Predictive Analytics and Healthcare

Healthcare organizations are constantly striving to improve their services to provide better care and experience for patients. The essential tool to unlock medical innovations is data. In the healthcare industry, data analytics is used in tracking, measuring, and predicting outcomes.

Data provided from the day-to-day operations of hospitals and clinics serve as a gold mine of information. Healthcare organizations can use them to understand patterns and events, leading to better treatments, therapies, and financial health.

Predictive Analytics

Generally, predictive analytics is the process of looking into existing data and building mathematical models to act as a guide to make predictions about something that is not present in the data set yet. Predictive analysts are in charge of assembling and organizing data, identifying which mathematical model applies, and drawing out necessary conclusions.

The definition is just the same in the healthcare setting. Through predictive analytics, healthcare providers can forecast future events through AI and machine learning. Predictive algorithms in healthcare serve various purposes. Finding the correlations in the patients’ data, the symptoms and their familiar antecedents, exploring the impact of multiple factors on treatments, and examining the possible influence of past and current diseases are some of the uses of predictive algorithms.

Healthcare organizations are struggling to provide value-based care with the best outcomes for their patients. With the vast amount of data in the healthcare systems, getting meaningful insights is becoming more difficult each day. Through predictive analytics, meaningful insights can be drawn and used to improve the treatments and service quality.

With the emergence of value-based reimbursements, healthcare systems have recognized the importance of predictive analytics in healthcare. It can be a big help in delivering cost-effective care. Also, it reduces readmission rates, predicts healthcare trends, and predicts future reimbursement impacts.

The application of predictive analytics in healthcare can be very beneficial in many components of the healthcare sector. Still, there are two that stand out: clinical performance management and financial performance management.

In Clinical Performance Management

Providers already have the necessary data in the form of EHRs and financial billing systems. Integrating these disparate sources and patient-centered data sets will result in a better understanding of patient populations. Based on what the system knows about the patients, healthcare organizations can share information across many applications and the different teams responsible for giving care to them.

PA is a big help in keeping patients healthy and reducing readmissions, thereby producing better outcomes. It investigates all the data to learn and understand the patients. Predictive analytics reveals the needs and vulnerabilities of patients, which exposes what care is needed for the patients to get better. Once all the required data is thoroughly analyzed, physicians will know what to do with the patient once they show up in the hospital.

With predictive analytics, physicians can forecast if a patient is shifting to a less healthy state. This way, they can immediately suggest treatments to prevent the patient from falling to a high-risk category.

Medical practitioners are very thankful for the predictive analytics technology. One of the main goals of predictive analytics in healthcare is to give physicians and nurses the data they need to make clinical decisions. If a physician is sure about his diagnosis, he can provide better treatment procedures.

Predictive Analytics can bring about many medical breakthroughs, especially if done correctly. Aside from the clinical benefits, it can bring the best power of predictive analytics to provide over the hospital’s finances.

In Financial Performance Management

In connection with the improvements that predictive analytics can bring to a healthcare organization’s clinical component, it can also do wonders for financial performance management.

Analyzing massive data sets needs to be done in an organized way. Sorting data can be done by dollar amount owed, by procedure codes, by the payer and insurance plan type, the frequency of appearance within the data set, or even by the patient’s projected health. The best by far is how predictive analytics can sort data depending on the costs to resubmit claims, the likelihood of claim reimbursement, and the predicted long-term effect of denials on the provider’s operational and financial standing.

Predictive analytics can help in looking for missing charges, coding variances, and other anomalies. Also, it can help in uncovering the root causes of claim errors. As a result, the healthcare provider will review all claims before submitting them to insurance companies. Increased visibility to errors and denials will drastically improve the rate of clean claims. As a result, the healthcare provider will increase their revenue.

With predictive analytics, organizations can be more thoughtful about addressing the root causes of claim errors and denials.

IntelyFi for Predictive Analytics

IntelyHealth offers a healthcare predictive analytics solution called intelyFi. IntelyFi uses AI and machine learning to analyze financial data for thousands of patients’ claims. It also helps in identifying root errors of past and future denied claims.

IntelyFi uses machine learning algorithms to see the patterns in claim data to put together similar patient procedures. As a result, organizations will have more insight into clinical workflows or patient types that could lead to increased exposure to clinical and technical denials. Additionally, physicians and clinicians can be able to identify which procedures’ costs are exceeding expectations. Not only that, but it can also improve the overall financial health of the institution.

Given the benefits and the purposes that predictive analytics serves in the healthcare setting, investing in a predictive analytics solution like intelyFi is a wise decision.

Contact us today to request a demo.