Pros and cons of data mining in healthcare

However these data patterns helps to predict the industry or informational trends. The analysis of data through data mining can provide countless advantages to companies for the optimization of their management and time.

Healthcare professionals can therefore benefit from an incredibly large amount of data.

Pros and cons of data mining in healthcare. We conclude that there are many pitfalls in the use of data mining in healthcare and more work is needed to show evidence of its utility in facilitating healthcare decision-making for healthcare providers managers and policy makers and more evidence is needed on data minings overall impact on healthcare services and patient care. One of the strongest negatives relating to big data is the lack of privacy especially when it comes to confidential medical records. To be effective and get the full comprehensive look at a patient big data must have access to everything including private records and social media posts.

Benefits of healthcare data mining Data mining is gaining momentum in the healthcare industry because it offers benefits to all stakeholders. Care providers can use data mining to identify effective treatments and best practices as well as to develop guidelines and standards of care. Data mining applications can greatly benefit all parties involved in the healthcare industry.

For example data mining can help hea. Data mining has been used intensively and extensively by many organizations. In healthcare data mining is becoming increasingly popular if not increasingly essential.

The MIP will also be pilot testing various data mining algorithms throughout the states as a tool to identify fraud waste and abuse. As the MIP program evolves it will utilize the data mining techniques to better combat these issues. Medicaid Integrity Contractors MICs a specific part of the MIP will also be employing Data Mining techniques.

Pros of Healthcare Databases. Healthcare databases promote standard record keeping including doctor and staff notes findings from assessments among other factors. The most significant benefit of any healthcare database system is in this area.

Data mining is an important part of knowledge discovery process that we can analyze an enormous set of data and get hidden and useful knowledge. Data mining is applied effectively not only in the business environment but also in other fields such as weather forecast medicine transportation healthcare insurance governmentetc. Data mining has a.

When performing the Data Mining advantages such as. Assists in the prevention of future adverse situations by showing true data. Contributes to strategic decision making by discovering key information.

Improvement in the compression of information and knowledge facilitating reading to users. Data mining discovers information that was not expected to be obtained. Mine shaft can collapse causing death to people underground.

Harmful to human health. The miners can suffer from some skin diseases lungs and respiratory problems which are caused by the chemicals released in the air and water from the mining zones. The use cases for big data analytics in healthcare are nearly limitless and build very quickly off of the patterns identified by data mining such as.

Developing a patient risk score by matching abnormally high utilization rates against medical complexity and socioeconomic factors. Pros and Cons of Data Mining Detection of Fraud and Misuse Data mining methods include determining normal patterns in this area identifying unusual medical claims by doctors hospitals and labs. Data mining can even help to establish erratic referrals or suggestions and false medical claims.

Data mining came about with the intention of helping to understand a huge amount of data. This could then be used to draw conclusions to contribute to the improvement and growth of companies. The analysis of data through data mining can provide countless advantages to companies for the optimization of their management and time.

While the traditional data mining is focused on patterns and trends in data sets data mining in healthcare is more focused on minority that is not in accordance with patterns and trends. The fact that standard data mining is more focused on describing and not explaining the patterns and trends. Healthcare professionals can therefore benefit from an incredibly large amount of data.

Recent reports suggest that US healthcare system alone stored around a total of 150 exabytes of data in 2011 with the perspective to reach the yottabyte. 7 Starting with the collection of individual data elements and moving to the fusion of heterogeneous data coming from different sources can reveal. The major purpose of data mining is useful in healthcare is to determine the useful and understandable patterns by analyzing huge sets of data.

However these data patterns helps to predict the industry or informational trends. Overall it identifies what to do about them. Opponents of data mining argue that since the process creates patterns such as purchasing behavior of people and demographic factors it is not unlikely that pertinent information can be disclosed and in effect is a violation of privacy.