Information Governance Addresses Patient Matching Initiatives

By Kristi Fahy, RHIA, and Lori Richter, MA, RHIA, CPHIT, CPEHR, CHPS

New and existing regulations, legal requirements, population health initiatives, patient care outcomes, and the shift from paper to electronic records have led healthcare organizations to face the challenges associated with patient medical record integrity, including solid patient identification and patient matching practices. Accurate patient identification and patient matching is critical to achieving better patient care outcomes, population health, health information exchange, and interoperability.

Poor Patient Matching Presents Risk

The challenge with patient matching is that organizations often do not have the right people, processes, technologies, or other resources available to stay ahead of the ceaseless patient identity issues or inaccuracies. To add to that, staffing levels have decreased, causing registration staff to do more in less time which in turn affects the quality and accuracy of matching patients to their appropriate medical record number. The increased workload and entry-level pay has led to high registration staff turnover rates and vulnerable transition periods when onboarding new registration employees. This represents a potential risk for patients.

Another contributing factor to improper patient matching includes the number of users who have access rights to update patient demographics in the electronic health record (EHR) system after registration. One wrong modification, something as simple as incorrectly updating a birthdate, can lead to a multitude of errors and mismatching. Managers, human resources personnel, and IT should collaborate to manage access rights through a continuous process that is audited and constantly updated, especially when new roles/authorities are created. Access should also be reviewed and updated as job roles change. This process ensures that authorized users have the appropriate access rights to make changes to patient records that are consistent with their job authority and function.

In addition, employees often assume that patient information is accurate and can be relied on for clinical or business decision making. Organizations’ clinical systems are often disparate and there is little to no linkage between these systems to correlate patient health information within the organization or across the healthcare ecosystem. The awareness that there may be a lack of information integrity and that patient matching error rates are much higher than they should be is the first step in the right direction to correcting the problem.

For example, in healthcare, providers utilize universal precautions when it comes to disease prevention and the transfer of germs. The awareness and necessity of disease management has influenced the way providers do their work and has proven to lower the risks of spreading diseases. Likewise, the healthcare industry is aware of the patient matching crisis and, as a result, organizations should require that all employees who utilize the EHR system use a similar approach and keep a keen eye on the details to ensure proper patient matching the first time around. This will prevent the need to go back and correct duplicate records, merged records, or other record errors.

Prioritize Error Prevention and Correction

If it is determined that there are two medical records for one patient, or an overlay of two patients in one medical record, the errors must be reported and worked on as soon as possible to confirm that all patient information in the mismatched records are accurate. An alert should be placed on the affected medical records until the errors are corrected. The remediation should include evaluations of each system where the mismatched patients have records. With this effort, organizations should see a decrease in patient matching errors.

Patient registration staff must follow defined standardized procedures to ensure the accuracy of patient entry into the organization’s systems as well as to support the integration of records into the enterprise master patient index (EMPI). This helps support the accuracy of integration and workflow of the information in all EHR and subsidiary systems throughout the organization.

It is important that organizations use legal identification methods to ensure proper patient matching within the organization as well as across other organizations in which data will be exchanged (i.e., patients must present a government-issued photo ID during registration). Organizations should also have standards for the following: legal name, photo ID, name changes, baby name, listing alias, order of names (first, middle, last, junior/senior), date of birth, date of death, Social Security number, address entry, gender, race, and more.

It is of utmost importance for staff to verify whether a patient already exists in the system before scheduling or registering that patient. This is important to minimize the creation of duplicate medical record entries into the EHR.

There are several areas to address when it comes to accurate patient matching. Information governance (IG) is a structured approach to addressing these concerns, managing patient information integrity and accuracy, reducing patient record duplication rates, and increasing successful patient matching. In addition, IG will help to promote awareness of the importance of correct patient matching and hold registration staff and EHR users responsible and accountable for accurate entries and modifications.

Using IGAM to Improve Patient Matching

IG is no longer optional; it is essential to advancing trusted exchange across the healthcare ecosystem, streamlining business and clinical practices to advance the continuum of care, and improving business operations. AHIMA defines IG as “an organization-wide framework for managing information throughout its lifecycle and for supporting the organization’s strategy, operations, regulatory, legal, risk, and environmental requirements.”

AHIMA recognized the industry need for IG not only in healthcare delivery organizations and providers, but also vendors, business associates, and insurance payers. Each of these organization types handle patient records and require accuracy to properly contribute to the patient care path.

To effectively share electronic health information across disparate systems, organizations must reduce data integrity issues with patient identity and place an emphasis on the importance of the registration process and diligence when working in the EHR. Patient health information and records must be governed in the same manner as all other enterprise-wide information.

AHIMA’s Information Governance Adoption Model (IGAM™) provides a structured approach for organizations to assess their current state of IG, prioritize IG initiatives, develop an IG strategic plan, measure successes, and determine next steps. “Identity Management” is one of the IGAM maturity markers that falls within the Enterprise Information Management (EIM) competency. This maturity marker assesses the sophistication of patient identity practices, in addition to physician, employee, and other identity practices.

Organizations that do not have solid identity management practices may not have appropriate resources in place to ensure and correlate patient identity to other types of information. More mature and proactive identity management practices include:

  • Standardized identity management policies
  • Control processes for accurate patient identification
  • Ongoing monitoring and measurement
  • Collaboration with external vendors and business associates
  • Employee workforce awareness and adherence

The sophistication of an organization’s identity management practices ensures the accuracy of patient identity as information is created, transmitted, or shared.

Information Governance Adoption Model

IG Critical for Data Exchange

Information governance is needed for organizations to develop standard practices and have consistency in data collection, which starts at patient registration. Without information governance, HIM professionals are unable to clearly communicate the criticality of data consistency necessary for successful data and information exchange. Information governance practices help to reduce duplication rates in the master patient index, improve data accuracy and consistency in the EHR, and streamline system processes that are all vital to accurate patient identification. Each of these play an important role in improving patient safety initiatives and process improvement for the organization.

Kristi Fahy ( is manager of IG, informatics, and standards at AHIMA. Lori Richter ( is OneCare EHR compliance director at Catholic Health Initiatives.