Ontology based semantic recommendations for discharge summary medication information for patients

Adnan, Mehnaz; Warren, James R.; Orr, Martin

doi:10.1109/cbms.2010.6042688

Cited by 13 publications

(8 citation statements)

References 11 publications

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“…[34] However, instead of semantically annotating PCeHRs, SemAssist has been developed to help healthcare workers in writing the patient advice section of the discharge summary. The goal of this NLP system is to reduce medical errors and improve physicians' efficiency, focusing on the fact that patients' limited knowledge about medications is a key factor in post-discharge adverse drug events.…”

Section: The Semassist System For Patient-friendly Personalized Discmentioning

confidence: 99%

10 Patient empowerment via technologies for patient-friendly personalized language

Adnan

Warren

Suominen

2015

Information Technology for Patient Empowerment in Healthcare

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Free-text reports are used in health care to transfer information between working shifts and sites. This text, written by a physician, nurse, specialist, ward secretary or other healthcare worker, is full of jargon, idioms and shorthand that patients find difficult to understand. If patients are to be empowered to take an active role and make informed decisions in their health care, they need support for understanding these reports. This chapter discusses language technologies as a way to provide support for patients to better understand free-text reports with difficult clinical language. This includes expanding shorthand, replacing words with patient-centric terms, providing term definitions, hyperlinking to further information on patientfriendly and reliable sites on the internet , and personalizing medication advice and other content. To conclude, statistical evaluations and benchmarks in shared tasks give evidence of language technologies being successful in making text easier to understand and better personalized. Moreover, electronic health record s that both patients and clinicians use to read, write and share information are becoming more commonplace and provide a platform for language technologies to assist patients in reading free-text reports.

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Section: The Semassist System For Patient-friendly Personalized Discmentioning

confidence: 99%

10 Patient empowerment via technologies for patient-friendly personalized language

Adnan

Warren

Suominen

2015

Information Technology for Patient Empowerment in Healthcare

Self Cite

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“…For example, in trying to capture "past history of myocardial infarction", system A may structure it as Past medical history > Myocardial infarction; system B may structure it as Past medical history > Myocardial infarction > Yes; and system C may give a single statement in a check box. Recent studies proposed to standardize the clinical information model (17,18) and introduce ontology to this model (19)(20)(21)(22). An ontology-based information model would define each information entity with specific properties and its relationships to other information entities in a logical manner.…”

Section: Seamless Data Transfermentioning

confidence: 99%

Mapping Acute Coronary Syndrome Registries to SNOMED CT

Sulaiman

Karlsson²,

Koch³

2017

Methods Inf Med

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“…Research projects funded for enabling Semantic Web technologies in the diagnosis and therapeutic procedures exist such as REMINE [1], PSIP [2], NeOn [3] and Active Semantic Documents [4] or works such as [5], but they don’t fully address the problem of automated drug prescription using drug-drug and drug-disease interactions.…”

Section: Introductionmentioning

confidence: 99%

Panacea, a semantic-enabled drug recommendations discovery framework

et al. 2014

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BackgroundPersonalized drug prescription can be benefited from the use of intelligent information management and sharing. International standard classifications and terminologies have been developed in order to provide unique and unambiguous information representation. Such standards can be used as the basis of automated decision support systems for providing drug-drug and drug-disease interaction discovery. Additionally, Semantic Web technologies have been proposed in earlier works, in order to support such systems.ResultsThe paper presents Panacea, a semantic framework capable of offering drug-drug and drug-diseases interaction discovery. For enabling this kind of service, medical information and terminology had to be translated to ontological terms and be appropriately coupled with medical knowledge of the field. International standard classifications and terminologies, provide the backbone of the common representation of medical data while the medical knowledge of drug interactions is represented by a rule base which makes use of the aforementioned standards. Representation is based on a lightweight ontology. A layered reasoning approach is implemented where at the first layer ontological inference is used in order to discover underlying knowledge, while at the second layer a two-step rule selection strategy is followed resulting in a computationally efficient reasoning approach. Details of the system architecture are presented while also giving an outline of the difficulties that had to be overcome.ConclusionsPanacea is evaluated both in terms of quality of recommendations against real clinical data and performance. The quality recommendation gave useful insights regarding requirements for real world deployment and revealed several parameters that affected the recommendation results. Performance-wise, Panacea is compared to a previous published work by the authors, a service for drug recommendations named GalenOWL, and presents their differences in modeling and approach to the problem, while also pinpointing the advantages of Panacea. Overall, the paper presents a framework for providing an efficient drug recommendations service where Semantic Web technologies are coupled with traditional business rule engines.

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Ontology based semantic recommendations for discharge summary medication information for patients

Cited by 13 publications

References 11 publications

10 Patient empowerment via technologies for patient-friendly personalized language

10 Patient empowerment via technologies for patient-friendly personalized language

Mapping Acute Coronary Syndrome Registries to SNOMED CT

Panacea, a semantic-enabled drug recommendations discovery framework

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