The Importance of Good Data Governance in Healthcare

Providers and other medical organizations are increasingly relying on data to guide their decision-making as the healthcare industry becomes more computerized. As a result, data governance in healthcare is a particular and growing problem in the industry, as data becomes an increasingly important instrument for business development, treatment planning, and other purposes.

Organizations must now assure proper storage and management of this crucial data in order to protect patient and consumer privacy while also allowing full utilization of the great power it may provide corporate users.

What is Healthcare Data Governance?

Data governance, at its most basic level, is the process of making strategic decisions about how to handle and retain an organization's data in order to achieve its objectives while ensuring that it is used ethically and in accordance with an increasing number of data protection standards.

Because most healthcare companies acquire a large quantity of personal information, good data governance is critical. In an ever-changing sector like medicine, these techniques can also help organizations stay nimble and current as they respond to the area's ongoing developments.

Information Management Matters

Because of the large amounts of sensitive patient and customer information that all healthcare businesses must deal with, the healthcare profession is one of the fastest-growing areas for data management and data governance.

This is due in part to the fact that data breaches can be costly, with average costs ranging from $1.25 million to $8.19 million. The US Department of Health and Human Services reported more than 3,700 healthcare data breaches of 500 or more records between 2009 and 2020, resulting in the 'loss, theft, exposure, or improper disclosure' of 268,189,693 healthcare records. More than 81 percent of the population of the United States is covered by this policy.

Of course, avoiding such scenarios is critical, but the process must also include ensuring that all patient and customer information is used to enhance healthcare decisions. A strong data governance program can protect patient data while also allowing it to be used clinically. It also keeps data structured and up to date. For example, having rapid and easy access to a patient's medical records makes it easier for clinicians to make data-driven decisions regarding their care, even if the system that allows such access is constructed with data security in mind.

However, it is not a straight line. In addition, businesses must ensure that they:

1. Keep up with the ever-increasing number of privacy requirements.
2. Prevent security breaches by being proactive.
3. Integrate data from the industry's rising number of cloud-based systems, then evaluate the data to gain essential insights.
4. The most effective strategy for healthcare businesses to achieve these goals while avoiding potentially costly failures is to implement information management and data governance systems.

Data Governance vs. Information Governance

Although data governance and information governance are commonly misunderstood, there are a few key differences between the two.

Because they need the ability to regulate data labeling and upkeep, inter-departmental data transfer, and data security, data governance is frequently handled primarily by a company's IT department. This type of governance governs the organization, management, and ethical use of an organization's data resources by a set of rules and procedures (typically maintained by data stewards).

The program that data governance is a part of, the big-picture strategy that data governance programs carry out, is commonly referred to as information governance. It is described as "the activities and technology that businesses deploy to maximize the value of their information while avoiding related risks and costs," according to the Information Governance Initiative.

Data governance professionals are generally tasked with developing ways to implement the goals specified by information governance.

What Happens When Data Governance and Data Management Collaborate?

Data management is another keyword that is sometimes confused with information governance and data governance. Data management refers to the total process of managing all data from the time it is received by an organization until it is retired.

This macro-scale picture of data's journey through a healthcare institution is critical for ensuring that data is used efficiently and safely. Data management encompasses everything from who gets access to a piece of data throughout its life cycle, how it is evaluated, and the controls in place to keep it safe.

Strong information governance, data governance, and data stewardship initiatives are the foundation of a healthcare organization's overall data management strategy. When dealing with multiple types of sensitive patient data at various levels of an organization, it's critical to ensure that both clinical and management departments can access the data in the most efficient and secure manner possible, putting the company and its customers at the least amount of risk. Take a look at the link between a patient's medical records and their billing and insurance information. Medical data can and should be used to help establish their course of treatment, whereas billing information is required by the financial side of the company.

Data governance and data management systems can efficiently organize and exploit data when they work together. Data governance programs are aided by data management programs, which set goals for them and motivate them to handle data in the most efficient manner feasible for the organization. These two types of initiatives frequently coexist and occasionally overlap, particularly in smaller firms. Employees from both departments may collaborate with the business development team to make data management decisions, and then work to put those decisions into action as part of the data governance program.

Having a solid decision-making chain going from the data management department and flowing into the data governance department is critical for the overall program's success, regardless of how it works or how many people are involved. Data management and data governance systems can help healthcare businesses stay up with changes in their areas and foresee future pivot points while keeping their data warehousing operations structured and their patients' privacy protected when they operate together effectively.

Data management and governance in healthcare provide unique issues in terms of preserving sensitive patient information while also ensuring that it is accessible across the enterprise as needed to dictate treatment and more. As a result, data governance in healthcare is becoming a growing concern in the medical industry, as businesses strive to ensure proper data handling and administration while also maximizing the value it can bring to both clinical and corporate operations.

Data Governance Best Practices in Healthcare

So far, we've looked at the various obstacles and opportunities that healthcare companies confront when it comes to data management. Let's look at how leaders may use data governance best practices to preserve their patients' sensitive data while also using it to improve operations and outcomes.

Ensure that your data management strategy is informed by your business goals.

Data governance solutions that aren't fine-tuned to your company's business goals and strategy aren't going to get you very far, and they may even be counterproductive. Hospital systems, health insurers, and others in the healthcare industry are motivated by a variety of factors, including patient outcomes, financial performance, and Medicare and other insurance payments, among others. That's why it's critical to start at the beginning, with the business development team meeting with data governance experts to establish a program that works for the company. This plan might identify a few specific ways that data can be used to help the business achieve its objectives, and then specify structural ways for the organization to assist the fledgling data governance team in achieving those objectives. When talking about your objectives and how to achieve them, it's a good idea to think about what sorts of insights you want to get out of your data and how to get them.

Ascertain that your governance team(s) is/are aware of the data they're working with.

Once your data governance strategy is in place, you'll need to hire data governance professionals who are familiar with the data they'll be working with. Assume your organization is involved in cancer research. In that instance, individuals having prior knowledge in the sector and with the types of data involved may be better suited to manage governance than those with no prior experience in cancer research or treatment. Data organization and upkeep is one of the most important responsibilities that data governance experts perform. As a result, it's beneficial for them to be able to look at any given piece of data and immediately understand what it is, what it could mean, and where it should go.

Build Your Team(s) To Be Self-Sufficient and Self-Organize

Once you've established robust data governance norms and a sound data governance strategy, allowing data governance professionals to make their own interior procedures and design decisions can help them work more efficiently. Allowing your team to self-organize will allow them to improve their procedures and complete their tasks as quickly as feasible. Once the link between the data priorities of the business office and the goals of the data governance team has been established, the team may work optimally with limited outside interference and effective internal supervision. Depending on the size of your company, you may only need one or two employees, or you may require a larger group. Filling all of the important data governance jobs (including oversight positions and more hands-on data stewards) may save your firm a lot of difficulties down the road, regardless of size.

Determine how data is distributed and who has access to it using a hierarchical strategy.

To depict the descending layers of data privacy and security, a pyramid can be helpful. The entire company's data warehouse is normally located at the bottom of the pyramid, and all data stewards and workers have easy access to it. The data governance team can then work their way up, choosing what distinctions between the higher rungs of the pyramid are appropriate, what types of data will be housed at that levels, and how to establish who will have access to them. Because each organization's needs are distinct, an excellent hierarchical system will seem different for each one. For example, hospital-held data is frequently more concerned with patient health and ensuring that internal processes work as smoothly and effectively as possible than with maximizing financial returns. However, at a health insurer or other sorts of healthcare companies, this isn't always the case. Data governance policies are difficult to picture since they are typically very conceptual, but creating a hierarchy might assist your staff understand data governance (especially those working outside of the data governance team.)

Author: Himanshu Sharma

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References

 Lydia, Lee., 2020. Data governance in healthcare. [online] KPMG. Available at: <https://home.kpmg/xx/en/home/insights/2018/06/data-governance-driving-value-in-health.html> [Accessed 20 March 2022].

 Ross, Pounds., 2021. The Importance of Good Data Governance in Healthcare. [online] Diligent. Available at: <https://www.diligent.com/insights/healthcare/data-governance/> [Accessed 20 March 2022].

Alex, Membrillo., 2021. 5 Healthcare Data Management Strategies Marketers Can Use to Drive Growth. [online] Cardinal. Available at: <https://www.cardinaldigitalmarketing.com/blog/5-healthcare-data-management-strategies-marketers-can-use-to-drive-growth/> [Accessed 20 March 2022].