizing companies respond by setting drug prices and choosing whether to invest in green pharmacy. Results: The regulator’s optimal patent extension offer can induce green pharmacy but only if the offer exceeds a threshold length that depends on the degree of product differentiation present in the pharmaceutical industry. The regulator’s correspondingly optimal take-back regulation generally prescribes a required collection rate that decreases as its optimal patent extension offer increases, and vice versa. Managerial implications: By isolating green pharmacy as a potential target to address pharmaceutical eco-toxicity at its source, the regulatory policy that we consider, which combines the incentive inherent in earning a patent extension on the one hand with the penalty inherent in complying with take-back regulation on the other hand, serves as a useful starting point for policymakers to optimally balance economic welfare considerations with environmental stewardship considerations.

An Empirical Bargaining Model with Left-Digit Bias: A Study on Auto Loan Monthly Payments

2021 ◽  
Author(s):  
Zhenling Jiang
Keyword(s):  
Interest Rate ◽  
Interest Rates ◽  
Large Data ◽  
The United States ◽  
Nash Bargaining ◽  
Bargaining Model ◽  
Data Set ◽  
Proposed Model ◽  
Lower Interest Rate ◽  
The Empirical Analysis

This paper studies price bargaining when both parties have left-digit bias when processing numbers. The empirical analysis focuses on the auto finance market in the United States, using a large data set of 35 million auto loans. Incorporating left-digit bias in bargaining is motivated by several intriguing observations. The scheduled monthly payments of auto loans bunch at both $9- and $0-ending digits, especially over $100 marks. In addition, $9-ending loans carry a higher interest rate, and $0-ending loans have a lower interest rate. We develop a Nash bargaining model that allows for left-digit bias from both consumers and finance managers of auto dealers. Results suggest that both parties are subject to this basic human bias: the perceived difference between $9- and the next $0-ending payments is larger than $1, especially between $99- and $00-ending payments. The proposed model can explain the phenomena of payments bunching and differential interest rates for loans with different ending digits. We use counterfactuals to show a nuanced impact of left-digit bias, which can both increase and decrease the payments. Overall, bias from both sides leads to a $33 increase in average payment per loan compared with a benchmark case with no bias. This paper was accepted by Matthew Shum, marketing.

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