The Truth About Advanced Analytics: What Healthcare Leaders Need to Know

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By CereCore Media Coverage | May 21, 2021

1 minute read EHR/EMR| Blog

How ready are healthcare leaders for the future of advanced analytics? The short answer—there is a way to go. A recent survey from IDG reveals that only 25% of IT leaders expect advanced analytics, machine learning (ML) and artificial intelligence (AI) to drive their technology investments in 2021.  CereCore Vice President Peyman Zand shared his insights on the matter in a May 6th HealthIT Answers article titled The State of Advanced Analytics in Healthcare: Seven Industry Leaders Speak Out.

The article shares Zand’s findings from working with a CIO cohort in a recent virtual roundtable event. Each of these executives faced pressure to implement advanced analytics at their respective companies and offered takeaways for others who are in the same scenario.

Key findings included:

  • Be realistic. COVID-19 is a prime example of how unready the healthcare industry is for advanced analytics, said Danielle Mintz, Chief Data Evangelist at Looker. Mintz reminded the group that it took a “volunteer, bootstrap effort” to set a precedent for county-by-county COVID data in the U.S. Moral of the story? Make sure the data you’re bringing into the system is clean and be sure to check it for any information that is incorrect or unstable.
  • Be willing to work with physicians. There is no better friend for a data analyst to win over than a physician. As Zand shares, physicians want to understand the role that each data element plays in the model’s final outcome in order to establish trust. Data is also a great way to determine proper intervention on behalf of patients, such as delivering refrigerators to diabetics who need to keep their insulin cold or sending an air purifier to an asthma sufferer during the peak of allergy season.
  • Be data hungry. In addition to using data to guide and care for patients, it can also be used to build relevant queries, create models, and interpret data to provide predictive practices.
  • Be smart about your data. Using best practices is not just recommended but is it vitally necessary to moving advanced analytics forward, says Zand. Some of the ways to do this are to reuse data assets, take advantage of advanced data warehouse technology and horsepower and move from ETL (Extract-Transform-Load) to ELT (Extract-Load-Transform).

The future of advanced analytics is bright, but there is still much to be done to get there. Improving data collection and use on the front end will ensure better system processes and a more conducive patient experience. To read Zand’s full article on, check it out here.

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