Abstract
BackgroundThe use of information and communication technologies to manage chronic diseases allows the application of integrated care pathways, and the optimization and standardization of care processes. Decision support tools can assist in the adherence to best-practice medicine in critical decision points during the execution of a care pathway.ObjectivesThe objectives are to design, develop, and assess a clinical decision support system (CDSS) offering a suite of services for the early detection and assessment of chronic obstructive pulmonary disease (COPD), which can be easily integrated into a healthcare providers' work-flow.MethodsThe software architecture model for the CDSS, interoperable clinical-knowledge representation, and inference engine were designed and implemented to form a base CDSS framework. The CDSS functionalities were iteratively developed through requirement-adjustment/development/validation cycles using enterprise-grade software-engineering methodologies and technologies. Within each cycle, clinical-knowledge acquisition was performed by a health-informatics engineer and a clinical-expert team.ResultsA suite of decision-support web services for (i) COPD early detection and diagnosis, (ii) spirometry quality-control support, (iii) patient stratification, was deployed in a secured environment on-line. The CDSS diagnostic performance was assessed using a validation set of 323 cases with 90% specificity, and 96% sensitivity. Web services were integrated in existing health information system platforms.ConclusionsSpecialized decision support can be offered as a complementary service to existing policies of integrated care for chronic-disease management. The CDSS was able to issue recommendations that have a high degree of accuracy to support COPD case-finding. Integration into healthcare providers' work-flow can be achieved seamlessly through the use of a modular design and service-oriented architecture that connect to existing health information systems.
Highlights
Introduction and backgroundAn important problem in healthcare is the significant gap between optimal evidence-based medical practice and the care applied
The clinical decision support system (CDSS) was able to issue recommendations that have a high degree of accuracy to support chronic obstructive pulmonary disease (COPD) case-finding
Decision support web services Spirometry quality control This service, through spirometry-test results consisting of a set of raw signals from spirometry manoeuvres, determines: quality grade (A, B, C, D or F) of the spirometry test; best lung function parameters for the volume that has been exhaled at the end of the first second of forced expiration (FEV1), the vital capacity from a maximally forced expiratory effort (FVC), the highest forced expiratory flow (PEF), back extrapolated volume (BEV), and their associated manoeuvres; acceptability of each manoeuvre; ranking of each manoeuvre; for manoeuvres deemed to unacceptable, the reasons for their rejection. case-finding: Eligibility for spirometry test Through an inclusion/exclusion criteria, represented as Drools rules in the clinical knowledge-base, this service generates advice on subjects at risk of COPD
Summary
Introduction and backgroundAn important problem in healthcare is the significant gap between optimal evidence-based medical practice and the care applied. A systematic review [1] of adherence to chronic obstructive pulmonary disease (COPD) guidelines by clinicians found that the assessment of the disease and the therapy applied to patients were suboptimal. This situation exists across all chronicdisease care in general: in a multinational survey [2] of Clinical decision support systems (CDSSs) can be defined as “software that is designed to be a direct aid to clinical decision-making in which the characteristics of an individual patient are matched to a computerized clinical knowledge base (KB), and patient-specific assessments or recommendations are presented to the clinician and/or the patient for a decision” [3]. Decision support tools can assist in the adherence to best-practice medicine in critical decision points during the execution of a care pathway
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