Peter Tarczy-Hornoch

Incorporating ideas from computer-supported cooperative work

Many information systems have failed when deployed into complex health-care settings. We believe that one cause of these failures is the difficulty in systematically accounting for the collaborative and exception-filled nature of medical work. In this methodological review paper, we highlight research from the field of computer-supported cooperative work (CSCW) that could help biomedical informaticists recognize and design around the kinds of challenges that lead to unanticipated breakdowns and eventual abandonment of their systems. The field of CSCW studies how people collaborate with each other and the role that technology plays in this collaboration for a wide variety of organizational settings. Thus, biomedical informaticists could benefit from the lessons learned by CSCW researchers. In this paper, we provide a focused review of CSCW methods and ideas-we review aspects of the field that could be applied to improve the design and deployment of medical information systems. To make our discussion concrete, we use electronic medical record systems as an example medical information system, and present three specific principles from CSCW: accounting for incentive structures, understanding workflow, and incorporating awareness.

Methodological Review: Data integration and genomic medicine

Genomic medicine aims to revolutionize health care by applying our growing understanding of the molecular basis of disease. Research in this arena is data intensive, which means data sets are large and highly heterogeneous. To create knowledge from data, researchers must integrate these large and diverse data sets. This presents daunting informatic challenges such as representation of data that is suitable for computational inference (knowledge representation), and linking heterogeneous data sets (data integration). Fortunately, many of these challenges can be classified as data integration problems, and technologies exist in the area of data integration that may be applied to these challenges. In this paper, we discuss the opportunities of genomic medicine as well as identify the informatics challenges in this domain. We also review concepts and methodologies in the field of data integration. These data integration concepts and methodologies are then aligned with informatics challenges in genomic medicine and presented as potential solutions. We conclude this paper with challenges still not addressed in genomic medicine and gaps that remain in data integration research to facilitate genomic medicine.

Amniotic fluid tumor necrosis factor-α and the risk of respiratory distress syndrome among preterm infants

OBJECTIVE We examined the effect of exposure to amniotic fluid infection and cytokines on the pulmonary outcome of preterm infants. STUDY DESIGN A cohort of 136 preterm infants born to women in preterm labor had amniotic fluid cultures and tumor necrosis factor-alpha assays performed. Amniotic fluid was collected by transabdominal amniocentesis. Outcome measures included respiratory distress syndrome and length of oxygen and ventilator support. Logistic regression and Cox proportional hazards regression adjusted for birth weight and other confounders. RESULTS Respiratory distress syndrome developed in 67 (49%) of 136 infants. Elevated amniotic fluid tumor necrosis factor-alpha levels and amniotic fluid infection were significantly associated with respiratory distress syndrome. This association persisted after adjustment for birth weight. Infants exposed to tumor necrosis factor-alpha remained on supplemental oxygen and assisted ventilation longer and had longer hospital stays compared with nonexposed infants. CONCLUSION Prenatal exposure to tumor necrosis factor-alpha may be a risk factor for respiratory distress syndrome and its complications.

Translational bioinformatics: linking knowledge across biological and clinical realms

Nearly a decade since the completion of the first draft of the human genome, the biomedical community is positioned to usher in a new era of scientific inquiry that links fundamental biological insights with clinical knowledge. Accordingly, holistic approaches are needed to develop and assess hypotheses that incorporate genotypic, phenotypic, and environmental knowledge. This perspective presents translational bioinformatics as a discipline that builds on the successes of bioinformatics and health informatics for the study of complex diseases. The early successes of translational bioinformatics are indicative of the potential to achieve the promise of the Human Genome Project for gaining deeper insights to the genetic underpinnings of disease and progress toward the development of a new generation of therapies.

Feasibility of incorporating genomic knowledge into electronic medical records for pharmacogenomic clinical decision support

In pursuing personalized medicine, pharmacogenomic (PGx) knowledge may help guide prescribing drugs based on a person’s genotype. Here we evaluate the feasibility of incorporating PGx knowledge, combined with clinical data, to support clinical decision-making by: 1) analyzing clinically relevant knowledge contained in PGx knowledge resources; 2) evaluating the feasibility of a rule-based framework to support formal representation of clinically relevant knowledge contained in PGx knowledge resources; and, 3) evaluating the ability of an electronic medical record/electronic health record (EMR/EHR) to provide computable forms of clinical data needed for PGx clinical decision support. Findings suggest that the PharmGKB is a good source for PGx knowledge to supplement information contained in FDA approved drug labels. Furthermore, we found that with supporting knowledge (e.g. IF age <18 THEN patient is a child), sufficient clinical data exists in University of Washington’s EMR systems to support 50% of PGx knowledge contained in drug labels that could be expressed as rules.

People and Organizational Issues in Research Systems Implementation

Knowledge about people and organizational issues pertinent to implementation and maintenance of clinical systems has grown steadily over the past fifteen years. Less is known about implementation of systems used for clinical and biomedical research. In conjunction with current National Institutes of Health Roadmap efforts that promote translational research, these issues should now be identified and addressed. During the 2007 American College of Medical Informatics Symposium, members discussed behavioral aspects of translational informatics. This article summarizes that discussion, which covered organizational issues, implications of how knowledge about clinical systems implementation can inform research systems implementation, and those issues unique to each kind of system.

Opportunities for genomic clinical decision support interventions

The development and availability of genomic applications for use in clinical care is accelerating rapidly. the routine use of genomic information, however, is beyond most health-care providers’ formal training, and the challenges of understanding and interpreting genomic data are compounded by the demands of clinical practice. nearly all physicians, for example, agree that genetic variations may influence drug response, but only a small fraction feel adequately informed about pharmacogenomic testing.1 Clinical decision support (CDS) embedded into clinical information systems, such as the electronic health record (EHR) and the personal health record (PHR), is recognized as being necessary to facilitate the appropriate use of genomic applications.2–4 CDS provides clinical knowledge and patient-specific information, filtered or presented at particular times to enhance clinical care.5 CDS solutions can assist clinical-care providers with personalizing care and can incorporate the preferences of health-care consumers. EHRs and PHRs theoretically may support access to and storage of genetic data. These systems may also support data exchange between repositories and enable CDS embedment and linkage. The use of EHRs and PHRs in this manner depends on characteristics of the underlying health information technology (IT) infrastructure. This article seeks to provide a common ground for discussing CDS for genetic testing and for data access processes among heterogeneous health IT infrastructures. There are many lessons learned from more than five decades of experience with CDS that can be applied to CDS implementation in the era of genomic data. Indeed, existing CDS technologies already play a role in supporting genetic testing and data access processes. In the following sections, we provide an overview of existing frameworks for local evaluation of health IT infrastructures for CDS, processes for genetic testing and data access, and the rationale behind the Electronic Medical Records and Genomics (eMERGE) Network’s6 work on establishing a common ground for discussing CDS solutions among heterogeneous IT infrastructures. We also provide examples from eMERGE to illustrate that we can characterize genomic CDS using frameworks from the pregenomic CDS era, and outline lessons learned from implementing pregenomic CDS that can account for variation in health IT infrastructure. Finally, we propose a framework to describe opportunities for genomic CDS that can support provider- and consumer-initiated genetic testing and data access processes. The work in this article is complementary to that of the Clinical Sequence Exploratory Research Electronic Records Working Group, also in this special issue.7 The Working Group’s manuscript surveys the six current Clinical Sequence Exploratory Research sites on the processes used for variant annotation, curation, report generation, and integration into the EHR, in order to determine commonalities, determine gaps, and to suggest future directions. This article takes a more top–down approach to system desiderata.

A survey of informatics approaches to whole-exome and whole-genome clinical reporting in the electronic health record

Purpose:Genome-scale clinical sequencing is being adopted more broadly in medical practice. The National Institutes of Health developed the Clinical Sequencing Exploratory Research (CSER) program to guide implementation and dissemination of best practices for the integration of sequencing into clinical care. This study describes and compares the state of the art of incorporating whole-exome and whole-genome sequencing results into the electronic health record, including approaches to decision support across the six current CSER sites.Methods:The CSER Medical Record Working Group collaboratively developed and completed an in-depth survey to assess the communication of genome-scale data into the electronic health record. We summarized commonalities and divergent approaches.Results:Despite common sequencing platform (Illumina) adoptions, there is a great diversity of approaches to annotation tools and workflow, as well as to report generation. At all sites, reports are human-readable structured documents available as passive decision support in the electronic health record. Active decision support is in early implementation at two sites.Conclusion:The parallel efforts across CSER sites in the creation of systems for report generation and integration of reports into the electronic health record, as well as the lack of standardized approaches to interfacing with variant databases to create active clinical decision support, create opportunities for cross-site and vendor collaborations.Genet Med 15 10, 824–832.Genetics in Medicine (2013); 15 10, 824–832. doi:10.1038/gim.2013.120

Incorporating collaboratory concepts into informatics in support of translational interdisciplinary biomedical research

Due to its complex nature, modern biomedical research has become increasingly interdisciplinary and collaborative in nature. Although a necessity, interdisciplinary biomedical collaboration is difficult. There is, however, a growing body of literature on the study and fostering of collaboration in fields such as computer supported cooperative work (CSCW) and information science (IS). These studies of collaboration provide insight into how to potentially alleviate the difficulties of interdisciplinary collaborative research. We, therefore, undertook a cross cutting study of science and engineering collaboratories to identify emergent themes. We review many relevant collaboratory concepts: (a) general collaboratory concepts across many domains: communication, common workspace and coordination, and data sharing and management, (b) specific collaboratory concepts of particular biomedical relevance: data integration and analysis, security structure, metadata and data provenance, and interoperability and data standards, (c) environmental factors that support collaboratories: administrative and management structure, technical support, and available funding as critical environmental factors, and (d) future considerations for biomedical collaboration: appropriate training and long-term planning. In our opinion, the collaboratory concepts we discuss can guide planning and design of future collaborative infrastructure by biomedical informatics researchers to alleviate some of the difficulties of interdisciplinary biomedical collaboration.

On the persistence of supplementary resources in biomedical publications

BackgroundProviding for long-term and consistent public access to scientific data is a growing concern in biomedical research. One aspect of this problem can be demonstrated by evaluating the persistence of supplementary data associated with published biomedical papers.MethodsWe manually evaluated 655 supplementary data links extracted from PubMed abstracts published 1998–2005 (Method 1) as well as a further focused subset of 162 full-text manuscripts published within three representative high-impact biomedical journals between September and December 2004 (Method 2).ResultsFor Method 1 we found that since 2001, only 71 – 92% of supplementary data were still accessible via the links provided, with 93% of these inaccessible links occurring where supplementary data was not stored with the publishing journal. Of the manuscripts evaluated in Method 2, we found that only 83% of these links were available approximately a year after publication, with 55% of these inaccessible links were at locations outside the journal of publication.ConclusionWe conclude that if supplemental data is required to support the publication, journals policies must take-on the responsibility to accept and store such data or require that it be maintained with a credible independent institution or under the terms of a strategic data storage plan specified by the authors. We further recommend that publishers provide automated systems to ensure that supplementary links remain persistent, and that granting bodies such as the NIH develop policies and funding mechanisms to maintain long-term persistent access to these data.