Clinical guidelines recommend quality standards for patient care. Encoding guidelines in a computer-interpretable format and integrating them with an Electronic Medical Record (EMR) can enable delivery of patient-specific recommendations when and where needed. GLIF3 is a language for representing computer-interpretable guidelines (CIGs) and sharing them among healthcare institutions. Sharing a CIG necessitates mapping its data items to the institutional EMRs. We developed a framework called Knowledge-Data Ontological Mapper (KDOM) that enables bridging the gap from abstractions used in CIGs to specific EMRs. Briding the gap involves: (1) using an ontology of mappings, and an optional reference information model, to map an abstraction gradually into EMR codes, and (2) automatically creating SQL queries to retrieve the EMR data. We evaluated the KDOM framework by mapping a GLIF3-encoded guideline into two different EMR schemas and by using the mapping ontology to define mappings from 15 GLIF3 CIGs and one SAGE CIG into our reference information model.

Access control is a central problem in privacy management. A common practice in controlling access to sensitive data, such as electronic health records (EHRs), is Role-Based Access Control (RBAC). RBAC is limited as it does not account for the circumstances under which access to sensitive data is requested. Following a qualitative study that elicited access scenarios, we used Object-Process Methodology to structure the scenarios and conceive a Situation-Based Access Control (SitBAC) model. SitBAC is a conceptual model, which defines scenarios where patient's data access is permitted or denied. The main concept underlying this model is the Situation Schema, which is a pattern consisting of the entities Data-Requestor, Patient, EHR, Access Task, Legal-Authorization, and Response, along with their properties and relations. The various data access scenarios are expressed via Situation Instances. While we focus on the medical domain, the model is generic and can be adapted to other domains.

When chest symptoms recur in a patient who underwent percutaneous transluminal coronary angioplasty (PTCA), it is necessary to rule out restenosis (R). Three main noninvasive tests suggest the presence of R: exercise stress test (XT), myocardial perfusion imaging (MPI) and stress echocardiography (s-echo). The objectives of this review were: (1) to estimate the pretest probability of R as a function of time after PTCA in symptomatic patients and (2) to obtain an approximation of the diagnostic parameters of the XT, MPI and s-echo for detecting R. A MEDLINE search (English-language, years: 1980-2001) was conducted to identify studies examining post-PTCA functional testing for diagnosing R. Data from the studies were pooled. Comparing studies was often difficult due to varying methodology in the studies. Pretest probability of R in symptomatic patients increases in a nonlinear fashion from 20% or less at 1 month, to nearly 90% at 1-year postangioplasty. The approximated accuracy of the XT, MPI, and s-echo for detecting R was 62, 82 and 84%, respectively. During the first month after PTCA, none of the noninvasive modalities is able to accurately detect R. Late (7-9 months) after PTCA, the pretest probability of R is high and therefore the noninvasive measure may be spared. Our analysis suggests that MPI and s-echo should be preferred over the XT for diagnosing R.

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