As the healthcare world becomes increasingly digitized, providers and other medical organizations rely more and more on data to drive their decision-making. As a result, data governance in healthcare is a particular and growing concern in the industry, as information becomes an essential tool for business development, treatment planning and more.
The onus is now on organizations to ensure proper handling and management of this critical data to maintain patient and customer privacy while also enabling full leverage of the incredible power it can bring to corporate users.
What is Data Governance in Healthcare?
At a high level, data governance is the process of making strategic decisions about how to manage and store an organization's data to advance its goals while ensuring it is used ethically and following a growing number of data privacy regulations.
Good data governance is crucial in healthcare because of the vast amount of personal information most healthcare organizations collect. Also, in an ever-changing field like medicine, these practices can help keep companies agile and up to date as they react to the constant changes in the field.
Information Management Matters
The healthcare field is one of the fastest-growing areas for data management and data governance, partially because of the enormous amounts of personal patient and client information that all healthcare organizations need to deal with.
In part, this stems from the fact that data breaches can be costly, costing organizations between $1.25 million and $8.19 million on average. Between 2009 and 2020, the U.S. Department of Health and Human Services reported more than 3,700 healthcare data breaches of 500 or more records, resulting in the 'loss, theft, exposure, or impermissible disclosure' of 268,189,693 healthcare records. That covers more than 81% of the U.S. population.
And they are accelerating. In 2018 HHS saw about one healthcare data breach per day, but by the end of 2020, that rate had nearly doubled to 1.76 per day.
Avoiding these types of situations is, of course, paramount, but the process goes hand-in-hand with making sure that all patient and client information is used to advance healthcare decisions. A robust data governance program can protect patient data and leverage it clinically while keeping data organized and updated. For instance, having a particular patient's healthcare records quickly and easily accessible makes it easier for doctors to make data-driven decisions about their care, even when the system that makes that access possible is designed with data security in mind.
It's not a straight line, however. Organizations must also make sure they:
- Keep up with the growing number of privacy-related regulations.
- Proactively prevent security breaches.
- Integrate data from the growing number of cloud-based systems that the industry relies on and then analyze that data to glean the necessary insights.
- Information management and data governance programs are often the most effective way for healthcare organizations to accomplish these goals while avoiding potentially costly setbacks.
Information Governance vs. Data Governance
Data governance is often confused with information governance, but the two have a few critical distinctions.
Data governance is usually handled primarily by a company's IT department, as they need the skills to control data labeling and upkeep, inter-department data transfer and data security. This type of governance is a set of rules and procedures (often managed by data stewards) that control the organization, management, and ethical use of an organization's data resources.
Information governance usually refers to the program that data governance is a part of, the big-picture strategy that data governance programs carry out. According to the Information Governance Initiative, it is defined as 'the activities and technologies that organizations employ to maximize the value of their information while minimizing associated risks and costs.'
Information governance sets the goals for data governance experts, who are often tasked with creating strategies to implement them.
Data Governance vs. Data Management: What Happens When They Work Together?
Another important term that is easily confused with information governance and data governance is data management. Data management is the overall process of how all data is managed from the moment an organization receives it, to the moment it is retired.
This macro-scale lifecycle view of the path data takes through a healthcare organization is very important for ensuring that data is used effectively and safely. Data management includes everything from who has access to a piece of data over its lifetime and how it is analyzed to the safeguards put in place to keep it secure.
In healthcare, strong information governance, data governance, and data stewardship programs form the backbone of an organization's total data management program. When dealing with multiple types of sensitive patient data across different levels of the organization, making sure that both clinical and management departments can effectively access the information in the best and safest way possible is essential, ensuring that the company and its customers are exposed to the least amount of risk. Consider the relationship between patient medical records and their billing and insurance information. The medical data can and should help determine their course of care, while the financial side of the organization needs access to their billing information.
When working in concert with each other, data governance and data management programs can effectively organize and utilize data. Data governance programs are supported by data management programs that give them goals and drive them to deal with data in the best way possible for the specific organization. These two types of programs often exist inside each other and sometimes overlap, especially in smaller organizations. Employees who work in both departments may make decisions with the business development team about managing the data and then work to make these decisions come to life as part of the data governance program.
No matter how it works or how many people are involved, having a strong decision-making chain running from the data management department and flowing into the data governance department is extremely important for the success of the overall program. When working together effectively, data management and data governance programs help healthcare organizations keep up with changes in their fields and predict where future pivot points will be while keeping their data warehousing programs clearly organized and their patients' privacy protected.
Healthcare presents unique challenges in data management and governance, both protecting sensitive patient information and ensuring that it is accessible across the organization as needed to dictate care and more. For that reason, data governance in healthcare is an emerging concern across the medical field as organizations work to ensure proper handling and management of their data while still leveraging what it can bring to both clinical and corporate operations.
Data Governance Best Practices in Healthcare
So far, we have discussed the many unique challenges and opportunities that healthcare organizations face in managing their data. Now let's consider how leaders can incorporate data governance best practices to protect their patients' sensitive information while also leveraging that data to improve operations and outcomes.
1) Ensure That Your Business Goals Inform Your Data Management Strategy
Data governance systems that are not fine-tuned to your organization's business goals and strategy will not get an organization far and may even be counterproductive. Hospital systems, health insurers and others in the healthcare field face multiple different motivations, ranging from patient outcomes to financial performance to Medicare and other insurance payments. That's why it's essential to start from the beginning, usually by having the business development team meet with data governance professionals to design a program that works for the organization. This plan might select a handful of specific ways that data might be used to further the organization's goals and then outline structural ways for the organization to help the fledgling data governance team achieve those goals. When discussing your goals and how to meet them, it may be useful to consider what kinds of insights you hope to draw from your data and how you can best extract them.
2) Ensure Your Governance Team(s) Know the Data They're Working With
Once your data governance plan is underway, it's essential to employ data governance professionals who are familiar with the context of the data that they will be working with. For example, suppose your organization works in cancer research. In that case, people who have experience in the field and with the kinds of data involved may be more qualified to manage governance than employees with no background in cancer research and treatment. One of the most critical tasks data governance professionals undertake is data organization and upkeep. So it is helpful for them to glance at any given piece of data and have a clear idea of what it is, what it could mean and where it should go.
3) Build Your Team(s) To Be Self-Sufficient and Self-Organize
Once you've set up sufficiently strong data governance protocols and have a solid data governance strategy, data governance professionals often work best when allowed to make their own interior processes and design decisions. Allowing your team to self-organize will ensure that they can optimize their processes and do their job as efficiently as possible. Once the connection between the business office's data priorities and the data governance team's goals has been established, the team may function best with minimal outside interference and strong internal management. Depending on the size of your organization, you may need a team as small as one or two people, or you may need a larger team. Regardless of size, filling all of the essential data governance roles (including oversight positions and the more boots-on-the-ground data stewards) may save your organization many headaches down the road.
4) Use a Hierarchical Strategy To Determine How Data Is Distributed and Who Can See What
It can be useful to use a pyramid to visualize the descending levels of data privacy and security. At the bottom of the pyramid, there is usually the entirety of the company's data warehouse, which all data stewards and data employees may easily access. From there, the data governance team can work their way up, deciding what delineations between the higher rungs of the pyramid make sense, what kind of data will be stored at those levels, and how to determine who will have access to them. An excellent hierarchical system will look different for every organization, as they are built around the individual needs of each. Hospital-held data, for instance, is often less focused on maximizing financial returns and more on patient health and ensuring that internal systems run as smoothly and efficiently as possible. That isn't always the case at a health insurer or other types of healthcare organizations, however. Data governance strategies are hard to visualize as they are often highly conceptual, but drawing out a hierarchy can help keep data governance straight for your employees (especially those working outside of the data governance team.)
How To Create a Robust Healthcare-Orientated Data Governance Strategy
Constructing a strong healthcare data governance system can seem like an intimidating task, but sticking to some best practice guidelines can help you get started.
The first step is to identify your business' data objectives and create a plan around those goals. What types of data are you collecting, from whom, and how do you expect to use it? This information can help shape the governance system that you'll need to manage your data.
Then select a team that knows both the specifics of your field and has a background in data governance. As mentioned, data managers deeply ingrained in the information they oversee can more nimbly and effectively manage that data by spotting irregularities and opportunities in real-time.
It's also important to let your experts develop their own management strategies. When the team creates its own robust processes for data collection, storage, analysis, and security, the result is a more specialized, efficient oversight system that fits within the overall data governance plan.
Once the strategy and processes are in place, it's imperative to find technology to run it all that matches your data governance strategy and needs. At the very least, most healthcare organizations will need both data warehousing software and hardware along with data analysis software.
Finally, enact your data governance plan and begin the ongoing process of reforming it to fit your organization's needs tightly. Keeping these fundamentals in mind when establishing data governance over your organization's data can help keep data governance streamlined and straightforward.
Challenges for Data Governance in Healthcare Organizations
- Data governance is a complex but increasingly important department for any modern healthcare organization to have. The associated challenges in healthcare include:
- Building and organizing a system that makes intuitive sense
- Ensuring efficient and intentional movement of data throughout an organization
- Reducing security breach risks
- Creating a foundation that can be built on as the healthcare organization grows
- While these are all issues, thoughtful and intentional planning in the first stages of the healthcare data governance process will help alleviate some of these potential challenges.
Why Data Governance Is Essential to Success in Healthcare
Data governance is the unifying process that allows healthcare companies to take full control of the data they collect from their clients and patients, extracting the most significant benefit from this data while minimizing the inherent risks associated with holding individuals' personal information.
With a team of experienced data governance professionals communicating with an organization's business development team, healthcare organizations can take their data analysis to the next level. They can do this by coming up with solutions and innovations that will keep them ahead of competitors while providing the highest quality of service to their patients.
The Diligent Solution
Patients are increasingly taking control of their own health and calling for the sector to become more proactive in prevention rather than cure, while at the same time, healthcare institutions are looking to increase efficiency while reducing costs. This is placing increased pressure on hospitals to operate more like businesses, making medical information more accessible by reducing admin-heavy processes that take staff away from patient care.
Diligent works with the healthcare sector to streamline these processes, enabling board and committee members to work more efficiently, share information swiftly and securely while providing more cost-effective levels of patient care. By centralizing all of your confidential materials into one convenient portal, Diligent's data governance software operates in real-time, is easy to use, delivers information and enhances collaboration within the confines of a single platform.