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Author Bio

Neil Andersen

Neil Andersen joined Health Catalyst as a data architect in October 2011. Prior to joining the Health Catalyst team, he was a partner at Practice Advisory Group. While there, he improved financial outcomes and the overall efficiency and productivity for many medical practices throughout Arizona. He also built and used analytical tools to monitor and direct management decisions. Prior to working at Practice Advisory Group, he worked at Grant Thornton as an IT and securities auditor. Neil graduated from Brigham Young University with a Bachelor of Science degree in business information systems.

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Mark McCourt
Mike Noke, MBA
Neil Andersen
Ryan Smith, MBA

Agnostic Analytics Solutions vs. EHRs: Six Reasons EHRs Can’t Deliver True Healthcare Interoperability

As enterprisewide analytics demands grow across healthcare, health systems that rely on EHRs from major vendors are hitting limitations in their analytics capabilities. EHR vendors have responded with custom and point-solution tools, but these tend to generate more complications (e.g., multiple data stores and disjointed solutions) than analytics interoperability.
To get value out of existing EHRs while also evolving towards more mature analytics, health systems must partner with an analytics vendor that provides an enterprise data management and analytics platform as well as deep improvement implementation experience. Vendor tools and expertise will help organizations leverage their EHRs to meet population health management and value-based payment goals, as well as pursue some of today’s top healthcare strategic goals:


Neil Andersen

The Healthcare Outcomes Improvement Engine: The Best Way to Ensure Sustainable, Scalable Change

How do healthcare organizations create a systemwide focus on outcomes improvement? They build a healthcare outcomes improvement engine—a mechanism designed to drive successful and sustainable change.
Creating this outcomes improvement engine requires four critical components:

Engaging executives around outcomes improvement.
Prioritizing opportunities most likely to succeed.
Adequately staffing initiatives.
Communicating success early and often.

Once up and running, multidisciplinary engagement and standardized improvement processes fuel the outcomes improvement engine in its mission to produce sustainable, scalable improvement.

Brian Eliason, MIS
Neil Andersen

Why the Data Steward’s Role Is Critical to Sustained Outcomes Improvement in Healthcare

The data steward is critical to sustained outcomes improvement, yet they tend to be underappreciated members of the healthcare analytics family. Combining the invaluable technical expertise of a data analyst with the vital clinical knowledge of an experienced caregiver, the data steward’s skills and proficiency at both positions brings value beyond measure to any outcomes improvement project. Unfortunately, all too often, their role is non-existent even though potential candidates for the job are located in multiple data sources throughout the organization. Among other responsibilities, the data steward:

Reinforces the global data governance principles.
Helps develop and refine details of local data governance practices.
Is the eyes and ears of the organization with respect to data governance and the governance committee.
Provides direction to peers regarding appropriate data definitions, usage, and access.
Anticipates local consequences of global changes

For innovative health system leaders who have specifically recognized this emerging role, the ROI of data stewards who help achieve improved outcomes is very worthwhile.