Information Science in the Analytics of Healthcare Data

Introduction

Information Science is an interdisciplinary field which deals with the effective collection, storage, retrieval and use of information. It also concerns about the analysis, classification, manipulation, movement, distribution and protection of information. It incorporates the recorded information with anticipated knowledge for better decision making through related technologies and services that facilitate their effective management and use.

Historically, Information Science is associated with computer science, Data Science, Psychology, Technology and Intelligence agencies. But now it has been extended to integrate the various aspects of diverse fields which are in need of managing and using information magnificently for their advancement. One such field is healthcare that collects stores and manages huge patient’s Electronic Medical Record (EMR) and data pertaining to hospital’s administration in order to aid healthcare policy decisions. Today, healthcare organizations are looking for more efficient and sophisticated means of collecting, managing, analyzing data and delivering medical information to physicians, clinicians and nurses. The role of Information Science in healthcare domain is to improve the quality of patient care, reduce operational cost and make the entire internal management process well organized for better decision-making. The primary concern is to identify the methodologies to effectively access, process and maintain large volumes of sensitive data catering to the needs.

Today, diagnosis of disease is a vital job in the medical field. It is essential to interpret the correct diagnosis of patient with the help of clinical examination and investigations. Most hospitals have a huge amount of patient data, which is rarely used to support clinical diagnosis (Motilal et. al., 2013). Our healthcare sector daily collects a huge data concerned with patients including clinical examination, vital parameters, investigation reports, treatment follow-ups, drug decisions etc. But very unfortunately it has not been analyzed and mined in an appropriate way. It is just stored as bunches of paper sheet or occupying hard disc space. These valuable data are handled mainly by researches and statisticians at professional level.

Computer information based decision support system that analyze and predict the data can play an important role in accurate diagnosis and cost effective treatment. In future, it will definitely be helpful in various diseases management including effectiveness of surgical procedures, medical tests, medication and the discovery of relationships among clinical and diagnosis data with accuracy.

Health data is collected from a variety of systems and devices, such as online patient portals, electronic medical records, glucometers, health tracking devices, diagnostic systems and genomics. As a result, data exists in different formats, from clinical notes to medical images such as CT scans and at times, the data is unstructured. Through the application of Technology, Data Analytics and Information Science practitioners help in driving data-informed health care decisions. Hence this chapter covers the techniques that provide support for Data Analytics and Information Management in healthcare such as Data Mining, Machine Learning, Cloud Computing and Data Visualization as shown in figure 1. An increased focus on these techniques supports the healthcare system through enhanced decisions for advance care process that can address the public healthcare issues on time. It offers a win-win situation for both the patients and the healthcare providers.

Figure 1.

Techniques for data analytics and information management in healthcare

Digital Medical Data

Health problems impact human lives (Marzyeh Ghassem et. al., 2019). During medical care, health providers collect clinical data about each particular patient and leverage knowledge from it to determine the treatment process of that patient. Clinical data thus play a fundamental role in addressing health problems and improved information is crucial in improving patient care.