Analysis of trends and challenges of public open data in health care industry using Artificial Intelligence

Abstract

Understanding the public open data being gathered and analyzed is necessary before we can discuss health data analytics and its function in the healthcare industry. A significant quantity of health data is also being obtained, kept, and analyzed, in addition to data on the operations and procedures of the commercial side of the healthcare industry. Any information about a patient’s or a population’s health is referred to as “health data.” Medical professionals and administrators may find areas that need improvement or are in danger by using data from the health industry. With this knowledge, they may take steps to improve any areas where patient care is deficient and elevate the standard of care for all patients. Lab findings, vital sign recordings, prescription diaries, and computerized medical records all include enormous amounts of data. A change in the patient’s health or the possibility of experiencing a major consequence may be detected by physicians and nurses using artificial intelligence (AI) techniques to spot data trends. Due to the complexity and expansion of data in the healthcare sector, AI will be employed there with greater frequency. Numerous types of AI are already being utilized by health insurance companies, medical organizations, and biological sciences enterprises. Solutions can be put into three main categories: operational tasks, patient engagement and participation, and medication and diagnosis recommendations. The health sector uses AI and data engineering to improve the processing and analysis of health data, compensation settlements, and other clinical records. The objective of this chapter is to learn about the capabilities of AI in using public open data as well as the trends and challenges in patient data.