{"title":"Applications of medical information: Using an enhanced likelihood measured approach based on intuitionistic fuzzy sets","authors":"Kuo-Chen Hung","doi":"10.1080/19488300.2012.713443","DOIUrl":"https://doi.org/10.1080/19488300.2012.713443","url":null,"abstract":"Similarity measure is a key role in the analysis and research of medical diagnosis, pattern recognition, machine learning and clustering analysis in uncertainty environment. In this paper, we take a simple and intelligent approach, called intuitionistic fuzzy likelihood-based Measurement (IFLM), towards the medical diagnosis and bacteria classification problems. The proposed approach considers the information carried by the membership degree and the non-membership degree of intuitionistic fuzzy sets (IFSs) to examine its capability in encountering uncertainty in the medical pattern recognition. The observation from the results shows the usefulness of the proposed IFLM approach, it can provide the preliminary diagnosis for the doctors.","PeriodicalId":89563,"journal":{"name":"IIE transactions on healthcare systems engineering","volume":"2 1","pages":"224 - 231"},"PeriodicalIF":0.0,"publicationDate":"2012-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/19488300.2012.713443","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"60562269","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"From group work to teamwork: A case study of “Lean” rapid process improvement in the ThedaCare Information Technology Department","authors":"R. Holden, Greg Hackbart","doi":"10.1080/19488300.2012.709584","DOIUrl":"https://doi.org/10.1080/19488300.2012.709584","url":null,"abstract":"This paper presents a mixed-methods case study of process improvement at the information technology (IT) Department of ThedaCare, a Northeast Wisconsin community health system. As part of its broader goal to improve care, ThedaCare launched a “Lean” improvement project directed at IT support or “fix work” services. IT Department staff, IT support service customers, and a Lean facilitator participated in a weeklong rapid improvement event. Participants identified opportunities for process improvement, collected baseline measures on how (and how well) the IT Department was providing support services, and jointly developed a preliminary solution centered on a new team-based organization of support services. Rather than forwarding service requests to groups of support staff organized by IT application type, service requests would now be resolved on-the-spot by a team with distributed knowledge of multiple applications. Six and twelve months post-intervention, there was some evidence of success, including performance improvement and staff buy-in. We use realistic evaluation as an organizing framework to describe potential links between the intervention content and process, the surrounding context, and the outcomes of the intervention. We hypothesize four mechanisms that mediate this link: work standardization; connections between people; seamless flow; and participatory problem solving. We conclude that other organizations can learn as much from ThedaCare's participatory rapid improvement process and Lean approach to transformational change as from the actual implemented changes. Supplemental materials are available for this article. Go to the publisher's online edition of IIE Transactions on Healthcare Systems Engineering to view the free supplemental file.","PeriodicalId":89563,"journal":{"name":"IIE transactions on healthcare systems engineering","volume":"2 1","pages":"190 - 201"},"PeriodicalIF":0.0,"publicationDate":"2012-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/19488300.2012.709584","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"60561934","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"An optimization approach for dispatching and relocating EMS vehicles","authors":"Farshad Majzoubi, Lihui Bai, S. Heragu","doi":"10.1080/19488300.2012.710297","DOIUrl":"https://doi.org/10.1080/19488300.2012.710297","url":null,"abstract":"We consider the problem of dispatching and relocating EMS vehicles during a medical emergency such as a influenza outbreak when the demand for EMS vehicles increases. In order to better utilize EMS vehicles’ capacity and based on our discussions with EMS personnel, we assume that ambulances can serve more than patient where appropriate. Specifically, a vehicle transporting a high-priority patient cannot serve another patient until service to the high-priority has been completed. However, a vehicle transporting a low-priority patient can be rerouted to pick up one more patient. The objective is to minimize the total travel costs, the penalty of not meeting response time window for patients, and the penalty of not covering census tracts. Integer linear and nonlinear program models and an approximation model are proposed. Numerical examples show that the proposed solution algorithm implemented with general-purpose solvers is efficient for solving large size problems, and thus is suitable for use in a real time decision support system.","PeriodicalId":89563,"journal":{"name":"IIE transactions on healthcare systems engineering","volume":"2 1","pages":"211 - 223"},"PeriodicalIF":0.0,"publicationDate":"2012-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/19488300.2012.710297","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"60562331","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
A. Rivera-Rodriguez, Hélène Faye, B. Karsh, P. Carayon, C. Baker, M. Scanlon
{"title":"A survey study of nursing contributions to medication management with special attention to health information technology","authors":"A. Rivera-Rodriguez, Hélène Faye, B. Karsh, P. Carayon, C. Baker, M. Scanlon","doi":"10.1080/19488300.2012.710296","DOIUrl":"https://doi.org/10.1080/19488300.2012.710296","url":null,"abstract":"Little detail is known about the types of activities intensive care unit (ICU) nurses perform to support medication management in ICUs in order to contribute to patient safety and quality of care. To understand nurses’ perceptions of the frequency and importance of medication management activities, including those related to using health information technologies (IT). A survey was developed, pilot tested, and administered to ICU nurses in two hospitals. Nurses perceived that they dealt with health IT problems infrequently and that those problems were only moderately important to patient care. Nurses perceived that they engaged in complex cognitive activities frequently and that those were highly important to patient care. Despite considerable focus on health IT problems in extant literature, this study found that nurses do not perceive these problems as frequent or very important. Instead, this study highlights the important role of complex cognitive activities for high quality nursing care, which is a departure from the simplistic notion that nurses only engage in prescribed nursing tasks. Importantly, the survey can be used to identify activities that are value and non-value added, which may lead to better tailored interventions to support nursing work.","PeriodicalId":89563,"journal":{"name":"IIE transactions on healthcare systems engineering","volume":"32 6 1","pages":"202 - 210"},"PeriodicalIF":0.0,"publicationDate":"2012-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/19488300.2012.710296","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"60561790","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"A simulation-based study of distribution strategies for pharmaceutical supply chains","authors":"L. Niziolek, T. Chiam, Yuehwern Yih","doi":"10.1080/19488300.2012.709583","DOIUrl":"https://doi.org/10.1080/19488300.2012.709583","url":null,"abstract":"This paper studies the impact of direct-ship distribution strategies in pharmaceutical supply chains. The typical supply chain for branded prescription pharmaceuticals consists of manufacturers, wholesalers, and pharmacies. A direct-ship strategy, also known as disintermediation, entails shipping directly to customers and is under consideration in the pharmaceutical industry. A direct-ship strategy can encompass partial or complete disintermediation of wholesalers, both of which have been successful in other industries. The goal of this work is to determine the impact of different delivery frequencies and degrees of disintermediation on pharmaceutical supply chains. Four direct-ship models with varying levels of disintermediation are compared. The operating policy under consideration is the frequency of deliveries to direct-ship customers. A simulation model is constructed to represent a pharmaceutical supply chain and distribution data is collected from an industry collaborator. The results show that a significantly lower total cost can be achieved with a hybrid strategy that sends 55% of volume directly to customers that operate their own distribution centers and customers that meet minimum order quantity requirements. Impact of delivery frequencies on transportation and inventory costs is also studied. Sensitivity analysis of the transportation: inventory cost ratio and truck utilization is performed to determine whether and when the best direct-ship distribution strategy should be changed.","PeriodicalId":89563,"journal":{"name":"IIE transactions on healthcare systems engineering","volume":"2 1","pages":"181 - 189"},"PeriodicalIF":0.0,"publicationDate":"2012-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/19488300.2012.709583","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"60562189","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Cost-effectiveness analysis in health policy decision making: Direct methods for progressive multi-state processes","authors":"M. DeFauw, V. Nair, Yang Yang","doi":"10.1080/19488300.2012.680004","DOIUrl":"https://doi.org/10.1080/19488300.2012.680004","url":null,"abstract":"Discrete-event simulation (DES) techniques are commonly used for cost-effectiveness analysis (CEA) in health policy decision making. This paper develops direct approaches for conducting CEA under a progressive multi-state framework, with a focus on semi-Markov processes. Analytical expressions are developed for the stationary case, and sensitivity analysis is considered. The advantages of these direct methods over DES are discussed, with most benefit in the case of time-stationary models, and only limited benefits in non-stationary situations. The method is demonstrated on illustrative applications.","PeriodicalId":89563,"journal":{"name":"IIE transactions on healthcare systems engineering","volume":"2 1","pages":"112 - 130"},"PeriodicalIF":0.0,"publicationDate":"2012-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/19488300.2012.680004","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"60561537","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"An analysis of sequencing surgeries with durations that follow the lognormal, gamma, or normal distribution","authors":"Sang-Kyu Choi, W. Wilhelm","doi":"10.1080/19488300.2012.684272","DOIUrl":"https://doi.org/10.1080/19488300.2012.684272","url":null,"abstract":"The smallest-variance-first-rule (SV) is generally accepted as the optimal policy for sequencing two surgeries, although it has been proven formally only for several restricted cases. We extend prior work, studying three distributions as models of surgery duration (the lognormal, gamma, and normal) and including overtime in a total-cost objective function comprising surgeon-and patient-waiting-, operating-room-idle-, and staff overtimes. We specify expected waiting and idle time as functions of the parameters of surgery duration to identify the best rule to sequence two surgeries. We compare the relative values of expected waiting and idle times numerically with that of expected overtime. Results recommend that the SV rule be used to minimize total expected cost of waiting, idle and overtime. We find that gamma and normal distributions with the same mean and variance as the lognormal give nearly the same expected waiting and idle times, observing that the lognormal in combination with either the gamma or normal gives a similar result. We extend to the three-surgery case, showing that sequencing the first surgery is most important. We demonstrate how our results can be applied by using them as a basis for a heuristic that assigns surgeries to multiple operating rooms and then sequences them.","PeriodicalId":89563,"journal":{"name":"IIE transactions on healthcare systems engineering","volume":"2 1","pages":"156 - 171"},"PeriodicalIF":0.0,"publicationDate":"2012-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/19488300.2012.684272","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"60561924","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
David Claudio, Luciano Ricondo, A. Freivalds, G. O. Okudan Kremer
{"title":"Physiological and descriptive variables as predictors for the Emergency Severity Index","authors":"David Claudio, Luciano Ricondo, A. Freivalds, G. O. Okudan Kremer","doi":"10.1080/19488300.2012.680572","DOIUrl":"https://doi.org/10.1080/19488300.2012.680572","url":null,"abstract":"Many hospital emergency departments (EDs) in the United States have implemented the use of the five-level Emergency Severity Index (ESI) as their clinical decision support method to enhance clinical decision making in the triage process. The ESI designates the most acutely ill patients as level 1 or 2 and those who do not meet these criteria are assigned to levels 3–5 based on estimated resource utilization. Although the number of resources is the primary decision rule to determine levels 3–5, physiological and descriptive variables can also be used to predict the ESI level. This study uses several physiological and descriptive variables as predictors to determine the ESI value. The physiological variables include heart rate, blood pressure, temperature, respiration rate, and oxygen level, whereas the descriptive variables include age, gender, pain level, and patient complaint. An ordered probit model was developed for ESI prediction. In addition, a linear regression model was also developed to demonstrate the necessity of having a decision making tool that allows for non-integer values. The results of this research can be used to enhance the precision of the ESI and the nurse's ability to prioritize treatment based on triage acuity. The decision making tool can also be used to stratify patients who are classified in the same priority group and may eliminate the necessity of grouping patients into different categories.","PeriodicalId":89563,"journal":{"name":"IIE transactions on healthcare systems engineering","volume":"2 1","pages":"131 - 141"},"PeriodicalIF":0.0,"publicationDate":"2012-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/19488300.2012.680572","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"60561706","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Michelle M. Alvarado, Lewis Ntaimo, A. Banerjee, Kiavash Kianfar
{"title":"Reducing pediatric medication errors: A survey and taxonomy","authors":"Michelle M. Alvarado, Lewis Ntaimo, A. Banerjee, Kiavash Kianfar","doi":"10.1080/19488300.2012.680799","DOIUrl":"https://doi.org/10.1080/19488300.2012.680799","url":null,"abstract":"According to a 1999 report by the Institute of Medicine an estimated 44,000 to 98,000 people die annually due to medication errors (MEs) in health care. Medication errors can occur at any point in the continuum of care and the literature suggests that MEs are common in our hospitals today, especially in the complex setting of pediatric medicine. This paper is a survey of reported research over the last decade on MEs in pediatrics and their prevention and reduction strategies. It is difficult to know the prevalence of pediatric MEs due to the lack of consistency in error definitions in past studies. Unlike previous surveys on this topic, this paper reviews several studies and provides a taxonomy chart listing the most common pediatric MEs, as well as contributing factors, severity, and possible prevention strategies. The objective is to provide interested researchers in this field with a resource that aggregates and compares related studies on MEs in pediatrics, and provides a comprehensive taxonomy of errors. Challenges and prevention strategies towards reducing pediatric MEs are also discussed.","PeriodicalId":89563,"journal":{"name":"IIE transactions on healthcare systems engineering","volume":"2 1","pages":"142 - 155"},"PeriodicalIF":0.0,"publicationDate":"2012-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/19488300.2012.680799","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"60561809","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
S. Levin, L. Sauer, G. Kelen, T. Kirsch, J. Pham, Samit Desai, D. France
{"title":"Situation awareness in emergency medicine","authors":"S. Levin, L. Sauer, G. Kelen, T. Kirsch, J. Pham, Samit Desai, D. France","doi":"10.1080/19488300.2012.684739","DOIUrl":"https://doi.org/10.1080/19488300.2012.684739","url":null,"abstract":"The objective of this study is to determine the effects of environmental factors on physician situation awareness (SA) in an emergency department (ED) setting. An objective method of level 1 (i.e., perception) SA measurement and evaluation was developed and applied. Resident physician level 1 SA was measured using the Situational Awareness Global Assessment Technique (SAGAT). SAGAT question probes (i.e., sets of 10 questions) were generated randomly from a pool of questions and administered hourly. Questions were answered at a 7.4% false response rate. Environmental measures (i.e., patient information, physician information, temporal information, and workload) were collected concurrently. Mixed-effects modeling was used to determine the relationship between physician SA and environmental factors adjusting for potential correlation within physician observed, patients managed, and questions asked. Significant factors associated with decreases in SA include: patient hand-offs (Odds Ratio (OR): 1.67), resident physician in final year of training (OR: 0.49), and number of patients managed (OR: 1.17). Significant correlation within question was observed and adjusted for. Overall, this study demonstrates a novel approach toward diagnosing factors contributing to physician SA during patient care. SA studies in healthcare may provide evidence for interventions aimed at improving healthcare work environments and patient safety.","PeriodicalId":89563,"journal":{"name":"IIE transactions on healthcare systems engineering","volume":"2 1","pages":"172 - 180"},"PeriodicalIF":0.0,"publicationDate":"2012-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/19488300.2012.684739","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"60562019","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}