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Validating identity and d link

validating identity and d link-57

It urges industry stakeholders to recognize that now is a critical time to address accuracy in patient identification systems.Various components of the healthcare ecosystem will address these goals and execute patient identification integrity activities to: Patient identification integrity is a complex concept, and one that is not well understood throughout the healthcare industry.

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To support high quality data exchange, AHIMA has published data quality standards that promote accurate, comprehensive, current, consistent, relevant, timely, granular, precise, accessible, and well-defined data.In these scenarios, the receiving provider generally already knows which patient the messages concern and thus uses relevant internal procedures to process the incoming transaction.Data trading partnerships between providers may dictate the content and format of the HL7 message.For example, the request for proof of identity is not always required at registration or check-in.Differences may include one or two forms of identification with or without a photo.Accurate patient identification is foundational to the successful linking of patient records within care delivery sites and across the healthcare ecosystem to underpin care delivery, data exchange, analytics, and critical business and clinical processes.

These goals have increased in importance as health information exchange has evolved over the last decade with the healthcare industry striving to reduce costs, increase interoperability, and transform to a patient-centric care delivery model.

Health information organizations (HIOs) support, oversee, or govern the exchange of health-related information among organizations according to nationally recognized standards.

HIOs are the recipients of the stewardship and governance applied to patient identification processes, thus HIOs are today highlighting many of the weaknesses in the historical systems and practices.

For more information on data quality attributes, refer to the 2012 AHIMA Data Quality Management Model practice brief here.

While data exchange is on the uptake, electronically exchanged data rarely meet the standard for each data quality attribute listed above.

More recent ONC activities such as an environmental scan of vendors, providers, and data exchange organizations are exploring current approaches, practices, and processes related to patient identification.