Patient Merge: Simplifying Duplicate Patient Records

By Gloria D’Souza, RHIT

One of the biggest challenges the US Healthcare system has encountered is the Coronavirus pandemic. However, the healthcare industry is not new to significant issues such as COVID-19. One challenging concern the healthcare system has encountered which has been exacerbated by high volumes of COVID-19 testing is patient identification errors that impact duplicate electronic medical records[RET1] .

If you are a health information professional who has come across multiple duplicate patient records and don’t know which one is the correct one to work on, then you would just call the data integrity specialist to look into it. Does this sound right? It is then the HIM data integrity specialist (DIS) who must investigate the matching attributes of patient’s name, date of birth, address, SSN, and other detailed information to authenticate the patient record. At times, the DIS team has to rely on third party database such as credit-bureau data to merge the records which is time consuming. Duplicate and fragmented medical records of patients can be a potential risk to the patient’s safety, continuity of care, billing, and leads to financial losses for the hospitals, as well as reduction in reimbursement rates and patient satisfaction scores for providers. In addition, the privacy of the patient is at stake, if the wrong patient’s medical information is added to a patient’s record, it could result in disclosure of that information to a provider or patient who is not authorized to view it.

In a 2017 survey conducted by the American Hospital Association (AHA), 45 percent of large hospitals reported difficulties in accurately identifying patients across health information technology (IT) systems, limiting health information exchanges within various health organizations. Existing patient EHR identification techniques tend to rely on probability and algorithms that identify the possibility that a given record matches a given individual patient. As per the American Health Information Management Association (AHIMA), health organizations need to rely on the expertise of health information management professionals, a team of data integrity specialists (DIS) to undertake data reliability inspections and [RET2] prioritize the EHR merges on a regular basis. Other healthcare professionals or clinicians are then able to flag a potential merge which they may have erroneously created or identified as a duplicate. The DIS team reviews the information in the records and assesses the potential identification of the same patient, and merges these records after the patient’s scheduled visit is complete.

Health information exchange (HIE) organizations use the range of semi-automated software with algorithms and manual approaches to match patient’s records. The inaccurate, incomplete, or inconsistent demographic information in patient’s medical records can be challenging to identify and match all the records belonging to a single patient. Even though these algorithms vary and not all attributes match to the same patient, HIE organizations have to rely on the DIS staff for the manual merges.

How do we resolve duplications in the first place?

  • First, various efforts should be focused on training the front office staff in entering accurate information of the patients in the system which could improve matching of the patient with existing EHR. The report of the successful merges can then be sent to the registration department to provide feedback. If there are frequent manual errors, then training or a review course could be provided.
  • Second, implementation of a common standard is critical for certain demographic data in the health information system—such as names and addresses that could later improve the consistency of data across organizations and thus make it easier to match records.
  • Finally, there has been some discussion of implementing a new national, unique patient identifier. Similar to a SSN, this would be the most effective way to improve the ability to match the patient’s medical records. While the institution of a unique patient identifier number would improve matching across organizations, many healthcare organizations and patients are skeptical of this approach.
  • There are various other approaches to reduce duplicate records through technical efforts such as biometrics to maintain unique identifiers and nontechnical efforts such as data quality improvement. These can enhance the capacity for matching, but additional research opportunities are needed.

It is not difficult to underscore the importance of an educated workforce, in a workplace engineered to prevent errors such as duplicate patient medical records. The implementation of employee education, new technologies and software, and patient identifiers will not only solve this current issue amidst a national healthcare crisis but will continue to benefit healthcare organizations. Taking advantage of the opportunity to improve our current system processes now, we will ultimately be able to provide a better patient care and employee experience in our healthcare system in the long run.

Reference:

United States Government Accountability Office Approaches and Challenges to Electronically Matching Patients’ Records across Providers.; 2019. https://www.gao.gov/assets/700/696

About the Author

Gloria D’Souza, RHIT, is a Data Integrity Specialist at HSHS St. Vincent Hospital. She is an active volunteer on the WHIMA Membership Engagement Team. Gloria can be reached at:
Gloria.Dsouza@Hshs.org
http://linkedin.com/in/gloria-dsouza-343a87ab