Don't overthink it: The paradoxical nature of expertise for the detection of errors in conceptual business process models.

Business process models are widely used artifacts in design activities to facilitate communication about business domains and processes. Despite being an extensively researched topic, some aspects of conceptual business modeling are yet to be fully explored and understood by academicians and practitioners alike. We study the attentional characteristics specific to experts and novices in a semantic and syntactic error detection task across 75 Business Process Model and Notation (BPMN) models.

Patient perspectives of telemedicine quality.

Background: The purpose of this study was to explore the quality attributes required for effective telemedicine encounters from the perspective of the patient.

Methods: We used a multi-method (direct observation, focus groups, survey) field study to collect data from patients who had experienced telemedicine encounters. Multi-perspectives (researcher and provider) were used to interpret a rich set of data from both a research and practice perspective.

Rating the health status of U.S. communities.

Although the existence of small-area variation in health care utilization and quality had been acknowledged decades ago, and the public release of data about the performance of hospitals and physicians is no longer controversial, the wide range of variability in the health status of U.S. communities has received relatively little attention.

Comparing alternative methods for composing community peer groups: a data warehouse application.

A method for assessing the health status of communities has been under development for a decade at the University of South Florida. Known as CATCH (Comprehensive Assessment for Tracking Community Health), the method utilizes health status indicators from multiple data sources. With federal grant support, a unique data warehouse has been created to automate CATCH assessments and to enhance online analytical processing for efficient data browsing, knowledge discovery, and model testing.

CATCH/IT: a data warehouse to support comprehensive assessment for tracking community health.

A systematic methodology, Comprehensive Assessment for Tracking Community Health (CATCH), for analyzing the health status of communities has been under development at the University of South Florida since the early 1990s. CATCH draws 226 health status indicators from multiple data sources and uses an innovative comparative framework and weighted evaluation criteria to produce a rank-ordered list of community health problems. CATCH has been applied successfully in many Florida counties; focusing attention on high priority health issues and measuring the impact of health expenditures on community health status outcomes.