Data Governance and Interoperability of Healthcare Information Systems – The Role They Play in Innovation

To better understand how data governance fits into the interoperability of healthcare
information systems, let’s first look at what data governance refers to.

According toAHIMA, data governance represents “The overall administration, through clearly defined procedures and plans that assure the availability, integrity, security, and usability of the structured and unstructured data available to an organization.”

Table of Contents

• Data Governance in Enabling Interoperability of Healthcare Information Systems – Promoting Innovation Across the Entire Industry
• Standard Operating Procedures That Should Be Taken into Account When Improving Interoperability of Healthcare Information Systems
• The Benefits of Data Quality for Enhancing Interoperability of Healthcare Information Systems and Their Interrelationship
• Ensure Seamless Data Governance Workflow When Looking To Facilitate Interoperability in Healthcare

Data Governance in Enabling Interoperability of Healthcare Information Systems – Promoting Innovation Across the Entire Industry

Considering the sensitivity of the information in healthcare, data governance is crucial. For healthcare providers, effective data governance leads to improved analytics, ensures that data is consistent and trustworthy, and doesn’t get misused. At the same time, it enhances operations support and better decision-making.

Organizations looking to have a robust data governance program in place have to follow certain steps, and it’s important for any health IT professional to be mindful of how they impact the entire digital transformation. For example, an organization looking to implement a data governance program has to establish the basic framework for the collection, retention, use, accessibility, and sharing of healthcare data. This framework may consist of policies, procedures, standards, ownership, decision rights, roles and responsibilities, and accountability related to the data. Further, it increases the accuracy of the data lifecycle.

Healthcare organizations frequently encounter obstacles when implementing healthcare data governance, mainly because key stakeholders are not fully aware of the full potential of data value. This in turn may result in data silos and delays in workflows, thereby reducing the value of the services provided. To avoid these situations and overcome current obstacles related to them, it is crucial to establish healthcare data governance as a culture within the organization, with subject matter experts onboard.

Once these aspects have been addressed, healthcare organizations will be able to reap the benefits of data governance and better utilize their data, ultimately improving the interoperability of healthcare information systems, if that is one of their goals. Here are some of the key benefits:

• At the business level

Data governance translates into cost reduction, minimizing risks, improving the likelihood of continuing business through risk management, and optimization, as well as improved communication both internally and externally;

• Reflected at operational levels

The elimination of rework through the use of trusted, standardized, and multipurpose data assets, as well as the optimization of internal data rules;

• On the technical side of healthcare providers

Effective data governance provides high reliability when it comes to implementing compliance requirements as well as an increase in data value.

Through the governance of data assets that meet the desired quality thresholds, healthcare stakeholders not only optimize staff effectiveness in healthcare facilities but also make it easier for all parties to improve interoperability of healthcare information systems.

Standard Operating Procedures That Should Be Taken into Account When Improving Interoperability of Healthcare Information Systems

Policies play a critical role in healthcare data governance. When crafting software aimed at enabling interoperability of healthcare information systems, health IT teams have to consider each of the policies that organizations may need to implement – depending on specific requirements and key areas of data governance. The most notable areas to address are data integrity policy, data access policy, data privacy and usage policy, data sharing policy, and data retention policy.

Each of these has a specific purpose, which is equally vital in contributing to the decision-making process, with data quality being the foundational element throughout the process of healthcare software development that aims towards interoperability.

The Benefits of Data Quality for Enhancing Interoperability of Healthcare Information Systems and Their Interrelationship

Ensuring data quality is often a goal of an organization’s healthcare data governance program. Yet, what exactly does data quality mean for the industry and how can it improve the chances of realizing the benefits of interoperability in healthcare?

The healthcare industry effectively utilizes data for multiple purposes, and an evaluation of the data’s quality is based on its ability to meet any intended purpose, such as:

• Maintaining reliability of HL7 FHIR when implementing software for the interoperability of healthcare information systems;
• Making sure electronic health records (EHR) are maintained and improved while preventing data loss as it is moved from the EHR to other systems;
• Achieving semantic uniformity at the point of care, while maintaining clinician flexibility, through accurate ICD-10 classification;
• Designing effective medical policies and procedures, providing timely accurate diagnosis, treating diseases and providing ailments within their integrated healthcare interoperability system;
• Conducting research and analysis on novel diseases and patient histories;
• Maintaining patient records in order to conduct public health surveillance;
• Assuring that policies and procedures are implemented accurately and in accordance with data quality, and that small errors are not aggregated and shown in the results.

Data quality ensures that healthcare providers’ data facilitates the execution of these processes. A lack of high-quality data can impede the process of executing these tasks and cause system bottlenecks.

The quality of data and interoperability in healthcare are mutually dependent – information sharing plays a major role in ensuring data quality, and vice versa. Since many people seek healthcare outside of one institution, information from a single source – for example, an electronic health record system from only one hospital – is almost always incomplete, which negatively affects both patient care and financial returns.

Which is why data quality, with all its comprising aspects, is an ongoing need for increased interoperability in healthcare and a high focus within the frame of data governance.

Healthcare interoperability companies that wish to improve the segment through reliable and established methodologies and management should be more concerned about data quality, an aspect of the industry that deserves all of their attention.

Ensure Seamless Data Governance Workflow When Looking To Facilitate Interoperability in Healthcare

The ability of a healthcare business to remain responsive is dependent upon data governance, and even more so when finding ways to improve interoperability of healthcare information systems and accelerate technological innovation. Since the latest technologies are highly dependent on the quality of data, you will not be able to take advantage of your data assets and achieve a successful digital transformation if your company doesn’t govern its data accordingly.

As a healthcare stakeholder, you need to ensure that your company adheres to best practices regarding data governance. Recommendations include establishing program priorities to attain desired results, defining roles and responsibilities clearly to ensure accountability for your data governance plan, establishing key metrics to measure and demonstrate value propositions, and encouraging collaboration by enabling the team to discuss challenges and share best practices.

Remember, establishing healthcare data governance is an ongoing learning process. Over time, the system will adapt and evolve in response to progress.