Healthcare Informational Data Analytics

This article is the first in a series that will provide an overview on an approach to healthcare data analytics, known as Healthcare Informational Data Analytics (HIDA), which allows patients, hospitals, and clinicians to use and share the ever-increasing volume of healthcare information. This process provides a step-by-step process for building out a data analytics solution. Data analytics is a process of inspecting, cleaning, transforming, and modeling data with the goal of highlighting useful information, suggesting conclusions, and supporting decision making. In short, data analytics turns data into actionable information. The Affordable Care Act (The Act) requires improvements in how hospitals, and clinicians use and share healthcare information. Specifically, there are several aspects of the act that will require improved use of data. The Act seeks to help patients take more control of their health care decisions by providing them better access to more information. The Act provides doctors better access to the latest medical research. Better information for patients and doctors strengthens the doctor-patient relationship by allowing for patients and doctors to collaboratively arrive at better healthcare decisions more efficiently. The Act also requires greater transparency by nursing homes. The Act is intended to promote nursing home safety by encouraging self-corrections of errors, requiring background checks for employees who provide direct care and by encouraging innovative programs that prevent and eliminate elder abuse. Finally, The Act attempts to rein in waste, fraud and abuse by imposing tough new information disclosure requirements to identify high-risk providers who have defrauded the American taxpayer. HIDA is a methodology that provides health care information workers with an easy to follow systematic way to create significant value from health care data while adhering to current and future regulatory requirements. HIDA provides a method to manage the petabytes, exabytes, zettabyes and eventually yottabytes of data the healthcare industry generates. The methodology is presented in three manageable steps that produce value early and often. The methodology is iterative and many of the steps can be performed in parallel. The steps are: 1) Manage, 2) Measure, and 3) Modify