Published by: Pat McGrath, Chief Technical Officer at WPC Healthcare, Inc.
The fundamental principles of science still apply, even in the world of Big Data.
I think of my 7th-grade lab teacher sometimes when I work with a client on a data science related project. When introducing the class to using metric scales, she emphasized the importance of calibrating the equipment first because, “Garbage in, garbage out.” Meaning, you can’t expect to deliver accurate results if you don’t get the foundational aspects right up front.
This same philosophy can also be applied to some of the most talked about, mulled over and trending topics in the world of healthcare – data science and predictive analytics. But, what’s forgotten in the conversation is the emphasis on first getting a solid data foundation in place. Some mistakenly think that data is data, and it’s all equally valuable, accurate and usable. Not so. The distinction is referred to as data literacy – understanding the origin and meaning of the data being considered to enact change.
Organizations that want to succeed deliver the best health outcomes and control costs need to focus on getting a solid data foundation in place. Hospitals that demonstrate the highest level of downstream analytical maturity focus attention on the following upstream data-related activities:
- Data capture
- Data quality
- Data integration
- Data trustworthiness
- Data governance
Strategies for Optimizing Your Data Infrastructure
For organizations who are committed to developing a holistic data governance methodology, there are several core strategies that can help your organization evolve.
- Value data as an asset!
- Don’t wait.
Savvy healthcare leaders are not waiting for a universal data governance protocol. Instead, they invest early to deliver accurate and reliable, actionable data. This strategy allows for targeted analytical solutions that can be put into practice by clinicians and operating staff immediately.
- A profound ROI in organized data and analytics.
Provider organizations who invest time and resources into their data and analytics capabilities report a compelling return on investment. Related to that, senior leaders and governing boards are now including how their organizations capture, manage, store and utilize their data assets in the list of more traditional competitive differentiators such as price, product features and supply chain.
- Your data foundation influences the value of your analytics.
While success in the world of analytics is driven by a variety of elements, high performing organizations prioritize data management and governance rather than trying to solve for all data issues.
- Prioritize a governance policy.
Astute analytical leaders invest in their data assets based on a list of prioritized analytics use cases. That is a critical step towards becoming an analytical competitor.
- Opportunities for Vast Improvements
Data science and analytics can and should drive the business and clinical decisions of hospitals in order to make significant improvements in health outcomes.
At the heart of the analytical hospital is a commitment to treating data as a valuable asset that must be managed over time and constantly improved. As Pete Aiken said, “data is not technology”.
I advise clients that while it may be initially intriguing to just focus on the ultimate goal (predictive analytics, machine learning, etc.) we bypass the infrastructure and data governance work which is so crucial to long-term success.