Assessing clinical researchers' information needs to create responsive portals and tools: my Research Assistant (MyRA) at the University of Utah: a case study.

QUESTION: How can health sciences librarians and biomedical informaticians offer relevant support to Clinical and Translational Science Award (CTSA) personnel? SETTING: The Spencer S. Eccles Health Sciences Library and the associate vice president for information technology for the health sciences office at the University of Utah conducted a needs assessment. METHODS: Faculty and staff from these two units, with the services of a consultant and other CTSA partners, employed a survey, focus groups, interviews, and committee discussions. An information portal was created to meet identified needs. RESULTS: A directive white paper was created. The process employed to plan a virtual and physical collaborative, collegial space for clinical researchers at the university and its three inter-institutional CTSA partners is described. CONCLUSION: The university's model can assist other librarians and informaticians with how to become part of a CTSA-focused infrastructure for clinical and translational research and serve researchers in general.

Nanoinformatics: a new area of research in nanomedicine.

Over a decade ago, nanotechnologists began research on applications of nanomaterials for medicine. This research has revealed a wide range of different challenges, as well as many opportunities. Some of these challenges are strongly related to informatics issues, dealing, for instance, with the management and integration of heterogeneous information, defining nomenclatures, taxonomies and classifications for various types of nanomaterials, and research on new modeling and simulation techniques for nanoparticles. Nanoinformatics has recently emerged in the USA and Europe to address these issues. In this paper, we present a review of nanoinformatics, describing its origins, the problems it addresses, areas of interest, and examples of current research initiatives and informatics resources. We suggest that nanoinformatics could accelerate research and development in nanomedicine, as has occurred in the past in other fields. For instance, biomedical informatics served as a fundamental catalyst for the Human Genome Project, and other genomic and -omics projects, as well as the translational efforts that link resulting molecular-level research to clinical problems and findings.

Consensus: a framework for evaluation of uncertain gene variants in laboratory test reporting.

Accurate interpretation of gene testing is a key component in customizing patient therapy. Where confirming evidence for a gene variant is lacking, computational prediction may be employed. A standardized framework, however, does not yet exist for quantitative evaluation of disease association for uncertain or novel gene variants in an objective manner. Here, complementary predictors for missense gene variants were incorporated into a weighted Consensus framework that includes calculated reference intervals from known disease outcomes. Data visualization for clinical reporting is also discussed.

Federating clinical data from six pediatric hospitals: process and initial results for microbiology from the PHIS+ consortium.

Microbiology study results are necessary for conducting many comparative effectiveness research studies. Unlike core laboratory test results, microbiology results have a complex structure. Federating and integrating microbiology data from six disparate electronic medical record systems is challenging and requires a team of varied skills. The PHIS+ consortium which is partnership between members of the Pediatric Research in Inpatient Settings (PRIS) network, the Children's Hospital Association and the University of Utah, have used "FURTHeR' for federating laboratory data. We present our process and initial results for federating microbiology data from six pediatric hospitals.

Utility of gene-specific algorithms for predicting pathogenicity of uncertain gene variants.

The rapid advance of gene sequencing technologies has produced an unprecedented rate of discovery of genome variation in humans. A growing number of authoritative clinical repositories archive gene variants and disease phenotypes, yet there are currently many more gene variants that lack clear annotation or disease association. To date, there has been very limited coverage of gene-specific predictors in the literature. Here the evaluation is presented of "gene-specific" predictor models based on a naïve Bayesian classifier for 20 gene-disease datasets, containing 3986 variants with clinically characterized patient conditions. The utility of gene-specific prediction is then compared with "all-gene" generalized prediction and also with existing popular predictors. Gene-specific computational prediction models derived from clinically curated gene variant disease datasets often outperform established generalized algorithms for novel and uncertain gene variants.

Integrating historical clinical and financial data for pharmacological research.

BACKGROUND: Retrospective research requires longitudinal data, and repositories derived from electronic health records (EHR) can be sources of such data. With Health Information Technology for Economic and Clinical Health (HITECH) Act meaningful use provisions, many institutions are expected to adopt EHRs, but may be left with large amounts of financial and historical clinical data, which can differ significantly from data obtained from newer systems, due to lack or inconsistent use of controlled medical terminologies (CMT) in older systems. We examined different approaches for semantic enrichment of financial data with CMT, and integration of clinical data from disparate historical and current sources for research. METHODS: Snapshots of financial data from 1999, 2004 and 2009 were mapped automatically to the current inpatient pharmacy catalog, and enriched with RxNorm. Administrative metadata from financial and dispensing systems, RxNorm and two commercial pharmacy vocabularies were used to integrate data from current and historical inpatient pharmacy modules, and the outpatient EHR. Data integration approaches were compared using percentages of automated matches, and effects on cohort size of a retrospective study. RESULTS: During 1999-2009, 71.52%-90.08% of items in use from the financial catalog were enriched using RxNorm; 64.95%-70.37% of items in use from the historical inpatient system were integrated using RxNorm, 85.96%-91.67% using a commercial vocabulary, 87.19%-94.23% using financial metadata, and 77.20%-94.68% using dispensing metadata. During 1999-2009, 48.01%-30.72% of items in use from the outpatient catalog were integrated using RxNorm, and 79.27%-48.60% using a commercial vocabulary. In a cohort of 16304 inpatients obtained from clinical systems, 4172 (25.58%) were found exclusively through integration of historical clinical data, while 15978 (98%) could be identified using semantically enriched financial data. CONCLUSIONS: Data integration using metadata from financial/dispensing systems and pharmacy vocabularies were comparable. Given the current state of EHR adoption, semantic enrichment of financial data and integration of historical clinical data would allow the repurposing of these data for research. With the push for HITECH meaningful use, institutions that are transitioning to newer EHRs will be able to use their older financial and clinical data for research using these methods.

Comparison of compliance for colorectal cancer screening and surveillance by colonoscopy based on risk.

PURPOSE: To compare colonoscopy screening/surveillance rates by level of risk for colorectal cancer based on age, personal history of adenomatous polyps or colorectal cancer, or family history of colorectal cancer. METHODS: Participants were aged 30-90 years, were seen within 5 years at Intermountain Healthcare, and had family history in the Utah Population Database. Colonoscopy rates were measured for those with/without risk factors. RESULTS: Among those aged 60-69 years, 48.4% had colonoscopy in the last 10 years, with rates declining after age 70 years. Percentages of those having had a colonoscopy in the last 10 years generally increased by risk level from 38.5% in those with a familial relative risk <1.0 to 47.6% in those with a familial relative risk >3.0. Compared with those with no family history, the odds ratio for being screened according to guidelines was higher for those with one first-degree relative diagnosed with colorectal cancer ≥ 60 years or two affected second-degree relatives (1.54, 95% confidence interval: 1.46-1.61) than those with one affected first-degree relative diagnosed <60 years or ≥2 affected first-degree relatives (1.25, 95% confidence interval: 1.14-1.37). CONCLUSIONS: Compliance with colonoscopy guidelines was higher for those with familial risk but did not correspond with the degree of risk.

Predicting phenotypic severity of uncertain gene variants in the RET proto-oncogene.

Although reported gene variants in the RET oncogene have been directly associated with multiple endocrine neoplasia type 2 and hereditary medullary thyroid carcinoma, other mutations are classified as variants of uncertain significance (VUS) until the associated clinical phenotype is made clear. Currently, some 46 non-synonymous VUS entries exist in curated archives. In the absence of a gold standard method for predicting phenotype outcomes, this follow up study applies feature selected amino acid physical and chemical properties feeding a Bayes classifier to predict disease association of uncertain gene variants into categories of benign and pathogenic. Algorithm performance and VUS predictions were compared to established phylogenetic based mutation prediction algorithms. Curated outcomes and unpublished RET gene variants with known disease association were used to benchmark predictor performance. Reliable classification of RET uncertain gene variants will augment current clinical information of RET mutations and assist in improving prediction algorithms as knowledge increases.

How well does family history predict who will get colorectal cancer? Implications for cancer screening and counseling.

PURPOSE: Using a large, retrospective cohort from the Utah Population Database, we assess how well family history predicts who will acquire colorectal cancer during a 20-year period. METHODS: Individuals were selected between ages 35 and 80 with no prior record of colorectal cancer diagnosis, as of the year 1985. Numbers of colorectal cancer-affected relatives and diagnosis ages were collected. Familial relative risk and absolute risk estimates were calculated. Colorectal cancer diagnoses in the cohort were counted between years 1986 and 2005. Cox regression and Harrell's C were used to measure the discriminatory power of resulting models. RESULTS: A total of 431,153 individuals were included with 5,334 colorectal cancer diagnoses. Familial relative risk ranged from 0.83 to 12.39 and 20-year absolute risk from 0.002 to 0.21. With familial relative risk as the only predictor, Harrell's C = 0.53 and with age only, Harrell's C = 0.66. Familial relative risk combined with age produced a Harrell's C = 0.67. CONCLUSION: Family history by itself is not a strong predictor of exactly who will acquire colorectal cancer within 20 years. However, stratification of risk using absolute risk probabilities may be more helpful in focusing screening on individuals who are more likely to develop the disease.

Using information prescriptions to refer patients with metabolic conditions to the Genetics Home Reference website.

OBJECTIVES: The objectives of this study were to assess the reactions of adult patients and parents of children with metabolic conditions to receipt of an "information prescription" (IP) to visit Genetics Home Reference (GHR), a National Institutes of Health/National Library of Medicine online resource, and evaluate the perceived utility of information found on the site. METHODS: Patients seen at the University of Utah Metabolic Service Clinic were invited to participate in the study and asked to complete an initial survey to gather demographic data and an online survey six weeks later to obtain information about user experience. RESULTS: Fifty-three of 82 individuals completed both surveys, for an overall response rate of 64.6%. Most respondents (88.7%) agreed that receiving the IP was a "good idea," and nearly all used the IP to visit GHR. More than three-quarters (79.6%) agreed that information on GHR supplemented a physician's advice; 60.4% reported an improved understanding of a health condition; and 41.5% either looked for or would consider looking for additional information. Eighty-six percent of respondents were satisfied with the information found on GHR, and 80% would recommend the site. CONCLUSIONS: Use of an IP to direct patients to GHR was well received, and retrieved information was perceived as useful in key areas. The high level of satisfaction with GHR argues for expanded use of the IP approach in this patient population.

Evaluating the informatics for integrating biology and the bedside system for clinical research.

BACKGROUND: Selecting patient cohorts is a critical, iterative, and often time-consuming aspect of studies involving human subjects; informatics tools for helping streamline the process have been identified as important infrastructure components for enabling clinical and translational research. We describe the evaluation of a free and open source cohort selection tool from the Informatics for Integrating Biology and the Bedside (i2b2) group: the i2b2 hive. METHODS: Our evaluation included the usability and functionality of the i2b2 hive using several real world examples of research data requests received electronically at the University of Utah Health Sciences Center between 2006 - 2008. The hive server component and the visual query tool application were evaluated for their suitability as a cohort selection tool on the basis of the types of data elements requested, as well as the effort required to fulfill each research data request using the i2b2 hive alone. RESULTS: We found the i2b2 hive to be suitable for obtaining estimates of cohort sizes and generating research cohorts based on simple inclusion/exclusion criteria, which consisted of about 44% of the clinical research data requests sampled at our institution. Data requests that relied on post-coordinated clinical concepts, aggregate values of clinical findings, or temporal conditions in their inclusion/exclusion criteria could not be fulfilled using the i2b2 hive alone, and required one or more intermediate data steps in the form of pre- or post-processing, modifications to the hive metadata, etc. CONCLUSION: The i2b2 hive was found to be a useful cohort-selection tool for fulfilling common types of requests for research data, and especially in the estimation of initial cohort sizes. For another institution that might want to use the i2b2 hive for clinical research, we recommend that the institution would need to have structured, coded clinical data and metadata available that can be transformed to fit the logical data models of the i2b2 hive, strategies for extracting relevant clinical data from source systems, and the ability to perform substantial pre- and post-processing of these data.

Nanoinformatics: new challenges for biomedical informatics at the nano level.

Over the last decades Nanotechnology has promised to advance science and technology in many areas. Within medicine, Nanomedicine promises to deliver new methods for diagnosis, prognosis and therapy. As the amount of available information is rapidly growing, new Biomedical Informatics approaches have to be developed to satisfy the increasing demand on data and knowledge management. In 2007, a new sub-discipline, already named "Nanoinformatics", was created with support from the US National Science Foundation. In Europe, a project named ACTION-Grid was launched in 2008 with support from the European Commission to analyze the challenges and agenda for developing Nanoinformatics as a discipline related to Nanotechnology, Biomedicine and Informatics. For MIE 2009, members of this consortium proposed a workshop to discuss the scientific and strategic issues associated with this topic. Nanoinformatics aims to create a bridge between Nanomedicine and Information Technology applying computational methods to manage the information created in the nanomedical domain.

Efficiency of CYP2C9 genetic test representation for automated pharmacogenetic decision support.

OBJECTIVES: We investigated the suitability of representing discrete genetic test results in the electronic health record (EHR) as individual single nucleotide polymorphisms (SNPs) and as alleles, using the CYP2C9 gene and its polymorphic states, as part of a pilot study. The purpose of our investigation was to determine the appropriate level of data abstraction when reporting genetic test results in the EHR that would allow meaningful interpretation and clinical decision support based on current knowledge, while retaining sufficient information in order to enable reinterpretation of the results in the context of future discoveries. METHODS: Based on the SNP & allele models, we designed two separate lab panels within the laboratory information system, one containing SNPs and the other containing alleles, built separate rules in the clinical decision support system based on each model, and evaluated the performance of these rules in an EHR simulation environment using real-world scenarios. RESULTS: Although decision-support rules based on allele model required significantly less computational time than rules based on SNP model, no difference was observed on the total time taken to chart medication orders between rules based on these two models. CONCLUSIONS: Both, SNP- and allele-based models, can be used effectively for representing genetic test results in the EHR without impacting clinical decision support systems. While storing and reporting genetic test results as alleles allow for the construction of simpler decision-support rules, and make it easier to present these results to clinicians, SNP-based model can retain a greater amount of information that could be useful for future reinterpretation.

Architecture of a federated query engine for heterogeneous resources.

The Federated Utah Research and Translational Health e-Repository (FURTHeR) is a Utah statewide informatics platform for the new Center for Clinical and Translational Science at the University of Utah. We have been working on one of FURTHeR's key components, a federated query engine for heterogeneous resources, that we believe has the potential to meet some of the fundamental needs of translational science to access and integrate diverse biomedical data and promote discovery of new knowledge. The architecture of the federated query engine for heterogeneous resources is described and demonstrated.

Evaluation of LOINC for representing constitutional cytogenetic test result reports.

Genetic testing is becoming increasingly important to medical practice. Integrating genetics and genomics data into electronic medical records is crucial in translating genetic discoveries into improved patient care. Information technology, especially Clinical Decision Support Systems, holds great potential to help clinical professionals take full advantage of genomic advances in their daily medical practice. However, issues relating to standard terminology and information models for exchanging genetic testing results remain relatively unexplored. This study evaluates whether the current LOINC standard is adequate to represent constitutional cytogenetic test result reports using sample result reports from ARUP Laboratories. The results demonstrate that current standard terminology is insufficient to support the needs of coding cytogenetic test results. The terminology infrastructure must be developed before clinical information systems will be able to handle the high volumes of genetic data expected in the near future.

Utah's statewide informatics platform for translational and clinical science.

The University of Utah has initiated the design and implementation of an innovative data and knowledge management informatics platform for the new Center for Clinical and Translational Science. The main component of the platform is described, along with preliminary project objectives and current status.

Effectiveness of topic-specific infobuttons: a randomized controlled trial.

OBJECTIVE: Infobuttons are decision support tools that provide links within electronic medical record systems to relevant content in online information resources. The aim of infobuttons is to help clinicians promptly meet their information needs. The objective of this study was to determine whether infobutton links that direct to specific content topics ("topic links") are more effective than links that point to general overview content ("nonspecific links"). DESIGN: Randomized controlled trial with a control and an intervention group. Clinicians in the control group had access to nonspecific links, while those in the intervention group had access to topic links. MEASUREMENTS: Infobutton session duration, number of infobutton sessions, session success rate, and the self-reported impact that the infobutton session produced on decision making. RESULTS: The analysis was performed on 90 subjects and 3,729 infobutton sessions. Subjects in the intervention group spent 17.4% less time seeking for information (35.5 seconds vs. 43 seconds, p = 0.008) than those in the control group. Subjects in the intervention group used infobuttons 20.5% (22 sessions vs. 17.5 sessions, p = 0.21) more often than in the control group, but the difference was not significant. The information seeking success rate was equally high in both groups (89.4% control vs. 87.2% intervention, p = 0.99). Subjects reported a high positive clinical impact (i.e., decision enhancement or knowledge update) in 62% of the sessions. Limitations The exclusion of users with a low frequency of infobutton use and the focus on medication-related information needs may limit the generalization of the results. The session outcomes measurement was based on clinicians' self-assessment and therefore prone to bias. CONCLUSION: The results support the hypothesis that topic links are more efficient than nonspecific links regarding the time seeking for information. It is unclear whether the statistical difference demonstrated will result in a clinically significant impact. However, the overall results confirm previous evidence that infobuttons are effective at helping clinicians to answer questions at the point of care and demonstrate a modest incremental change in the efficiency of information delivery for routine users of this tool.

Status of clinical gene sequencing data reporting and associated risks for information loss.

Clinical gene sequencing is growing in importance and cost-effectiveness. In the past two years, the number of genes associated with disease has grown by roughly 25%. Knowledge of genetic variations will soon guide drug selection and dosages, predict risks from toxin exposures, and inform nutritional needs. Despite the significance of sequencing, methods for reporting results are problematic. Frequent use of paper and infrequent use of naming standards impede data exchange and make incorporation into the electronic medical record difficult. Reports often describe only variations found, rather than all data (all patient bases sequenced). Also, reports frequently do not describe reference data used to define variations. These practices create risks for loss of both data and information. Standardized electronic reporting of all data (all bases sequenced and all reference data) and electronic record systems capable of storing these results would both prevent data loss and simplify the preservation of information those data provide.

A model of interprofessional informatics education.

An emphasis on patient safety and an administrative mandate to have information systems in place in most health care agencies in the USA by 2014 has put pressure on nursing informatics programs to increase the number of graduates. At the same time a need for change in health professions education was emphasized at an educational summit sponsored by the Institute of Medicine. Interprofessional education (IPE) will help to provide needed educational reform in informatics and is defined as planned occasions when two or more professions learn from each other and about each other in a structured manner. This paper discusses an evolving interprofessional (IPE) model of informatics education that has been developed at the University of Utah. Because of interprofessional collaboration, faculty, students, and support staff from both the medical and nursing informatics programs moved into a suite on the fifth floor of a state-of-art technology-rich health sciences education building. The co-located space has enabled the informatics programs to increase activities that promote interprofessional education.