Question

1. Name a few characteristics making data research and analysis in healthcare a separate industry. Think holistically and consider scientific, policy and social impact sides.

2. Explain how processed and analyzed data is used in healthcare. Offer a minimum of 2 examples where the data analysis supports health service delivery decision making.

Answer 1

Ans)1. Big data and predictive analytics aid in making care management decisions leading to a stronger more motivational relationships between providers and patients. This plays a crucial role in generating long-term positive engagement, prevent readmission wherever possible and reduce risks of chronic diseases. By studying and analyzing structured and unstructured data it is possible for the organizations to predict illnesses, prevent epidemics and reduce mortality rates.

- Combine artificial intelligence with data analysis and machine learning IoT, and it is easy to provide proactive care to patients. Hence, it would be a good move to invest in analytical solutions that can control and mitigate clinical and financial risks, with new payment bundles and models to go with it.

2) Big data analytics has the potential to transform the way healthcare providers use sophisticated technologies to gain insight from their clinical and other data repositories and make informed decisions. In the future we’ll see the rapid, widespread implementation and use of big data analytics across the healthcare organization and the healthcare industry. To that end, the several challenges highlighted above, must be addressed. As big data analytics becomes more mainstream, issues such as guaranteeing privacy, safeguarding security, establishing standards and governance, and continually improving the tools and technologies will garner attention. Big data analytics and applications in healthcare are at a nascent stage of development, but rapid advances in platforms and tools can accelerate their maturing process.