Medical billing contains an abundance of medical and financial data which can sometimes get confusing and complex to understand. However, you can still keep track of some analytics in your medical billing which can provide some meaningful information and can be put to good use. New software tools have made it easier for payers, providers, consumers, employees and other stakeholders to access, compare, combine and analyze medical data to know what it means. These analytics have become quite useful and necessary when it comes to medical billing and reporting.
Data Analytics can drive positive results and change the way payers and providers work. The Affordable Care Act brought many Americans into the US healthcare system, projections show that 65 and above age groups will get double in size over time and government data would indicate more spending for this aging population and it will become expensive to support. This means that organizations must find the opportunity to measure, monitor and demonstrate improved outcomes at an affordable cost.
The most interesting analysis option in analytics is predictive and prescriptive analytics. It goes beyond the use of data to understand past performance. It would use and analyze information to generate and provide an overview of past, present and forecasted performance. It would give evidence-based measures to achieve the best results. With medical billing, it would help hospitals to understand and predict avoidable 30-day readmissions. Such analytics through different data sources can identify patients who are at risk of readmission, which can help hospital administration to create better discharge planning and post-discharge policies. This may also help payers and providers to apply predictive and prescriptive analytics to reduce admission risks, spot frauds, improve efficiency, and save lives, time, resources and money.
Predictive and prescriptive analytics relies on understanding the key patterns from other available sources of data including:
By combining medical clinical data with other sources of data such as socio-demographics and claims data, it can create an opportunity to drive real-time predictive and prescriptive analytics. In this way, healthcare and medical billing companies can identify and prioritize patients who are at risk and proactively manage their care. By using advanced analytics, it can be possible to drive improvements for patients.
Such data analytics can help medical billing providers to harness data from clinical visits, healthcare claims and community-based assessments to understand risk factors and deliver medical billing services accordingly.
With the help of analytics, there can be timely interventions that can improve clinical outcomes and it can prevent or minimize the need for expensive critical care services. With predictive analytics, medical billing automated software can generate alerts and reminders to healthcare practitioners and providers.
With the efficient use of medical analytics, you can minimize return hospital visits which can sometimes become expensive for the medical provider, payer and the patient. The importance of analytics in medical billing can match patient needs with available services such as home care, rehab facilities, medical services or diagnostic tests. As Analytics relies on medical history, medication services received, hospital billing and financial performance, therefore, it highlights the indicators to tell whether or not the patient is most likely to return to the hospital within the next 30 days.
Analytics in medical billing can increase accuracy for reimbursement decisions in Medicaid and preserve time and resources. It can help to avoid billing for unnecessary medical procedures, identify fraud and theft or nonpayment history.
Contact GreenSense Billing to know more about our expert Data Analytical tools.