The American Health Information Management Association (AHIMA) serves more than 64,000 members and is a recognized leader in the health information management (HIM) space. The organization provides professional certification to advance the HIM profession, an increasingly demanding role in the era of EHR.
As part of their Though Leadership series, AHIMA recently released a new white paper, Ensuring Data Integrity in Health Information Exchange. The white paper looks at data exchange and integrity issues in HIE models and addresses how health information management professionals can take a role in local health data exchanges to help solve these issues.
The summary in part states:
Ensuring data quality is not a trivial task. Ideally, the health data in an electronic record should be accurate, up-to-date and complete; but unfortunately the real world is far from ideal. High-quality data requires us to have a very clear understanding of the meaning, context, and intent of the data—unambiguous and, ideally, standardized computable definitions of data that can form the basis for future safe decision making.
To facilitate data quality, the ultimate goal of any HIE should be accurate identification of the patient. HIE patient identity and administration has three patient identification profiles: (1) the patient identifier cross-reference profile that matches patients by cross-referencing IDs; (2) the patient demographics query profile queries a central patient information server; (3) patient administration management knows where the patient is, was, or is going. In addition the HIE should assign a unique patient/person identifier by using advanced record matching techniques, for example, probabilistic algorithms, and manual processes, as needed.
The AHIMA report makes recommendations on how health information exchanges can ensure data integrity by establishing:
- Oversight and accountability mechanisms
- Acceptance criteria and patient identification practices as part of an internal review processes
- An understanding by exchange participants on how and when corrections will be made to patient data