What Is Data Control? A Guide for Healthcare Facilities

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Written by Kerry Larkey, MSN, RN Content Writer, IntelyCare
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Reviewed by William C. Peacock, Esq. Senior Manager, Performance Marketing, IntelyCare
A team of medical professionals looks at a patient's data together.

The amount of “big data” produced by the healthcare system is staggering. Due to the sheer volume of information captured and stored within electronic health record (EHR) systems, it’s easy to feel overwhelmed and experience data overload. Still, it’s estimated that 95% of hospital data goes unused, revealing a mismatch between the quantity and usability of information.

But the value of this data — when properly collected, organized, and utilized — is enormous for driving patient safety and quality of care. We’ll guide you through one approach facilities can take to begin wrangling data and use a data controls framework to structure its management.

What Is Data Control?

Data control, in programming language, is simple: It defines who has access to data by either granting or denying privileges. While programming may not be difficult, deciding who has access to what, and when, can be extremely difficult for an organization to establish. One factor that makes this process difficult is the large number of people and systems that manage a single piece of data throughout its lifecycle.

The stages of the data lifecycle include:

  1. Capture — record information
  2. Process — create a product/service
  3. Use — share, analyze
  4. Store — keep, archive
  5. Dispose — destroy

Data control ensures that information is handled properly at each stage of this lifecycle. As technology advances and new security risks arise, there are many different types of access control models that can be implemented by organizations. Some examples include:

  • Role-based controls — This model grants access to data systems based on an individual’s role within an organization. This model assumes that users will only access what’s needed to fulfill their job duties.
  • Attribute-based controls — This model combines observable attributes of users and determines what types of data can be accessed based on these attributes.
  • Purpose-based controls — This system grants access to specific actions based on a user’s intended purpose for the data, including actions like creating new documents or conducting system-wide audits.

Why Is Data Control Important in Healthcare Settings?

You may more specifically be wondering, what is data control in healthcare settings and why does it matter to my facility? One of the biggest pitfalls for organizations is assuming that an EHR is all that’s needed to effectively manage data. An EHR can’t tackle it all without your guidance. It’s essential for a facility to develop customized data control systems, and optimize EHR functions, to ensure their information is safe and available to the right people at the right time.

During each stage of the data lifecycle, one piece of data may be accessed by multiple users (and systems) to carry out a range of activities related to direct patient care activities, research, reporting, medical records, finances, and billing. Enabling the correct access permissions for the facility’s internal and external users is vital to ensure privacy and security, which are also fundamental aspects of maintaining regulatory compliance.

How to Establish Data Control Through Data Governance

An effective data strategy is needed to manage and monitor these vast amounts of information. By launching a data governance program, an organization commits to the value of data use. It also invests in a company culture that encourages trust in data and its ability to enrich the quality of healthcare delivery.

1. Get Organized and Make a Plan

Because data decisions can impact the entire enterprise, a data governance workgroup must be interdisciplinary and include representation by stakeholders from across the organization. After all, what is data control, and how effective can it really be, if it doesn’t involve everyone with access to your IT systems? As a first step, the group may be tasked with determining:

  • Decision-making principles
  • Organizational obstacles
  • Processes and committees for performing data governance
  • Balanced stakeholder needs
  • Communication plans

2. Build a Framework

Working together, the team will develop policies and procedures that lay the groundwork for how data is managed and used. To ensure the availability, integrity, security, and usability of data, policies should address key areas such as:

  • Data integrity — establishes reliability, accuracy, and validity
  • Data access — employee-related
  • Data privacy and usage — legal compliance
  • Data sharing — internal and external use
  • Data retention — storing and destroying

This framework should also address the lifecycle for each user, including termination of access for individuals who leave your organization. A shockingly high percentage of former employees — more than one-third, according to one survey — still had access to their previous employer’s company data.

3. Cultivate Confidence

It’s particularly important to build trust within organizations or units new to working closely with data. Awareness of the governance team’s work increases staff confidence in the data they rely on. Nurses and managers want to be assured that the policies support patient safety, improve outcomes, and comply with industry regulations, including:

  • Health Insurance Portability and Accountability Act (HIPAA)
  • Health Information Technology for Economic and Clinical Health Act (HITECH)
  • General Data Protection Regulation (GDPR)

Show your nurses the value data brings to your team by driving quality and safety initiatives to improve care. Use data to document your team’s progress and successes.

4. Maintain and Monitor

Creating a data framework is a big accomplishment and deserves celebration. But the work is never completely done. Once these systems are defined and put into place, your team will probably uncover areas that were overlooked and other unanticipated issues. It’s a normal part of the process, so don’t worry.

It requires ongoing commitment from senior leaders to continue supporting the data governance program. The workgroups and committees you’ve created stay in place to solve problems that arise. Teams are needed to monitor data and enforce accountability for agreed-upon standards.

As new systems are integrated, the data governance program will continue to weigh in on data control.

Healthcare data is here to stay and requires thoughtful management to maximize its potential. As big data continues to grow exponentially, so does the need for trustworthy and useful information.

Looking for More Ways to Manage Data Systems?

Now that you know the answer to the question, What is data control and how is it important to my facility? you’ll likely have additional questions about using information technology to improve patient outcomes. IntelyCare has what you’re looking for. Our newsletter is full of free nursing management insights to support healthcare managers.

IntelyCare content writer Katherine Zheng, PhD, BSN contributed to the writing and research for this article.