The consolidated Clinical Document Architecture (c-cda) is an HL7 document markup standard that specifies the structure and semantics of clinical documents. It is flexible xml-based clinical document architecture. There are many types of c-cda documents including the consultation note, discharge summary, imaging integration and dicom diagnostic Imaging Reports, history and Physical, Operative note, progress Note, procedure note, and Unstructured documents. A centralized data model can use both push and pull technologies. Each organization participating in the hio sends (pushes) patient demographic along with clinical results to a central database managed by the hio. Providers search the empi of this centralized database and pull the corresponding information for the applicable patient across to their system.
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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. Pull technology is used in scenarios where an hio provides a record locator service (RLS) that requires a centralized index of all patients (Enterprise master Person Index or empi) collected from hio participants homework and a cross-reference to each participating organizations medical record number (MRN). A provider searches the hio empi using either the patients demographic information or the providers previously assigned patient identifier. Once the corresponding hio patient record identifier is located in the empi, the provider can use the rls to request specific clinical information from other participating providers. Electronic messages are then sent to each of the participating organizations that have stored records pertaining to the patient. Specific types of electronic clinical results required by the federal meaningful use requirements are extracted from each participating organization to be shared or exchanged with the requesting provider or in transition of care cases. The resume continuity of care document is a required transport mechanism in stage 2 of the meaningful use ehr incentive program. The continuity of care document is a core data set of the most relevant administrative, demographic, and clinical information facts about a patients healthcare, covering one or more healthcare encounters. It provides a means for one healthcare practitioner, system, or setting to aggregate all of the pertinent data about a patient and forward it to another practitioner, system, or setting to support the continuity of care. Its primary use is to represent a snapshot in time in the patients health history.
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. 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 essays for each data quality attribute listed above. This incompatibility compromises healthcares ability to achieve truly successful interoperability. Exchange relies entirely upon demographic information contained in the individual persons record to initially match their clinical information amongst multiple provider organizations. Errors in the collection and transcription of demographic data, aging data, and lack of complete data contained within each providers patient record severely limits interoperability. Hios currently use a variety of data delivery methods, which determine how patient records are sought and matched. Data from one provider may be pushed to another. For example, all electronic prescriptions generated within a hospital are automatically sent to a specific pharmacy, or all transcribed documents are forwarded to the provider(s) listed in the hl7 message.
Examples include: The patient Identification (PID) segments in the health level seven (HL7) message not being consistently populated. The use of components in the pid segment is not consistently implemented. Vendors and providers typically do not upgrade to management newer versions of the hl7 standards that incorporate better support of patient identification integrity. The healthcare industry initiative integrating the healthcare Enterprise (IHE) has long embraced the need for protocols that address patient identification, including Patient Identifier Cross Referencing Integration (pix short patient Data query (pdq and Patient Administration Management (PAM) integration profiles. However these protocols and standards are not routinely adopted or consistently implemented by vendors, enterprises, or hios. Organizations rely instead on data being captured in compliance with older HL7 standards. Understanding hie participation, todays health data exchange is working toward the goal of interoperability by increasing information sharing across disparate provider organizations using networks and internet-based technologies.
As mentioned above, identification requirements vary greatly across provider organizations. 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. Government-issued identification should be the standard. There is a lack of data standards addressing accurate and complete data capture and data matching for patient identification. And the standards that do exist are limited in scope and adherence is suboptimal. Existing standards are largely targeted at vendor and source system data format and position, not content accuracy, completeness, or relevance to industry changes.
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The output from this activity will be presented to the health it policy and health it standards Committees, and could potentially influence requirements for stage 3 of the meaningful use ehr incentive program. 3, ensuring Patient Identity Integrity, establishing and maintaining patient identity integrity is a complex issue with challenges that encompass standards, technologies, and business practices. The scope of the challenges includes factors such as: Proof of identification is not routinely required at the time of data capture and lack of accountability in validating patient identity compounds duplicate resume and overlay creation. Accurate registration is secondary to patient treatment in the emergency department, which in turn causes the creation of overlays and duplicate patient records after acquiring the patients identification information. Registration is a high staff turnover area where entry-level employees typically do not have adequate education and training. High-volume registration areas such as scheduling have a much higher risk of duplicate creation and overlays due to the lack of direct patient contact.
Specimen registration information typically contains minimal identifiable patient information to locate existing patient records. The abundance of poor quality patient identification data stored and managed in siloed legacy systems causes the potential for data integrity issues. Data quality issues are resume magnified when source systems are not kept in sync throughout the exchange network. Data error corrections and duplicate remediation practices are not always performed in a timely and comprehensive fashion. Corrections that do occur are often performed by understaffed teams or inadequately trained staff. Variation in the tools and solutions that measure or address patient identification integrity also may compromise data integrity.
There is no single solution. Ensure hipaa compliance when managing and releasing individually identifiable health information (iihi). Support compliance with various patient matching guidelines and/or standards from accreditation and standard development organizations (SDOs as well as governmental agencies or departments. Calculate unique patient records for meaningful use reporting. 1, support patient-centered medical home initiatives and accountable care organizations. Patient identification integrity is a complex concept, and one that is not well understood throughout the healthcare industry.
The complexity stems from many factors including variability in practices of authentication, data collection, technology, and the historical silo approach to patient identification. Previously, patient identity integrity was seen as a health information management (HIM) or registration/patient access function, with limited staffing devoted to the issue and a site-specific approach. Todays health transformation initiatives push this function to the front of the health information exchange effort. Incorrect or incomplete data capture within the healthcare setting can create critical patient care issues and risk privacy breaches, thus degrading consumer and user trust. 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. As data exchange methods through Direct messaging, private exchange, or state hios continue to evolve, patient identification errors will increase significantly. Policymakers and industry leaders are beginning to recognize the importance of patient identification, as exhibited by the early 2011 patient matching recommendations from the Office of the national coordinator for health it (ONC) health it policy committee following a public hearing on patient matching hosted. 2, 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.
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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. Strong information governance that addresses patient identity integrity and accurate patient matching is key to a patient-centric health system and patient-centric processes. This Practice Brief explores the complexity of patient identification integrity, including how organizations can manage patient identification systems from front end data capture to back end quality control as an ongoing process and carry local quality operations into health information exchange efforts. It urges industry stakeholders to recognize that now is a critical time to address accuracy in patient identification systems. Patient Identity Integrity vital to healthcare. Various components of the healthcare ecosystem will address these goals and execute patient identification integrity activities to: Support care delivery and care coordination within an enterprise, as well as data exchange across healthcare systems. Underpin analytics within and across organizations, including pattern recognition, big Data, and predictive analytics. Support information governance strategy and practices. This governance must underscore the complexity of patient identity integrity, including people, processes, and technologies.travel
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