04110nam a2200325 i 4500 CSPC 20250905164117.0 250905s2023 flua b 001 0 eng d 9781032068459 CSPC eng CSPC rda R858 .H43 2023 362.1028 H349 23 Healthcare analytics : emergency preparedness for COVID-19 / edited by Edward M. Rafalski and Ross M. Mullner. First edition. Boca Raton, Florida : CRC Press, 2023. xiv, 289 pages : illustrations ; 24 cm. rdacontent text rdamedia unmediated rdacarrier volume Includes bibliographical references and index. Introduction -- Section 1. Epidemiology and analytics -- What is an epidemic, a pandemic? -- A brief history of pandemics -- The healthcare continuum -- The fog of war and data -- Sources of data/modeling -- Quantifying and responding to COVID's financial and operational impact -- Section 2. State case studies -- Measuring and addressing healthcare employee well-being in an Alabama health system during COVID-19 -- Colorado state case study -- Case study: a Florida COVID-19 dashboard -- State case study: Illinois -- Tennessee case study -- Regional modeling -- Section 3. Topics -- Healthcare analytics: the effects of the pandemic on behavioral health -- Digital transformation in healthcare: how COVID-19 was an agent for rapid change -- Telehealth -- The COVID-19 pandemic and development of drugs and vaccinations -- Value of health information exchanges to support public health reporting -- Conclusion -- Epilogue. "The first COVID-19 case in the US was reported on January 20, 2020. As the first cases were being reported in the US, Washington State became a reliable source not just for hospital bed demand based on incidence and community spread but also for modeling the impact of skilled nursing facilities and assisted living facilities on hospital bed demand. Various hospital bed demand modeling efforts began in earnest across the United States in university settings, private consulting and health systems. Nationally, the University of Washington Institute of Health Metrics and Evaluation seemed to gain a footing and was adopted as a source for many states for its ability to predict the epidemiological curve by state, including the peak. This book therefore addresses a compelling need for documenting what has been learned by the academic and professional healthcare communities in healthcare analytics and disaster preparedness to this point in the pandemic. What is clear, at least from the US perspective, is that the healthcare system was unprepared and uncoordinated from an analytics perspective. Learning from this experience will only better prepare all healthcare systems and leaders for future crisis. Both prospectively, from a modeling perspective and retrospectively from a root cause analysis perspective, analytics provide clarity and help explain causation and data relationships. A more structured approach to teaching healthcare analytics to students, using the pandemic and the rich dataset that has been developed, provides a ready-made case study from which to learn and inform disaster planning and preparedness. The pandemic has strained the healthcare and public health systems. Researchers and practitioners must learn from this crisis to better prepare our processes for future pandemics, at minimum. Finally, government officials and policy makers can use this data to decide how best to assist the healthcare and public health systems in crisis." -- back cover. Medical informatics United States. Medical care United States Data processing. COVID-19 (Disease) United States Data processing. Rafalski, Edward M., editor. Mullner, Ross M., editor. ddc 0 BK 23 362.1028 H349 GRD 2023 0 0 ddc 0 0 CSPC CSPC GRD 2025-09-05 0 GRD 362.1028 H349 2023 030151 2025-09-05 16:37:26 1-1 2025-09-05 BK 30394 30394