ISBN: 9798193088752 - the definitive reference to healthcare analytics: data strategy, predictive modeling and executive dashboard (6 risultati)

Taschenbuch. Condizione: Neu. Neuware - Turn healthcare data into clearer insights, stronger strategies, and more informed decisions. Healthcare organizations generate enormous amounts of information every day from patient encounters and clinical outcomes to staffing, financial performance, utilization, quality measures, operational activity, and population-health data. The challenge is no longer simply collecting data. The real challenge is knowing \*what the data means, how to analyze it, how to communicate the findings, and how to turn those findings into useful decisions.\* \*\*The Definitive Reference to Healthcare Analytics\*\* provides a practical framework for understanding how healthcare data can support operational improvement, predictive analysis, strategic planning, performance management, and executive decision-making. This reference brings together the major concepts professionals need to understand when working with healthcare analytics. Inside, readers will explore: - Healthcare Data Strategy>- Data Governance and Quality>- Healthcare Analytics Foundations>- Predictive Modeling>- Performance Measurement>- Executive Dashboards>- Healthcare Forecasting>- Quality and Patient Outcomes>- Financial and Operational Analytics>- Population Health Analytics>- Data Visualization>- Analytical Decision-MakingDevelop a structured approach to moving from a business question to data collection, analysis, interpretation, communication, and action. …

Paperback. Condizione: new. Paperback. Turn healthcare data into clearer insights, stronger strategies, and more informed decisions. Healthcare organizations generate enormous amounts of information every day from patient encounters and clinical outcomes to staffing, financial performance, utilization, quality measures, operational activity, and population-health data. The challenge is no longer simply collecting data. The real challenge is knowing *what the data means, how to analyze it, how to communicate the findings, and how to turn those findings into useful decisions.* **The Definitive Reference to Healthcare Analytics** provides a practical framework for understanding how healthcare data can support operational improvement, predictive analysis, strategic planning, performance management, and executive decision-making. This reference brings together the major concepts professionals need to understand when working with healthcare analytics. Inside, readers will explore: - Healthcare Data StrategyUnderstand how organizations can structure data initiatives around meaningful business, clinical, operational, and strategic objectives. - Data Governance and QualityExplore the importance of data accuracy, consistency, completeness, standardization, stewardship, and responsible data management. - Healthcare Analytics FoundationsBuild a practical understanding of descriptive, diagnostic, predictive, and prescriptive analytics and how each approach can support different organizational questions. - Predictive ModelingExamine the concepts behind forecasting, risk prediction, pattern recognition, probability, model interpretation, and healthcare decision support. - Performance MeasurementLearn how healthcare organizations can use meaningful indicators to monitor quality, efficiency, utilization, financial performance, and operational results. - Executive DashboardsUnderstand how dashboards can transform complex datasets into concise visual information that supports leadership decisions. - Healthcare ForecastingExplore how historical patterns and analytical methods can support planning for demand, capacity, staffing, utilization, and resources. - Quality and Patient OutcomesConnect healthcare analytics with quality improvement, patient safety, outcome measurement, and performance management. - Financial and Operational AnalyticsExamine how data can help organizations understand costs, revenue, productivity, resource utilization, and operational performance. - Population Health AnalyticsExplore how aggregated healthcare information can support identification of trends, risks, utilization patterns, and opportunities for intervention. - Data VisualizationLearn why effective visualization matters and how charts, graphs, scorecards, and dashboards can communicate information more efficiently. - Analytical Decision-MakingDevelop a structured approach to moving from a business question to data collection, analysis, interpretation, communication, and action. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. …

PAP. Condizione: New. New Book. Shipped from UK. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.

PAP. Condizione: New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.

Condizione: New. Print on Demand.

Paperback. Condizione: new. Paperback. Turn healthcare data into clearer insights, stronger strategies, and more informed decisions. Healthcare organizations generate enormous amounts of information every day from patient encounters and clinical outcomes to staffing, financial performance, utilization, quality measures, operational activity, and population-health data. The challenge is no longer simply collecting data. The real challenge is knowing *what the data means, how to analyze it, how to communicate the findings, and how to turn those findings into useful decisions.* **The Definitive Reference to Healthcare Analytics** provides a practical framework for understanding how healthcare data can support operational improvement, predictive analysis, strategic planning, performance management, and executive decision-making. This reference brings together the major concepts professionals need to understand when working with healthcare analytics. Inside, readers will explore: - Healthcare Data StrategyUnderstand how organizations can structure data initiatives around meaningful business, clinical, operational, and strategic objectives. - Data Governance and QualityExplore the importance of data accuracy, consistency, completeness, standardization, stewardship, and responsible data management. - Healthcare Analytics FoundationsBuild a practical understanding of descriptive, diagnostic, predictive, and prescriptive analytics and how each approach can support different organizational questions. - Predictive ModelingExamine the concepts behind forecasting, risk prediction, pattern recognition, probability, model interpretation, and healthcare decision support. - Performance MeasurementLearn how healthcare organizations can use meaningful indicators to monitor quality, efficiency, utilization, financial performance, and operational results. - Executive DashboardsUnderstand how dashboards can transform complex datasets into concise visual information that supports leadership decisions. - Healthcare ForecastingExplore how historical patterns and analytical methods can support planning for demand, capacity, staffing, utilization, and resources. - Quality and Patient OutcomesConnect healthcare analytics with quality improvement, patient safety, outcome measurement, and performance management. - Financial and Operational AnalyticsExamine how data can help organizations understand costs, revenue, productivity, resource utilization, and operational performance. - Population Health AnalyticsExplore how aggregated healthcare information can support identification of trends, risks, utilization patterns, and opportunities for intervention. - Data VisualizationLearn why effective visualization matters and how charts, graphs, scorecards, and dashboards can communicate information more efficiently. - Analytical Decision-MakingDevelop a structured approach to moving from a business question to data collection, analysis, interpretation, communication, and action. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. …