Learn more about Dan Lowder

Author Bio

Dan Lowder

Dan Lowder joined Health Catalyst in December 2013. Prior to coming to Health Catalyst, Dan was a Business Intelligence Engineer at the Church of Jesus Christ of Latter Day Saints, and before that a data architect at Intermountain Healthcare. Dan has a degree in computer Information Systems from Regis University in Colorado; as well as an MBA from the University of Utah.

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Dan Lowder
Trevor Smith

Hiring Top Healthcare Analytics Talent: Five Best Practices

COVID-19 has escalated healthcare’s decision-making demands, reinforcing the industry’s need for highly skilled analytics team members. As a result, health systems face mounting pressure to hire the best-suited analytics talent in a timely manner and with minimal burden on existing team members.
Five proven inclusive strategies will help hiring managers efficiently build an analytics team that can adapt to healthcare’s shifting environment and also fit within an organization’s culture:

Open positions to remote employees and conduct interviews via video conferencing.
Insert “tollgates” into the hiring process.
Use scenario-based role play to assess many competencies concurrently.
Assess cultural fit.
Follow up with and provide feedback to all candidates.

Dan Lowder

Healthcare Dashboards vs. Scorecards: Use Both to Improve Outcomes

Healthcare IT leaders tend to debate over which tool is best for measuring and sustaining outcomes improvement goals: healthcare dashboards or scorecards. But using both tools is the most effective approach.
“Scoreboards” take advantage of the high-level, strategic capacity of scorecards and the real-time, operational functionality of dashboards. But using both effectively requires a thorough understanding of the who, what, when, and how of each tool.

Who: Scorecards are for leaders; dashboards are for the frontline.
What: Scorecards are strategic; dashboards are operational.
When: Scorecards are daily, weekly, or monthly reports; dashboards are real-time or near real-time.
How: Scorecards enforce accountability and provide actionable data; dashboards provide drill-down capability and inform root cause.

Despite the different but equally important aspects of each tool, they best support outcomes improvement when used together.

Dan Lowder

The Healthcare Data Warehouse: Evolved for Today’s Analytics Demands

What do health systems risk when they hold onto an older enterprise data warehouse (EDW) perspective? By thinking about the EDW as a tool for only historic data that’s not highly reliable and can’t support important decisions, organizations miss out on near real-time (NRT) reporting and valuable decision-making resources.
Far from an outdated tool, today’s EDW is capable of meeting rising demands for timely, quality data. Health systems can ensure their EDW reaches its full potential by prioritizing it among their technology and properly supporting it—with the best equipment and human resources. The well maintained EDW is not stuck in the past, but rather, an invaluable tool to move healthcare analytics forward.

Dan Lowder

The Surprising Benefits of Bad Healthcare Data

Bad healthcare data is inevitable. Whether it happens as a result of human input error or an incorrect rule, bad healthcare data will happen. And rather than ignoring it, hiding it, or scrubbing it, health systems need to take a more transparent approach.
Bad healthcare data, when approached correctly, has four surprising benefits:

Provides valuable feedback to application users/data consumers.
Inspires an improvement culture.
Creates a Snowball Effect of Success.
Improves Data Accuracy.

It’s not easy to make the shift from fearing bad data to embracing it, but there are several steps systems can take to start creating a data transparency culture:

Empower: encourage data consumers to provide feedback.
Share: Provide a mechanism for sharing feedback.
Act: dedicate time and resources to respond and act.

Health systems prepared and willing to fix bad data will ultimately improve data quality.