HIM 650 Topic 5 DQ 2

HIM 650 Topic 5 DQ 2


Today, data analytics is used in every industry to discover trends and patterns in business data and predict future events based on the discoveries. In health care, data analytics has improved clinical decision-making capabilities by offering solutions to some of the most complex health problems. There are two types of analytics you can employ today to understand your data; explanatory or predictive.

Data analytics of health data can be used to discover trends and patterns, predict future events, and or explain outcomes. In order to use explanatory analysis on the data the question will have to be asked in a way that the sample allows for a statistical comparison. The question asked when using predictive analysis is focused on predicting future outcomes. Also, predictive analytics might be employed to analyze patterns in data and identify overall probabilities.

Predictive analysis is used to predict future events based on the discoveries made using explanatory analysis. The biggest difference between these two types of analytics is that while explanatory analytics discovers trends, predictive analytics predicts upcoming events from the discovered trends. However, it may not always be possible to predict an event in advance; for example, the risk of a patient developing diabetes can be calculated through body mass index and other risk factors like family history, but predicting the date of onset of diabetes may not be possible unless more information about patient habits is collected.

Unlike descriptive analysis, which describes the historical information to identify problems, data analytics uses the large amount of data to assess future outcomes. People use descriptive analysis to discover what has happened in a health care organization or with a group of patients, but it does not give valuable insight into what will happen. Predictive analysis is used to solve problems before they occur. It will improve operational efficiency, quality of care and patient safety by analyzing and evaluating past events, current issues and possible future occurrences.

Consider the following scenario: You have been hired as an analytics consultant for a large health care organization. The CIO of the organization is considering implementing a data analytics platform that will work with its databases to conduct explanatory or predictive analysis. Analyze what you believe would be best for this health care organization based on your research and experience.

Several techniques for data analytics are used by hospitals and health care providers to gain knowledge from their patient and facility data. Some are exploratory, such as service quality level and customer satisfaction. Others – like estimating the risk of a disease – are predictive, anticipating when and how events will unfold. Proper use of data analytics can build the trust of patients, staff and stakeholders while improving business performance dramatically.

Data Analytics is the discovery and communication of meaningful patterns in data. Predictive analytics enables one to make predictions about uncertian future events based on historical data, and it uses advanced statistical methods from different fields including operations research and economics. Explanatory analytics provides an understandable explanation of what has happened and why, for further analysis through predictive modeling.

Data analytics involves the use of data, statistical and quantitative analysis, explanatory and predictive modeling, and information technology to drive decisions and actions.”

Analyzing data can provide many benefits in health care. For example, data analytics is being used in health care to improve the efficiency of a practice. One way this is occurring is through streaming patient data, which is then processed and monitored in real time, which helps streamline processes and predict problems before they become a problem.

Analytics is a fast-growing field of data analysis that focuses on interpreting huge volumes of data. It’s the science of gaining useful insights from data, and the skills to do it are in high demand. Being able to make sense of data has been called one of today’s most important job skills, and you will learn it in this course.




Data analytics is applied to discover trends and patterns in health care data, and it predicts future events based on the discoveries. Compare and contrast data analytics, specifically the use of explanatory or predictive analysis, that you might employ for analyzing health data.

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