As a chief data officer, healthcare CEO, or other executive in the industry, you know how vital data governance is across all departments and within your organization’s supply chains. The well-being of your patients and company depend on it. By adhering to comprehensive yet practicable data governance policies, your organization can reduce risks associated with inappropriate handling and use of critical information while simultaneously optimizing operational performance. Grounding strategies for implementing effective data governance in the healthcare sector is critical.
What is data governance and why it matters
Data governance is a process for managing data assets in an organization, with the primary goal of ensuring data interoperability and data quality. Healthcare data governance is especially essential as it allows organizations to ensure that data is secure and also accessible in communities where data sharing and data privacy are of major importance. Health Level 7 (HL7) and Fast Healthcare Interoperability Resources (FHIR) are two standards used within data governance strategies to enable better data management, and consequently, a better patient experience. With the help of data governance, disparities can be addressed in healthcare organizations, allowing for greater equity when it comes to patient care in healthcare delivery settings. Therefore, data governance should be seen as an important feature of any successful organization that strives to leverage technology to provide comprehensive healthcare experiences.
As per MIT’ s survey, Chief Data Officers priorities were as follows:
- Establishing clear and effective data governance (51%)
- Improving data quality (48%)
- Building and maintaining advanced analytics capabilities (42%)
- Building and maintaining business intelligence capabilities (36%)
- Data monetization capabilities (21%)
- Data, analytics, and AI ethics (21%)
Data governance also ranked highest when chief data officers were asked to rank their top three priorities, with 45% citing clear and effective data governance as a top concern.
Key challenges in the healthcare industry when implementing data governance
The healthcare industry is complex, and implementing data governance can present certain challenges when it comes to collaboration between various stakeholders. Data silos, legacy systems , and data inconsistencies can all present obstacles to effective data governance. Additionally, the implementation of new technologies must be accompanied by policies to ensure their compliance with regulatory requirements. Finally, data privacy and security are also major concerns in the healthcare industry and must be addressed when implementing data governance strategies.
Consideration
A solid data governance program is essential to ensure the proper management of valuable healthcare data and the associated risks, such as data privacy, quality control and security. Implementing effective data governance requires a comprehensive plan that involves various strategies throughout the entire value chain. Some strategies include conducting internal policy reviews, forming governing bodies responsible for developing and implementing standards, policies and procedures that apply to teams across organizations, leveraging technology to provide insights into usage trends, developing communication plans with stakeholders regarding policies and processes, ensuring transparency in leadership roles related to this governance program, monitoring compliance activities and encouraging user feedback through surveys and focus group interviews. These steps are necessary for successful implementation of a data governance program in the healthcare sector.
How to ensure proper data governance
Proper data governance is essential to ensure the efficient and accurate operation of an organization. It involves creating static rules, dynamic management processes and a comprehensive set of business objectives which must be met to protect the integrity of data within the system. Best practices can include investing in high-quality security tools, educating personnel about applicable regulations and legal requirements related to data management and setting up internal procedures for compliance monitoring. Additionally, incorporating artificial intelligence into existing data platforms could help with predictive analytics that can create even more secure solutions moving forward. Taking these steps can help organizations set up a robust process for data governance which will allow them to remain compliant while maximizing their operational efficiency.
Conclusion
To summarize, data governance is an essential tool for healthcare organizations to ensure trust, transparency and compliance within their data systems. There are several key challenges that organizations face when trying to implement proper guidelines including the need for effective communication and change management strategies. Artificial Intelligence can enable healthcare organizations to make better use of their data and optimize the process of data governance.
Ultimately, a successful adoption of data governance in healthcare requires both good planning and execution as well as robust monitoring mechanisms. With the promised benefits of improved patient outcomes, reduced costs, better personnel organization and more efficient operations, now is the time for healthcare systems everywhere to embrace the practice of implementing an effective data governance program.
Photo: Galeanu Mihai, Getty Images
