(US and Canada) Patrick Chen, Senior Director of Business Intelligence, Growth & Accountable Care Enterprise, Scripps Health, speaks with Savio Rodrigues, VP Client Partnership, Trianz – USA and CDO Magazine Editorial Board Member, about ways to measure the success of a data and analytics strategy, increasing data accuracy and trust, execution of strategy versus creating a strategy, the best way to build a data-driven culture, and having a successful framework for a data and analytic strategy.

Chen maintains that their KPIs align well with business operations and patient leadership team members. They are structured to focus on leveraging data to drive those KPIs. As a data analytics and strategy team, they have significant checkpoints to help the operation and clinical leadership members execute them.

He adds that the KPIs are qualitative regarding having specific capabilities in place and how quickly models are developed. It all boils down to improving patient care, says Chen.

He states that data accuracy and trust are crucial in health care decisions and investments in populations. He notes that analytics drive decisions on population health and individual health care.

Chen affirms that Scripps Health centralizes information by partnering with physicians and allowing the “last-mile delivery” by primary care physicians. He states that AI is not appropriate for the health care environment compared to other industries. Hence, Chen and his team primarily focus on partnering with medical directors and clinical lab members to provide them with optimum information for better results.

Data scientists find it hard to explain downstream effects such as data integrity issues. Chen maintains that they can be explained by returning to the raw data sets, making execution difficult.

A data and analytics leader, Chen believes roadmaps are tailored toward organizational needs, but the execution tends to be much more complicated. Hence, it is imperative that decision making and implementation deliver sustainable solutions. He says that organizations must focus on establishing an aligned data strategy for the long term.

Chen also believes in making people’s lives easier with data and in sharing the data’s impact on patient outcome levels. Data does not replace health care providers’ work but makes them more efficient. Chen affirms from a clinical perspective that patients are satisfied and providers are happy with the saved time. 

A data strategy framework requires key components, Chen says. It starts with ready-to-go executive leadership. Next comes data architecture, where time is spent analyzing the best product, the right software, and hiring staff. Then comes the enterprise data warehouse and the research and development environment for predictive modeling.

The next part of the framework is data governance, which is critical because it allows the data strategy team a certain level of autonomy. This is where organizations have the highest level of joint leadership at an operational level. Chen pinpoints compliance as a part of data governance.

Implementation is the final part of the framework where the informatics and IT infrastructure team develops back-end tools for the technical staff. Moreover, Chen concludes that the informatics team needs to implement solutions so that the frontline staff is satisfied.