Health Data ppt

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This document discusses whether health data constitutes big data. It identifies several sources of health data, such as clinical data, medical publications, and genomic data. While health data storage is projected to reach 25,000 petabytes by 2020, health data only accounts for 30% of the world's total data storage compared to other data-rich domains. However, the healthcare system has not fully optimized the potential benefits of big data due to issues like a lack of data integration and standardization. While health data is large, it is not as big as data from other domains that have more successfully harnessed the value of big data analytics.

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Digital healthcare technologies are transforming healthcare delivery globally. Companies are developing technologies like mobile apps, big data analytics, and smart medical devices to improve patient monitoring and outcomes. These digital innovations extract insights from medical data to enhance healthcare provisioning, reduce costs, and support preventative care and remote patient monitoring. Emerging areas like bioinformatics and medical analytics utilize big data to provide actionable clinical insights.

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A health information system (HIS) refers to a system designed to manage healthcare data, including a patient's electronic medical record, a hospital's operations, and supporting healthcare policy decisions. [HIS] has five core components: hardware, software, telecommunications, databases, and human resources/procedures. Good information management is crucial at all levels of healthcare from local to national as it provides data to policymakers, managers, and healthcare providers. A HIS aims to adequately enable information processing for patient care, administration, research, and education while considering economic and legal factors. It should provide the right information, knowledge, and data to the right people at the right time and place in the right format to support decision making and

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This document discusses the development and management of information systems in healthcare. It outlines how health IT can help improve quality of care by making information more accessible and reducing errors. Effective management of IT requires balancing people, processes, and technology, and using strategic and project management approaches. Health IT development may involve in-house or outsourced software solutions using methodologies like waterfall or agile development. The goal is to apply technology to enhance care while considering the complex, information-rich nature of healthcare.

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The document discusses hospital information management and hospital information systems. It defines key terms like hospital, information, health information management. It describes the objectives of health information management as acquiring, analyzing and protecting medical information to provide quality patient care. It also discusses how information systems can streamline hospital operations and increase efficiency.

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The document discusses using data mining techniques to diagnose coronary artery disease (CAD) through three case studies. Case 1 uses association rule mining on the Cleveland dataset to identify risk factors for CAD. Case 2 uses decision trees and bagging algorithms on laboratory and echocardiography features to diagnose CAD. Case 3 applies classification algorithms like SMO and Naive Bayes as well as feature selection and creation to the Z-Alizadeh Sani dataset to predict artery stenosis. The studies demonstrate how data mining can effectively analyze medical data and extract rules to diagnose CAD.

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Health Data ppt

1. Critical Analysis of Health Data STEVE IDUYE DALHOUSIE UNIVERSITY.

2. Questions  Is health data big?  How big is health data compared to other data rich domain?

3. Big Data  The concept of Big Data has transformed the way we live  Last two decades  Remarkable increase in global data  90% of world’s data created in the last two years (IBM, 2013)  Data is growing by 40% annually  Gradually reaching 45ZB (IBM, 2013)  When big data is mentioned, size is what easily comes to mind

4. What exactly is Big Data?  “A large volume of high velocity, complex, and variable data that require advanced techniques and technologies to enable the capture, storage, distribution, management, and analysis of the information” (Tech America Foundation, 2012)  Large data  Appropriate IT  To capture, analyze and disseminate the information

5. What constitutes a Big Data?

6. Is Health Data big? Sources of Health Data (Canada Health Infoway Inc. 2013)  Clinical data – structured and unstructured documents, images, and transcribed notes  Medical Publications – clinical research and medical reference material  Clinical references – text-based practice guidelines and health product (e.g., drug information) data  Genomic data – represents significant amounts of new gene sequencing data

7. Is Health Data big? Sources of Health Data (Canada Health Infoway Inc. 2013)  Streamed data – home monitoring, telehealth, handheld and sensor-based wireless or smart devices are new data sources and types  Web and social networking data – consumer use of Internet data from search engines and social networking sites  Business, organizational and external data – administrative data such as billing and scheduling and other non-health data

8. Data Storage Capacity

9. Health Data vs Other Data-Rich Domain  Approximately 2.5 quintillion bytes of data are generated everyday (Pathak, Shah, 2014)  In 2011, global data storage reached 1.8 ZB (Bao, Hoque)  It will take 47million years to view all the data in HD movies (Hoover,2013)  Health Data constitutes just 30% of the world data storage  Projected to reach 25,000 petabytes in 2020 (Feldman et al., 2012)

10. Health Data vs Other Data-Rich Domain  Other sectors have successfully harnessed the value and the benefits of big data Health care system is just getting started- Why? Lack of data integration Poor standardization of data format Other logistic problems (Pathak, Shah, 2014)

11. Conclusion  Health data is big, but not as compared to other data rich domain, because HD potential benefits have not been fully optimized.

12. Reference  Bao, Y., Hoque, R (2016) Big Data: Concepts, Methodologies, Tools, and Applications: Concepts, Methodologies, Tools, and Application. Management Association, Information Resources. IGI Global - p: 2478  Emerging Technology Series (2013)Big Data Analytics in Health: White Paper (Full Report).Canada Health Infoway Inc.  IBM (2013) IBM’s smarter cities challenge: Syracuse. Armonk,NY:IBM Corporate. Available from: http:/smartercitieschallenge.org/executive_reports/SmarterCities-Syracuse.pdf  Roski, J., Bo-Linn, G., & Andrews, T. (2014). Creating Value In Health Care Through Big Data: Opportunities And Policy Implications. Health Affairs, 33(7), 1115-22.  Tech America Foundation(2012)Demystifying Big Data: A practical Guide to Transforming Business of Government. Retrieved from http://ctolabs.com/wp-content/uploads/2012/10/techamericabigdatareport.pdf

Editor's Notes

Retrieved from: http://bigdata-101.blogspot.ca/2013/08/3vs-of-big-data.html

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