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The Role of Business Intelligence in Managing Compliance

A properly implemented business intelligence framework allows the enterprise to use business rules and repeatable processes to automate many routine regulatory tasks, effectively aligning the requirements with enterprise processes.

This article originally appeared on the BeyeNETWORK

It seems elementary to point out that healthcare, pharmaceutical and biotechnology organizations today are operating under an increasing number of regulatory requirements. They face regulatory challenges not only in their core areas of service (clinical, manufacturing, outcomes, improved performance), but also around the process of just doing business (for example, financial and corporate governance). In this environment, the act of finding adequate, cost-efficient solutions for compliance is not just an operational necessity, but also a clear business advantage.

Researchers, doctors and administrators are not in the business of compliance, but it is a necessary requirement. Meeting and proving compliance requires detailed records – something that involves lots of data. For example, in clinical trials, having source records, signatures, audit trails and chain of custody all are prerequisites for being able to safely say that a drug or device is worthy of investigation. In healthcare, with increased pressure from the government, payers and consumers, we have a plethora of requirements for documenting patterns of care such as Physician Quality Reporting Initiative (PQRI), Core Measures reporting to CMS, medical mistakes, medication reconciliation, adverse events and demonstration of privacy and security (especially around HIPAA.)

You may be asking, "What does this have to do with business intelligence (BI)?" Well, we know that most of this data is stored in electronic formats. Everything from audit trails to electronic medical records (EMR) to electronic data capture (EDC) is available as raw data. However, most organizations just don’t have a particularly compelling environment for making business intelligence useful outside of isolated core business areas. Business intelligence should benefit the whole enterprise by supporting the whole enterprise.

Healthcare and biopharma organizations are flush with data. Wouldn’t it be nice if we could instead say that these organizations are flush with information or flush with insights? Certainly these organizations are built upon the back of innovation, but it’s probably safe to say that on the whole their data is, well, a mess. Sure, it’s fine in most areas, but then most areas are isolated from one another – which ensures that identifying and merging diverse data sources will generally be challenging. This makes it difficult to glean insightful information from across the whole of the enterprise’s data.

So what can be done?

Better choices now exist to access useful information from your systems with advanced business intelligence solutions. Today's BI tools have evolved to tackle the issues that hindered business intelligence in the past, and business intelligence as a methodology has progressed to become more about strategies rather than technologies. Some of the major benefits current BI solutions can offer are:

  • Integrate data from disparate systems and sources (create access to data)

  • Establish automated compliance processes

  • Encourage collaboration across the organization

  • Streamline processes from data capture to analysis

  • Provide a centralized, searchable repository for all research, clinical and financial/administrative information

  • Empower users to explore data (self service)

  • Support data exploration across multiple disciplines (and data sources)

  • Enable early warning detection for issues before they affect financial or health outcomes

  • Provide appropriate, secured access to data based on user roles

While it is not uncommon for some of these benefits to be realized within organizations, rarely do they get used on an enterprise scale, and even less so on non-financial data. Rather, organizations tend to implement business intelligence within isolated environments for a specific group of users. We know, for example, that most large pharmaceutical companies use business intelligence for sales force optimization and analyzing prescription data. Healthcare outcomes researchers and quality experts use business intelligence for reporting on quality metrics and financial performance, and even to help identify patterns of fraud. But rarely have we seen business intelligence used to report on compliance issues (and even more rarely have we seen this used outside of Sarbanes-Oxley, operational risk or other financial compliance scenarios). Instead, most people tasked with reporting on a compliance metric have crafted some Excel spreadsheet to collect what they need and update it manually whenever required – leading to an unwieldy environment of “spreadmarts” or isolated datasets.

A properly implemented BI framework will allow the enterprise to use business rules and repeatable processes to automate many routine regulatory tasks in a reliable and consistent manner for all related activities across the enterprise, effectively aligning the regulatory requirements with the whole of enterprise processes. This automation frees up human resources to leverage the increasingly transparent data resources to perform more in-depth auditing and investigations into the enterprise systems of checks and balances to guard against fraud, corrupted information and other compliance risks. This leads to the immediate benefits of increased efficiency and reduced risks associated with incorrect or overlooked compliance activities. Thus, the alignment of regulatory compliance requirements with the enterprise’s business processes provides a competitive advantage.

While the idea of using business intelligence to help manage compliance is not a new concept, it is still underused in biopharma and healthcare. Because business intelligence is pervasive in most large organizations, you probably already have the tools, and expertise, to gain access to the information you want, when you want it, in the format you want it. What you may need is a plan to extract the information with an automated process. After that, it’s up to you to figure out which problems you won't miss once you automate the process.

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