SNOMED CT Implementation

2012 ◽  
Vol 51 (06) ◽  
pp. 529-538 ◽  
Author(s):  
K. Rosenbeck Gøeg ◽  
A. Randorff Højen
Keyword(s):  
Quality Assurance ◽  
Clinical Practice ◽  
Electronic Health Record ◽  
Quality Criteria ◽  
Clinical Information ◽  
Health Record ◽  
Snomed Ct ◽  
Depth Analysis ◽  
Systematized Nomenclature Of Medicine ◽  
Future Work

SummaryClinical practice as well as research and quality-assurance benefit from unambiguous clinical information resulting from the use of a common terminology like the Systematized Nomenclature of Medicine – Clinical Terms (SNOMED CT). A common terminology is a necessity to enable consistent reuse of data, and supporting semantic interoperability. Managing use of terminology for large cross specialty Electronic Health Record systems (EHR systems) or just beyond the level of single EHR systems requires that mappings are kept consistent. The objective of this study is to provide a clear methodology for SNOMED CT mapping to enhance applicability of SNOMED CT despite incompleteness and redundancy. Such mapping guidelines are presented based on an in depth analysis of 14 different EHR templates retrieved from five Danish and Swedish EHR systems. Each mapping is assessed against defined quality criteria and mapping guidelines are specified. Future work will include guideline validation.

Introducing SNOMED-CT* Coding into an Electronic Health Record: Impact on Clinicians, Data Sharing and Research potential *Systemised Nomenclature of Medicine Clinical Terminology (Preprint)

2021 ◽  
Author(s):  
Tanya Pankhurst ◽  
Felicity Evison ◽  
Jolene Atia ◽  
Suzy Gallier ◽  
Jamie Coleman ◽  
...  
Keyword(s):  
Decision Support ◽  
Electronic Health Record ◽  
Data Sharing ◽  
Clinical Decision ◽  
Health Record ◽  
Coding System ◽  
Snomed Ct ◽  
Healthcare Settings ◽  
Electronic Health ◽  
Systematized Nomenclature Of Medicine

BACKGROUND This study describes the conversion within an existing Electronic Health Record (EHR) from the coding system International Classification of Diseases version 10 (ICD-10) to the Systematized Nomenclature Of MEDicine - Clinical Terms (SNOMED-CT), for collection of patients’ history and diagnoses. The setting is a large acute hospital, designing and building its own EHR. Well-designed EHRs create opportunities for continuous data collection which can be utilised in Clinical Decision Support rules to drive patient safety. Collected data can be exchanged across healthcare systems to support patients in all healthcare settings. Data can be used for research to prevent disease and protect future populations. OBJECTIVE To migrate a current electronic health record, with all relevant patient data, to the coding system, Systematized Nomenclature of Medicine - Clinical Terms, to optimise clinical utilisation and clinical decision support, and facilitate data sharing across organisational boundaries for national programmes, and remodelling of medical pathways. METHODS The study used qualitative and quantitative data to understand the successes and gaps in the project, clinician attitudes to the new tool, and future use. RESULTS The new coding system (“tool”) was well received and immediately widely used in all specialities. It resulted in increased, accurate and clinically relevant data collection. Clinicians appreciated the increased depth and detail of the new coding, welcomed the potential for both data sharing and research, and gave extensive feedback for further development. CONCLUSIONS Successful implementation aligned the Trust with national strategy and can be used as a Blueprint for similar projects in other healthcare settings. CLINICALTRIAL NA

Function-specific Design Principles for the Electronic Health Record

2016 ◽  
Vol 60 (1) ◽  
pp. 578-582 ◽  
Author(s):  
Jason J. Saleem ◽  
Jennifer Herout ◽  
Nancy R. Wilck
Keyword(s):  
Electronic Health Record ◽  
Relevant Literature ◽  
Clinical Decision ◽  
Design Principles ◽  
Health Record ◽  
Progress Notes ◽  
Practical Guidelines ◽  
Electronic Health ◽  
Future Work ◽  
Clinical Reminders

This practice-oriented paper provides a collection of design principles that are specific to certain functions within the electronic health record (EHR). Design principles for EHRs tend to be broad rules of thumb rather than specific and actionable because the relevant literature is organized by specific EHR functions. That is, a good amount of research has been conducted on specific functions, rather than EHRs as a whole. Based on the relevant literature, we provide design principles with underlying rationale for progress notes, problem list, consults, clinical reminders, clinical decision support, medication list, medication alerts, and medication reconciliation. This paper is meant to offer a collection of practical guidelines for designers, grounded in the academic literature, that are more actionable than broad usability heuristics. Future work should include refinement of these principles through systematic literature review and the inclusion of additional EHR functions.

scholarly journals A tribal abstraction network for SNOMED CT target hierarchies without attribute relationships

2014 ◽  
Vol 22 (3) ◽  
pp. 628-639 ◽  
Author(s):  
Christopher Ochs ◽  
James Geller ◽  
Yehoshua Perl ◽  
Yan Chen ◽  
Ankur Agrawal ◽  
...  
Keyword(s):  
Quality Assurance ◽  
Description Logic ◽  
Snomed Ct ◽  
Hierarchical Relationships ◽  
Similar Description ◽  
Systematized Nomenclature Of Medicine

Abstract Objective Large and complex terminologies, such as Systematized Nomenclature of Medicine–Clinical Terms (SNOMED CT), are prone to errors and inconsistencies. Abstraction networks are compact summarizations of the content and structure of a terminology. Abstraction networks have been shown to support terminology quality assurance. In this paper, we introduce an abstraction network derivation methodology which can be applied to SNOMED CT target hierarchies whose classes are defined using only hierarchical relationships (ie, without attribute relationships) and similar description-logic-based terminologies. Methods We introduce the tribal abstraction network (TAN), based on the notion of a tribe—a subhierarchy rooted at a child of a hierarchy root, assuming only the existence of concepts with multiple parents. The TAN summarizes a hierarchy that does not have attribute relationships using sets of concepts, called tribal units that belong to exactly the same multiple tribes. Tribal units are further divided into refined tribal units which contain closely related concepts. A quality assurance methodology that utilizes TAN summarizations is introduced. Results A TAN is derived for the Observable entity hierarchy of SNOMED CT, summarizing its content. A TAN-based quality assurance review of the concepts of the hierarchy is performed, and erroneous concepts are shown to appear more frequently in large refined tribal units than in small refined tribal units. Furthermore, more erroneous concepts appear in large refined tribal units of more tribes than of fewer tribes. Conclusions In this paper we introduce the TAN for summarizing SNOMED CT target hierarchies. A TAN was derived for the Observable entity hierarchy of SNOMED CT. A quality assurance methodology utilizing the TAN was introduced and demonstrated.

Implementation of Electronic Health Record as a Clinical Information Tool to Improve Gastric Cancer Care

2021 ◽  
Author(s):  
Leila Shahmoradi ◽  
Rogayeh KhoramiMoghadam ◽  
Marjan Ghazisaeedi ◽  
Marsa Gholamzadeh
Keyword(s):  
Gastric Cancer ◽  
Electronic Health Record ◽  
Cancer Care ◽  
Clinical Information ◽  
Health Record ◽  
Functional Requirements ◽  
Record System ◽  
Web Based ◽  
Electronic Health ◽  
And Performance

Aim: According to the high prevalence of gastric cancer in Iran, this study aimed to develop a gastric cancer electronic health record (EHR) to improve outpatient gastric cancer care. Method: This study represented the stepwise process used to develop a web-based gastric cancer EHR to overcome the documentation problems and cancer care complications. These iterative phases included determining the required minimum data sets (MDS), designing, developing and implementation, and usability evaluation. The system functional and non-functional requirements were determined using needs assessment. The MDSs were identified through consensus by a multidisciplinary expert panel. Finally, the web-based system was implemented in PHP language. Results: Initially, the required datasets were verified by experts. Later, an EHR-based gastric cancer system was implemented successfully to support outpatient cancer care. Based on the analysis, the functional requirements and main modules of the system were specified. The designed system reached an acceptable level of usability and performance. Conclusion: The system was successfully implemented in the gastric cancer clinic. Implementation of an electronic health record system can not only provide ease of access to clinical information, but also improve the quality of complicated cancer care.

scholarly journals Cognitive Usability Evaluation of Electronic Health Record Systems (CUE-E)

2019 ◽  
Vol 8 (1) ◽  
pp. 13-17 ◽  
Author(s):  
Mark S. Pfaff ◽  
Amanda Anganes ◽  
Ozgur Eris ◽  
Aileen Prior ◽  
Merry Ward ◽  
...  
Keyword(s):  
Electronic Health Record ◽  
Conceptual Framework ◽  
Reliability And Validity ◽  
Evaluation Methods ◽  
Usability Evaluation ◽  
Health Record ◽  
Health Records ◽  
Electronic Health ◽  
Future Work ◽  
Usability Evaluation Methods

This project’s purpose was to develop cognitively-focused usability evaluation methods for electronic health records (EHRs). This research involved developing a conceptual framework for evaluating EHR usability in terms of clinical cognition and operationalizing the framework in the form of two novel EHR usability evaluation methods. The two evaluation methods - one observational and one lab-based - are described in a suite of protocol materials and recommendations for EHR evaluation and design. This resulting body of work is referred to as CUE-E: Cognitive Usability Evaluation - EHR. This paper describes the process behind the development of the CUE-E evaluation methods, summarizes the use of both, and discusses directions for future work. The two CUE-E evaluation methods are currently ready for pilot applications to assess their reliability and validity and identify opportunities for further improvement.

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