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An ontology driven clinical evidence service providing diagnostic decision support in family practice.

Corrigan D - AMIA Jt Summits Transl Sci Proc (2015)

Bottom Line: Formulation of a working diagnostic hypothesis in family practice requires consideration of many differential diagnoses associated with any presenting patient complaint.The solution implements ontology models of evidence accessible to consumers as a web service using open source components and standards.An implementation example is described that consumes the service to drive a diagnostic decision support tool developed for the TRANSFoRm project.

View Article: PubMed Central - PubMed

Affiliation: HRB Centre for Primary Care Research, Royal College of Surgeons in Ireland, Dublin, Ireland.

ABSTRACT
Formulation of a working diagnostic hypothesis in family practice requires consideration of many differential diagnoses associated with any presenting patient complaint. There follows a process of refinement of the differentials to consider, through ruling in or out each candidate differential based on the confirmed presence or absence of diagnostic cues elicited during patient consultation. The patient safety implications of diagnostic error are potentially severe for patient and clinician. This paper describes a clinical evidence service supporting this diagnostic process. It allows decision support consumers to provide coded evidence-based recommendations to assist with diagnostic hypothesis formulation, integrated with an EHR in primary care. The solution implements ontology models of evidence accessible to consumers as a web service using open source components and standards. An implementation example is described that consumes the service to drive a diagnostic decision support tool developed for the TRANSFoRm project.

No MeSH data available.


Related in: MedlinePlus

An evidence service reply describing a symptom collection for Urinary Tract Infection including Frequency and Haematuria.
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Related In: Results  -  Collection


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f4-2081312: An evidence service reply describing a symptom collection for Urinary Tract Infection including Frequency and Haematuria.

Mentions: To access the cues supporting diagnosis of urinary tract infection (output shown in figure 4) the query is:


An ontology driven clinical evidence service providing diagnostic decision support in family practice.

Corrigan D - AMIA Jt Summits Transl Sci Proc (2015)

An evidence service reply describing a symptom collection for Urinary Tract Infection including Frequency and Haematuria.
© Copyright Policy
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC4525252&req=5

f4-2081312: An evidence service reply describing a symptom collection for Urinary Tract Infection including Frequency and Haematuria.
Mentions: To access the cues supporting diagnosis of urinary tract infection (output shown in figure 4) the query is:

Bottom Line: Formulation of a working diagnostic hypothesis in family practice requires consideration of many differential diagnoses associated with any presenting patient complaint.The solution implements ontology models of evidence accessible to consumers as a web service using open source components and standards.An implementation example is described that consumes the service to drive a diagnostic decision support tool developed for the TRANSFoRm project.

View Article: PubMed Central - PubMed

Affiliation: HRB Centre for Primary Care Research, Royal College of Surgeons in Ireland, Dublin, Ireland.

ABSTRACT
Formulation of a working diagnostic hypothesis in family practice requires consideration of many differential diagnoses associated with any presenting patient complaint. There follows a process of refinement of the differentials to consider, through ruling in or out each candidate differential based on the confirmed presence or absence of diagnostic cues elicited during patient consultation. The patient safety implications of diagnostic error are potentially severe for patient and clinician. This paper describes a clinical evidence service supporting this diagnostic process. It allows decision support consumers to provide coded evidence-based recommendations to assist with diagnostic hypothesis formulation, integrated with an EHR in primary care. The solution implements ontology models of evidence accessible to consumers as a web service using open source components and standards. An implementation example is described that consumes the service to drive a diagnostic decision support tool developed for the TRANSFoRm project.

No MeSH data available.


Related in: MedlinePlus