An openEHR Approach to Detailed Clinical Model Development: Tobacco Smoking Summary Archetype as a Case Study

Wei, Ping-Cheng; Atalag, Koray; Day, Karen

doi:10.1055/s-0039-1681074

Cited by 9 publications

(4 citation statements)

References 22 publications

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“…Future efforts may also consider how population health strategies combined with clinical informatics may enhance tobacco treatment efforts outside of the clinical encounter setting. 46…”

Section: Resultsmentioning

confidence: 99%

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Health System Implementation of a Tobacco Quitline eReferral

et al. 2019

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Background Proactive referrals through electronic orders (eReferrals) can increase patient connection with tobacco quitlines. More information is needed on “real-world” implementation of electronic health record tools to promote tobacco cessation while minimizing provider burden. Objectives This paper examines the health system implementation of an eReferral to a tobacco quitline without best practice alerts in primary care, specialty, and hospital settings in an academic health system. Methods This is a prospective implementation study of a health system tobacco eReferral to a state quitline that was completed with an approach to minimize provider cognitive burden. Data are drawn from electronic health record data at University of California, Davis Health Systems (March 2013–February 2016). Results Over 3 years, 16,083 encounters with smokers resulted in 1,137 eReferral orders (7.1%). Treatment reach was 1.6% for quitline services and 2.3% for outpatient group classes. While the group classes were offered to outpatient smokers, the eReferral order was included in an outpatient order set and eventually an automated inpatient discharge order set; no provider alerts were implemented. Referrals were sustained and doubled after inpatient order set implementation. Among all first time eReferral patients, 12.2% had a 6 to 12 month follow-up visit at which they were documented as nonsmoking. Conclusion This study demonstrates a quitline eReferral order can be successfully implemented and sustained with minimal promotion, without provider alerts and in conjunction with group classes. Reach and effectiveness were similar to previously described literature.

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“…Future efforts may also consider how population health strategies combined with clinical informatics may enhance tobacco treatment efforts outside of the clinical encounter setting. 46…”

Section: Resultsmentioning

confidence: 99%

“…Interoperability between tobacco cessation EHR resources may be a model when developing clinical informatics tools, such as an open EHR. 46…”

Section: Discussionmentioning

confidence: 99%

Health System Implementation of a Tobacco Quitline eReferral

et al. 2019

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“…This can influence the way in which the records accurately represent the phenomena of patients, interfering in the decisions of health professionals. 25 The maximum representation of a concept in an archetype enables choosing what information will be kept when it is restricted at the template level. This collaborates so that the structured models correspond to the needs of each service, considering specific contexts.…”

Section: Diagnosis and Interventions In The Openehr Standard Gomes Et Al 343mentioning

confidence: 99%

Representation of Diagnosis and Nursing Interventions in OpenEHR Archetypes

et al. 2021

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Objective The study aimed to represent the content of nursing diagnosis and interventions in the openEHR standard. Methods This is a developmental study with the models developed according to ISO 18104: 2014. The Ocean Archetype Editor tool from the openEHR Foundation was used. Results Two archetypes were created; one to represent the nursing diagnosis concept and the other the nursing intervention concept. Existing archetypes available in the Clinical Knowledge Manager were reused in modeling. Conclusion The representation of nursing diagnosis and interventions based on the openEHR standard contributes to representing nursing care phenomena and needs in health information systems.

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“…OpenEHR-related research is gradually becoming one of the most discussed semantic interoperability-related research topics. Such research involves archetype modeling [17][18][19][20][21][22][23], data persistence [24][25][26], language design [27], model mapping [28], model retrieval [29,30], and reuse [19].…”

Section: Introductionmentioning

confidence: 99%

Verifying the Feasibility of Implementing Semantic Interoperability in Different Countries Based on the OpenEHR Approach: Comparative Study of Acute Coronary Syndrome Registries

Min¹,

Atalag²,

Tian³

et al. 2021

JMIR Med Inform

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Background The semantic interoperability of health care information has been a critical challenge in medical informatics and has influenced the integration, sharing, analysis, and use of medical big data. International standard organizations have developed standards, approaches, and models to improve and implement semantic interoperability. The openEHR approach—one of the standout semantic interoperability approaches—has been implemented worldwide to improve semantic interoperability based on reused archetypes. Objective This study aimed to verify the feasibility of implementing semantic interoperability in different countries by comparing the openEHR-based information models of 2 acute coronary syndrome (ACS) registries from China and New Zealand. Methods A semantic archetype comparison method was proposed to determine the semantics reuse degree of reused archetypes in 2 ACS-related clinical registries from 2 countries. This method involved (1) determining the scope of reused archetypes; (2) identifying corresponding data items within corresponding archetypes; (3) comparing the semantics of corresponding data items; and (4) calculating the number of mappings in corresponding data items and analyzing results. Results Among the related archetypes in the two ACS-related, openEHR-based clinical registries from China and New Zealand, there were 8 pairs of reusable archetypes, which included 89 pairs of corresponding data items and 120 noncorresponding data items. Of the 89 corresponding data item pairs, 87 pairs (98%) were mappable and therefore supported semantic interoperability, and 71 pairs (80%) were labeled as “direct mapping” data items. Of the 120 noncorresponding data items, 114 (95%) data items were generated via archetype evolution, and 6 (5%) data items were generated via archetype localization. Conclusions The results of the semantic comparison between the two ACS-related clinical registries prove the feasibility of establishing the semantic interoperability of health care data from different countries based on the openEHR approach. Archetype reuse provides data on the degree to which semantic interoperability exists when using the openEHR approach. Although the openEHR community has effectively promoted archetype reuse and semantic interoperability by providing archetype modeling methods, tools, model repositories, and archetype design patterns, the uncontrolled evolution of archetypes and inconsistent localization have resulted in major challenges for achieving higher levels of semantic interoperability.

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An openEHR Approach to Detailed Clinical Model Development: Tobacco Smoking Summary Archetype as a Case Study

Cited by 9 publications

References 22 publications

Health System Implementation of a Tobacco Quitline eReferral

Health System Implementation of a Tobacco Quitline eReferral

Representation of Diagnosis and Nursing Interventions in OpenEHR Archetypes

Verifying the Feasibility of Implementing Semantic Interoperability in Different Countries Based on the OpenEHR Approach: Comparative Study of Acute Coronary Syndrome Registries

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