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Essential analytics for hospital man...

Calichman, Murray V.

Essential analytics for hospital managersa guide to statistical problem solving /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Essential analytics for hospital managersby Murray V. Calichman.
Reminder of title:	a guide to statistical problem solving /
Author:	Calichman, Murray V.
Published:	Cham :Springer International Publishing :2019.
Description:	ix, 72 p. :ill., digital ;24 cm.
Contained By:	Springer eBooks
Subject:	HospitalsAdministration
Online resource:	https://doi.org/10.1007/978-3-030-16365-5
ISBN:	9783030163655$q(electronic bk.)

Essential analytics for hospital managersa guide to statistical problem solving /
Calichman, Murray V.

Essential analytics for hospital managersa guide to statistical problem solving /[electronic resource] :by Murray V. Calichman. - Cham :Springer International Publishing :2019. - ix, 72 p. :ill., digital ;24 cm. - SpringerBriefs in health care management and economics,2193-1704. - SpringerBriefs in health care management and economics..

Work Simplification: A Method to Improve Processes - A Work Flow Diagram, A Little Logic -- The Linen Multiplier: Derivation of the Linen Multiplier - Simple Mathematics, Simple Logic -- The Emergency Room Holding Area: How Many Beds - The Use of Averages, Standard Deviations and Confidence Levels -- Determining "Par" Levels for Patient Supply Items: How Many Supply Items - The Use of Averages, Standard Deviations and Confidence Levels -- Merging Staffing Standards with a Patient Classification System: The Use of Weighted Averages -- Productivity & Cost Application: An Analytics Reporting Program for Department Managers and Administrators -- An CCU Bed Expansion: How many Beds - Use of Poisson Arrival Rates and Summed Poisson with Truncated Data -- Inventory Management: The Minimization of the Total Costs of Ordering and Holding Supplies -- Forecasting Resource Needs: The Use of Trend Lines and Seasonality -- Computer Simulation: Determining an Emergency Department Trigger (to Enact a Plan of Action) -- Use of Linear Programming: To Maximize Net Revenue (Optimum Pricing) -- Use of Linear Programming: To Eliminate Hospital Overcrowding (Optimum O.R. Scheduling)

This book provides practical applications of statistical and mathematical concepts to resolve common issues in hospital management. Each chapter discusses a key component of hospital operations, such as maximizing hospital profitability through pricing optimization, forecasting facility requirements from historical data, and determining optimal patient schedules to fully utilize hospital resources in order to eliminate over-crowding in the emergency department. Structured by the degree of mathematical complexity, this professional book utilizes problem-solving methodologies ranging from basic statistical concepts (means and standard deviations) to more advanced statistics (Poisson distributions and queuing theory) Concluding with computer applications and simulations, the practical examples will help hospital managers to optimally and innovatively make use of linear programming. The book's main goal is to make hospital personnel more aware of the benefits of management science methodologies that are not usually employed in today's hospitals.

ISBN: 9783030163655$q(electronic bk.)

Standard No.: 10.1007/978-3-030-16365-5doiSubjects--Topical Terms:

699141
Hospitals
--Administration

LC Class. No.: RA971 / .C355 2019

Dewey Class. No.: 362.11068

Essential analytics for hospital managersa guide to statistical problem solving /
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520 $a This book provides practical applications of statistical and mathematical concepts to resolve common issues in hospital management. Each chapter discusses a key component of hospital operations, such as maximizing hospital profitability through pricing optimization, forecasting facility requirements from historical data, and determining optimal patient schedules to fully utilize hospital resources in order to eliminate over-crowding in the emergency department. Structured by the degree of mathematical complexity, this professional book utilizes problem-solving methodologies ranging from basic statistical concepts (means and standard deviations) to more advanced statistics (Poisson distributions and queuing theory) Concluding with computer applications and simulations, the practical examples will help hospital managers to optimally and innovatively make use of linear programming. The book's main goal is to make hospital personnel more aware of the benefits of management science methodologies that are not usually employed in today's hospitals.
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