Main description:

Integrate cutting-edge data-driven technology to improve the quality, reach and effectiveness of preventive healthcare. Use statistical modeling to derive insights and make revolutionary changes in the healthcare industry so that the physical distance between patients and health specialists becomes immaterial. Transforming Healthcare through Big Data Intensive Technology demonstrates how important it is to build collaboration between patients, clinics, businesses, government, and healthcare organizations, with a goal of safe, effective, predictive and efficient patient care.
Topics covered are: * With the emergence of wearable technology, a person can capture early key indicators from their body without going to a diagnosis center* Data generated by sensors can be gathered through a connected device either at a centralized location or in the cloud* Further data will be enriched by non-wearable diagnosis tools available at established diagnostics centers * A centralized analytics center will mine data using statistical modeling so that best healthcare recommendation can be communicated back to patients Imagine that you could get optimal preventive health advice on a regular basis without seeking an appointment from your doctor and without disturbing your normal routine. This book describes multiple tangible and intangible benefits that can be enabled by this visionary solution for the healthcare industry. The future of the healthcare industry requires a comprehensive solution (supported by data-intensive technologies) that makes preventive medication proactive. This allows patients and even healthy people to get recommendations without delay.
What You'll Learn * How data-driven technology can improve healthcare quality and performance* How historical information, which can be used to predict the nature and likelihood of future events or occurrences, can alter the course of predictive diagnostics* How technology can help population health management* How hospitals can leverage a technology-driven healthcare delivery business model* How pattern recognition and machine learning can improve disease surveillance and detection of other health anomalies Who This Book Is For Decision makers in the healthcare industry; healthcare domain experts in the IT industry; technology experts in wearable and connected devices, cloud, big data, mobile/social, and visualization; and data scientists in healthcare, educational institutes, and government.

Contents:

Table of ContentsChapter 1: Current Preventive HealthCare Assessment Chapter Goal: Make readers familiar with context Sub -Topics * Overview* The Current Scenarios of Healthcare Quality , Cost and Complexity* The Harder Problem being faced by healthcare industry* Quantitative Impact Assessment of healthcare Challenges under current scenario.Chapter 2: Seemingly Ideal Preventive HealthCare Model Chapter Goal: Convey author's vision to build a system that can help patients / Healthcare providers / Government to improve health condition Sub - Topics * If everything were to become right - Ideal Scenario* Opportunity Cost for ignoring Ideal Model* Who will benefit Most* Patients * Healthcare provider* Government/Research* Market ImplicationChapter 3: Data - Raw Material for Insights - Its Context , Imperative ,Prospects and future Chapter Goal: Data is a Critical component of Healthcare industry, and working and understanding data is a critical element for meaningful insight generation through Data driven Technology. Due to its nature, healthcare data is often more complex than that in other industries. Sub - Topics: * Current Challenges with Healthcare Data* Need for effective Data Management , Quality & Data Governance* Positioning the Data for right use and developing effective indicators* Data Mining - Possible implication of Early detection and Prevention* Summary Chapter 4: Effective Healthcare Indicators Chapter Goal: Idea is to make "Measures" more effective by suggesting certain Effectiv e indicators and Metrics Sub - Topics: * Define Life enhancing based indicators* Using critical indicators to Guide Healthcare improvement activities Chapter 5: EHealth - Technology Use & Impact Chapter Goal: High level understanding of technology components being part of solution Sub - Topics: * How Technology can change the "HEALTH" of Healthcare Industry* Defining different component of Technology* Role of each component* Impact of Aggregated technology impact Chapter 6 : IOT ( Internet of Things) - Wearable Technology , Sensors & Instruments Chapter Goal: Detailed description of IOT (Wearable technology, Sensors and connected healthcare equipments) that would baseline to build a transformative HealthCare solution Chapter 7: Infrastructure - Cloud /Private Cloud, Mobile, Big Data, Social & Visualization Chapter Goal: Detailed description of all related infrastructure components that would play a key role in effective Operations of Proposed solution Chapter 8: Insights - Advanced Analytical (Data Mining) Chapter Goal: How healthcare as a system can leverage Data Mining, Text mining, Predictive, Prescriptive and Neural Analytics to efficiently and effectively recommend most optimized option to Patients. * Statistical methods for determining transformative changes in the healthcare system* Predictive ,Prescriptive and Neural Algorithm* Putting it all together* Validating the Model Chapter 9: Protected Healthcare Information - Secur ity, Privacy and Regulation Chapter Goal: Patients privacy and security of sensitivity data will be core criteria to make this technology driven solution operational. Therefore this chapter discusses author's point of view on this. Chapter 10: Commercialization Viability -Product , Services , Consumers and Pricing Chapter Goal: Abundant of data collected from across demography will provide new opportunity. Authors explains how solution will help various agency on understanding future requirement well in advance and help them make investment decision. Chapter 11: Future Roadmap - Transforming an healthcare Organization to Analytical Healthcare Organization Chapter Goal: Author's points of view on further long term roadmap to make it more practical and robust Chapter 12: Challenges, Opportunities and Conclusions Chapter Goal: Discuss various challenges and opportunities that authors can foresee.