Gaining the best return on your healthcare analytics investment

Big data analytics holds the promise of transforming clinical healthcare by enabling better patient outcomes while reducing costs to providers.

But to make analytics pay off, healthcare providers must do more than invest in analytics software. Instead, providers also need to define the goals of their analytics initiatives and build an analytics culture.

Big data analytics works best when applied to specific questions or challenges. “How can we use analytics to become more profitable?” isn’t specific enough to help providers guide an analytics initiative. Better questions would be:

·  Where are we missing revenue collection opportunities?

·  Which patients are most likely to pay their medical bills?

·  What are the biggest impediments to prompt claims processing?

Asking specific questions of the data keeps analytics initiatives on track and helps avoid providers being overwhelmed by collected data that is analyzed with no specific goal in mind.

It’s also important to use the right analytics tools. University of Texas, Austin, engineering and data science professor Sriram Vishwanath tells Healthcare IT News that providers shouldn’t rely on analytics software until they determine it yields highly accurate results. A poorly configured system can generate unreliable data, which in turn can lead to poor decisions:

"Analytics should be based on measured, field-tested accuracy, and not be sold as a solve-all for everything under the sun. There are limitations to what any engine can do, and we should be honest about those limitations."

An experienced data scientist or analyst will know the capabilities of their tools and communicate effectively with healthcare clinicians and financial professionals to ensure that analytics results are based on accurate and reliable data.

While a knowledgeable data scientist/analyst can be invaluable to providers, an analytics initiative can fail to meet its goals without broad support throughout the organization. Not everyone can be – or should be – a data scientist, but all clinicians and financial workers in healthcare should be part of a culture that understands the important of analytics. This requires a symbiotic relationship between clinicians, other provider employees, and the data science team.

“Working together is critical,” Vishwanath tells HITN’s Jessica Davis. “Neither side knows it all and each must learn from the other.”

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