HYGIA: Design and Application of New Techniques of Artificial Intelligence for the Acquisition and...

HYGIA: Design and Application of New Techniques of Artificial Intelligence for the Acquisition and Use of Represented Medical Knowledge as Care Pathways

David RiaoMara TaboadaMar MarcosBegoa MartnezAlbert Alonso

jspTIN 2009, Friday Feb 20th 2009, Madrid

OutlineSummary of the projectConsortiumObjectivesAchievementsThe ten remaining TasksConclusions


Summary of the ProjectClinical practice guidelines (CPG) reflect the best scientific evidence for clinical handling of patients with a concrete pathology. They have a direct impact in the quality and standardization of health-care but their application is below the desirable level. In order to increase their use, Care Pathways (CPs) operative versions of CPGs in a certain segment of patients and concrete healthcare context are set out. In this project we propose the use of Intelligent Systems in the processes of acquiring, formalizing, adapting, using and assessing knowledge models that describe CPs. Electronic CPs are obtained and used by intelligent agents to facilitate health-care decision making.


Consortium


ObjectivesO1.Design and implementation of a set of tools to automate, as far as possible, the knowledge acquisition from textual CPG documents.O2.Proposal of a methodological framework to develop electronic protocols from electronic CPGs.O3.Proposal of a methodological framework to develop CPs from electronic protocols and other additional resources, such as the data stored in hospital databases.O4.New inductive learning algorithms to generate health-care knowledge from data of medical interventions stored in hospital databases, and using ontologies providing the semantics of the medical domain of the guideline.O5.Utilization of these knowledge structures or CPs for health-care decision support by means of a multi-agent system (MAS) that interprets this knowledge within the institutional context in which the medical activity is carried out.O6.Identification and evaluation of the adherence degree by health-care professionals to multi-pathology CPs resulting from the technologies integrated in the project, applied to a programme for chronic patient care.



Achievements IKnowledge-Engineering approaches based on Natural Language Processing techniques, terminologies and ontologiesAcquisition of ontology concepts from GPC documentsAutomated recognition of diagnosis entities Automated recognition of therapy entitiesVerification and validation on CHF and COPD GPCs Automated generation of ontology relationshipsAutomated recognition of some diagnosis relationshipsAutomated recognition of some therapy relationshipsVerification and validation on CHF and COPD GPCs


Achievements IIMethodologies for knowledge engineeringAnalysis of alternatives to represent electronic CPGs, protocols and CPsA CP-oriented approach to obtain protocols from CPGsA CP-oriented approach to obtain CPs from protocolsThese contemplate:Definition of reusable CP fragmentsMethodological guidelines to integrate electronic CP fragments using CPG toolsStrategies to apply formal methods to the integration of CP fragmentsKnowledge acquisition of a CP for the prevention of exacerbations in stable COPD and CHF patientsDevelopment of electronic CPs that support the management of comorbidities. This is the result of 1) development of general protocols for each condition considered and 2) analysis of historical data


Achievements III


Achievements IVInductive learning algorithmsData and SDA ModelsData ExtractionData available in HCB databasesQueries to extract relevant dataA complete extraction of dataData PreprocessingDetect & correct data anomaliesAdapt data to the data modelSearch & Replace techniquesData model editor and converterData ready for machine learningInductive ML AlgorithmTransform procedural data into knowledgeTwo inductive ML algorithms implementedApplicationData on hypertensionResults 8% -1% type 1-2 error respect to the CPG of the Spanish Society of Hypertension


Achievements VMulti-Agent System

Elaboration of a set of adherence indicators together with a mechanism to monitor them (task about to finish)


The 10 Remaining TasksAdjust the methods to recognize entities and relationships. Conclude the generation of electronic CPGs. The case study about obtaining CPs (stable COPD+CHF patients)A methodology for the development of CPs, including the utilization of CPG tools and formal methods, and the integration of other knowledge sourcesFinish the data pre-processing of DIA, COPD, Heart Failure.Apply the inductive algorithm on DIA, COPD, Heart Failure.Introduce the CPs of the project in the MAS for execution.Introduce the adherence indicators in the MAS for medical assessment.Pilot the developed algorithms on existing chronic programs.Determine the impact of applying the developed algorithms on current processes and in the related clinical outcomes.


ConclusionsGeneration of actionable knowledge in healthcareFrom text to knowledgeit is possible to extract ontologiesthere are methodologies to ease knowledge engineeringFrom data to knowledgeit is possible to induce correct from healthcare databasesfiltering the data can provide alterative views of healthcare processesMaking knowledge actionableon-line: formal knowledge as a way to supervise healthcare actionsoff-line: formal knowledge as a way to adherence analysis to standards

HYGIA: Design and Application of New Techniques of Artificial Intelligence for the Acquisition and...

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