Severity: Warning
Message: file_get_contents(https://...@pubfacts.com&api_key=b8daa3ad693db53b1410957c26c9a51b4908&a=1): Failed to open stream: HTTP request failed! HTTP/1.1 429 Too Many Requests
Filename: helpers/my_audit_helper.php
Line Number: 176
Backtrace:
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 176
Function: file_get_contents
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 250
Function: simplexml_load_file_from_url
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 3122
Function: getPubMedXML
File: /var/www/html/application/controllers/Detail.php
Line: 575
Function: pubMedSearch_Global
File: /var/www/html/application/controllers/Detail.php
Line: 489
Function: pubMedGetRelatedKeyword
File: /var/www/html/index.php
Line: 316
Function: require_once
Computerised identity management is in general encountered as a low-level mechanism that enables users in a particular system or region to securely access resources. In the Electronic Health Record (EHR), the identifying information of both the healthcare professionals who access the EHR and the patients whose EHR is accessed, are subject to change. Demographics services have been developed to manage federated patient and healthcare professional identities and to support challenging healthcare-specific use cases in the presence of diverse and sometimes conflicting demographic identities. Demographics services are not the only use for identities in healthcare. Nevertheless, contemporary EHR specifications limit the types of entities that can be the actor or subject of a record to health professionals and patients, thus limiting the use of two level models in other healthcare information systems. Demographics are ubiquitous in healthcare, so for a general identity model to be usable, it should be capable of managing demographic information. In this paper, we introduce a generalised identity reference model (GIRM) based on key characteristics of five surveyed demographic models. We evaluate the GIRM by using it to express the EN13606 demographics model in an extensible way at the metadata level and show how two-level modelling can support the exchange of instances of demographic identities. This use of the GIRM to express demographics information shows its application for standards-compliant two-level modelling alongside heterogeneous demographics models. We advocate this approach to facilitate the interoperability of identities between two-level model-based EHR systems and show the validity and the extensibility of using GIRM for the expression of other health-related identities.
Download full-text PDF |
Source |
---|---|
http://dx.doi.org/10.1109/EMBC.2015.7319963 | DOI Listing |
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!