Digital inmigrants and digital natives expectation collection in the Andalusian Public Health System Virtual Library: communication with our users

The Andalusian Public Health System Virtual Library (Biblioteca Virtual del Sistema Sanitario Público de Andalucía, BV-SSPA) provides access to health information resources and services to healthcare professionals through its Website. This virtual environment demands higher users’ knowledge in order to satisfy of the need of information of our users, as digital natives as digital immigrants, improving at the same time the communication with all of them. 1. To collect clients' views and expectations according to their nature of digital natives and immigrants. 2. To know our online reputation. A Collecting User Expectation Questionnaire will be built, taking into account the segmentation of the BV-SSPA users’ professional groups of the Andalusian Public Health System. A pilot test will be run to check the survey dimensions and items about practices, attitudes and knowledge of our users. Two Quality Function Deployment (QFD) matrices will enable the BV-SSPA services to be targeted to our digital natives or digital immigrants, according to their nature, finding the best way to satisfy their information needs. We provide feedback on BV-SSPA: users can have the opportunity to post feedback about the site via the 'Contact us' section and comment about their experience. And Web 2.0 is a shop window, providing the opportunity to show the comments; and through time, our online reputation will be built, but the BV-SSPA must manage its own personal branding. Web 2.0 tools are a driver of improvement, because they provide a key source of insight into people's attitudes. Besides, the BV-SSPA digital identity will be analyzed through indicators like major search engine referrals breakdown, top referring sites (non search engines), or top search engine referral phrases, among others. Definition of digital native and digital immigrant profiles of the BV-SSPA, and their difference, will be explained by their expectations. The design of the two QFD matrices will illustrate in just one graph the requirements of both groups for tackling digital abilities and inequalities. The BV-SSPA could deliver information and services through alternative channels. On the other hand, we are developing a strategy to identify, to measure and to manage a digital identity through communication with the user and to find out our online reputation. With the use of different tools from quantitative and qualitative methodology, and the opportunities offered by Web 2.0 tools, the BV-SSPA will know the expectations of their users as a first step to satisfy their necessities. Personalization is pivotal to the success of the Site, delivering tailored content to individuals based on their recorded preferences. The valuable user research can be used during new product development and redesign. Besides positive interaction let us build trust, show authenticity, and foster loyalty: we improve with effort, communication and show.

Use of Hy's law and a new composite algorithm to predict acute liver failure in patients with drug-induced liver injury.

BACKGROUND & AIMS Hy's Law, which states that hepatocellular drug-induced liver injury (DILI) with jaundice indicates a serious reaction, is used widely to determine risk for acute liver failure (ALF). We aimed to optimize the definition of Hy's Law and to develop a model for predicting ALF in patients with DILI. METHODS We collected data from 771 patients with DILI (805 episodes) from the Spanish DILI registry, from April 1994 through August 2012. We analyzed data collected at DILI recognition and at the time of peak levels of alanine aminotransferase (ALT) and total bilirubin (TBL). RESULTS Of the 771 patients with DILI, 32 developed ALF. Hepatocellular injury, female sex, high levels of TBL, and a high ratio of aspartate aminotransferase (AST):ALT were independent risk factors for ALF. We compared 3 ways to use Hy's Law to predict which patients would develop ALF; all included TBL greater than 2-fold the upper limit of normal (×ULN) and either ALT level greater than 3 × ULN, a ratio (R) value (ALT × ULN/alkaline phosphatase × ULN) of 5 or greater, or a new ratio (nR) value (ALT or AST, whichever produced the highest ×ULN/ alkaline phosphatase × ULN value) of 5 or greater. At recognition of DILI, the R- and nR-based models identified patients who developed ALF with 67% and 63% specificity, respectively, whereas use of only ALT level identified them with 44% specificity. However, the level of ALT and the nR model each identified patients who developed ALF with 90% sensitivity, whereas the R criteria identified them with 83% sensitivity. An equal number of patients who did and did not develop ALF had alkaline phosphatase levels greater than 2 × ULN. An algorithm based on AST level greater than 17.3 × ULN, TBL greater than 6.6 × ULN, and AST:ALT greater than 1.5 identified patients who developed ALF with 82% specificity and 80% sensitivity. CONCLUSIONS When applied at DILI recognition, the nR criteria for Hy's Law provides the best balance of sensitivity and specificity whereas our new composite algorithm provides additional specificity in predicting the ultimate development of ALF.