Healthcare's Out Sick: Predicting a Cure - Solutions That Work, Predictive Analytic Modeling, Decision Making, Innovations and Precision, Correct the Broken Healthcare Delivery System

Healthcare's Out Sick: Predicting a Cure - Solutions That Work, Predictive Analytic Modeling, Decision Making, Innovations and Precision, Correct the Broken Healthcare Delivery System

Gary D. Miner , Linda Miner , Darrell L. Dean
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Sep 30, 2021 · English · Paperback (312 pages)
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Book Details

Format Paperback
Pages 312
Language English
Published Sep 30, 2021
Publisher Productivity Press
Edition 1
ISBN-10 1032178426
ISBN-13 9781032178424

Description

This insightful examination delves into the intricate challenges facing the healthcare delivery system, offering a fresh perspective on the pressing need for innovation and reform. The authors present a compelling case for utilizing predictive analytic modeling as a pivotal tool to engineer effective solutions. By highlighting how data-driven decision-making can transform healthcare practices, they emphasize the potential to enhance patient outcomes and streamline efficiency.

Throughout the narrative, readers are invited to explore ways to correct the failures of the existing healthcare framework. With an emphasis on practicality, the authors outline various innovative strategies designed to address systemic issues, making it clear that transformation is not just possible but necessary.

In their call for precision and thoughtful intervention, the Miners and Dean blend real-world examples with theoretical insights, showcasing the tangible benefits of adopting these advanced methodologies. As they lay out a path toward a reimagined healthcare landscape, the book serves as both a guide and an inspiration for practitioners and policymakers alike.

With a focus on collaboration and shared accountability, this work advocates for a collective effort in pursuing a healthier future. It resonates with anyone invested in the evolution of healthcare, making a strong argument for harnessing the power of data to drive meaningful change.
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