DOES THE MESSAGE MATTER? ENHANCING PATIENT ADHERENCE THROUGH PERSUASIVE MESSAGES

To improve health and reduce costs, we need to encourage patients to make better healthcare decisions. Many informatics interventions are aimed at improving health outcomes by influencing patient behavior. However, we know little about how the content of a message in these interventions can influence a health-related decision. In this research we formulate a conceptual model to help explain and guide the design of “persuasive messages”, those which can change and influence patient behavior. We apply the conceptual model to design persuasive appointment reminder messages using humancentered design principles. Finally, we empirically test our hypotheses in a randomized controlled trial in order to determine the effectiveness of persuasive appointment reminders to reduce the number of missed appointments in a sample of 1016 subjects in a community health center. The results of the study confirm that reminder messages are effective in reducing missed appointment compared with no reminders (p=0.028). Further, reminder messages that incorporate heuristic cues such as authority, commitment, liking, and scarcity are more effective than reminder messages without such cues (p=0.006). However, the addition of systematic arguments or reasons for attending appointments have no effect on appointment adherence (p=0.646). The results of this research suggest that the content of reminder messages may be an important factor in helping to reduce missed appointments.

Candidate gene identification following linkage: Search for hypertension susceptibility genes

Following up genetic linkage studies to identify the underlying susceptibility gene(s) for complex disease traits is an arduous yet biologically and clinically important task. Complex traits, such as hypertension, are considered polygenic with many genes influencing risk, each with small effects. Chromosome 2 has been consistently identified as a genomic region with genetic linkage evidence suggesting that one or more loci contribute to blood pressure levels and hypertension status. Using combined positional candidate gene methods, the Family Blood Pressure Program has concentrated efforts in investigating this region of chromosome 2 in an effort to identify underlying candidate hypertension susceptibility gene(s). Initial informatics efforts identified the boundaries of the region and the known genes within it. A total of 82 polymorphic sites in eight positional candidate genes were genotyped in a large hypothesis-generating sample consisting of 1640 African Americans, 1339 whites, and 1616 Mexican Americans. To adjust for multiple comparisons, resampling-based false discovery adjustment was applied, extending traditional resampling methods to sibship samples. Following this adjustment for multiple comparisons, SLC4A5, a sodium bicarbonate transporter, was identified as a primary candidate gene for hypertension. Polymorphisms in SLC4A5 were subsequently genotyped and analyzed for validation in two populations of African Americans (N = 461; N = 778) and two of whites (N = 550; N = 967). Again, SNPs within SLC4A5 were significantly associated with blood pressure levels and hypertension status. While not identifying a single causal DNA sequence variation that is significantly associated with blood pressure levels and hypertension status across all samples, the results further implicate SLC4A5 as a candidate hypertension susceptibility gene, validating previous evidence for one or more genes on chromosome 2 that influence hypertension related phenotypes in the population-at-large. The methodology and results reported provide a case study of one approach for following up the results of genetic linkage analyses to identify genes influencing complex traits. ^

BIOMEDICAL LANGUAGE UNDERSTANDING AND EXTRACTION (BLUE-TEXT): A MINIMAL SYNTACTIC, SEMANTIC METHOD

Clinical text understanding (CTU) is of interest to health informatics because critical clinical information frequently represented as unconstrained text in electronic health records are extensively used by human experts to guide clinical practice, decision making, and to document delivery of care, but are largely unusable by information systems for queries and computations. Recent initiatives advocating for translational research call for generation of technologies that can integrate structured clinical data with unstructured data, provide a unified interface to all data, and contextualize clinical information for reuse in multidisciplinary and collaborative environment envisioned by CTSA program. This implies that technologies for the processing and interpretation of clinical text should be evaluated not only in terms of their validity and reliability in their intended environment, but also in light of their interoperability, and ability to support information integration and contextualization in a distributed and dynamic environment. This vision adds a new layer of information representation requirements that needs to be accounted for when conceptualizing implementation or acquisition of clinical text processing tools and technologies for multidisciplinary research. On the other hand, electronic health records frequently contain unconstrained clinical text with high variability in use of terms and documentation practices, and without commitmentto grammatical or syntactic structure of the language (e.g. Triage notes, physician and nurse notes, chief complaints, etc). This hinders performance of natural language processing technologies which typically rely heavily on the syntax of language and grammatical structure of the text. This document introduces our method to transform unconstrained clinical text found in electronic health information systems to a formal (computationally understandable) representation that is suitable for querying, integration, contextualization and reuse, and is resilient to the grammatical and syntactic irregularities of the clinical text. We present our design rationale, method, and results of evaluation in processing chief complaints and triage notes from 8 different emergency departments in Houston Texas. At the end, we will discuss significance of our contribution in enabling use of clinical text in a practical bio-surveillance setting.