Papers by Charles Tirrell
Background: Multiple factors are causing an increase in the need for both local and multi-site co... more Background: Multiple factors are causing an increase in the need for both local and multi-site collaboration in autism research (OARC/IACC, 2012). This increased need, while arguably beneficial in a still-emerging research domain, such as autism, often produces significant unanticipated problems for collaborators: (1) They typically lack access to research informatics expertise, resulting in homegrown re-creations of appropriate (read: HIPAA-compliant) data access rules; and (2) their usual “data” tools (e.g., Excel, SPSS, R, Access) are not designed to facilitate the enforcement of these rules. Objectives: Suggest a relational data model and set of cascading data access rules for creating a shareable data repository capable of complying with all relevant sections of HIPAA’s Administrative and Technical Safeguards using a newly available database tool. Methods: We interviewed investigators, clinicians, and research staff at the Marcus Autism Center and Emory University about their p...
Background: Making decisions about scientific direction, such as funding of research programs, re... more Background: Making decisions about scientific direction, such as funding of research programs, requires a variety of information sources. Science officers require knowledge of multiple internal sources about grants, as well as multiple external sources about grants and publications. Access to a wide range of systems can increase costs and reduce the speed of decisions. Different kinds of tasks (use cases) often result in very different software solutions, such as customized “dashboards”. These attempts usually fail due to long delivery times, measured in months or years. By the time the dashboard is delivered, decisions and data have changed. Our approach is to produce a platform for rapidly configuring decision support dashboards that can be delivered in a matter of days or hours. Objectives: Our goal was to produce a decision support platform with the following capabilities: 1. Build a typical dashboard in hours, with more complex dashboards taking a few days. 2. Build most dashbo...
Background: Current EDC systems boast secure and user-friendly online survey management and data ... more Background: Current EDC systems boast secure and user-friendly online survey management and data monitoring. However, these systems often fail to meet the difficult integration requirements of multidisciplinary and collaborative research projects. To meet these requirements for an autism research project, we migrated and re-packaged our own proprietary EDC system into an open-source, web-based integrated EDC system called RexAcquire. Methods: We (1) defined the data collection needs of a large-scale autism research project; (2) developed a new code base; (3) obtained an open-source license; (4) made the code freely available through BitBucket; (5) converted the pre-existing configuration, user and assessment data into the new OS-compatible format; and (6) evaluated the platform. Results: Users reported a need for a self-administered EDC, where patients could directly submit answers to common research forms. Interactive user configurability, reusability of study instruments, sophisti...
Background: Public health administrators are increasingly required to make decisions about scient... more Background: Public health administrators are increasingly required to make decisions about scientific direction including funding of research and wellness programs. Administrators require knowledge of multiple internal and external grants and publications sources. However, access to a wide range of systems can increase costs and reduce the speed of decisions. Attempts to create dashboards to summarize relevant information usually fail. By the time the dashboard is delivered, decisions and data have changed. We produced a platform for rapidly configuring decision support dashboards that can be delivered in days or hours. Methods: We designed a data warehouse with an extensible data model for storing a wide variety of data about scientific research, and defined lightweight methods for extracting and loading data from internal and external sources. Next, we added a robust, web-native data-access layer (HTSQL), a rapid web-application development framework (HTRAF), and, finally, a visua...
Background: Understanding the scope of research activities in a scientific community requires lev... more Background: Understanding the scope of research activities in a scientific community requires leveraging data from multiple public and private sources. However, data from different sources, such as PubMed and NIH RePORTER, may be difficult to link because data are organized differently, are of inconsistent or poor quality or lack appropriate identifiers. The standard solution to these challenges is to use an Extract, Transform and Load process (ETL), which pulls the data out of the original data source, changes its structure and content, then stores it in the target database. However, ETL processes tend to be brittle, expensive, and difficult to run. We needed a data-integration solution that would remain flexible and inexpensive, and would support an expanding list of ad hoc data sources to support decisions about scientific funding. Objectives: We set out to build a process that could inexpensively integrate data about autism research projects from multiple sources into a unified ...
Background: The need for effective centralized management of biomedical and behavioral research d... more Background: The need for effective centralized management of biomedical and behavioral research data has expanded dramatically in the past decade. Interdisciplinary, longitudinal, and multi-center research benefits from secure, flexible data management platforms. Current solutions are either insufficiently flexible or too expensive. Our team has developed an integrated data management platform used at over a dozen leading autism research centers over the last 6 years. In late 2011, we began to package this platform, originally developed as a mix of proprietary and open-source components, as an open-source project with the goal of making it freely available to all autism research centers and programs. Methods: We open-sourced RexDB in four phases:(1) Working with stakeholders to define requirements for an integrated data management system to support autism research. (2) Packaging existing components into a modular, open-source RexDB system. (3) Evaluation of the new system at four re...
Visual Information Processing XIV, 2005
The primary goal of this research was to provide image processing support to aid in the identific... more The primary goal of this research was to provide image processing support to aid in the identification of those subjects most affected by bone loss when exposed to weightlessness and provide insight into the causes for large variability. Past research has demonstrated that genetically distinct strains of mice exhibit different degrees of bone loss when subjected to simulated weightlessness. Bone loss is quantified by in vivo computed tomography (CT) imaging. The first step in evaluating bone density is to segment gray scale images into separate regions of bone and background. Two of the most common methods for implementing image segmentation are thresholding and edge detection. Thresholding is generally considered the simplest segmentation process which can be obtained by having a user visually select a threshold using a sliding scale. This is a highly subjective process with great potential for variation from one observer to another. One way to reduce inter-observer variability is to have several users independently set the threshold and average their results but this is a very time consuming process. A better approach is to apply an objective adaptive technique such as the Riddler / Calvard method. In our study we have concluded that thresholding was better than edge detection and pre-processing these images with an iterative deconvolution algorithm prior to adaptive thresholding yields superior visualization when compared with images that have not been pre-processed or images that have been pre-processed with a filter.
Summary: Disease- and procedure-specific registries are powerful tools for the improvement of lon... more Summary: Disease- and procedure-specific registries are powerful tools for the improvement of long-term patient care. Unfortunately, registries are typically too expensive for smaller practices and organizations to develop and maintain. We describe an affordable and scalable alternative: an open source solution that can integrate institutional (EHR) and primary research data. Introduction and Background: Medical registries are growing both in importance and value with rapid increases in (a) the amount of data on each patient and procedure, (b) the value of tracking outcomes, and (c) the desirability of sharing information between health professionals. Registries enable researchers to track individual patient and outcomes and evaluate cohort-level statistics that guide the improvement of patient care. Prominent examples of recent registry systems include the Intelligent Research in Sight (IRIS) Registry™ [1] and the National Cardiovascular Data Registry® (NCDR) [2]. Two difficulties ...
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Papers by Charles Tirrell