Today, the healthcare industry is moving rapidly from volume-based reimbursement (fee for a service) approach to a value-based reimbursement (fee for value) approach, which benefits healthcare providers, patients, and payers alike. Healthcare organizations are looking to step up their quality of services at the lowest cost, and patients, in turn, receive a higher quality of care at a better value.

Predictive business analytics is being used widely in the healthcare industry to make quicker and more informed decisions pertaining to patient care.  The popularity of Electronic Health Records (EHRs) in the recent years has also been a primary factor for the rise in demand for predictive analytics.

But why is it so essential to leverage business analytics in today’s healthcare scenario? The answer lies in developing a value framework that is holistic, patient-centered, and addresses business goals.

Business analytics in healthcare is emerging as a vital area of research owing to the help it has extended to health care organizations in solving problems and making decisions. Analytics is now slowly progressing from just being at the operational analytics level to a higher level of strategic analysis. It is diversifying from simple descriptive analytics toward predictive, prescriptive, and diagnostic health analytics.

Healthcare organizations collect data on the performance of various services offered by hospitals and perform analytics on this medical data. They use data visualizations, such as dashboards and score cards to identify trends or patterns in patient care. This method can identify performance gaps and previously unnoticed patterns in patient care and can be used to come up with better strategies to obtain a better balance between service and cost.

Business analytics helps hospitals analyze and find the root causes of problems and based on that, develop key performance indicators (KPIs) to enhance the performance. For example, waiting time of patients, patient readmissions, length of a patient’s stay in the hospital, and so on can be tracked down to its most influential factors.  Predictive analytics uses historical data to predict future trends, such as, which patients might opt for a surgery, and which patients might not, which patients have more chances of developing complications after a surgery, or what are the chances of an outbreak of an epidemic disease.

In one of the famous examples, one hospital saved $850,000 in overtime costs through the use of big data analysis for real-time staffing adjustments.

Some other areas in which business analytics offers a solution are:

Make the correct real estate investment for hospitals

Business analytics can forecast potentially viable clinical sites and help healthcare providers identify places that are most suited for opening health care facilities, thus making them profitable.

Optimize healthcare business operations

Predictive analytics can help hospitals optimize their staff depending on the workload in the facility. It helps businesses cut down on administrative costs, monitor and control fraud and abuse, improve coordination among different departments, improve clinical decision support, and prevent duplication of data.

Improve the quality of patient care

By giving a centralized view of all the patients, analytics can help improve patient safety, patient wellness, and also help in improving patient satisfaction, acquisition, and retention.

Improve patient care in ICU

With the help of EHR data and predictive analytics, healthcare professionals can better predict which patients in the ICU are at high risk of developing infections, sepsis, and other critical issues. This allows hospitals to be better equipped to handle such emergency cases which are often difficult for busy staff to predict.

Support long-term expansion plans

Healthcare organizations use a variety of predictive tools for long-term planning and expansion projects. These tools help teams with another actionable insight to assist with important decision-making.

Help pharmaceutical industries develop new and more effective drugs

With the help of predictive analysis, clinical trials are now shorter, more effective, more powerful, and less expensive. Owing to the large amounts of data received from various sources, pharmaceutical companies can now quickly identify new potential drug molecules and develop them into medicines more easily.

Conclusion

Using business analytics, the healthcare industry can gain better insights that can help add value and achieve better outcomes with disease management, new drug development, and better treatments. Analytics can help design and plan new policies and programs, explore new areas of growth, mitigate risks, and improve service delivery and operations, which are key to any health care institutions success.