Why Data Governance in Healthcare Is a Necessity: Tech Talk With Excellarate’s CSO

Lauren Reiss, chief service officer, Excellarate, joins Neha Pradhan Kulkarni to discuss the kind of challenges healthcare providers face when establishing effective data governance. Reiss also talks about how healthcare organizations can build a culture of adding AI and ML into their data governance practices.

In this edition of Tech Talk, Reiss shares some of the data governance learnings that healthcare needs to integrate in a COVID-19 influenced world. She also addresses why healthcare needs to keep their fingers on the pulse of what’s happening to outweigh the challenges to data standardization.

Key Takeaways on Why Data Governance in Healthcare Is a Necessity:

• Data governance strategies must establish the infrastructure and technology for the creation of policies.
• To become data-driven, one must start with the identification of what drives their business.
• Collaboration and concerted efforts at an enterprise level are needed to build a data-driven culture. 

Here are the edited excerpts from our exclusive interview with Lauren Reiss, Chief Service Officer, Excellarate:

Toolbox: Since inception, Excellarate has provided deep domain expertise in health tech. What are the data governance learnings that healthcare organizations need to integrate in a COVID-19 influenced world? 

Lauren: In the aftermath of the COVID 19 pandemic, many organizations have had to re-look at their data governance best practices. We have found that not one approach works for everyone, an organization’s strategy on data governance needs to specifically be fit to meet their needs. To boil it down, it’s about providing trusted data to the right user at the right time.  

Data governance strategies must start with establishing the infrastructure and technology for the creation and maintenance of policies. The initial question for many organizations has been how to deal with data sharing and privacy amidst a pandemic, where there is a fine line between privacy and public safety.  How do we respond to a crisis that is impacted by the movement and interaction between people and their health data which is highly sensitive information? 

“Data governance practices have often been about the “no”, however, we have learned we need to focus on a systematic approach that allows for the sharing of data in a secure, private and specific manner. The pandemic forced healthcare providers to digitize and quickly.”

The use of telemedicine, remote patient monitoring, and AI-powered tools has driven healthcare organizations to revisit or implement new data-driven practices.

Toolbox: Excellarate boasts of top-notch solutions in predictive analytics and big data. In your experience, what kind of challenges healthcare providers face when establishing effective data governance? 

Lauren: Post-COVID, there are many changes that impact data governance, these include the changing work environment due to remote workers and the addition of new vendors and data channels causing data management to become of greater importance.  It is important to remember different people within an organization need different data, you might consider a combined data approach instead of independent sources, allowing different teams to access more reliable and relevant information.

Toolbox: What are the necessary steps to take for success in data governance?

Lauren: The focus first must be to identify the key areas your strategy will address, which includes collecting, processing, sharing, and analyzing data. To be successful and continue to innovate organizations must focus on the importance of this data across individuals, teams, and business functions. There are many options today regarding how to transform data. First, we must determine the technology to manage data successfully. One major focus must be on the data management processes including to:  

• • Identify data storage and processing requirements
  • Design structures and plans to meet the current and long-term data requirements of the enterprise 
  • Define the current state of data in the organization 
  • Provide a standard business vocabulary for data and components
  • Align data architecture with enterprise strategy and business architecture
  • Handling unstructured data

Organizations must bring together disparate data and start to look at information differently.   Data modeling and design are essential for success and require governance responsibilities including:

• • Creating standards for data modeling and ensuring the entire organization follows these standards
  • Maintaining the quality of data models and database designs 
  • Maintaining version controls 
  • Ensuring that these data models are available company-wide

There are many things to consider around data governance and while we have covered only a few we cannot forget about data security and the role it plays in today’s organizations. This has changed drastically, and we must be open to new ideas.  The objective of a governance team is to ensure that all the procedures are well documented, and encryption and standards are met.  

Toolbox: It seems like data collected in healthcare organizations is an untapped resource. What tips do you have for healthcare providers to become a more data-driven organization? 

Lauren: To become data-driven, one must start with the identification of what drives their business.  You cannot measure what you do not know. Data is the most valuable resource for providers to find ways to improve patient care. There are many different sources of data including patient behavior, claims and cost data, research and development data, and clinical data on which providers can rely. 

“Healthcare providers need to transition to new ways of working, adopt new technologies and scale operations, investing in effective data management methodologies and solutions. The goal is to convert valuable data into trusted insights that lead to better business decisions.”

Another way to improve data collection is a focus on standards in the collection of data, finding ways to leverage information systems developed by EHR vendors and Health IT developers. One of the latest techniques for collection and sharing of data is using API’s (application programming interfaces) allowing easy access to real-time data, this would improve the collection and exchange of information across and between healthcare providers.   

Toolbox: Data standards are critical to a system-agnostic interoperability and the benefits significantly outweigh the challenges to standardization. So how can healthcare providers keep their fingers on the pulse of what’s happening? 

Lauren: First, this must be a priority, understanding the importance of integration and interoperability to the overall success of any program around data. Collaboration and concerted efforts at an enterprise level are needed to build a data-driven culture.  

“Consider the need for technical integration across multiple platforms, determine systems of truth for critical data and information entities, and establish data governance practices. Understanding the need to maintain and protect patient privacy, it is essential that such data is made interoperable and shared across healthcare’s internal systems as well as with other healthcare providers.”

Work closely with internal and external resources who can focus on finding the synergies linking business outcomes with technical implementations of any solutions. Healthcare organizations will need to be more entrepreneurial in investing in and sponsoring innovative data-driven initiatives.

Toolbox: As data explodes and advanced technologies come into play, how can healthcare organizations build a culture of incorporating technologies like AI and ML into their data governance practices? 

Lauren: Health-related data is expanding rapidly — both in terms of what constitutes medical information and the range of organizations that collect it. To support this transformational change healthcare providers will need not only to attract, train, and retain more healthcare professionals but also need to ensure their time is used where it adds the most value—caring for patients. Building on automation with the use of AI will help some of these challenges.  

“AI can lead to better care outcomes and improve the productivity and efficiency of care delivery. First, solutions should address routine, repetitive, and largely administrative tasks, optimizing healthcare operations will likely increase adoption and further build on this data-driven culture. Like any organization looking to make a major change, it will not come easily and will require some effort.”

Setting standards for digitization, data quality, data access, governance, risk management, security and sharing, and system interoperability will in turn continue to move healthcare organizations into a patient-centric, data-driven culture.  

Toolbox: In an industry already shifting toward increased transparency and data sharing, which health tech trends will provide a better business for healthcare service providers?

Lauren: Managing patients is expensive and requires systems to shift from an episodic care-based philosophy to one that is much more proactive and focused on long-term care management.  AI and ML can improve the speed and accuracy in the use of diagnostics, give practitioners faster and easier access to more knowledge, and enable remote monitoring and patient empowerment through self-care. This will shift the focus away from memorizing facts and moving to innovation, entrepreneurship, and continuous learning with a focus on patient care.

About Lauren ReissOpens a new window :

Lauren Reiss is the chief service officer at Excellarate. She has more than 15 years of healthcare experience working in pharmacy solutions and service delivery experience. Lauren focuses on Healthcare Information Technology solutions specializing in areas that impact, connect and integrate members, providers and payers. 

About Excellarate

Excellarate is a global technology services and solutions company with more than 20 years of domain expertise within health, insurance, financial and enterprise technologies. The company is a trusted partner of over 250 clients, including Change Healthcare, Ad Giants, Alchemy Systems, and Centric Software, to accelerate innovation and achieve business agility. Excellarate’s strategic technology and solution partners include Azure, Google Cloud, Appian and Salesforce to help drive digital transformation for its clients. 

About Tech Talk

Tech Talk is an interview series that features notable CTOs and senior technology executives from around the world. Join us as we talk to these technology and IT leaders who share their insights and research on data, analytics, and emerging technologies. If you are a tech expert and wish to share your thoughts, write to [email protected]Opens a new window

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