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Virginia M. Miori, Daniel J. Miori and Brian W. Segulin

The authors have previously validated a design of the health-care supply chain which treats patients as inventory without loss of respect for the patients. This work…

Abstract

The authors have previously validated a design of the health-care supply chain which treats patients as inventory without loss of respect for the patients. This work continues examination of patients as inventory while addressing the dual objectives of reducing redundancy in services and creating greater efficiency in the health-care supply chain. Historical data is used to forecast health care needs in light of the increasingly specialized health-care professionals, which have resulted in much more flexible and expensive supply chains. The lack of common data storage, or electronic medical records (EMRs), has created a need for redundancy (or rework) in medical testing. The use of EMR will also enhance our ability to forecast needs in the future. We perform simulations using SigmaFlow software to address our goals relative to the resource constraints, monetary constraints, and the overall culture of the medical supply chain. The simulation outcomes lead us to recommendations for data warehousing as well as providing mechanisms, like inventory postponement strategies, to establish structures for more efficiency, and reduced flexibility in the supply chains.

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Advances in Business and Management Forecasting
Type: Book
ISBN: 978-0-85724-959-3

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Virginia M. Miori, Kathleen Campbell Garwood and Catherine Cardamone

This is the second in a series of papers focused on alcohol and substance abuse rehabilitation centers. Centers face the ongoing challenge of validating outcomes to meet…

Abstract

This is the second in a series of papers focused on alcohol and substance abuse rehabilitation centers. Centers face the ongoing challenge of validating outcomes to meet the burden of evidence for insurance companies. In the first paper, data mining was used to establish baseline patterns in treatment success rates, for the Futures: Palm Beach Rehabilitation Center, that have a direct impact on a client’s ability to receive insurance coverage for treatment programs. In this paper, we examine 2016 outcomes and report on facility efficacy, alumni progression and sobriety, and forecast treatment success rates (short and long term) in support of client insurability. Data collection has been standardized and includes admissions data, electronic medical records data, satisfaction survey data, post-discharge survey data, Centers for Disease Control (CDC) data, and demographic data. Clustering, partitioning, ANOVA, stepwise regression and stepwise Logistic regression are applied to the data to determine statistically significant drivers of treatment success.

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Advances in Business and Management Forecasting
Type: Book
ISBN: 978-1-78743-069-3

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Virginia M. Miori and Daniel J. Miori

Palliative care concentrates on reducing the severity of disease symptoms, rather than providing a cure. The goal is to prevent and relieve suffering and to improve the…

Abstract

Palliative care concentrates on reducing the severity of disease symptoms, rather than providing a cure. The goal is to prevent and relieve suffering and to improve the quality of life for people facing serious, complex illness. It is therefore critical in the palliative environment that caregivers are able to make recommendations to patients and families based on reasonable assessments of amount of suffering and quality of life. This research uses statistical methods of evaluation and prediction as well as simulation to create a multiple criteria model of survival rates, survival likelihoods, and quality of life assessments. The results have been reviewed by caregivers and are seen to provide a solid analytical base for patient recommendations.

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Advances in Business and Management Forecasting
Type: Book
ISBN: 978-0-85724-201-3

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Virginia M. Miori

The challenge of truckload routing is increased in complexity by the introduction of stochastic demand. Typically, this demand is generalized to follow a Poisson…

Abstract

The challenge of truckload routing is increased in complexity by the introduction of stochastic demand. Typically, this demand is generalized to follow a Poisson distribution. In this chapter, we cluster the demand data using data mining techniques to establish the more acceptable distribution to predict demand. We then examine this stochastic truckload demand using an econometric discrete choice model known as a count data model. Using actual truckload demand data and data from the bureau of transportation statistics, we perform count data regressions. Two outcomes are produced from every regression run, the predicted demand between every origin and destination, and the likelihood that that demand will occur. The two allow us to generate an expected value forecast of truckload demand as input to a truckload routing formulation. The negative binomial distribution produces an improved forecast over the Poisson distribution.

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Advances in Business and Management Forecasting
Type: Book
ISBN: 978-1-84855-548-8

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Virginia M. Miori

Truckload routing has always been a challenge. This paper explores the development of continuous flow truckload routes, which resemble less than truckload routes, and a…

Abstract

Truckload routing has always been a challenge. This paper explores the development of continuous flow truckload routes, which resemble less than truckload routes, and a new way to formulate the truckload routing problem (TRP). Rather than view the problem as a succession of origin/destination pairs, we look at the problem as a series of routing triplets. This enables us to use alternate solution methods, which may result in greater efficiency and improved solutions.

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Applications of Management Science: In Productivity, Finance, and Operations
Type: Book
ISBN: 978-0-85724-999-9

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Virginia M. Miori, Zhenpeng Miao and Yingdao Qu

This is the third in a series of papers aimed at providing models effective in predicting the degree of pain and discomfort in canines. The first two papers provided…

Abstract

This is the third in a series of papers aimed at providing models effective in predicting the degree of pain and discomfort in canines. The first two papers provided benchmarking and examination of dogs suffering from osteoarthritis (OA). In this chapter, we extend the study to include dogs suffering from OA, sarcoma, and oral mucositis (a side effect of chemotherapy and radiation treatments). The R programming language and SAS JMP are used to clean data, generate ANOVA, LSR regression, decision tree, and nominal logistic regression models to predict changes in activity levels associated with the progression of arthritis. The predictive models provide a diagnostic basis for determining the degree of disease in a dog (based on demographics and activity levels) and provide forecasts that assist in establishing appropriate medication dosages for suffering dogs.

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Advances in Business and Management Forecasting
Type: Book
ISBN: 978-1-78635-534-8

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Advances in Business and Management Forecasting
Type: Book
ISBN: 978-1-78743-069-3

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Virginia M. Miori, James Algeo, Brian Segulin and Dorothy Cimino Brown

Evaluating pain and discomfort in animals is difficult at best. Veterinarians believe however, that they can establish a proxy for estimating levels of pain and discomfort…

Abstract

Evaluating pain and discomfort in animals is difficult at best. Veterinarians believe however, that they can establish a proxy for estimating levels of pain and discomfort in canines by observing variations in their activity levels. Sufficient research has been conducted to justify this assertion, but little has been conducted to analyze the volumes of activity data collected. We present the first of a series of analyses aimed at ultimately presenting an effective predictive tool for canine pain and discomfort levels. In this chapter, we perform analyses on a dataset of normal (control) dogs, containing almost 3 million records. The forecasting analyses incorporated multiple polynomial regression models with transcendental transformations and ARIMA models to provide effective determination and prediction of baseline normal canine activity levels.

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Advances in Business and Management Forecasting
Type: Book
ISBN: 978-1-78190-331-5

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Advances in Business and Management Forecasting
Type: Book
ISBN: 978-0-85724-201-3

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Advances in Business and Management Forecasting
Type: Book
ISBN: 978-0-85724-959-3

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