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NLP Healthcare – Risk Adjustment Meets Artificial Intelligence

Healthcare Technology

Big data is all the rage – transforming industries from tech to retail and much more. Healthcare – an industry slow to adopt technology in many ways now has access to more data than ever before with the widespread adoption of electronic health records (EHRs). But, what do we do with all this data in an industry that is traditionally relatively lean and non-tech savvy? Without experts on-hand to analyze the data and transform it into meaningful information, many healthcare companies leave their wealth of data virtually untouched – an untapped bank of all the secrets needed to better understand their patients, improve efficiencies, enhance performance and much more.

In comes artificial intelligence – the perfect solution to transforming the mind-numbing amount of data generated by health care providers into valuable intel that can help people better manage their health – while also helping payers and health systems better understand their patients and members in aggregate. Artificial intelligence in health care is a growing market – estimated at $2.1 billion industry in 2018 and expected to explode to $36.1 billion by 2025. How can AI help? In essence, AI is like the all-powerful brain that can read and comprehend the hundreds of thousands of fields of data that represent each patients’ complex medical history.

While there’s no way a human can read and understand all this data in real-time, AI uses complex algorithms and tools such as Natural Language Processing (NLP) and Machine Learning (ML) to decipher this massive amount of data and help ensure payers understand the full picture of their members’ health so they can accurately plan for each participants’ anticipated health care spend.

How do they do it? Coders are using these innovative technology solutions with AI-based algorithms to support their chart reviews – quickly finding key elements of documentation such as HCCs to support faster and more accurate audits. In numerous studies, audits supported by AI have higher accuracy rates than those without assistance.

Particularly in today’s world where accurate risk adjustment is closely tied to a payer’s bottom line – the ability for payers to really understand their members’ diagnoses, medical conditions, etc. has become increasingly important. Underestimating a member’s risk adjustment factor (RAF) is like leaving money on the table that can help insurance companies better manage their members’ complex health conditions.

The real bottom line? Technology-assisted automation is a key element in the future of risk adjustment and value-based care. When you combine the expertise of trained and certified coders, with the speed, efficiency and accuracy of machine learning – you’ll find the perfect match to support your risk adjustment program.

Getting the most out of shared risk programs requires a continued, expert focus on risk adjustment. This comes with an in-depth evaluation and understanding of your data – and an outside look is often the most effective way to truly get it right. GeBBS can help you maximize the impact of risk sharing programs for your organization. Our technology enabled risk adjustment services provide an accurate, real-time look at your risk scores – based on a comprehensive and ongoing review of your data.

Our proven service delivery model takes chart review to the highest level, ensuring timeliness, quality, accurate documentation and optimal results. Services include medical record retrieval, risk adjustment chart review (for HCC coding), RAF Score reporting, HEDIS abstraction/workflow and solutions, quality review/auditing services, as well as provider education and support. To learn more about our technology and services click here to schedule a demo.

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