Journal Publications

The Center for Health Organization (CHOT) contributes to the scientific community by publishing high impact research findings in prestigious journals on a yearly basis. Listed below are the CHOT publications to date which are derived from the industry research projects. Please move through each tab and peruse our publication library to your content.

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Davis, E.C., Menser, T., Cerda Juarez, A., Tomaszewski, L.E., Kash, B.A. (2018). Examining healthcare systems: A market analysis for KenyaEuropean Journal of Training and Development,

This paper aims to present a literature review of the health workforce, hospital and clinic systems, infrastructure, primary care, regulatory climate, the pharmaceutical industry and community health behavior of the Kenyan health-care system with the purpose of providing a thorough background on the health-care environment in Kenya. An initial review of 615 Pubmed articles included 455 relevant articles. A complete review of these studies was conducted, resulting in a final sample of 389 articles. These articles were categorized into three main subject areas with 14 secondary subject areas.

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Keywords: Innovation, Kenya, Infrastructure, Healthcare systems, Health workforce, Market analysis

Davis, E., Evans, A., Uptmore, C., Lang, S., McElroy, J., Ellenburg, D., Nguyen, T., & Kash, B.A. (2018). Proposed business and franchising models for primary care in Kenya. European Journal of Training and Development, 42(1-2), 48-56.

The purpose of this paper is to present proposed solutions and interventions to some of the major barriers to providing adequate access to healthcare in Kenya. Specific business models are proposed to improve access to quality healthcare in low- and middle-income countries. Finally, strategies are developed for the retail clinic concept (RCC). After a review of current methodologies and approaches to business and franchising models in various settings, the most relevant models are proposed as solutions to improving quality healthcare in Kenya through the RCC. For example, authors reviewed physician recruitment strategies, insurance plans and community engagement. The paper is informed by existing literature and reports as well as key informants.

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Keywords: Kenya, Franchising, Patient engagement, Physician recruiting, Retail clinic, Social franchising

Davis, E., Arana, E., Creel, J., Ibarra, S., Lechuga, J., Norman, R., Parks, H., Qasim, A., Watkins, D., & Kash, B.A. (2018). The role of community engagement in building sustainable health-care delivery interventions for Kenya. European Journal of Training and Development, 42(1-2), 35-47.

The purpose of this article is to provide a general review of the health-care needs in Kenya which focuses on the role of community engagement in facilitating access and diminishing barriers to quality care services. Health-care concerns throughout Kenya and the culture of Kenyan’s health-care practices care are considered. Suggestions for community engagement, including defining the community, are proposed. A model for improved health-care delivery introduces community health workers (CHWs), mHealth technologies and the use of mobile clinics to engage the community and improve health and quality of care in low-income settings.

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Keywords: Kenya, Access, Quality of care, Community engagement, mHealth, Community health worker, Mobile clinic

Ferdinand, A.O., Cheon, O., Bako, A.T., Kash, B.A. (2018). Interventions aimed at addressing unplanned hospital readmissions in the U.S.: A systematic review. Journal of Hospital Administration, 8 (1), 16-26.

One of the policy mechanisms aimed at improving population health through health care delivery is the Hospital Readmissions Reduction Program (HRRP) as outlined in the Affordable Care Act. Although numerous procedural and behavioral interventions have been implemented, the empirical evidence of the efficacy of these interventions is mixed and specific to certain patient segments. This review aimed to systematically assess studies of hospital interventions to reduce 30-day readmissions for specific diseases and populations. Following the PRISMA review checklist, searches were conducted from January 2000 to August 2018 in the MEDLINE and EMBASE databases using terms such as “patient readmission”, “readmit” and “re-hospitalization” in conjunction with disease terms such as “asthma”, “chronic obstructive pulmonary disease (COPD)” and “pneumonia”. Of 3,806 articles identified, 45 were included after a 3-step inclusion process. The age group most frequently considered among the studies was the 65 age cohort. Multidisciplinary collaborative interventions were most frequently effective for the subset of elderly, female, Caucasian, and heart failure patients. Interventions involving patient or family education delivered before and after care were most effective for racial minority, elderly, COPD, and heart failure patients. Telephone follow-up, tele-homecare, and medication reconciliation were largely found to be successful in reducing readmissions. Major gaps exist in identifying successful interventions for reducing 30-day readmissions among patients who sought treatment for sepsis, stroke, and replacement of the hip or knee. Our findings indicate an opportunity for researchers to further study, and for healthcare organizations to implement, more well-informed interventional strategies to reduce readmissions.

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Keywords: Hospital readmission, Interventions, Population, Systematic review

Huang, H., Ma, L., Sabljak, L.A., & Puhala, Z.A. (2018). Development of sustainable community paramedicine programmes: A case study in Pennsylvania. Emergency Medicine Journal, 35(6), 372-378.

Community paramedicine (CP) models have been applied across rural and urban communities in support of healthcare delivery systems for nearly two decades. However, there is still insufficient information regarding the development of sustainable CP programmes. This study explores the strategies used by active CP programmes and investigates their operational statuses, community demographics, financial models and challenges for programme development.

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Keywords: Paramedicine

Kash, B.A., Cheon, O., Halzack, N.M., & Miller, T.R. (2018). Measuring team effectiveness in the health care setting: An intervention of survey tools. Health Services Insights, 11, 1-18.

Guidance for measuring team effectiveness in dynamic clinical settings is necessary; however, there are no consensus strategies to help health care organizations achieve optimal teamwork. This systematic review aims to identify validated survey instruments of team effectiveness by clinical settings.The 22 articles focused on surgical, primary care, and other health care settings. Few instruments report the required psychometric properties or feature non-self-reported outcomes. The major conceptual dimensions measured in the survey instruments difference across settings. Team cohesion and overall perceived team effectiveness can be found in all the team effectiveness measurement tools regardless of the health care setting. We found that surgical settings have distinctive conditions for measuring team effectiveness relative to primary or ambulatory care.

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Keywords: Team effectiveness, surveys, systematic review, health care quality assessment

Sasangohar, F., *Davis, E., & Kash, B.A. (2018). Remote patient monitoring and telemedicine in neonatal and pediatric settings: A scoping literature review. Journal of Medical Internet Research , 20(12), e295. doing:10.2196/jmir.9403

This paper aims to examine the role of remote patient monitoring (RPM) and telemedicine in neonatal and pediatric settings. Findings can be used to identify strengths, weaknesses, and gaps in the field. The identification of gaps will allow for interventions or research to improve health care quality and costs.

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Keywords: Neonatal, pediatric, remote patient monitoring, telehealth, telemedicine

Wekullo, C., Davis, E., Nafukho, F.M., & Kash, B.A. (2018). Health and human development in Kenya: A review of literature from high income, middle income, and low income countries. European Journal of Training and Development, 42(2), 5-34.

This paper aims to critically analyze the empirical literature on health and human development in high-, middle- and low-income countries to develop a sustainable model for investing in human health. The model is critical in building a comprehensive health-care system that fosters the stakeholders’ financial stability, economic growth and high-quality education for the local community.

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Keywords: Kenya, Sustainable development, Human development, Social development, Human health development, Sustainable health, Human health improvement

Kash, B.A., Ogden, P., Popp, E., Shaffer, M., & Bolin, J. (2017). Exploring future models of primary care for Texas. International Journal of Innovation Science, 9(4), 435-454.

The purpose of this study is to identify best practices for innovative primary care models and to describe a potential future primary care (PC) model for Texas to address the burden of chronic disease in a population-based approach.

Keywords: Primary care, innovative, academic medical training, models or care, physician shortage, primary care access, primary care workforce

Langabeer II, J.R., Champagne-Langabeer, T., Helton, J.R., Segrest, W., Kash, B.A., DelliFraine, J., & Folwer, R. (2017). Interorganizational collaboration in emergency cardiovascular care. Quality Management in Health Care, 26(1), 1-6.

Interorganizational collaboration management theory contends that cooperation between distinct but related organizations can yield innovation and competitive advantage to the participating organization. Yet, it is unclear if a multi-institutional collaborative can improve quality outcomes across communities.

Keywords: Interorganizational collaboration, population health, quality

Lim, S., & Tucker, C.S. (2017). Mitigating online product rating biases through the discovery of optimistic, pessimistic, and realistic reviewers. Journal of Mechanical Design.

The authors of this work present a model that reduces product rating biases that are a result of varying degrees of customers’ optimism/pessimism. Recently, large-scale customer reviews and numerical product ratings have served as substantial criteria for new customers who make their purchasing decisions through electronic word-of mouth. However, due to differences among reviewers’ rating criteria, customer ratings are often biased. For example, a three-star rating can be considered low for an optimistic reviewer. On the other hand, the same three-star rating can be considered high for a pessimistic reviewer. Many existing studies of online customer reviews overlook the significance of reviewers’ rating histories and tendencies. Considering reviewers’ rating histories and tendencies is significant for identifying unbiased customer ratings and true product quality, because each reviewer has different criteria for buying and rating products. The proposed customer rating analysis model adjusts product ratings in order to provide customers with more objective and accurate feedback. The authors propose an unsupervised model aimed at mitigating customer ratings based on rating histories and tendencies, instead of human-labeled training data.

Keywords: Data-driven design, user generated data, electronic word-of-mouth, online review, customer rating

Lin, S.H., Adepoju, O.E., Kash, B.A., DeSalvo, B., & McMaughan, D.K. (2017). Psychological distress and the use of clinical preventive services by community-dwelling older adults. Journal of Applied Gerontology, 1-19.

In this study, we explored whether psychological distress plays a role in the use of recommended clinical preventive services among community-dwelling older adults. The sample is drawn from respondents 65 years and older who participated in the 2011 Medical Expenditure Panel Survey (MEPS). Logistic regressions with selected covariates were entered in the model to estimate odds ratios (OR) with 95% confidence interval (CI) interval for the independent effect of pathological distress on the utilization of each of the five preventative services.

Keywords: Preventive services, psychological distress, older adults

Schuller, K.A., Kash, B.A., & Gamm, L.D. (2017). Enhanced transitions of care: Centralizing discharge phone calls improves ability to reach patients and reduces hospital readmissions. Journal of Healthcare Quality, 39(2), e10-e21.

The discharge phone call (DPC) is an important initiative aimed at improving transitions of care and reducing readmission. It is of added importance as financial penalties will be imposed on hospitals with “excessive” Medicare readmissions. This study examines the impact of DPCs on percentages of patients reached through the DPCs and hospital readmission rates based on the centralized or non-centralized mode of DPCs.

Keywords: Transitions of care, discharge phone call, hospital readmissions, quality of care

Spaulding, A., Kash, B.A., Johnson, C.E., & Gamm, L. (2017). Organizational capacity for change in health care: Development and validation of a scaleHealthcare Management Review, 42(2), 151-161.

We do not have a strong understanding of a health care organization’s capacity fir attempting and completing multiple and sometimes competing change initiatives. Capacity for change implementation is a critical success factor as the health care industry is faced with ongoing demands for change and transformation because of technological advances, market forces, and regulatory environment.

Keywords: Absorptive capacity, culture, leadership, organizational change, organizational readiness for change, organizational technologies

Yu, Y., Nembhard, H., Sillner, A., & Fareed, N. (2017). Monitoring total hip outcomes with a comparison of risk-adjustment frameworks, 2017 Industrial and Systems Engineering Conference.

Unplanned readmission after total hip arthroplasty (THA) has become an increasingly serious problem in the U.S., especially after the Centers for Medicare and Medicaid Services (CMS) carried out the penalty program for readmission in 2015. Thus, it is important to accurately identify high-risk patients and monitor the surgical outcomes of the medical team. In this study, we used modern machine learning algorithms to conduct patient risk stratification. We compared random forest with decision tree and the most commonly-used risk-adjustment method, logistic regression, using the THA patient-level data records from an academic medical center during 2011-2015. The results indicate that random forest outperforms logistic regression and decision tree in accurately identifying high-risk patients. Thus, this study provides new opportunities for medical decision support. Such informed medical decision making may help clinicians obtain insights into targeting medical interventions, providing patient-centered care, and reducing unplanned readmissions.

Keywords: Total hip arthroplasty, readmission, risk adjustment, logistic regression, random forest

Huang, H., Sabljak, S.A., & Puhala, Z.A. (2017) Emergency department patient experience and waiting time. American Journal of Emergency Medicine, 36(3), 510-511.

Emergency department (ED) waiting time has been known strongly related to patient satisfaction [1-3]. Hospitals continuously work on the projects to reduce actual ED waiting times, but it may not improve ED patient satisfaction [4]. Thus, it is important to investigate perceptions about the general population’s experiences with ED visits and the waiting times during each ED process. A paper-based questionnaire was designed in six sequential sections covering (1) history of ED visits, (2) perceptions about the ED visits (11 items), (3) perceptions about ED waiting time (11 items), (4) privacy and personal issues regarding ED visits (6 items), and (5) demographic information.

Keywords: Emergency department, patient experience, waiting time perception

Lim, S., Tucker, C.S., & Kumara, S. (2017) An unsupervised machine learning model for discovering latent infectious diseases using social media data. Journal of Biomedical Informatics, 66, 82-94.

The authors of this work propose an unsupervised machine learning model that has the ability to identify real-world latent infectious diseases by mining social media data. In this study, a latent infectious disease is defined as a communicable disease that has not yet been formalized by national public health institutes and explicitly communicated to the general public. Most existing approaches to modeling infectious-disease-related knowledge discovery through social media networks are top-down approaches that are based on already known information, such as the names of diseases and their symptoms. In existing top-down approaches, necessary but unknown information, such as disease names and symptoms, is mostly unidentified in social media data until national public health institutes have formalized that disease. Most of the formalizing processes for latent infectious diseases are time consuming. Therefore, this study presents a bottom-up approach for latent infectious disease discovery in a given location without prior information, such as disease names and related symptoms.

Keywords: Information retrieval, Latent infectious diseases, Sentiment analysis, Social media, Unsupervised machine learning

Lee, E.K. (2017) Innovation in Big Data Analytics: Applications of Mathematical Programming in Medicine and Healthcare. 2017 IEEE International Conference on Big Data, 3586-3595.

Risk and decision models and predictive analytics have long been cornerstones for advancement of business analytics in industrial, government, and military applications. In particular, multi-source data system modeling and big data analytics and technologies play an increasingly important role in modern business enterprise. Many problems arising in these domains can be formulated into mathematical models and can be analyzed using sophisticated optimization, decision analysis, and computational techniques. In this talk, we will share some of our successes in healthcare, defense, and service sector applications through innovation in predictive and big data analytics through the modeling and computational advances in integer programming. Specifically, the first model is a discrete support vector machine predictive model that incorporates comprehensive factors related to demographics and socioeconomic status, clinical and hospital resources, operations and utilization, and patient complaints and risk factors for global prediction of readmission and treatment outcome of patients. The second model describes an outcome-driven personalized treatment planning model for cancer patients.

Keywords: Data-driven analytics, integer programming, predictive models, classification, machine learning, discrete support vector machine, personalized treatment planning, cancer, multi-objective optimization

Lee, E.K., Shapoval, A., Wang, Z. (2017). Inpatient bed management to improve care delivery. 2017 IEEE International Conference on Bioinformatics and Biomedicine, 1033-1039.

We consider the problem of partitioning clinical services in hospitals into groups with the goal of efficiently allocating existing inpatient beds. At the strategic level, there are two major possibilities: pooling versus focusing. Pooling the bed capacity allows one to achieve an overall high occupancy level for a fixed number of beds. On the other hand, focusing by dividing the capacity into groups with restricted access may offer increased efficiency and better resource utilization. We derive a two-stage schema to address the 3-fold problem: 1) how many groups of services to form; 2) how many beds to allocate to each group; and 3) how to partition services among the groups. Stage 1 uses cluster analysis utilizing the similarity principle for possible advantages of economies of scale, coupled with queueing-based optimization models to obtain a set of candidate groups. Stage 2 incorporates utility/benefit functions to optimize the partitions and allocation of beds. Three full-scale examples demonstrate the flexibility and diverse application of our framework with managerial insights for different utility optimization goals and queueing systems.

Keywords: Pooling, Resource allocation, Queuing systems, Bed capacity management, clustering, optimization, nonlinear mixed integer program

Lee, E.K., Wang, Y., Davis, R.A., & Egan, B.M. (2017). Designing a low-cost adaptable and personalized remote patient monitoring system. 2017 IEEE International Conference on Bioinformatics and Biomedicine, 1040-1046.

Remote patient monitoring systems (RMS) have gained increasing popularity in recent years. RMS have great potential to improve medical services by providing more affordable, timely, and accessible care. This paper describes an effective low-cost RMS that is readily deployable. The system targets chronic disease patients and attempts to reduce patient visits to the hospital and healthcare costs. The system is comprised of three modules: (1) an application for data acquisition, processing, and transmission, (2) an adaptable set of “personalized” sensors for measuring vitals and reporting emergency situations, and (3) a secure communication module for remote patient-physician interactions. The users interface with the RMS through an application installed on a mobile device. Using a return of investment (ROI) cost-benefit analysis and a cohort of 2.7 million patients, we estimate that through the implementation of such a system, the patients and the healthcare system would see benefits within one year.

Keywords: Remote patient monitoring system, telehealth, timely access, chronic disease, affordability, security, digital healthcare system

Lee, E.K., Pietz, F.H., Chen, C.H., & Liu, Y. (2017). An interactive web-based decision support system for mass dispensing, emergency preparedness, and biosurveillance. Proceedings of the 2017 International Conference on Digital Health, 137-146.

In this study, we present an interactive web-based real-time decision support suite, RealOpt©. The system integrates visualization, information and cognitive analytics, and dynamic large-scale computational modeling and optimization tools that allow public health emergency preparedness coordinators to determine optimal response facilities and locations, resource needs and supply-routes, and population flow in real time. With an eye towards flexibility and future system expansion, RealOpt is designed in modular format allowing direct linkage to multiple functional modules. Currently, the system has twelve modules covering emergency response preparedness and operations for biological, chemical, radiological/nuclear incidents, biosurveillance, epidemiology, and decontamination models, operations logistics and networks, a real-time crowd sourcing data feed, and evacuation planning. RealOpt has been used for biodefense and H1N1 regional planning and operations, regional flood and hurricane responses, 2010 Haiti earthquake disaster relief, 2011 Japan Fukushima disaster, 2014-2015 Ebola containment assistance and after-event public health preparedness training in West Africa, and current Zika virus containment analysis. The fast solution engines enable real-time use for rapid decision and scenario analysis, since it requires only one CPU minute to determine an optimal network of facilities and resource needs to serve a population of over 10 million.

Keywords: Emergency response, real-time decision support, mass dispensing, simulation-optimization, facility location optimization, disease modeling, network analysis, agent-based modeling

Schmit, C., Wetter, S., & Kash B.A. (2017). Falling short: How can state laws address health information exchange barriers and enablers. Journal of the American Medical Informatics Association, ocx122,

Research on the implementation of health information exchange (HIE) organizations has identified both positive and negative effects of laws relating to governance, incentives, mandates, sustainability, stakeholder participation, patient engagement, privacy, confidentiality, and security. We fill a substantial research gap by describing whether comprehensive state and territorial HIE legal frameworks address identified legal facilitators and barriers.

Keywords: Health information exchange, health information technology, Law, Regulation

Kash, B.A., *Baek, J., *Davis, E., Langabeer, J.R., & Champagne, T. (2017). Review of successful hospital readmission reduction strategies and the role of health information exchange. International Journal of Medical Informatics, 104, 97-104.

The United States has invested substantially in technologies that enable health information exchange (HIE), which in turn can be deployed to reduce avoidable hospital readmission rates in many communities. With avoidable hospital readmissions as the primary focus, this study profiles successful hospital readmission rate reduction initiatives that integrate HIE as a strategy. We hypothesized that the use of HIE is associated with decreased hospital readmissions beyond other observed population health benefits. Results of this systematic review are used to describe and profile successful readmission reduction programs that integrate HIE as a tool.

Keywords: Health information exchange, Hospital readmission, Population Health, Systematic Review

Kash, B.A., *McKahan, M., *Mack, S., & Nanda U. (2017). Systematic review of merging models of cancer care: Implications for the health industry. Journal of Integrative Oncology, 6, 196, doi:10.4172/2329-6771.1000196.

In selected patients diagnosed with Breast Cancer (BC), adjuvant chemotherapy might reduce local and systemic recurrence risk, as well as cancer death rate. The combination of Docetaxel and Cyclophosphamide (TC) is a wellrecognized effective adjuvant chemotherapy regimen. Nonetheless, a considerable high rate of febrile neutropenia (FN) is associated with this regimen. We sought to investigate hematologic toxicity associated with adjuvant TC in a non-selected, “real world” cohort of BC patients.

Keywords: Cancer care, Emerging models, Facility implications

Kash, B.A., Lin S.H., *Baek, J., & Ohsfeldt, R. (2017). The diabetes management education program in south Texas: An economic and clinical impact analysis. Frontiers in Public Health, 5,345. doi: 10.3389/fpubh.2017.00345.

Diabetes is a major chronic disease that can lead to serious health problems and high healthcare costs without appropriate disease management and treatment. In the United States, the number of people diagnosed with diabetes and the cost for diabetes treatment has dramatically increased over time. To improve patients’ self-management skills and clinical outcomes, diabetes management education (DME) programs have been developed and operated in various regions. This community case study explores and calculates the economic and clinical impacts of expanding a model DME program into 26 counties located in South Texas.

Keywords: Diabetes management education program, Economic impact, Healthcare cost savings, Clinical benefits, South texas counties, Cost differentials model, uKPds risk engine model

Kash, B.A. & *McKahan, M. (2017). The evolution of measuring patient satisfaction. Journal of Primary Health Care and General Practice, 1(1), 1-4.

Creating a positive patient experience, as measured by current leading satisfaction surveys, is highly relevant in today’s healthcare environment as it has been recently linked to payment. Researchers began building the concept and measurement of patient experience in the 1980s. Today patient experience encompasses interpersonal manner, technical quality, accessibility and convenience, finances, efficacy and outcomes, continuity, physical environment, and availability. Measuring the patient experience, which can be thought of as a compilation of patient satisfaction, perceptions, engagement, participation, and preferences, since these tend to be overlapping measures, can be conducted using different methods: mixed, quantitative, qualitative, ethnographic, photo voice, and guided tours. Technology influences when and how the measurement takes place; measurement can be conducted at the time of care or at any time after. Since patient perceptions drive patient satisfaction, it is important to measure factors the patient values. In this paper, we discuss the history of patient satisfaction survey tools, the role of the patient experience, and strategies that can improve patient satisfaction metrics. Based on our review of literature and research, strategies to influence and improve patient satisfaction metrics need to consider the concept of the patient experience as complex and multi-dimensional phenomenon driven by patient expectations and perceptions.

Keywords: Patient satisfaction, Patient experience, Measuring satisfaction, Expectations, Perceptions

Bastian, N.D., Swenson, E.R., Ma, L., Na, H.S. & Griffin, P.M. (2017). Incentive contract design for food retailers to reduce food deserts in the US. Socio-Economic Planning Sciences, 60, 87-98.

In the US, obesity affects over 37% of the adult population and over 16% of the child and adolescent population. Although not-for-profit agencies cannot directly control what a person eats, they can influence the supply side of the obesity epidemic by incentivizing food retailers to open stores in regions of the US where food deserts exist. An incentive contract design dependent upon performance and resulting health benefit is presented for food retailers to reduce food deserts in the US. A principal-agent framework is used to capture the competing interests and moral hazard from the contracting mechanism. Optimization models are developed to determine the most effective and equitable resource allocations from the initiative given a target reduction in obesity rate or a set budget, while determining the optimal subsidy these agencies should offer to food retailers to incentivize operation in certain counties. These subsidies are designed to create financially viable conditions for food retailers to offer high quality, healthy food alternatives. The impact of retailer location on obesity is based on estimates of marginal effect on obesity rate. Given an example initiative in metropolitan Atlanta, Georgia and surrounding counties, the overall county-wide obesity rate would decrease by 1.17% with a fixed budget of $400M. Sensitivity analysis on the reduction in obesity is performed for varying total budget amounts. This incentive contract design strategy is a positive step toward ensuring that the underserved US population has better access to healthy foods while helping solve the obesity epidemic.

Keywords: Obesity, Food deserts, Incentive contract design, Resource allocation, Multi-objective optimization

Lim S, Tucker CS, Jablokow K, Pursel B. (2017). Quantifying the Mismatch Between Course Content and Students’ Dialogue in Online Learning Environments. ASME International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, Volume 3: 19th International Conference on Advanced Vehicle Technologies; 14th International Conference on Design Education; 10th Frontiers in Biomedical Devices ():V003T04A016. doi:10.1115/DETC2017-67339.

Due to the internet’s increasing global availability, online learning has become a new paradigm for distance learning in higher education. While student interactions and reactions are readily observable in a physical classroom environment, monitoring student interactions and quantifying divergence between lecture topics and the topics that interest students are challenging in online learning platforms. Understanding the effects of this divergence is important for monitoring student engagement and aiding instructors, who are focused on improving the quality of their online courses. The authors of this paper propose a topic modeling method, based on latent Dirichlet allocation (LDA), that quantifies the effects of divergence between course topics (mined from textual transcriptions) and student-discussed topics (mined from discussion forums).

Keywords: NA

Vest, J. R., & Kash, B. A. (2016). Differing Strategies to Meet Information‐Sharing Needs: Publicly Supported Community Health Information Exchanges Versus Health Systems’ Enterprise Health Information Exchanges. The Milbank Quarterly, 94(1), 77-108.

The United States has invested billions of dollars to increase the utilization of health information exchanges (HIEs), which allow providers to obtain and share patient information with other health providers. There are two options for HIEs: 1) enterprise HIEs, which support strategic goals through information sharing with affiliated hospitals and physicians, and 2) community HIEs, which help obtain information from a broad set of providers. Currently, policies more strongly support enterprise HIEs, while community HIEs could require public funding and regulation support. The benefit arising from HIEs is the ability to follow patients through the care cycle across a variety of settings.

Keywords: Health information systems, health information exchange, integrated delivery systems, qualitative research

Kash, B., & Tan, D. (2016). Physician Group Practice Trends: A Comprehensive ReviewJournal of Hospital & Medical Management, 2(1:3), 1-8

Physician group practices are growing and changing in the U.S. in terms of team composition, contract types, size, and management from the progression of managed care and the Patient Protection and Affordable Care Act. About 32.5% of physicians work in solo and two-physician practices, a decrease from 40.7% between 1996-1997 and 2004-2005. Although self-employment and participation in small practices (less than 10 physicians) used to be popular, the majority of physicians today are being employed by large healthcare organizations and practice in mid-sized, single specialty groups.

Keywords:  Physician group, trends

Kash, B. A., & Davis, E. (2016). Active Barrier Apparel: The Simple, Evidence-Based Workplace and Patient Safety StrategyOccupational Medicine & Health Affairs, 4(3), 1-2.

Healthcare professionals are at risk of contracting a healthcare-associated infection, but workplace apparel can provide a protective barrier. The current uniform does not provide this protective barrier and has been found to acquire and retain multi-drug resistant organisms. Advances are being made in textile technology to create uniforms that repel fluid splatters and spills, which can serve as a barrier when personal protective equipment is not worn in the unanticipated situations.

Keywords:  Patient safety strategy, uniforms, work conditions

Lee, E. K., & Yang, H. (2016). Predictive Analytics: Classification in Medicine and Biology. In Healthcare Analytics: From Data to Knowledge to Healthcare Improvement: From Data to Knowledge to Healthcare Improvement (pp. 159-187). Hoboken, NJ: John Wiley & Sons, Inc.

Classification is a way of learning through the development of rules to create groups from independent entities. Classification models are important for medical advances because they can be used for diagnosis, intervention, and treatment outcome prediction. This study sought to maximize the correct classification through biological and medical applications with the utilization of models. The models could simultaneously classify groups, incorporate attribute inputs, transform data to reduce noise and errors, constrain misclassification, and conduct multistage classification. Examples of applications include neuropsychological tests for Alzheimer’s disease, the CpG island study for cancer, and ultrasounds for drug delivery or device implants.

Keywords:  Pattern recognition, artificial intelligence, machine learning, statistics

Mahle, W. T., Nicolson, S. C., Hollenbeck-Pringle, D., Gaies, M. G., Witte, M. K., Lee, E. K.,& Cooper, D. S. (2016). Utilizing a Collaborative Learning Model to Promote Early Extubation Following Infant Heart Surgery. Pediatric Critical Care Medicine, 17(10), 939-947.

Collaborative learning was used in this study to improve postoperative care for children with congenital heart disease by developing a clinical practice guideline (CPG). The goal was to increase the rate of early extubation in these infants. Many centers found the operating room, immediately after surgery, to be the ideal setting for early extubation. The study also found that early extubation was associated with lower total doses and duration of continuous IV sedation. Though the rate of early extubation increased, there was no change in the reintubation rate and the postoperative ICU length of stay did not significantly change.

Keywords:  Mechanical ventilation, outcomes, tetralogy of Fallot

Lee, E. K., Nakaya, H. I., Yuan, F., Querec, T. D., Burel, G., Pietz, F. H., Benecke, B. A., & Pulendran, B. (2016). Machine Learning for Predicting Vaccine Immunogenicity. Interfaces, 46(5), 368-390.

Next-generation vaccine development is greatly influenced by the prediction of how individuals will respond and understanding what best protects people from infection. The general-purpose machine-learning framework, DAMIP, was used in this study, which discovers gene signatures to predict vaccine immunity and efficacy. DAMIP was implemented to predict immunity in an individual who received a vaccination for yellow fever. For the first time, the study found that the vaccine’s ability to immunize could be successfully predicted within a week post-vaccination. The findings from this study lead the way for rapid development of better vaccines to address existing and emerging infections, as well as monitor for those with poor responses.

Keywords:  Machine learning, multiple group classification, vaccine immunogenicity prediction,influenza, yellow fever, malaria, health security, prophylactic medical countermeasures, hypothesis generation, vaccine design for emerging infections

Hu, W. T., Watts, K. D., Tailor, P., Nguyen, T. P., Howell, J. C., Lee, R. C., Seyfried, N. T., Gearing., Hales, C. M., Levey, A. I., Lah, J. J., & Lee, E. K. (2016). CSF complement 3 and factor H are staging biomarkers in Alzheimer’s diseaseActa Neuropathologica Communications, 4(14), 1-10.

With cerebrospinal fluid (CSF) levels remaining stable in established Alzheimer’s disease (AD) biomarkers, non-amyloid non-tau biomarkers have the ability to inform care givers of the stage and progression. The researchers have found the levels of C3 and associated factor H (FH) are influenced by age and disease status, but believe that the levels can distinguish between mild cognitive impairment (MCI) and dementia stages of AD. Studies involving CSF amyloid and tau levels did not provide reliable differences between MCI and mild AD. The study suggests that the alterations in CSF, C3, and FH could represent stage-associated biomarker changes in AD.

Keywords: Amyloid beta, Diagnosis, C3, FH, Machine learning, Replication, Tau

Nakaya, H. I., Hagan, T., Duraisingham, S. S., Lee, E. K., Kwissa, M., Rouphael, N., Frasca, D., Gersten, M., Mehta, A. K., Gaujoux, R., LI, G.M., Ahmed, R., Mulligan, M. J., Shen-Orr, S., Blomberg, B. B., Subramaniam, S., & Pulendran, B. (2015). Systems analysis of immunity to influenza vaccination across multiple years and in diverse populations reveals shared molecular signaturesImmunity43(6), 1186-1198.

Molecular signatures that drive influenza immunity are described using system approaches. This study used system approaches to examine immune responses in young, elderly, and diabetic individuals who received the seasonal influenza vaccination. The results include signatures of innate immunity and plasmablasts associated with influenza antibody titers and baseline signatures of lymphocyte and monocyte inflammation one month post vaccination, as well as vaccine immunity potential regulators. With monitoring the subjects, who came from diverse populations, over five consecutive seasons, these results could lead the way for development of the next-generation vaccines for persistent immunity against influenza.

Keywords: Immunity,  influenza vaccination,  plasmablasts

Lee, E. K., Callahan, M., Wei, X., Tailor, P. D., Quarshie, A., & Wright, M. (2015). A systems approach to reducing central line associated blood stream infections. 2015 IEEE International Conference on Bioinformatics and Biomedicine 948-955.

This study strived to reduce the incidence of central line associated bloodstream infections (CLABSI). The researchers created a computer model that attempts to capture major events in the patient care from arrival through removal of the central line. The goal was to predict deaths among patients with CLABSI while reducing Type II error, which gave providers the best opportunity to intervene. Reminder and protocol implementation led to an 18% reduction in CLABSI-related deaths in a twelve month period.

Keywords: Healthcare associated infection, central-line associated blood stream infection, system modeling and simulation, machine learning, predictive analytics

Chen, B., Matis, T., & Benneyan, J. (2016). Computing exact bundle compliance control charts via probability generating functions. Health care management science, 19(2), 103-110.

An important focus for healthcare quality improvement is the compliance to individual and bundled evidence-base practices. A bundle is made up of three to six care elements, where compliance is monitored for quality and outcome improvement purposes. To monitor compliance, the use of practical, fast, and accurate statistical methods is necessary. The method illustrated in this paper was based on probability generating functions, which is a rather simple approach. This approach can provide accelerated improvement efforts since the exact results are easily obtained.

Keywords: Health care, convolutions, probability generating function, control charts

Bharathi, A. K. B. G., Singh, A., Tucker, C. S., & Nembhard, H. B. (2016). Knowledge discovery of game design features by mining user-generated feedbackComputers in Human Behavior, 60(1), 361-371.

Gamification is on the rise and strives to provide effective ways to motivate consumers to take action by offering challenges, levels, and rewards. This paper wanted to bridge the knowledge gap through quantifying the successful applications to help designers understand the gamification features that have greater impact for user experience and prolonged engagement. Gamification can be used in healthcare to change behavior and enhance outcomes with patients who are partaking in therapy or those who are struggling to meet protocols.

Keywords: Gamification, Game design features, Machine learning, Behavior change, User engagement

Swenson, E. R., Bastian, N. D., & Nembhard, H. B. (2016). Data analytics in health promotion: Health market segmentation and classification of total joint replacement surgery patientsExpert Systems with Applications, 60(1), 118-129.

Machine learning was used with a patient data set from a Pennsylvania academic medical center’s electronic medical records (EMRs). Unsupervised machine learning was used to identify clusters and then supervised machine learning classified the data. EMRs allow for the data storage to support health market segmentation efforts, which can be of great potential if applied to large populations, providing detailed demographic, geographical, and clinical characteristics. To create positive health outcomes, it is important to understand patient clusters and their response to health promotions to allow for effective and efficient targeting.

Keywords: Health market segmentation, Health promotion, Data analytics, Machine learning, Total joint arthroplasty, Value-based healthcare

Bettinger, B., & Benneyan, J. C. (2016). The volunteer’s dilemma and alternate solutions for ensuring responsibility within accountable care organizations. The Engineering Economist, 61(1), 1-15.

Collaboration in an accountable care organization (ACO) has major potential, but maximization is needed for this opportunity. Providers in an ACO receive incentives based on group performance and specified quality measures. When providers’ opinions vary on intervention effectiveness, unreliability could be created. To ensure patients receive indicated interventions, three economic mechanisms can be utilized: 1) reassign interventions to optimistic providers, 2) outsource to third party/vendor outside ACO, and 3) create a penalty to incentivize. When these options are not feasible, it is important to allow an individual to intervene and make sure the proper intervention is rendered.

Keywords: Accountable care, social dilemmas, volunteers dilemma,

Wan, H., Zhang, L., Witz, S., Musselman, K. J., Yi, F., Mullen, C. J., Benneyan, J. C., Zayas-Castro, J. L., Rico, F., Cure, L. N., & Martinez, D. A. (2016). A literature review of preventable hospital readmissions: Preceding the Readmissions Reduction ActIIE Transactions on Healthcare Systems Engineering, 6(4), 193-211.

Preventable readmissions represent about 20% of 30-day post-discharge hospitalizations in the United States, resulting in $17-$26 billion unnecessary costs each year. Evaluating the risk of preventable readmissions is a difficult task because of the lack of standardization of clinical data with physician notes, tests results, and images. Prevention interventions like discharge planning, transitions of care, and follow-up can be implemented to reduce readmissions through education, enhanced communication and coordination, patient and family engagement, telephone calls, home visits, and/or primary care follow up. Also, industrial engineers can apply their knowledge to address this issue by applying statistical modeling or data reduction models.

Keywords: Re admissions, re-hospitalizations, bounce backs, discharge process

Wolf, M. J., Lee, E. K., Nicolson, S. C., Pearson, G. D., Witte, M. K., Huckaby, J., Gaies, M., Shekerdemian, L. S., & Mahle, W. T.(2016). Rationale and methodology of a collaborative learning project in congenital cardiac care. American heart journal, 174(1), 129-137.

Collaborative learning is a technique where individuals or teams can learn from one another’s skills, knowledge, resources, experiences and ideas. Clinicians providing care to patients with congenital heart disease could benefit from a collaborative learning environment due to the complex patient population. In this study, broad-based time-motion and process analyses were conducted on five pediatric centers to better understand cardiac post-operative mechanical ventilation in infants; data analysis is currently being conducted. Rapid fact-finding and dissemination of information can be accomplished through collaborative learning that utilizes multidisciplinary team site visits and information sharing. Guidelines can be developed once system modeling and machine learning identify and prioritize the areas in which they are needed.

Keywords: Collaborativelearning, congenital cardiac care, mechanical ventilation

Kang, H., Nembhard, H. B., Curry, W., Ghahramani, N., & Hwang, W. (2016). A systems thinking approach to prospective planning of interventions for chronic kidney disease care. Health Systems, 5(1), 1-18.

Chronic kidney disease (CKD) is a growing health problem in the United States. While CKD is irreversible, there are evidence-based interventions that can slow its progression, enabling patients to live longer without complications. This research study was conducted with the goal to improve overall CKD outcomes by transforming the current healthcare delivery system into a patient-centered and coordinated system for CKD care. The results revealed four proposed interventions: (1) education and implementation of the adapted KDOQI guidelines for PCPs, (2) education and implementation of the adapted KDOQI guidelines for care managers, (3) enhancement of PCPs awareness of care managers’ role, and (4) care coordination between PCPs and nephrologists, including early referrals to nephrology care. The prioritization of interventions was created by patient groups. Overall, this study demonstrated how a systems thinking approach can support effective planning of interventions for improved CKD care.

Keywords: Health-care system; intervention planning; systems thinking; causal loop diagram; feedback loops; chronic kidney disease (CKD)

Bastian, N. D., Munoz, D., & Ventura, M. (2016). A Mixed-Methods Research Framework for Healthcare Process Improvement. Journal of pediatric nursing, 31(1), 39-51.

Efficient workflow is vital to improve healthcare value. The mixed-methods research framework, which consists of stakeholder analysis, survey design, time-motion study, and process improvement, was applied to a pediatric intensive care unit at Pennsylvania State Hershey Children’s Hospital. The framework allowed for a more holistic assessment of workflow. This framework takes complexity into account and helps stakeholders and decision makers continuously improve efficiency.

Keywords: Machine learning classification of design team members’ body language patterns for real time emotional state detection

Bastian, N. D., Kang, H., Nembhard, H. B., Bloschichak, A., & Griffin, P. M. (2016). The Impact of a Pay-for-Performance Program on Central Line–Associated Blood Stream Infections in Pennsylvania. Hospital topics, 94(1), 8-14.

Healthcare associated infections have significantly contributed to the rising cost of hospital care in the United States. A CHOT study set at Highmark’s Quality Blue (QB) hospital quantified the impact of a pay-performance (P4P) program and  found that P4P programs can be beneficial in terms of improving healthcare quality outcomes; in particular, the program was associated with a significant reduction in central line-associated blood stream infections (CLABSI) in hospitals in Pennsylvania. On average, those hospitals that participated in QB program had a 27% reduction in CLABSI compared to those hospitals that did not participate in the QB program. Hospitals that participated in QB for four or more years had on average 3.13 fewer CLABSI pre year compared to those participating for less than four years.  Researchers used the implementation of pay-for-performance (P4P) programs since it has been one approach to improve quality of care and reduce costs.

Keywords: Mixed-methods research, Healthcare management, Pediatric care, Quality engineering, Process improvement, Workflow assessment

Kash, B.A., Tan, D., Tittle, K.O., & Tomaszewski, L. (2016). The pediatric medical home: What evidence-based models look like?. American Journal of Accountable Care 6(16), 34-40.

A pediatric medical home is a system made up of health and social providers who support the medical and nonmedical needs of the patients and families. To better serve these children, the primary care patient segmentation framework can be refined and utilized. The framework suggests the creation of subgroups for patients that have similar needs and medical conditions, as well as measuring outcomes and costs for each unique subgroup. Applying segmentation to the pediatric primary care population helped address several factors including limited English proficiency, pediatric emergency care, mental health issues, and management of overweight and obese patients.

Keywords: delivery systems, qualitative research

Tucker, C. S., Han, Y., Nembhard, H. B., Lee, W.-C., Lewis, M., Sterling, N., Huang, X. (2015). “A Data Mining Methodology for Predicting Early Stage Parkinson’s Disease Using Non-Invasive, High Dimensional Gait Sensor Data,” IIE Transactions on Healthcare Systems Engineering , 5, 238-254.

Parkinson’s disease (PD) is the second most common neurodegenerative disorder, after Alzheimer’s disease, with critically important and challenging early-stage detection methods. A recent CHOT study proposes using a methodology involving low-cost, non-invasive sensors that capture 3D gait data and then subsequent algorithms use the data to detect features relevant to PD, whereas the current process for testing for PD is invasive and time-consuming. By generating dating mining predictive models, researchers are able to predict whether or not a patient displays early stages of PD. The data points collected for this study came from 20 detectors located on major parts of the human body are analyzed to detect features related to PD in walking motion, such as the height of an arm at full swing.  This new method of testing is not as invasive and time-consuming is not as the current process for testing for PD.

Keywords: Parkinson’s disease, gait, data mining, machine learning, sensor, non-invasive, non-wearable, image mining

Bolin, J. N., Bellamy, G. R., Ferdinand, A. O., Vuong, A. M., Kash, B. A., Schulze, A., & Helduser, J. W. (2015). Rural healthy people 2020: new decade, same challenges. The Journal of Rural Health, 31(3), 326-333.

The goal of Rural Healthy People 2020 is to identify rural health priorities among Healthy People 2020’s national priorities. Rural Americans face unique challenges due to socio-economic status, age, increasing racial/ethnic diversity, and infrastructure needs, which leads to lower health status in rural communities compared to urban communities. Rural Healthy People 2020 conducted a national survey of rural health stakeholders to identify the priority focus areas of Healthy People 2020 for rural America. The top ten rural health priorities are identified as: (1) access to quality health services, (2) nutrition and weight status, (3) diabetes, (4) mental health and mental disorders, (5) substance abuse, (6) heart disease and stroke, (7) physical activity and health, (8) older adults, (9) maternal, infant, and child health, and (10) tobacco use.

Keywords: access, Healthy People 2020, RHP2020, rural disparities, Rural

Lee, E. K., Atallah, H. Y., Wright, M. D., Post, E. T., Thomas IV, C., Wu, D. T., & Haley Jr, L. L. (2015). Transforming Hospital Emergency Department Workflow and Patient Care. Interfaces.

Improving an emergency department’s (ED) timeliness of care, quality of care, and operational efficiency while reducing avoidable readmissions, is fraught with difficulties, which arise from complexity and uncertainty. A recent CHOT study describes an ED decision support system that allows healthcare administrators to globally associated care, thereby significantly reducing patient length of stay (by 33% in the study hospital).  This system couples machine learning, stimulation, and optimization to address these improvement goals. Using this system offers significant advantages in that it permits a comprehensive analysis of the entire patient flow from registration to discharge, enables a decision maker to understand the complexities and interdependencies of individual steps in the process sequence, and ultimately allows the users to perform system optimization. Overall benefits and impacts included improved efficiency and emergency care, annual financial savings and revenues, encouragement of external sponsorship, health cost reductions, and improved quality of care in other facilities.

Keywords: systems transformation; systems optimization; machine learning; multiple-resource allocation; mixed-integer program; simulation; decision support; emergency department; acuity level; length of stay; readmission; operations efficiency

Lee, E. K., Yuan, F., Pietz, F. H., Benecke, B. A., & Burel, G. (2015). Vaccine Prioritization for Effective Pandemic Response. Interfaces, 45(5), 425-443.

When limited vaccines are available, prioritized vaccination is considered the best strategy to mitigate the impact of a pandemic. A recent study by CHOT researchers found that without delay in vaccination start time, there is a reduction in prevalence of more than twofold of H1N1. Policy makers can use the results from this study to more rapidly evaluate better trade-offs to save more lives and better utilize limited resources during a pandemic event.  This study is believed to be the first mathematical computational model to combine disease propagation, dispensing operations, and optimization capability. It is also the first to define and allow for rapid determination of optimal switch triggers. The CDC confirms that this is the first time an actionable and operation switch trigger has been defined, an advance that is critical and vital to better mitigation of infections and mass casualties.

Keywords: ordinary differential equations; queueing; optimization; public health policy making; pandemic containment; vaccine prioritization; disease propagation; decision support; agent-based simulation; epidemiology

Behoora, I., & Tucker, C. S. (2015). Machine learning classification of design team members’ body language patterns for real time emotional state detection. Design Studies, 39, 100-127.

Design team interactions are one of the least understood aspects of the engineering design process. Given the integral role that designers play in the engineering design process, understanding the emotional states of individual design team members will help us quantify interpersonal interactions and how those interactions affect resulting design solutions. The methodology presented in this paper enables automated detection of individual team member’s emotional states using non-wearable sensors. The methodology uses the link between body language and emotions to detect emotional states with accuracies above 98%. The practical implications include that machine learning to detect emotions using non-invasive sensors in design teams and that there was a high accuracy over 90% achieved for detecting many body language poses.

Keywords: Computational models, information processing, design activity, team work, user behavior

Cline, K. M., Roopani, R., Kash, B. A., & Vetter, T. R. (2015). Residency Board Certification Requirements and Preoperative Surgical Home Activities in the United States: Comparing Anesthesiology, Family Medicine, Internal Medicine, and Surgery. Anesthesia & Analgesia, 120(6), 1420-1425.

Surgical care is not often standardized or coordinated, resulting in duplicated or unnecessary care that costs an estimated $18 billion annually in the United States. Better management of the perioperative process could reduce costs while improving the quality of care; however, it is not a subject traditionally comprehensively covered in any one medical specialty. This research study looked at various elements of perioperative care, including four medical residencies (anesthesiology, family medicine, internal medicine, and surgery), and found that many of the activities inherent to the PSH are not required for board certification in any of the specialties, particularly in the intraoperative and postoperative phases. All four specialties appear to have room for improvement by expanding perioperative care education.

Keywords: Residency board requirements, Peroperative surgical home

DeFlitch, C., Geeting, G., & Paz, H. L. (2015). Reinventing emergency department flow via healthcare delivery science. HERD : Health Environments Research & Design Journal, 8(3), 105-115.

In this CHOT study, a new flow model of emergency care delivery, physician-directed queuing (PDQ) and found that through the implementation of the PDQ model, there was decreased   door-to-bed time (91% to 19 minutes), decreased average waiting time (83% to 12 minutes), and increased patient satisfaction (17th to 85th percentile).  To create this PDQ, researchers analyzed the operational data and staff input of an overcrowded academic health center emergency department (ED) with increasing patient volumes and limited physical space for expansion. EDs are a critical point of entry into the healthcare system. Hospital crowding and its resulting ED overcrowding create barriers to access and provision of care. Crowding is associated with less timely care, decreases in patient satisfaction, produces less effective care, and poor outcomes. With the new proposed PDQ model, providers passively evaluate all patients upon arrival, actively manage patients requiring fewer resources, and direct patients requiring complex resources to further evaluation in ED areas. This model of practice can be applied to other patient care settings such as ambulatory care, inpatient hospital flow, and imaging diagnostics.

Keywords: emergency medicine, healthcare delivery, workflow, healthcare process assessment, healthcare evaluation

Gregory, S. T., & Menser, T. (2015). Burnout among primary care physicians: A test of the areas of worklife model. Journal Of Healthcare Management, 60(2), 133-148.

Examinations of the current state of the physician workforce in the US and globally indicate a declining overall well-being, and specifically increasing levels of burnout. The consequences of these effects include early retirements or exits from the medical profession, difficulties improving the patient experience, and low levels of provider engagement with clinic-level and system-level initiatives. Such consequences affect physicians, healthcare organizations, and patients. The goal of this study was to test an etiological model, the Areas of Worklife Scale (AWS), for practicing primary care physicians. Using the AWS and the Maslach Burnout Inventory, the study used a longitudinal survey research design method to query primary care physicians employed at a large integrated delivery system in the United States. Data collected successfully fit the AWS model for burnout among primary care physicians, supporting our theory that workplace drivers are responsible for burnout. Workload, control, and values congruence are the largest drivers of burnout for practicing primary care physicians. The AWS model provides key insights into the domains of work that cause stress and ultimately burnout for physicians, and these domains can guide physicians and managers to develop interventions to fight the rising incidence of burnout.

Keywords: Physician burnout, workplace well-being, physician engagement

Kash, B. A., Cline, K. M., Timmons, S., Roopani, R., & Miller, T. R. (2015). International comparison of preoperative testing and assessment protocols and best practices to reduce surgical care costs: A systematic literature reviewAdvances in Health Care Management, 17, 161-194.

Health care institutions in many Western countries have developed preoperative testing and assessment guidelines to improve surgical outcomes and reduce cost of surgical care. The aims of this research study are to (1) summarize the literature on the effect of preoperative testing on clinical outcomes, efficiency, and cost; and (2) to compare preoperative testing guidelines developed in the United States, the United Kingdom, and Canada.  Most studies indicate that preoperative testing is overused and comes at a high cost. Guidelines are tied to payment only in one country studied.  Although the empirical research is not as conclusive as would be preferred, it is clear that there is substantial untapped potential both for savings in costs and for improvement in quality and outcomes by improved guidelines and, particularly, adherence to guidelines for preoperative testing. In the US it is estimated that minimizing unnecessary preoperative tests could reduce health care costs by $10 billion while improving patient experience.  In just one institution in Canada in one year, more appropriate preoperative testing could save $87,000 annually; the nationwide savings could be significant.  For these savings and improvements to be realized, commonly agreed upon guidelines need to be fully implemented.

Keywords: Preoperative testing, preoperative guidelines, perioperative surgical home, cost, clinical outcomes, operating room efficiency

Mutlu, S., Benneyan, J. C., Terrell, J., Jordan, V., & Turkcan, A. (2015). A co-availability scheduling model for coordinating multi-disciplinary care teams. International Journal of Production Research, 1-12.

This research study introduces a co-availability scheduling problem that arises in various healthcare settings in which personnel from different disciplines work together as care teams and for which synchronization of their availability impacts scheduling flexibility and procedure timeliness. Examples include breast cancer surgery involving oncologic and plastic surgeons, primary and specialty care integrated visits, and vascular interventions involving cardiac surgeons, radiologists and radiology technicians. For this research, an integer programming model was developed to help create optimal schedules that maximize the amount of co-available time across the scheduling templates of the desired team members, while still satisfying each of their clinic coverage, preference and extraneous responsibilities constraints. Application to breast surgery at a major cancer center increased team co-availability by 94%, with sensitivity analysis in other scenarios producing 64–152%, increases in favorable team assignments, and without negatively affecting operating room neither utilization nor surgery delays.

Keywords: Healthcare; personnel scheduling; multi-disciplinary teams

Schuller, K. A., Kash, B. A., & Gamm, L. D. (2015). Comparing success and sustainability in two health systems. Journal of health organization and management, 29(6), 684-700.

In the healthcare sector, organizational change is vital for ensuring a positive financial margin and long-term sustainability through competitive positioning and differentiation.  This study investigated how to successfully implement an innovative care management model such as Studer Group’s Evidence-based Leadership (EBL) tool found that culture (accountability, buy-in and communication) is most important for sustainability of initiative (long-term) and leadership seems most important initially during kick-off and early implementation stage.  This research study analyzed the implementation of EBL in two large, US health systems by comparing and contrasting the factors associated with successful implementation and sustainability of the EBL initiative.  Researchers found three themes associated with success and sustainability of EBL: leadership; culture; and organizational processes.  This study offers health system leaders practical guidance on how to effectively implement organizational change initiatives by designing the appropriate system and environment conducive to successful and sustainable implementation of key patient care and management change initiatives.  .

Keywords: Organizational theory, Hospital management, Organizational change, Health services,

Sheldrick, R. C., Benneyan, J. C., Kiss, I. G., Briggs‐Gowan, M. J., Copeland, W., & Carter, A. S. (2015). Thresholds and accuracy in screening tools for early detection of psychopathology. Journal of Child Psychology and Psychiatry.

The accuracy of any screening instrument designed to detect psychopathology among children is ideally assessed through rigorous comparison to ‘gold standard’ tests and interviews. Such comparisons typically yield estimates of what we refer to as ‘standard indices of diagnostic accuracy’, including sensitivity, specificity, positive predictive value (PPV), and negative predictive value. However, whereas these statistics were originally designed to detect binary signals (e.g., diagnosis present or absent), screening questionnaires commonly used in psychology, psychiatry, and pediatrics typically result in ordinal scores. The study results found that both screening measures were effective in identifying groups of children at elevated risk for psychopathology in all samples (odds ratios ranged from 5.2 to 9.7), children who scored at or near the clinical thresholds that optimized sensitivity and specificity were unlikely to meet criteria for psychopathology on gold standard interviews.

Keywords: Assessment, screening, psychopathology, developmental psychopathology, methodology

Vaughn-Cooke, M., Nembhard, H. B., Ulbrecht, J., & Gabbay, R. (2015). Informing Patient Self-Management Technology Design Using a Patient Adherence Error Classification. Engineering Management Journal, 27(3), 124-130.

Patient adherence is one of the most difficult changes to healthcare providers. This study models human behavior, both intentional and unintentional, relating to error in patient adherence of diabetes treatment. In a recent study, Penn State-CHOT researchers found that patient adherence was primarily driven by skill-based errors and intentional violations which lent itself to several risk mitigation strategies. This research study indicates that error classifications may be helpful in individualizing treatment interventions. By including device design modification, such as: (1) reduce patient inattention, (2) increase motivation to adhere, and (3) reduce pain barriers for glucometer use, this study demonstrated the feasibility of using an error classification approach in the identification and mitigation of the diabetes patients’ non-adherence with self-monitoring of blood glucose (SMBG).

Keywords: Human Error, Diabetes, Patient Self-Management, Design Decision Making, Human Factors Engineering, Risk Management

Yan, R., Bastian, N. D., & Griffin, P. M. (2015). Association of food environment and food retailers with obesity in US adultsHealth & place, 33, 19-24.

The food environment has been shown to be a factor affecting the obesity rate. For this research study, the association of density of food retailer type with obesity rate in U.S. adults in local regions controlling for socioeconomic factors was analyzed. Parametric nonlinear regression was used on publically available data (year 2009) at the county level. We used the results of this association to estimate the impact of the addition of a new food retailer type in a geographic region. Obesity rate increased in supercenters (0.25–0.28%) and convenience stores(0.05%) and decreased in grocery stores(0.08%) and specialized food stores(0.27– 0.36%). The marginal measures estimated in this work could be useful in identifying regions where interventions based on food retailer type would be most effective.

Keywords: food environment, food retailers, obesity rate

Ceyhan, M. E., & Benneyan, J. C. (2014). Handling estimated proportions in public sector data envelopment analysisAnnals of Operations Research, 221(1), 107-132.

CHOT researchers at the Georgia Institute for Technology used systems modeling and simulation to analyze the medication workflow in a pediatric setting. They focused on ‘High Alert’ medications, which are more likely to produce serious patient harm when errors occur, and found that strategic process interventions (e.g., independent intervention check points) can significantly reduce error occurrence (by as much as 50.25%) and the cost savings could be significant.   This work offers a system-decision support framework for analysis of medication workflow and helps in understanding error propagation mechanisms and process interdependencies.  By using this framework, users were able to derive intervention strategies and evaluate their overall mitigation effectiveness.  The estimated errors from this model remain consistently close to the reported error statistics (within 5%).

Keywords: Data envelopment analysis, stochastic DEA, bootstrapping, chance constraint DEA, bayesian inference

Chen, B., Matis, T., & Benneyan, J. C. (2014). Computing exact bundle compliance control charts via probability generating functions. Health Care Management Science, 1-8.

Compliance to evidenced-base practices, individually and in ‘bundles’, remains an important focus of healthcare quality improvement for many clinical conditions. The exact probability distribution of composite bundle compliance measures used to develop corresponding control charts and other statistical tests is based on a fairly large convolution whose direct calculation can be computationally prohibitive. Various series expansions and other approximation approaches have been proposed, each with computational and accuracy tradeoffs, especially in the tails. This same probability distribution also arises in other important healthcare applications, such as for risk-adjusted outcomes and bed demand prediction, with the same computational difficulties. As an alternative, we use probability generating functions to rapidly obtain exact results and illustrate the improved accuracy and detection over other methods. Numerical testing across a wide range of applications demonstrates the computational efficiency and accuracy of this approach.

Keywords: Health care Convolutions Probability generating function Control charts

Gregory, S., Tan, D., Tilrico, M., Edwardson, N., & Gamm, L. (2014). Bedside shift reports: What does the evidence say? Journal of Nursing Administration, 44(10), 541-545.

Bedside shift reports are viewed as an opportunity to reduce errors and important to ensure communication between nurses and communication. Models of bedside report incorporating the patient into the triad have been shown to increase patient engagement and enhance caregiver support and education. Nurse shift reports and nurse handovers are two of the most critical processes in patient care that can support patient safety and reduce medical errors in the United States. The evidence is clear that there are multiple benefits to models of BSR. The challenge for nurse executives is to identify a model for their organization and patient populations, ensure consistency in practice and implementation, set measurable indicators, support the adoption by clinical nurses, and adjust models as appropriate to attain and sustain the outcomes.

Kash, B., Spaulding, A., Gamm, L., & Johnson, C. (2014). Healthcare strategic management and the resource based view. Journal of Strategy and Management, 7(3), 251-264.

Post-traumatic stress disorder (PTSD) is associated with poor health but there is a gap between need and receipt of care.  CHOT researchers at NEU University developed a service location systems engineering model to help determine where to best locate and use in-person and video-based care to minimize access to care barriers, care outside the Veterans Affairs system, and total costs.  Their results suggest that in New England alone a potential $3,655,387 reduction in average annual total costs by shifting 9.73% of care to video-based treatment, with an average 12.6 miles travel distance for the remaining in-person care.  The researchers based their service location systems engineering model on 2010 to 2020 projected care needs for veterans across New England in order to determine the optimal geographic locations and capacities for in-person care for veterans with PTSD across the New England VA network (VISN-1) and where instead video-based care would be advantageous over either expensive within-system capacity expansion or fee-based external care, if even feasible.  They found that access to care was a particular concern for veterans who were unable to readily access PTSD treatment, such as those living in rural environments. In such cases, new treatment modalities such as tele-health (i.e., via video conference) could be considered. Such treatments may actually be preferred by some veterans given it increased convenience and reduced privacy concerns.

Keywords: Strategy implementation, Resource based view, Healthcare strategic planning

Kang, H., Nembhard, H.B., Rafferty, C., & DeFlitch, C. Patient flow in the emergency department: A classification and analysis of admission process policies. To appear in Annals of Emergency Medicine, 2014.

This research study is aimed to investigate the effect of admission process policies on patient flow in the emergency department (ED). To do this, an advisory panel group was surveyed to determine approaches to admission process policies and classified them as admission decision is made by the team of providers (attending physicians, residents, physician extenders) (type 1) or attending physicians (type 2) on the admitting service, team of providers (type 3), or attending physicians (type 4) in the ED. A discrete-event simulation models of patient flow were developed to evaluate the potential effect of the 4 basic policy types and 2 hybrid types.  When comparing the current admission process policy (type 1), the alternatives were all effective in reducing the length of stay of admitted patients by 14% to 26%. In other words, patients may spend 1.4 to 2.5 hours fewer on average in the ED before being admitted to internal medicine under a new admission process policy. The improved flow of admitted patients decreased both the ED length of stay of discharged patients and the overall length of stay by up to 5% and 6.4%, respective. In conclusion, an efficient admission process can reduce waiting times for both admitted and discharged ED patients.

Kash, B. A., Zhang, Y., Cline, K. M., Menser, T., & Miller, T. R. (2014). The perioperative surgical home (PSH): A comprehensive review of US and non‐US studies shows predominantly positive quality and cost outcomesMilbank Quarterly92(4), 796-821.

Cardiac arrest results in numerous deaths and serious morbidities in hospital settings every year.  Rapid response teams (RRT), consisting of interdisciplinary team members, can be called prior to a patient’s need for resuscitation during cardiac arrest. Determining the effectiveness of these teams has been a concern to researchers as well as to the hospitals implementing these teams. In this research study, total personnel costs associated with different RRTs were analyzed, and RRT effectiveness was compared to existing code blue or cardiac arrest teams. The new RRT models demonstrated effectiveness in reducing the number of cardiac arrests as compared to the standard care.  The other strategies provide an additional layer of support for those who might experiences a cardiac arrest.  The results of the cost-effectiveness model revealed teams who shared personnel between the RRT and the code blue team were most cost effective.  Compared to RRTs/EMTs comprised of the same members as the code blue or cardiac arrest team were more expensive than the standard care using the base case estimates. The consideration of team composition and the impact different teams have on patient safety and patient outcomes seem to be an obvious oversight. This is particularly true in light of the amount of team training, team satisfaction, team outcome, and team culture studies which exist in management and health care.

Keywords: Perioperative management, enhanced recovery after surgery, early patient engagement, care coordination

Lee, E.K., Kang, H.J., Cinalioglu, D., Davis, L., & Frank, G.  (2014). Systems modeling and simulation for reducing medication errorsIEEE Biomedical and Health Informatics.

While the American Academy of Emergency Medicine encourages hospitals to develop policies that reduce the interval for completion of inpatient admissions orders, CHOT researchers at PSU found that when reviewing existing literature, rigorous investigation of the admission process had been largely overlooked.  To provide a framework as a precursor to actual changes in policy, CHOT researchers developed six simulation models that represented each admission process policy and evaluated their potential effect on patient flow.  They found that all the models were effective in reducing the length of stay of admitted patients by 14% to 16% compared to the current admission process policy. In practical terms, patients may spend 1.4 to 2.5 hours fewer on average in the ED before being admitted to internal medicine under a new admission process policy. The simulation results also showed that the improved flow of admitted patients decreased both the ED length of stay of discharged patients and the overall length of stay by up to 5% and 6.4%, respectively.  Through the classification of existing admission process policies and the analysis of simulation results, this study contributed to demonstrating the potential value of leveraging admission process polices and developing a framework for pursuing these polices.  The study also demonstrated that small changes in procedure can make importance changes in patient flow.

Keywords: Strategic management framework

McCaughey, D., McGhan, G., Walsh, E. M., Rathert, C., & Belue, R. (2014). The relationship of positive work environments and workplace injury: Evidence from the national nursing assistant survey. Health Care Management Review, 39(1), 75-88.

With estimates of a 51% growth in the number of nursing assistants needed by 2016, there is a critical need to examine workplace factors that negatively contribute to the recruitment and retention of nursing assistants. Studies have shown that high demands, physical stress, and chronic workforce shortages contribute to a working environment that fosters one of the highest workforce injury rates in the United States.  The aim of this study was to explore the relationship between nursing assistant injury rates and key outcomes, such as job satisfaction and turnover intent, while exploring workplace factors, such as injury prevention training, supervisor support, and employee engagement that can decrease the rates of workplace injury.  Findings included nursing assistants who experience job-related injuries have lower levels of job satisfaction, increased turnover intentions, and are less likely to recommend their facility as a place to work or seek care services. It was also found that nursing assistant injury rates are related to employee ratings of injury prevention training, supervisor support, and employee engagement. NAs with multiple injuries (>2) were 1.3–1.6 times more likely to report being injured at work than NAs who had not been injured when supervisor support, employee engagement, and training ratings were low.  The practical implications from this study are that health care organizations can use to better understand how workplace injuries occur and insight into ways to reduce the current staggering rate of on-the-job injuries occurring in health care workplaces were offered in this study. The findings also offer empirical support for an extension of the National Institute for Occupational Health and Safety/National Occupational Research Agenda Work Organization Framework for Occupational Illness and Injury.

Menser, T. L., Radcliff, T. A., & Schuller, K. A. (2014). Implementing a medical screening and referral program for rural emergency departmentsThe Journal of Rural Health, 31(2), 126-134.

Emergency Department (ED) overcrowding due to non-emergent use is an ongoing concern. In 2011, a regional health system that primarily serves rural communities in Texas instituted a new program to medically screen and refer non-emergent patients to nearby affiliated rural health clinics (RHCs). The purpose of this study is to describe the program goals, process, and early implementation experiences at 2 sites that adopted the program before wider implementation within the rural health system. This study found out that the program, as implemented, aligned with initial program goals, but it was dependent on ED screening staff and RHC availability. Stakeholders reported lessons learned related to training, staff buy-in, Emergency Medical Treatment and Labor Act (EMTALA), and intra-organizational cooperation. In conclusion, the system was able to leverage excess capacity of affiliated RHCs to accommodate low-acuity patients referred from the ED and may lead to improvements in Triple Aim goals of increased patient satisfaction, better population health and outcomes, and lower per capita costs.

Keywords: Emergency medicine, medical screening, organizational change, quality improvement, rural health clinic

Milburn, A. B., Hewitt, M., Griffin, P., & Savelsbergh, M. (2014). The value of remote monitoring systems for treatment of chronic disease. IIE Transactions on Healthcare Systems Engineering, 4(2), 65-79.

Caring for patients with chronic illnesses is costly.  75% of US healthcare spending can be attributed to treating chronic conditions.  Several components contribute to the cost of treating chronic disease. There are the direct costs associated with treating the disease, and those associated with complications that arise as a result of the disease. There are also indirect costs associated with loss of productivity and quality of life. Technological advances in remote monitoring systems (RMS) may provide a more cost effective and less labor-intensive way to manage chronic disease by focusing on preventive measures and continuous monitoring instead of emergency care and hospital admissions. In this paper, we develop a model that estimates the total potential savings associated with broad introduction of RMS, and considers how capacity constraints and fairness concerns should impact RMS allocation to target populations. The computational study shows that, under reasonable assumptions, broad introduction of RMS will lead to substantial cost savings for target populations. The study provides proof of concept that the model could serve as a useful tool for policy makers, as it allows a decision maker to modify cost, risk, and capacity parameters to determine reasonable policies for the allocation of and reimbursement for RMS.

Munoz, D., Nembhard, H. B., & Kraschnewski, J. (2014). Quantifying complexity in translational research: An integrated quality function deployment – analytical hierarchy process methodology. International Journal of Health Care Quality Assurance, 27(8), 760-776.

The National Institute of Health (NIH) managers explicitly made translational research a central priority in their 2003 medical research roadmap.  This research study quantifies complexity in translational research. The impact of major operational steps and technical requirements (TR) is calculated with respect to their ability to accelerate moving new discoveries into clinical practice.  The research findings were that the evidence generated was valuable for understanding various components in translational research. Particularly, collaboration networks, multidisciplinary team capacity and community engagement are crucial for translating new discoveries into   . The practical implications from this research are that the integrated QFD-AHP framework provides evidence that could be helpful to generate agreement, develop guidelines, allocate resources wisely, identify benchmarks and enhance collaboration among similar projects.

Keywords: Translational research; Quality Function Deployment; Analytic hierarchy process; Evidence-based; Resource allocation

Musdal, H., Shiner, B., Chen, T., Ceyhan, M.E., Waatts, B.V., & Benneyan, J. (2014). In-person and video-based post-traumatic stress disorder treatment for veterans: A location-allocation model. Military Medicine, 179(2), 150-156.

Post-traumatic stress disorder (PTSD) is associated with poor health but there is a gap between need and receipt of care. It is useful to understand where to optimally locate in-person care and where video-based PTSD care would be most useful to minimize access to care barriers, care outside the Veterans Affairs system, and total costs. We developed a service location systems engineering model based on 2010 to 2020 projected care needs for veterans across New England to help determine where to best locate and use in-person and video-based care. This analysis determined specific locations and capacities of each type of PTSD care relative to patient home locations to help inform allocation of mental health resources. Not surprisingly Massachusetts, Connecticut, and Rhode Island are well suited for in-person care, whereas some rural areas of Maine, Vermont, and New Hampshire where in-patient services are infeasible could be better served by video-based care than external care, if the latter is even available. Results in New England alone suggest a potential $3,655,387 reduction in average annual total costs by shifting 9.73% of care to video-based treatment, with an average 12.6 miles travel distance for the remaining in-person care.

Peck, J. S., Benneyan, J. C., Nightingale, D. J., & Gaehde, S. A. (2014). Characterizing the value of predictive analytics in facilitating hospital patient flow. IIE Transactions on Healthcare Systems Engineering, 4(3), 135-143.

Prediction continues to grow as a recommended tool for enabling effective and efficient healthcare. The Institute of Medicine (2001) includes the “anticipation of needs” as one of the “new rules” for redesigning and improving care. We apply discrete event simulation to characterize the patient flow affects of using admission predictions and current state information, generated in an Emergency Department (ED), to influence the prioritization of inpatient unit (IU) physicians between treating and discharging IU patients. Shared information includes crowding levels and total expected bed need based on the sum of individual patients’ imperfect admission predictions and perfect admission predictions). It is found that sharing prediction and crowding information to influence inpatient staff priorities, using specific information sensitivity schedules, can result in statistically significant  (p_ 0.05) reductions in boarding time (between 11.69% and 18.38% compared to baseline performance). The range of improvement is dependent on varying simulated hospital configurations.

Keywords: Patient flow, emergency department crowding, inpatient unit, simulation

Spaulding, A., & Ohsfeldt, R. L. (2014). Rapid response teams and team composition: A cost-effectiveness analysis. Nursing Economics, 32(4), 194-203.

Cardiac arrest results in numerous deaths and serious morbidities in hospital settings every year.  Rapid response teams (RRT), consisting of interdisciplinary team members, can be called prior to a patient’s need for resuscitation during cardiac arrest. Determining the effectiveness of these teams has been a concern to researchers as well as to the hospitals implementing these teams. In this research study, total personnel costs associated with different RRTs were analyzed, and RRT effectiveness was compared to existing code blue or cardiac arrest teams. The new RRT models demonstrated effectiveness in reducing the number of cardiac arrests as compared to the standard care.  The other strategies provide an additional layer of support for those who might experiences a cardiac arrest.  The results of the cost-effectiveness model revealed teams who shared personnel between the RRT and the code blue team were most cost effective.  Compared to RRTs/EMTs comprised of the same members as the code blue or cardiac arrest team were more expensive than the standard care using the base case estimates. The consideration of team composition and the impact different teams have on patient safety and patient outcomes seem to be an obvious oversight. This is particularly true in light of the amount of team training, team satisfaction, team outcome, and team culture studies which exist in management and health care.

Spaulding, A., Gamm, L., & Menser, T. (2014). Physician engagement: Strategic considerations among leaders at a major health systemHospital Topics92(3), 66-73.

Currently, steps toward pay-for performance, value-based purchasing, bundled payment options, Accountable Care Organizations (ACOs), and reductions in preventable readmissions contribute to increased interest among hospitals in physician engagement. However, improving physician engagement continues to be a major challenge for hospitals. Challenges often exist due to cultural differences between hospitals and physician practices, perceptions of the correct care referent (population vs. individual) and flexibility in patient care versus adherence to specific efficiency and quality standards.  This study focuses on strategic considerations among current leaders—administrators and physician leaders—within a health system actively pursuing increased physician engagement. In particular, it focuses on factors they identify as critical to these efforts. The results show that health system leaders are not unaware of challenges in the engagement of physicians. They tend to align their likelihood of success with building and maintaining relationships with physicians in terms of carefully listening to physician concerns and building positive physician experiences in working with hospital staff, including effective multidisciplinary care teams.  The emphasis on executive level management and physician teams and multi-professional care teams suggests, however, that the term accountability may be better applied with the organization as a whole as the referent rather than the physicians as the target of management control.

Keywords: Physician alignment, physician engagement, success factors

Spaulding, A., Gamm, L., Kim, J., & Menser, T. (2014). Multiproject interdependencies in health systems management: A longitudinal qualitative studyHealth Care Management Review39(1), 31-40.

A health care organization often engages in the simultaneous implementation of multiple organization change initiatives. However, the degree to which these initiatives are implemented and can be enhanced based on their interdependencies is an open question. How organizations and the change initiatives they pursue might benefit from more careful examination of potential interdependencies among projects was explored in this article. The research study aimed to introduce a multi-project management conceptualization that stresses project interdependencies and suggests synergies can be found to enhance overall project and organizational performance. It examines this conceptualization in the context of a health system pursuing several major initiatives to capture insights into the nature of such interdependencies. The implementation of an electronic medical record (EMR) is empirically identified as the most central among multiple projects based on other projects dependencies on the EMR. This reinforces the depiction of the EMR as a central organizational focus.

Keywords: Absorptive capacity, electronic medical record, multiproject management

Benneyan, J. C., & Bond, C. (2013). Systems Engineering Approaches For Improving Reusable Medical Equipment Reprocessing Processes. International Journal of Innovation and Technology Management, 10(03), 1340009.

Ferris, T. K. (2013). Evidence-based design and the fields of human factors and ergonomics: Complementary systems-oriented approaches to healthcare design. HERD: Health Environments Research & Design Journal, 6(3), 3-5.

Ferris, T. K., & Shepley, M. M. (2013). Encouraging developments in incubator design. Journal of Perinatology, 33(12), 990-990.

Ferris, T. K., & Shepley, M. M. (2013). The design of neonatal incubators: a systems-oriented, human-centered approach. Journal of Perinatology, 33, S24-S31.

Hagen, M. S., Jopling, J. K., Buchman, T. G., & Lee, E. K. (2013). Priority Queuing Models for Hospital Intensive Care Units and Impacts to Severe Case Patients. AMIA Annual Symposium Proceedings, 2013, 841″“850.

Hagen, M.S., Jopling, J.K., Buchman, T.G., & Lee, E.K. (2013). Advancing public health and medical preparedness with operations researchs.American Medical Informatics Association Annual Symposium Proceedings:841-850.

Kash, B. A., Spaulding, A., Gamm, L., & Johnson, C. E. (2013). Health care administrators’ perspectives on the role of absorptive capacity for strategic change initiatives: A qualitative study. Health care management review, 38(4), 339-348.

Kash, B.A., Gamm, L.D., & Spaulding, A.C. (2013). Absorptive capacity (ACAP) for transformation in healthcare: A framework for research. Change Management: An International Journal, 13(1), 1-13.

Kraschnewski, J.L., Sciamanna, C., Stuckey, H.L., Chuang, C.H., Lehman, E.B., Hwang, K.O., Sherwood, L.L., & Nembhard, H.B. (2013). A silent response to the obesity epidemic: Decline in US physician weight counseling. Medical Care, 51(2), 186-192.

Lee, E.K., Yuan, F., Zhou, R., Post, E., & Wright, M. (2013). Healthcare Analytics: Modeling and Optimizing Emergency Department Workflow. Encyclopedia of Business Analytics and Optimization.

Lee, E.K., Pietz, F., Benecke, B., Mason, J., & Burel, G. (2013). Advancing public health and medical preparedness with operations research. Interfaces, 43(1), 79-98.

Lee, E.K., Yuan, F. Templeton, A., Tao, R., Kiel, K, & Chu, J.C.H. (2013). Biological planning for high-dose rate brachytherapy: Applicastion to cervical cancer treatment. Interfaces, 43(5), 462-447.

Lee, E. K., Pietz, F., & Benecke, B. (2013). Service networks for public health and medical preparedness: medical countermeasures dispensing and large-scale disaster relief efforts. In Handbook of Operations Research for Homeland Security (pp. 167-196). Springer New York.

Peck, J.S., Gaehde, S.A., Nightingale, D.J., Gelman, D.Y., Huckins, D.S., Lemons, M.F., Dickson, E.W., & Benneyan, J.C. (2013). Generalizability of a simple approach for predicting hospital admission from an emergency department.Academic Emergency Medicine, 20(11), 1156-1163.

Pope, B., Mekaroonreung, M., Banerjee, A., & Johnson, A. (2013). Healthcare Systems. In The Handbook of Industrial and Systems Engineering (2nd ed.). CRC Press.

Ross, S. E., Radcliff, T. A., LeBlanc, W. G., Dickinson, L. M., Libby, A. M., & Nease, D. E. (2013). Effects of health information exchange adoption on ambulatory testing rates. Journal of the American Medical Informatics Association, 20(6), 1137-1142.

Schuller, K.A., Kash, B.A., Edwardson, N., & Gamm, L.D. (2013). Enabling and disabling factors in implementation of Studer Group’s evidence-based leadership initiative: A qualitative case study. Journal of Communication in Healthcare, 6(2), 90-99.

Schuller, K. A., Lin, S. H., Gamm, L. D., & Edwardson, N. (2013). Discharge Phone Calls: A Technique to Improve Patient Care during the Transition from Hospital to Home. Journal for Healthcare Quality. doi: 10.1111/jhq.12051

Watts, B.V., Shiner, B., Ceyhan, M.E., Musdal, H., Sinangil, S., Benneyan, J. (2013).Health systems engineering as an improvement strategy: A case example using location – allocation modelling. Journal for Healthcare Quality, 35(3), 35-40.

Alvarado, M. M., Ntaimo, L., Banerjee, A., & Kianfar, K. (2012). Reducing pediatric medication errors: A survey and taxonomy. IIE Transactions on Healthcare Systems Engineering, 2(2), 142-155.

Jordan, V., & Benneyan, J. (2012). Common Errors and Pitfalls in Using Control Charts in Healthcare. Statistical Methods in Healthcare, 268-285.

Lee, E. K., Wu, T. L., Goldstein, F., & Levey, A. (2012). Predictive Model for Early Detection of Mild Cognitive Impairment and Alzheimer’s Disease. In Optimization and Data Analysis in Biomedical Informatics (pp. 83-97). Springer New York.

Lee, E. K., Yuan, F., Hirsh, D. A., Mallory, M. D., & Simon, H. K. (2012). A Clinical Decision Tool for Predicting Patient Care Characteristics: Patients returning within 72 Hours in the Emergency Department. AMIA Annual Symposium Proceedings, 2012, 495″“504.

McComb, S. A., Banerjee, A., Mechler, K. K., & Morrow, R. B. (2012). Enhancing learning through an interprofessional project competition. The Journal of nursing education, 51(12), 706-709.

Park, J., Lee, E. K., Wang, Q., Li, J., Lin, Q., & Pu, C. (2012, August). Health-connect: An ontology-based model-driven information integration framework and its application to integrating clinical databases. In Information Reuse and Integration (IRI), 2012 IEEE 13th International Conference on (pp. 393-400). IEEE.

Peck, J. S., Benneyan, J. C., Nightingale, D. J., & Gaehde, S. A. (2012). Predicting Emergency Department Inpatient Admissions to Improve Same”day Patient Flow. Academic Emergency Medicine, 19(9), E1045-E1054.

Radcliff, T. A., Bobroff, L. B., Lutes, L. D., Durning, P. E., Daniels, M. J., Limacher, M. C., Janicke, D.M, Martin, A.D, & Perri, M. G. (2012). Comparing costs of telephone vs face-to-face extended-care programs for the management of obesity in rural settings. Journal of the Academy of Nutrition and Dietetics, 112(9), 1363-1373.

Radcliff, T., West, D., James, K., & Côté, M. (2012). Regression and data envelopment analysis methods to assess medical practice efficiency. In Economic Issues, Problems and Perspectives: Econometrics: New Research (pp. 121-134). Nova Science.

Schneider, J. E., Ohsfeldt, R. L., Scheibling, C. M., & Jeffers, S. A. (2012). Organizational boundaries of medical practice: the case of physician ownership of ancillary services. Health economics review, 2(1), 1-8.

Sen, A., Banerjee, A., Sinha, A. P., & Bansal, M. (2012). Clinical decision support: Converging toward an integrated architecture. Journal of biomedical informatics, 45(5), 1009-1017.

Vest, J. R., & Jasperson, J. S. (2012). How are health professionals using health information exchange systems? Measuring usage for evaluation and system improvement. Journal of medical systems, 36(5), 3195-3204.

Vest, J. R., Gamm, L. D., Ohsfeldt, R. L., Zhao, H., & Jasperson, J. S. (2012). Factors associated with health information exchange system usage in a safety-net ambulatory care clinic setting. Journal of medical systems, 36(4), 2455-2461.

Woodall, W. H., Adams, B. M., & Benneyan, J. C. (2012). The use of control charts in healthcare. Statistical Methods in Healthcare, 251-267.

Artzrouni, M., Begg, C., Chabiniok, R., Clairambault, J., Foss, A. J. E., Hargrove, J., … & Tindall, M. (2011). The first international workshop on the role and impact of mathematics in medicine: A collective account. American Journal of Translational Research, 3(5), 492.

Bell, S., Benneyan, J., Best, A., Birnbaum, D., Borycki, E.M., Gallagher, T.H., . . . Mazor, K.M. (2011). Mandatory public reporting: build it and who will come?Studies in health technology and informatics, 164, 346.

Bellamy, G. R., Bolin, J. N., & Gamm, L. D. (2011). Rural healthy people 2010, 2020, and beyond: the need goes on. Family & community health, 34(2), 182-188.

Bolin, J. N., Gamm, L., Vest, J. R., Edwardson, N., & Miller, T. R. (2011). Patient-centered medical homes: will health care reform provide new options for rural communities and providers?Family & Community Health, 34(2), 93-101.

Chen, B., Matis, T., & Benneyan, J. (2011). Improved one”sided control charts for the mean of a positively skewed population using truncated saddlepoint approximations. Quality and Reliability Engineering International, 27(8), 1043-1058.

Denton, B. T., Alagoz, O., Holder, A., & Lee, E. K. (2011). Medical decision making: open research challenges. IIE Transactions on Healthcare Systems Engineering, 1(3), 161-167.

Ferris, T. K., & Sarter, N. (2011). Continuously informing vibrotactile displays in support of attention management and multitasking in anesthesiology. Human Factors: The Journal of the Human Factors and Ergonomics Society, 53(6), 600-611.

Lee, E.K., Lee, H.R., & Quarshie, A. (2011). SEACOIN — An investigative tool for biomedical informatics researchers.American Medical Informatics Association 2011 Symposium Proceedings, 750-759.

Vest, J. R., & Miller, T. R. (2011). The association between health information exchange and measures of patient satisfaction. Appl Clin Inform, 2(4), 447-459.

Vest, J. R., Jasperson, J. S., Zhao, H., Gamm, L. D., & Ohsfeldt, R. L. (2011). Use of a health information exchange system in the emergency care of children. BMC medical informatics and decision making, 11(1), 78.

Vest, J. R., Zhao, H., Jaspserson, J., Gamm, L. D., & Ohsfeldt, R. L. (2011). Factors motivating and affecting health information exchange usage. Journal of the American Medical Informatics Association, 18(2), 143-149.

Benneyan, J.C., & Taseli, A. (2010). Exact and approximate probability distributions of evidence-based bundle composite compliance measures.Health Care Management Science, 13(3), 193-209.

Ferris, T. K., & Sarter, N. (2010). When content matters: The role of processing code in tactile display design. Haptics, IEEE Transactions on, 3(3), 199-210.

Hagen, M. S., & Lee, E. K. (2010). BIOSPIDA: A relational database translator for NCBI. In AMIA Annual Symposium Proceedings (Vol. 2010, p. 422). American Medical Informatics Association.

Kaskie, B., Obrizan, M., Cook, E. A., Jones, M. P., Liu, L., Bentler, S., Wallace, R.B, & Wolinsky, F. D. (2010). Defining emergency department episodes by severity and intensity: A 15-year study of Medicare beneficiaries. BMC health services research, 10(1), 173.

Lee, E.K., Mejia, A.F., Senior, T., & Jose, J. (2010). Improving patient safety through medical alert management: an automated decision tool to reduce alert fatigue.Paper presented at the American Medical Informatics Association Symposium, Washington D.C.

Lee, E.K. & Cha, K. (Mar, 2010). Automated data collection and integration for cancer treatment design and clinical quality evaluation investigations.2010 AMIA Summit on Clinical Research Informatics, San Francisco, CA.

Lee, E.K., Chen, C.H., Pietz, F., & Benecke, B. (2010). Disease propagation analysis and mitigation strategies for effective mass dispensing.American Medical Informatics Association 2010 Symposium Proceedings, 427-431.

Spaulding, A. C., Gamm, L. D., & Griffith, J. M. (2010). Studer Unplugged: Identifying Underlying Managerial Concepts. Hospital Topics, 88(1), 1-9.

Sturm, J.J., Hirsh, D.A., Lee, EK, Massey, R., Weselman, B., & Simon, H.K. (2010).Practice characteristics that influence nonurgent pediatric emergency department utilization.Academic Pediatrics, 10(1): 70-74.

Vest, J.R. (2010). More than just a question of technology: Factors related to hospitals’ adoption and implementation of health information exchange.International Journal of Medical Informatics, 79(12), 797-806.

Vest, J.R., & Gamm, L.D. (2010). Health information exchange: persistent challenges and new strategies.Journal of the American Medical Informatics Association, 17(3), 288-294.

Vest, J. R., & Jasperson, J. (2010). What should we measure? Conceptualizing usage in health information exchange. Journal of the American Medical Informatics Association, 17(3), 302-307.

Vest, J. R., Bolin, J. N., Miller, T. R., Gamm, L. D., Siegrist, T. E., & Martinez, L. E. (2010). Review: Medical homes:”Where you stand on definitions depends on where you sit”.Medical Care Research and Review, 67(4), 393-411.

Vest, J. R., Gamm, L. D., Oxford, B. A., Gonzalez, M. I., & Slawson, K. M. (2010).Determinants of preventable readmissions in the United States: a systematic review. Implementation Science, 5(1), 1-27.

Hameed, S., Ferris, T., Jayaraman, S., & Sarter, N. (2009). Using informative peripheral visual and tactile cues to support task and interruption management. Human Factors: The Journal of the Human Factors and Ergonomics Society, 51(2), 126-135.

Kash, B., Ohsfeldt, R., & Gamm, L. (2009). An attempt to forecast hospital market share using admission data. Journal of Healthcare Management, 54(1), 44-56.

Lee, E. K., & Wu, T. L. (2009). Disease Diagnosis: Optimization-Based Methods. In Encyclopedia of Optimization (pp. 753-784). Springer US.

Lee, E.K., Chen, C.H., Pietz, F., & Benecke, B. (2009). Modeling and optimizing the public health infrastructure for emergency response. Interfaces, 39(5), 476-490.

Ohsfeldt, R. L., Gandhi, S. K., & Fox, K. M. (2009). Medicare-eligible patients diagnosed with atherosclerosis: patterns in statin therapy and lipid monitoring. Current medical research and opinion, 25(6), 1403-1411.

Vest, J. R., & Gamm, L. D. (2009). A critical review of the research literature on Six Sigma, Lean and StuderGroup’s Hardwiring Excellence in the United States: the need to demonstrate and communicate the effectiveness of transformation strategies in healthcare. Implementation Science, 4(1), 35.

Vest, J. R. (2009). Health information exchange and healthcare utilization. Journal of medical systems, 33(3), 223-231.