Literature DB >> 33796987

Patient Identity Management Maturity Model (PIM3) for Imaging Information Technology Systems.

Don Dennison1.   

Abstract

In Consolidated Enterprises, there are often more than one set of patient identities or some amount of historic records, such as imaging exams that are still identified by more than one patient identity (also known as a Patient Identifier or Medical Record Number) per person. Information technology systems often need some capability to cross-reference records for the same patient so that the records are linked to the one, correct person. If not, it may create a risk for the patient. Historically, each independent facility or organization managed its own patient identity information, including the unique identifier/Medical Record Number. This can result in a fractured view of a patient's records. To present a longitudinal, unified-view record of a patient, it is necessary to have functions to manage these multiple domains. Without this capability, multiple patient identity domains result in a broken imaging record for the patient and often prevents the discovery of, access to, and comparison of a patient's imaging exams. Even worse, without a method to manage patient identity across records where more than one patient identity domain is involved, the records for two different people can be linked to one patient, resulting in a potentially serious risk for harm. This paper proposes a maturity model to assess and categorize the capabilities of different imaging information technology systems, such as Picture Archiving Communication and Archiving System, Vendor Neutral Archive, and other image management and viewing applications.
© 2021. Society for Imaging Informatics in Medicine.

Entities:  

Keywords:  Identifiers; Imaging; Informatics; Model; PACS; VNA

Mesh:

Year:  2021        PMID: 33796987      PMCID: PMC8289952          DOI: 10.1007/s10278-021-00429-2

Source DB:  PubMed          Journal:  J Digit Imaging        ISSN: 0897-1889            Impact factor:   4.056


  1 in total

1.  Why Patient Matching Is a Challenge: Research on Master Patient Index (MPI) Data Discrepancies in Key Identifying Fields.

Authors:  Beth Haenke Just; David Marc; Megan Munns; Ryan Sandefer
Journal:  Perspect Health Inf Manag       Date:  2016-04-01
  1 in total
  1 in total

1.  Scaling up a decentralized offline patient ID generation and matching algorithm to accelerate universal health coverage: Insights from a literature review and health facility survey in Nigeria.

Authors:  Emeka Chukwu; Iniobong Ekong; Lalit Garg
Journal:  Front Digit Health       Date:  2022-09-07
  1 in total

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