Evaluating digital libraries: a systematised review.

OBJECTIVE: The purpose of this study was to examine the models and methods for evaluating digital libraries. METHODS: Springer, Science Direct, ProQuest, Emerald, Wiley, LISTA, Web of Science (WOS), Scopus, Magiran (Persian), Irandoc (Persian), SID (Persian) and Noormags (Persian) databases were searched systematically based on the defined criteria. Selection criteria included full-text articles and dissertations published in English and Persian languages in 2004-2017. The final included articles (n = 64) were reviewed, selected and analysed by group discussions. RESULTS: The results of analysing 64 included articles for this systematised review specified that the evaluation of digital libraries is mostly focused on the service quality aspect, and DigiQual was the most frequently used model. Few studies have evaluated digital libraries in the health sector. The researcher developed questionnaire is the most frequently used method to evaluate digital libraries. CONCLUSION: Because there are fewer studies of digital libraries evaluation in the health sector, the specific features of health digital libraries should be addressed by librarians and health digital library designers to develop specific models.

Advanced querying features for disease surveillance systems.

Most automated disease surveillance systems notify users of increases in the prevalence of reports in syndrome categories and allow users to view patient level data related to those increases. Occasionally, a more dynamic level of control is required to properly detect an emerging disease in a community. Dynamic querying features are invaluable when using existing surveillance systems to investigate outbreaks of newly emergent diseases or to identify cases of reportable diseases within data being captured for surveillance. The objective of the Advance Querying Tool (AQT) is to build a more flexible query interface for most web-based disease surveillance systems. This interface allows users to define and build their query as if they were writing a logical expression for a mathematical computation. The AQT allows users to develop, investigate, save, and share complex case definitions. It provides a flexible interface that accommodates both advanced and novice users, checks the validity of the expression as it is built, and marks errors for users.

Electronic medical record (EMR) utilization for public health surveillance.

INTRODUCTION: Public health surveillance systems need to be refined. We intend to use a generic approach for early identification of patients with severe influenza-like illness (ILI) by calculating a score that estimates a patients disease-severity. Accordingly, we built the Intelligent Severity Score Estimation Model (ISSEM), structured so that the inference process would reflect experts decision-making logic. Each patients disease-severity score is calculated from numbers of respiratory ICD9 encounters, and laboratory, radiologic, and prescription-therapeutic orders in the EMR. Other ISSEM components include chronic disease evidence, probability of immunodeficiency, and the providers general practice-behavior patterns. RESULTS: Sensitivity was determined from 200 randomly selected patients with upper- and lower-respiratory tract ILI; specificity, from 300 randomly selected patients with URI only. For different age groups, ISSEM sensitivity ranged between 90% and 95%; specificity was 72% to 84%. CONCLUSION: Our preliminary assessment of ISSEM performance demonstrated 93.5% sensitivity and 77.3% specificity across all age groups.