scholarly journals Towards Semantic Interoperability for Electronic Health Records

2007 ◽  
Vol 46 (03) ◽  
pp. 332-343 ◽  
Author(s):  
P. Knaup ◽  
E. J. S. Hovenga ◽  
S. Heard ◽  
S. Garde
Keyword(s):  
Electronic Health Records ◽  
Domain Knowledge ◽  
Semantic Interoperability ◽  
Health Records ◽  
Face To Face ◽  
Telephone Interviews ◽  
Development Organisation ◽  
Knowledge Governance ◽  
Electronic Health ◽  
Definition Of

Summary Objectives: In the field of open electronic health records (EHRs), openEHR as an archetype-based approach is being increasingly recognised. It is the objective of this paper to shortly describe this approach, and to analyse how openEHR archetypes impact on health professionals and semantic interoperability. Methods: Analysis of current approaches to EHR systems, terminology and standards developments. In addition to literature reviews, we organised face-to-face and additional telephone interviews and tele-conferences with members of relevant organisations and committees. Results: The openEHR archetypes approach enables syntactic interoperability and semantic interpretability – both important prerequisites for semantic interoperability. Archetypes enable the formal definition of clinical content by clinicians. To enable comprehensive semantic interoperability, the development and maintenance of archetypes needs to be coordinated internationally and across health professions. Domain knowledge governance comprises a set of processes that enable the creation, development, organisation, sharing, dissemination, use and continuous maintenance of archetypes. It needs to be supported by information technology. Conclusions: To enable EHRs, semantic interoperability is essential. The openEHR archetypes approach enables syntactic interoperability and semantic interpretability. However, without coordinated archetype development and maintenance, ‘rank growth’ of archetypes would jeopardize semantic interoperability. We therefore believe that openEHR archetypes and domain knowledge governance together create the knowledge environment required to adopt EHRs.

Pre-Processing Highly Sparse and Frequently Evolving Standardized Electronic Health Records for Mining

2021 ◽  
pp. 8-21
Author(s):  
Shivani Batra ◽  
Shelly Sachdeva
Keyword(s):  
Electronic Health Records ◽  
Data Model ◽  
Semantic Interoperability ◽  
Relational Model ◽  
Health Records ◽  
Related Information ◽  
Health Related ◽  
Electronic Health ◽  
Mining Tools ◽  
Attribute Value

EHRs aid in maintaining longitudinal (lifelong) health records constituting a multitude of representations in order to make health related information accessible. However, storing EHRs data is non-trivial due to the issues of semantic interoperability, sparseness, and frequent evolution. Standard-based EHRs are recommended to attain semantic interoperability. However, standard-based EHRs possess challenges (in terms of sparseness and frequent evolution) that need to be handled through a suitable data model. The traditional RDBMS is not well-suited for standardized EHRs (due to sparseness and frequent evolution). Thus, modifications to the existing relational model is required. One such widely adopted data model for EHRs is entity attribute value (EAV) model. However, EAV representation is not compatible with mining tools available in the market. To style the representation of EAV, as per the requirement of mining tools, pivoting is required. The chapter explains the architecture to organize EAV for the purpose of preparing the dataset for use by existing mining tools.

scholarly journals Recordkeeping Metadata Standardization for Electronic Health Records System Integration: a Preliminary Study

2018 ◽  
Vol 7 (3.7) ◽  
pp. 266
Author(s):  
Seri Intan Idayu Binti Shahrul Asari ◽  
Nurussobah Binti Hussin ◽  
Ahmad Zam Hariro Bin Samsudin ◽  
Mohd Nizam Bin Yunus
Keyword(s):  
Electronic Health Records ◽  
System Integration ◽  
Health Records ◽  
Metadata Standard ◽  
Information Technology Managers ◽  
Record Keeping ◽  
Recordkeeping System ◽  
Face To Face ◽  
Electronic Health ◽  
Technology Managers

Electronic Health Records (EHRs) are beneficial in improving patient care, promoting safe practice, as well as enhancing patients and multiple providers’ communication and risk error reduction. However, it seems that the adoption of EHR system is happening very slowly to become fully integrated in both primary care and within hospital settings. In Malaysia, the implemented system still has limited integration and interoperability for supporting clinical operations among other Ministry of Health Malaysia (MOHM) hospitals, health centres, and clinics. Therefore, the objective of this paper is to discuss about this scenario and strain the need for solution through the consideration towards metadata standard establishment in health records system integration. Method used in this study is literature review analysis and face-to-face interview. The paper begins with discussions from various literatures highlighting the need of metadata standard for recordkeeping system integration. Subsequently, the face-to-face interview is done to explore the real situation in Malaysia to encounter the scenario discuss in the literatures. The finding of this study reveals that there is significant need for further research on record keeping metadata standard development for realization of electronic health records system integration. This study is significant for records managers, information technology managers, system developers and record keeping audit.   

Creating personalised clinical pathways by semantic interoperability with electronic health records

2013 ◽  
Vol 58 (2) ◽  
pp. 81-89 ◽  
Author(s):  
Hua-Qiong Wang ◽  
Jing-Song Li ◽  
Yi-Fan Zhang ◽  
Muneou Suzuki ◽  
Kenji Araki
Keyword(s):  
Electronic Health Records ◽  
Clinical Pathways ◽  
Semantic Interoperability ◽  
Health Records ◽  
Electronic Health

scholarly journals Digital Phenotypes for Personalized Medicine

2021 ◽  
Author(s):  
Carlos Molina ◽  
Belén Prados-Suarez
Keyword(s):  
Health Status ◽  
Personalized Medicine ◽  
Electronic Health Records ◽  
Health State ◽  
Health Records ◽  
The Future ◽  
Electronic Health ◽  
Definition Of

In this paper we propose a new definition of digital phenotype to enrich the formulation with information stored in the Electronic Health Records (EHR) plus data obtained using wearables. On this basis, we describe how to use this formalism to represent the health state of a patient in a given moment (retrospective, present, or future) and how can it be applied for personalized medicine to find out the mutations that should be introduced at present to reach a better health status in the future.

scholarly journals Similarity Analyzer for Semantic Interoperability of Electronic Health Records Using Artificial Intelligence (AI)

2019 ◽  
Vol 1 (2) ◽  
Author(s):  
Arjmand Naveed
Keyword(s):  
Artificial Intelligence ◽  
Electronic Health Records ◽  
Semantic Interoperability ◽  
Healthcare Sector ◽  
Data Mapping ◽  
Mapping Data ◽  
Data Types ◽  
Health Records ◽  
Different Types ◽  
Electronic Health

The introduction of Electronic Health Records (EHR) has opened possibilities for solving interoperability issues within the healthcare sector. However, even with the introduction of EHRs, healthcare systems like hospitals and pharmacies remain isolated with no sharing of EHRs due to semantic interoperability issues. This paper extends our previous work in which we proposed a framework that dealt with semantic interoperability and security of EHR. The extension is the proposal of a cloud-based similarity analyzer for data structuring, data mapping, data modeling and conflict removal using Word2vec Artificial Intelligence (AI) technique.  Different types of conflicts are removed from data in order to model data into common data types which can be interpreted by different stakeholders.

Comparison of Patient Record Types Concerning the Applicability for Patient Recruitment (Preprint)

2019 ◽  
Author(s):  
Björn Schreiweis ◽  
Antje Brandner ◽  
Björn Bergh
Keyword(s):  
Electronic Health Records ◽  
Medical Records ◽  
Patient Empowerment ◽  
Patient Recruitment ◽  
Patient Records ◽  
Health Records ◽  
Case Record ◽  
Different Types ◽  
Electronic Health ◽  
Definition Of

BACKGROUND Supporting recruitment of clinical trials using software tools integrated into medical care environments, so called patient recruitment systems (PRSs), recently increased. PRSs in literature are integrated in electronic medical records (EMRs), electronic health records (EHRs), and also personal health records (PHRs) integrating PRSs are mentioned. Further patient or medical records available are EHRs for distinct medical conditions (electronic medical case record (ECR); ger: Elektronische Fallakte) and personal electronic health records (PEHRs). But yet, the applicability of these different types of patient records for integration with PRSs has to be researched. OBJECTIVE Thus, this paper describes the different types of patient records and evaluates their applicability for integration with PRSs. METHODS Requirements on PRSs were gathered from literature and unstructured interviews with stakeholders in a previous study. These requirements were amended and afterwards evaluated by comparison to functionality and definition of EMR, EHR, ECR, PHR PEHR. Definitions of EMR, EHR, ECR, PHR and PEHR were taken from literature analysis concerning definitions of the record types. RESULTS All requirements could be partially met by at least one of these types of patient records. Only one requirement was fully met by all five types. According to the analysis PEHRs fulfill most requirements on PRSs. PEHRs especially fulfill patient empowerment and medical history integration requirements. CONCLUSIONS PEHRs are the most applicable records, when it comes to integration with PRSs. Thus, PRS integration with PEHRs is worth further research. CLINICALTRIAL No trial has been performed.

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