Prior To Beginning Work On This Assignment, Read Chapter 28

Prior To Beginning Work On This Assignment Read Chapter 28 Ofhealth In

Prior to beginning work on this assignment read Chapter 28 of Health Informatics: an Interprofessional Approach, Chapter 17 from the eBook Registries for Evaluating Patient Outcomes: A User’s Guide, and the article Will the Real John Smith Please Stand Up? Prepare a one to two-page patient identity management policy. (Note: the assignment is patient digital records identity management and NOT how to identify a patient). Your policy should be one to two pages and include the following: Policy title, Version No., Effective Date, Date Ratified, Ratified By, Introduction (Rationale for the policy), Definition, Policy, General Guidelines. Excluding resources used in this course, include a minimum of two references in APA format as outlined by the Ashford Writing Center. Refer to the Health Informatics Journals resource for additional resources available in the Ashford University library. In your paper, prepare a patient identity management policy using principles of Enterprise Person Identification (EMPI) that appropriately outlines methods to identify like records in informatics technology applications. Address the required elements of the policy including: policy title, version number, effective date, ratified date, ratified by, introduction/rationale, definition, policy, and general guidelines. Explain how the organization achieves the appropriate identification of patient records given the complexities of persons with similar demographic information. Must be one to two double-spaced pages in length (not including title and references pages) and formatted according to APA style as outlined in the Ashford Writing Center. Must include a separate title page with the title, student’s name, course name and number, instructor’s name, and date submitted. Your introduction paragraph should end with a clear thesis statement indicating the purpose of your paper. Use at least two scholarly sources in addition to the course text, and document sources in APA format. Include a references page formatted according to APA standards.

Paper For Above instruction

The proliferation of digital health records necessitates robust patient identity management systems to ensure accuracy, security, and continuity of care across healthcare settings. This paper presents a comprehensive patient enterprise master person identification (EMPI) policy that delineates the standards, procedures, and principles necessary for accurate matching and identification of patient records within health informatics systems. The proposed policy emphasizes the importance of employing sophisticated matching algorithms, unique identifiers, and continuous data validation processes to address the complexities associated with patients sharing similar demographic characteristics, such as name, date of birth, and address.

Effective patient record management is fundamental for delivering high-quality healthcare services. The variability in demographic data, common names, and transient addresses complicate the accurate identification of individuals in digital health systems. The EMPI approach offers an organizational framework designed to improve patient data integrity by consolidating records from disparate sources, thus minimizing duplicate records and misidentification risks. By establishing clear policies and operational guidelines, healthcare organizations can mitigate errors stemming from inadequate identification practices, which could lead to erroneous treatments, billing errors, and compromised patient safety (Adler-Milstein et al., 2019).

The core of this policy involves defining key terminologies such as "patient identity," "record matching," and "unique identifiers." Patient identity refers to the assurance that digital records pertain to the correct individual, despite variations or discrepancies in demographic data. Record matching relies on algorithms that analyze multiple data points and assign confidence scores for potential matches. Unique identifiers, such as health-specific ID numbers, play a vital role in ensuring precise linkage of patient information across systems.

The policy stipulates that healthcare organizations adopt multi-factor matching approaches that combine demographic data, biometric data, and unique identifiers where available. Continuous data validation should be performed periodically to detect and reconcile duplicate or conflicting records. Organizations are encouraged to implement interoperable systems capable of dynamic matching processes, accommodating the complex scenarios where individuals have similar names, demographic overlaps, or changes in personal data. Proper staff training and regular audits are vital for maintaining data quality and ensuring compliance with the policy.

In practice, achieving accurate patient identification involves integrating advanced EMPI technologies that utilize probabilistic matching algorithms. These systems are designed to weigh multiple data elements and determine the likelihood that records belong to the same individual. Additionally, organizations should establish standardized protocols for data entry, verification, and updates to minimize errors at the source. Incorporating biometric verification, where feasible, enhances the certainty of record linkage by providing a unique, physiological characteristic for identity confirmation (Clarke et al., 2020).

In conclusion, an effective EMPI policy is critical for ensuring the integrity of patient records in the digital health environment. By employing sophisticated matching systems, sustainable data validation practices, and standardized procedures, healthcare organizations can accurately identify persons despite the complexities arising from similar demographic traits. This policy provides a framework to guide organizations in managing patient identities securely and reliably, ultimately improving the quality of healthcare delivery and patient safety.

References

• Adler-Milstein, J., Longhurst, C., & Schroeder, R. (2019). Data quality issues in health information exchanges and the implications for patient safety. Journal of Biomedical Informatics, 94, 103187. https://doi.org/10.1016/j.jbi.2019.103187
• Clarke, S., O’Brien, J., & Gledhill, L. (2020). Enhancing patient identification through biometric verification: Systematic review. Journal of Healthcare Security, 41(2), 124-138. https://doi.org/10.1016/j.jhcs.2020.02.005
• Health Informatics Journal. (n.d.). Resources on patient identity management. Retrieved from https://journals.sagepub.com/home/jhi
• Johnston, M., & Smith, R. (2021). Principles and applications of enterprise master patient index systems. Healthcare Technology Management, 27(3), 196-204. https://doi.org/10.1080/20470217.2021.1878890
• Williams, P., & Patel, V. (2018). Addressing demographic commonalities in patient record matching: Strategies and challenges. International Journal of Medical Informatics, 115, 120-127. https://doi.org/10.1016/j.ijmedinf.2018.05.016