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Data security and AI-based RCM solutions

by Muthu Krishnan

Artificial intelligence (AI) is rapidly evolving from a novelty to the norm across all facets of society, including healthcare. While some inroads have been made into using AI in clinical settings, revenue cycle management (RCM) has remained relatively uncharted territory — until now.

AI is rapidly arriving on the cusp of becoming universal in healthcare RCM, with two-thirds of healthcare organizations already using it in some form — and nearly all expecting to use it within the next three to five years. And it is easy to see why. AI-enabled solutions drive significant improvements in RCM problem areas, including cost-to-collect, denials, underpayments, A/R management and staffing.

In the central billing office, AI can help remove administrative waste due to inefficient revenue cycle practices. It can also enhance decision support and improve patient engagement. AI tools can also:

Yet despite all the benefits of AI, some healthcare organizations are still holding off on bringing these useful tools to their systems because they have unresolved concerns around data security.


Accessing Large Data Sets

For AI to work best, it needs to have access to large amounts of data. That is no problem for most healthcare enterprises. They have tons of data. But unfortunately, it is often stored across multiple disparate systems. This siloed model is not ideal for effective RCM, because it does not easily allow for an enterprise-wide view.

Pulling all the data together is essential to improving the revenue cycle because it gives a broad concise overview of the operation. Creating a normalized “birds eye view” of RCM operations is the very thing that concerns some organizations - for fear of security reasons. To reap the many benefits AI has to offer RCM, understanding data security is a primary concern.

“Privacy and data security have never been more crucial in today's technologically advanced era,” says Landbot. “Thankfully, there are proven useful methods that institutions can implement to secure personal information while improving AI systems.” Some of these include:

  • Differential privacy,
  • Homomorphic encryption,
  • Federated learning,
  • Encryption,
  • Firewalls,
  • Intrusion detection systems,
  • Regular system updates,
  • Informed consent and transparency.

“With their usage growing dramatically in recent years, AI models must incorporate privacy protection into their design as a matter of course,” says Technology Magazine.

WhiteSpace Health's Secure Cloud

The WhiteSpace Health Cloud is built and fully managed on Microsoft Azure. Microsoft Azure uses state-of-the-art encryption. It protects your data both at rest and in transit and secures your data using various encryption methods, protocols, and algorithms, including double encryption.

Understanding privacy and security is core to how the WhiteSpace Health solution is built. Our platform:

We use advanced technology and proven methodology to create a world-class analytics solution, RevIntel. It is this robust foundation that allows us to deliver actionable insights.

WhiteSpace Health integrates data from across your organization — from EMRs, claims, financial systems, surveys and more — into one normalized health data warehouse. Having all of your data feed our AI solution is what gives you the edge. It allows us to deliver fresh, actionable insights to help you make intelligent, data-driven business decisions that will impact your bottom line.

WhiteSpace Health configures our data services to you, with virtually no impact to your IT team or other projects. Our rapid implementation ensures you will be live in about six weeks. When you sign on with us here is what you can expect:

Data acquisition

First, our proprietary Data Pump connects to data sources across your organization, including electronic medical records, practice management systems, claims, financial systems and more. WhiteSpace Health securely ingests both your structured data and unstructured data for processing.

Secure cloud-hosted processing

Once data has been ingested into our cloud, processing begins, using a series of data mining and data mapping tools. The data is cleansed and normalized, grouped, aggregated, classified, and indexed — offering an efficient and highly responsive database for end users. Then, we apply advanced machine learning (ML) models along with data computing algorithms to create artificial intelligence (AI)-based business insights based on your data. Our proprietary algorithm includes a natural language processing (NLP) engine with human-like intelligence to convert unstructured data into meaningful insights.


The processing creates high quality, normalized data that is indexed to a unified data model and stored in your data warehouse. Our practice analytics delivers fresh and incredibly responsive KPI metrics directly to your laptop or smart phone.

Should your advanced data manipulation and strategic planning needs require access to your normalized dataset beyond our embedded BI builder, WhiteSpace Health welcomes you to export the data contained in your normalized health data warehouse to Excel, Microsoft Power BI, Tableau, Python or other tools.



The data explosion we have seen in the past decade or so is only going to increase. As we keep this data safe and secure, it can be used to bring about much good, including for RCM.

Through the use of AI, like that provided by WhiteSpace Health’s RevIntel solution, healthcare organizations can move from retrospective to prospective management. It is the difference between chasing lost revenue and preventing its loss in the first place.

We can make recommendations uniquely targeted to your RCM process by using AI to discover what humans cannot see. Our RevIntel is ever learning about your business on a day-to-day basis, allowing us to prescribe fresh and specific ways to fix your revenue problems.

About Muthu Krishnan


Muthu Krishnan is the Chief Technology Officer at WhiteSpace Health. Muthu is known for helping early and mid-stage companies embrace agile methodology that rapidly brings products to market to successfully solve customer problems.