Data integrity is a critical concern for both the clinical and financial sides of the healthcare enterprise, ensuring both quality of care provided and accurate payment for services—and that also makes it a critical concern for the CFO.  

At a Glance
  • When considering information governance, CFOs should ask two primary questions: How accurate are our data, and is there a process in place to ensure that data are reliable, timely, up-to-date, and consistent?
  • CFOs also should have at least a general sense of how and where data are flowing and whether the data accurately reflect services rendered.
  • The goal of a formal enterprisewide information governance process is to enable employees to identify data-quality issues up front, thereby avoiding the need to devote valuable time and resources to resolving problems after an error occurs.

Accurate, timely data can ensure a patient’s successful outcome and help a hospital’s business grow and thrive. If not handled correctly, however, issues with data quality can have an impact on patient care and can indirectly be a source of financial strain that no CFO wants to experience.

Information governance—the process for closely monitoring healthcare data throughout its lifecycle—has become a buzzword throughout the healthcare industry. And there is good reason, given the industry’s increasing focus on using large quantities of data to monitor and identify ways to improve the performance of the nation’s healthcare organizations. For example, in March 2012, the Obama administration announced the Big Data Research and Development Initiative, designed to improve the tools and techniques necessary to access, organize, and glean discoveries from huge volumes of digital information. The National Institute of Health also has shown particular interest in data sets related to health and disease (e.g., imaging, molecular, cellular, electrophysiological, chemical, behavioral, epidemiological, and clinical data sets) and how those data sets can be used to improve care processes. 

Because a healthcare organization’s data also serve as the foundation on which best practices are developed, critical clinical decisions are made, and accurate payment is determined, helping to govern their organization’s healthcare data should be at the top of every CFO’s priority list. In short, healthcare finance leaders should think of information governance as essentially a form of risk management that no hospital can afford to ignore.

What CFOs Should Know

Although technology drives the collection of big data, the quality and integrity of that data often depend more on business processes and rules than on technology. Understanding the creation and flow of information helps to ensure: 

  • Positive ROI for an electronic health record (EHR) and other source systems that feed into the EHR
  • Effective management of total patient care
  • Appropriate links between documentation and the services rendered
  • Establishment of medical necessity for services rendered
  • Patient safety and quality of care 

What exactly is the business value of quality data? The answer is simple: Quality data supports high-quality care, accurate research, positive patient outcomes, accurate payment, a cost-effective risk assessment, comprehensive responses to auditors, and strategic decision-making.

The costs associated with poor data quality are less obvious. These costs can be hidden, for example, in the human resources expenses required for data integrity issues, system improvements, error correction, individual data studies, and more. 

A report released by Oracle in July 2012, From Overload to Impact: An Industry Scorecard on Big Data Business Challenges, states that up to 14 percent of a company’s revenue is lost when enterprises do not manage and analyze data. The report is based on a survey of 333 C-level executives from U.S. and Canadian enterprises spanning 11 industries.

Notable is the fact that 40 percent of executives in the healthcare industry gave themselves a “D” or “F” rating regarding their level of preparedness for a data deluge. Within the survey, 94 percent of C-level executives said their organization was 97 percent reported that they still had to make changes to improve information optimization. collecting and managing more business information in 2012 than in 2010, yet 

Creating an Information Governance Program

A successful information governance program requires the following essential elements.

A data dictionary and data map. A data dictionary provides a descriptive list of names, definitions, and attributes of data elements that an information system or database captures. For example, a data dictionary helps identify how different systems use multiple conventions for common data elements. The date of a patient’s admission may be “date of admission” in the hospital EHR, “admit date” in the fetal monitoring system, and “admission date” in the cardiology system. The data dictionary identifies these differences and serves as a critical tool to help organizations share, exchange, and integrate data.

A data map allows organizations to link or associate data captured in one format or system with data captured in another format or system. The use of a data map to connect ICD-9-CM codes to ICD-10-CM is one common example.

Both the data dictionary and data map are critical to understanding the source, meaning, and potential implications of data. The lack of a data dictionary or data map limits a hospital’s ability to take full advantage of the data it possesses. 

Clean master patient index (MPI). The MPI—a database that holds information on every patient ever treated at a healthcare organization—is a hospital’s data lifeline. Errors and duplicate entries in the MPI can permeate throughout an entire record. This significantly affects data integrity—and compromises staff’s ability to provide comprehensive care and the organization’s ability to share information with other organizations.

Health information management (HIM) directors can take steps to maintain a clean MPI, including requiring use of a multifactor ID lookup when searching for a patient in the system, monitoring duplicate reports to determine how often staff members correct duplicates or override prompts to further investigate a patient’s identity before completing the registration process, and requiring patient access staff members to fix overlaps and overlays concurrently—not after the patient has been discharged. 

Policies and procedures that promote data integrity as well as ongoing user education. One especially vital policy involves the use of copy-and-paste documentation in the EHR. Assuming the organization has decided it will allow physicians to copy and paste information, the organization must also define when physicians can or cannot use this approach. For example, physicians should never copy information from one patient record to another. On the other hand, a hospital may decide to allow its physicians to copy a patient’s own medication list after the list has been verified. Other essential policy decisions include how the hospital will monitor the documentation being inputted into the EHR and what the process should be for amending the medical record. 

Clear communication with vendors. Data integrity is not just about the users of IT systems and tools; vendors also play a role in the process. When selecting a technology vendor, an organization should consider how that vendor can support—or potentially complicate—the organization’s efforts to achieve and maintain data integrity. Following are questions to consider:

  • What is the accuracy rate of computer-assisted coding or speech recognition software and/or tools? 
  • How can these rates be monitored, and how can flags be developed that prompt an audit, when necessary? 
  • Do EHR templates capture the appropriate information and allow for a clear and compliant amendment process? 

Strategies for Achieving Data Integrity

CFOs should undertake four action steps for establishing a framework for data integrity. 

Become a data steward. Employees should understand that data integrity is an organizational priority. They also should understand how their actions directly affect the validity of data and the potential to use data to promote positive patient outcomes. The CFO should set the tone by emphasizing the need for data integrity and should serve as a role model for employees by educating them on the uses of data throughout the continuum of care as well as the risks of incorrect data for both patients and the organization as a whole. The hospital’s information governance function should work to establish an atmosphere of compliance and integrity that centers on patient safety.

Create an enterprise data quality steering committee. The CFO is an important member of this team because he or she provides executive support for data integrity initiatives. Executive support is particularly vital in large health systems that bring many formerly independent physician practices into their fold and face additional challenges in establishing enterprisewide processes for ensuring data integrity. Other members of this team should include the chief information officer, all data administrators and representatives from the organization’s HIM, patient access, legal, and risk management departments. The committee’s priorities should include, but not be limited to:

  • Creating, reviewing, and validating the organization’s data dictionary and data maps
  • Reviewing documentation for errors
  • Establishing policies that promote data integrity
  • Developing strategies to train users while recording integrity best practices

The CFO should insist on a global, enterprisewide approach to achieving and maintaining data integrity. Key steps to this end include financially quantifying any results or benefits achieved, leveraging data analytics when making decisions, and promoting the overarching goal of data integrity—even if it means abandoning existing power structures within the organization that may have previously guided decisions.

Focus on the cost of poor quality data. CFOs have the knowledge and skills to perform the investigative work necessary to quantify the potential costs associated with inaccurate, incomplete, or compromised data. Making leaders and staff aware of the costs associated with a lack of data integrity can help raise awareness and drive positive change within the organization.

To promote understanding of the cost of poor data quality, the CFO can analyze a high-visibility incident (e.g., a wrong-site surgery) that encapsulates the issues related to workflow and other problems. The CFO should consult EHR logs, management reports on staff allocation, documents that reflect the internal impact of poor data integrity (such as litigation costs), and sources of information related to the external impact of compromised data quality (such as lower quality ratings and surveys that shed light on the organization’s reputation in the community) to gain a better sense of the actual costs associated with the error.
CFOs and other finance leaders also should consider reviewing billing patterns to understand the revenue impact of a lack of data integrity. For example, how often has incorrect data led to repeated tests or procedures? How often has the organization been unable to bill when lab results are posted to an old account or wrong account? The finance leaders should collaborate with the HIM department to identify the key questions or trouble spots that have financial ramifications.

Look for opportunities to collaborate. Information governance has a direct financial impact for healthcare organizations; for example, organizations cannot successfully implement ICD-10 and take advantage of the specificity inherent in the new code set without establishing a strong governance program that advocates for accuracy and thoroughness. Therefore, it makes sense to partner with other organizations through training and education related to information governance, ICD-10, and more to reduce the costs associated with enhancing data integrity. For example, training and education related to information governance as well as ICD-10 can be provided simultaneously at partnering organizations. 

An Ongoing Role

The CFO has a pivotal role to play in promoting data integrity within a healthcare organization—and that role does not stop with implementing an information governance program. The CFO should continue to work collaboratively with HIM professionals to achieve goals related to enterprise information governance while continually remaining alert for opportunities to eliminate duplication in the collection of data and streamline efforts.

The CFO’s ongoing role also should include monitoring MPI accuracy and ensuring that registration staff receive ongoing education. Once an organization has an information governance program in place, it will be the CFO’s responsibility to ensure progress is made.

Rita Bowen, RHIA, CHPS, SSGB,is senior vice president of health information management and privacy officer, HealthPort, Alpharetta, Ga.

Alisha R. Smith, RHIA, is health information management educator, HealthPort LLC, Alpharetta, Ga.


Where to Budget Dollars for Data Governance

Managing data is certainly not an easy—or inexpensive—venture. Other industries are light years ahead of health care in terms of expending efforts to manage data properly, yet even these industries still spend a significant amount of money to do it.

For example, American Banker reported in August 2012 that managing data costs banks 7 to 10 percent of their operating costs. These costs are probably much higher for hospitals. The average hospital relies on more than 100 systems that churn out 100 megabytes of data per patient annually (see, for example, Miliard, M., “HIT Unprepared for ‘Omics’ Onslaught,” Heathcare IT News, April 4, 2013).

When budgeting for an information governance program, consider the current budget for IT infrastructure and the intended goals for data integrity and information governance. Some data quality issues may be less costly to resolve than others. In general, hospitals will incur costs associated with the education, IT infrastructure, and master patient index cleanup, whether done in-house or in partnership with an outside company, and staff costs associated with audits of data to maintain integrity.

Budgets for data governance will differ depending on an organization’s specific goals. CFOs should support budget requests related to ongoing information governance efforts as well as review the reports regarding data quality and integrity. This is information that should be shared with patient safety and data quality teams and the organization’s board of trustees regularly.

Publication Date: Tuesday, April 01, 2014

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