Providers must recognize each encounter as a standalone record, and ensure the documentation within that encounter reflects the level of service actually provided and meets payer requirements for appropriate reimbursement. As Michelle Dougherty, MA, RHIA, CHP, noted in her testimony to the Office of the National Coordinator for Health IT’s (ONC) HIT Policy Committee, “If clinical documentation was inaccurate when used for billing or legal purposes, it was wrong when it was used by another provider, another provider at transition, a researcher, the public health authority, or quality reporting agency.” The documentation may need to include any health information such as labs, changes in medications, or updates to any chronic health conditions impacting an encounter that was reviewed by the provider during the visit.Data quality and record integrity issues must be addressed now, before widespread deployment of health information exchange (HIE).Electronic documentation tools offer many features that are designed to increase both the quality and the utility of clinical documentation, enhancing communication between all healthcare providers.
With the continued advancement of electronic health records (EHRs), there is increasing concern that a potential loss of documentation integrity could lead to compromised patient care, care coordination, and quality reporting and research as well as fraud and abuse.
This practice brief provides guidance for maintaining documentation integrity while using automated EHR functions.
There are a number of existing rules and regulations on documentation principles and guidelines that primarily address documentation authorship principles, auditing, and forms development in a paper health record.
New guidelines are being sought by the healthcare industry that ensure and preserve documentation integrity in an age of electronic exchange and changes in the legal evidentiary requirements for electronic business and health records.
Documentation integrity involves the accuracy of the complete health record.
It encompasses information governance, patient identification, authorship validation, amendments and record corrections as well as auditing the record for documentation validity when submitting reimbursement claims.
Organizations using voice recognition without a validation step in place are experiencing significant data quality problems and documentation errors.
Organizations should have in place a process to ensure providers review, edit, and approve dictated information in a timely manner.
AHIMA defines information governance as “the accountability framework and decision rights to achieve EIM.
EIM is defined as the infrastructure and processes that ensure information is trustworthy and actionable.” The multitude of federal and state health information exchange initiatives are making information governance and the integrity of EHRs more challenging every day.
Use of these features without appropriate management and guidelines, however, may create information integrity concerns such as invalid auto-population of data fields and manufactured documentation aimed to enhance expected reimbursement.