Table Of Content
- Applications of Data Mining In Healthcare Sector
- Measuring Treatment Effectiveness
- Improved Healthcare Management
- Customer Relationship Management
- Detecting Fraud and Abuse
Applications of Data Mining: Nowadays, an electronic health record is the most popular among healthcare establishments. With an improved access to a huge amount of patient information, major healthcare companies are in the position. It helps to increase the performance and quality of the businesses with the help of data mining techniques.
Over the past few years, many companies have use data mining for some specific activities such as credit scoring and fraud detection etc. In these days, many healthcare businesses across the globe are starting to realize the advantages of medical latest data mining projects with the predictive analytics.
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. On the other hand, data mining technology allows reducing the costs by improving efficiencies, improving the patient’s quality of life, and even it helps to save the lives of more patients.
Applications of Data Mining In Healthcare Sector
As a matter of fact, data mining is useful in various industries. It helps to improves customer experience, customer satisfaction. As well as, it helps to improves product usability and safety. In healthcare sector, data mining has proven effective in areas such as predictive medicine, customer relationship management, fraud detection and also the measuring the effective of particular treatments.
Here, there are four types of applications such as
- Measuring treatment effectiveness
- Detecting fraud and abuse
- Improved Healthcare management
- Customer Relationship Management
Measuring Treatment Effectiveness
The application of data mining includes comparing and contrasting symptoms, causes and courses of treatment to determine the most effective course of action of a certain illness or condition. For an example, patient groups those who are treated with several drug regimens can be compared to identify which treatment plans work best and save the money. Moreover, the continues usage of application can helps to standardize the method of treatment for particular diseases. Therefore, it helps to make the diagnosis and treatment process very easy.
Improved Healthcare Management
To determine, it will develop data mining applications for the better can be traced chronic conditions dangerous for patients. Also, the data mining and disease decrease the admissions number in the hospitals and ask hospitals to help health care management. It is collecting a huge amount of details with the progress in the electronic health record. At the same time, the activation of disease data service in a digital format which helps to increase the quality of health care system. In fact, it extracts the data helps service providers to identify the current and future patients to improve the level of patient satisfaction needs.
Customer Relationship Management
In that case, data mining helps health care system to understand the requirements, patterns and preferences of behaviour. As well as, it helps to educate the customers to provide the better relationship with customers via the data mining is customers are curriculum core to manage the interactions between organizations such as banks, retailers or customers. On the other hand, it is useful approach to extract the data to analyze the several hospital information’s to identify their ranks are chosen the order of the hospital on the basis of their ability to deal with patients with serious cases.
Identifying Fraud and Abuse
It includes an establishment of normal patterns, and then identifying unusual patterns of medical claims by clinics, physicians, labs and so on. In fact, this application can be useful to determine inappropriate referrals or prescriptions, insurance fraud and fraudulent medical claims.
Data Mining – Its Effects on Privacy
As a matter of fact, it is very beneficial for healthcare system. At the same time, it comes with a few privacy concerns. Huge amount of patient information being shared during the data mining process enhances patient concerns which their personal details could falls.
While this technology can be useful to the healthcare industry, the privacy concerns can be acknowledged. Further, patients may not be comfortable with their data being useful for data mining processes. Several experts believe the advantage of outweigh the risks.
On the other hand, to solve the issue of privacy concerns, it has proposed that patients can allow deciding if their details can be shared for data mining purposes. Those who opt to share the details can enjoy the advantage of a tax break. And it can encourage more people to participate.
Future of Data Mining in Healthcare
To determine, the application of data mining helps to improve the aspects of the healthcare industry. It has facilitated by the transition from paper records and files to Electronic Health Records. In fact, practitioners in the healthcare sectors can dispense information across various sectors of healthcare. However, it allows the players in the healthcare industry to deduct the mistakes, improve more comprehensive documentation of processes and procedures, and also improve the level of patient care.
According to a report, this data mining technology can be expected to help in deducting costs. Also, this report states that if big data projects is applied with the goal of improving efficiency and quality, its value can rise to about $500 billion per annum.
In the final analysis, data mining technology plays an essential role in reducing costs in healthcare industry. Further, the enhancement of best practices and treatment options, identifying and enhancing efficiency, identifying false medical and insurance claims. Finally, it helps to raise the level of patient care.