Jihad S. Obeid

Procurement of shared data instruments for Research Electronic Data Capture (REDCap)

REDCap (Research Electronic Data Capture) is a web-based software solution and tool set that allows biomedical researchers to create secure online forms for data capture, management and analysis with minimal effort and training. The Shared Data Instrument Library (SDIL) is a relatively new component of REDCap that allows sharing of commonly used data collection instruments for immediate study use by research teams. Objectives of the SDIL project include: (1) facilitating reuse of data dictionaries and reducing duplication of effort; (2) promoting the use of validated data collection instruments, data standards and best practices; and (3) promoting research collaboration and data sharing. Instruments submitted to the library are reviewed by a library oversight committee, with rotating membership from multiple institutions, which ensures quality, relevance and legality of shared instruments. The design allows researchers to download the instruments in a consumable electronic format in the REDCap environment. At the time of this writing, the SDIL contains over 128 data collection instruments. Over 2500 instances of instruments have been downloaded by researchers at multiple institutions. In this paper we describe the library platform, provide detail about experience gained during the first 25months of sharing public domain instruments and provide evidence of impact for the SDIL across the REDCap consortium research community. We postulate that the shared library of instruments reduces the burden of adhering to sound data collection principles while promoting best practices.

An investigation of the efficacy of electronic consenting interfaces of research permissions management system in a hospital setting

PURPOSE Ethical and legal requirements for healthcare providers in the United States, stipulate that patients sign a consent form prior to undergoing medical treatment or participating in a research study. Currently, the majority of the hospitals obtain these consents using paper-based forms, which makes patient preference data cumbersome to store, search and retrieve. To address these issues, Health Sciences of South Carolina (HSSC), a collaborative of academic medical institutions and research universities in South Carolina, is developing an electronic consenting system, the Research Permissions Management System (RPMS). This article reports the findings of a study conducted to investigate the efficacy of the two proposed interfaces for this system - an iPad-based and touchscreen-based by comparing them to the paper-based and Topaz-based systems currently in use. METHODS This study involved 50 participants: 10 hospital admission staff and 40 patients. The four systems were compared with respect to the time taken to complete the consenting process, the number of errors made by the patients, the workload experienced by the hospital staff and the subjective ratings of both patients and staff on post-test questionnaires. RESULTS The results from the empirical study indicated no significant differences in the time taken to complete the tasks. More importantly, the participants found the new systems more usable than the conventional methods with the registration staff experiencing the least workload in the iPad and touchscreen-based conditions and the patients experiencing more privacy and control during the consenting process with the proposed electronic systems. In addition, they indicated better comprehension and awareness of what they were signing using the new interfaces. DISCUSSION The results indicate the two methods proposed for capturing patient consents are at least as effective as the conventional methods, and superior in several important respects. While more research is needed, these findings suggest the viability of cautious adoption of electronic consenting systems, especially because these new systems appear to address the challenge of identifying the participants required for the complex research being conducted as the result of advances in the biomedical sciences.

Development and pilot testing of a video-assisted informed consent process.

The informed consent process for research has come under scrutiny, as consent documents are increasingly long and difficult to understand. Innovations are needed to improve comprehension in order to make the consent process truly informed. We report on the development and pilot testing of video clips that could be used during the consent process to better explain research procedures to potential participants. Based on input from researchers and community partners, 15 videos of common research procedures/concepts were produced. The utility of the videos was then tested by embedding them in mock-informed consent documents that were presented via an online electronic consent system designed for delivery via iPad. Three mock consents were developed, each containing five videos. All participants (n = 61) read both a paper version and the video-assisted iPad version of the same mock consent and were randomized to which format they reviewed first. Participants were given a competency quiz that posed specific questions about the information in the consent after reviewing the first consent document to which they were exposed. Most participants (78.7%) preferred the video-assisted format compared to paper (12.9%). Nearly all (96.7%) reported that the videos improved their understanding of the procedures described in the consent document; however, the comprehension of material did not significantly differ by consent format. Results suggest videos may be helpful in providing participants with information about study procedures in a way that is easy to understand. Additional testing of video consents for complex protocols and with subjects of lower literacy is warranted.

Managing clinical research permissions electronically: A novel approach to enhancing recruitment and managing consents

Background One mechanism to increase participation in research is to solicit potential research participants’ general willingness to be recruited into clinical trials. Such research permissions and consents typically are collected on paper upon patient registration. We describe a novel method of capturing this information electronically. Purpose The objective is to enable the collection of research permissions and informed consent data electronically to permit tracking of potential research participants’ interest in current and future research involvement and to provide a foundation for facilitating the research workflow. Methods The project involved systematic analysis focused on key areas, including existing business practices, registration processes, and permission collection workflows, and ascertaining best practices for presenting consent information to users via tablet technology and capturing permissions data. Analysis was followed by an iterative software development cycle with feedback from subject matter experts and users. Results An initial version of the software was piloted at one institution in South Carolina for a period of 1 year, during which consents and permission were collected during 2524 registrations of patients. The captured research permission data were transmitted to a clinical data warehouse. The software was later released as an open-source package that can be adopted for use by other institutions. Limitations There are significant ethical, legal, and informatics challenges that must be addressed at an institution to deploy such a system. We have not yet assessed the long-term impact of the system on recruitment of patients to clinical trials. Conclusions We propose that by improving the ability to track willing potential research participants, we can improve recruitment into clinical trials and, in the process, improve patient education by introducing multimedia to informed consent documents.

Word2Vec inversion and traditional text classifiers for phenotyping lupus

BackgroundIdentifying patients with certain clinical criteria based on manual chart review of doctors’ notes is a daunting task given the massive amounts of text notes in the electronic health records (EHR). This task can be automated using text classifiers based on Natural Language Processing (NLP) techniques along with pattern recognition machine learning (ML) algorithms. The aim of this research is to evaluate the performance of traditional classifiers for identifying patients with Systemic Lupus Erythematosus (SLE) in comparison with a newer Bayesian word vector method.MethodsWe obtained clinical notes for patients with SLE diagnosis along with controls from the Rheumatology Clinic (662 total patients). Sparse bag-of-words (BOWs) and Unified Medical Language System (UMLS) Concept Unique Identifiers (CUIs) matrices were produced using NLP pipelines. These matrices were subjected to several different NLP classifiers: neural networks, random forests, naïve Bayes, support vector machines, and Word2Vec inversion, a Bayesian inversion method. Performance was measured by calculating accuracy and area under the Receiver Operating Characteristic (ROC) curve (AUC) of a cross-validated (CV) set and a separate testing set.ResultsWe calculated the accuracy of the ICD-9 billing codes as a baseline to be 90.00% with an AUC of 0.900, the shallow neural network with CUIs to be 92.10% with an AUC of 0.970, the random forest with BOWs to be 95.25% with an AUC of 0.994, the random forest with CUIs to be 95.00% with an AUC of 0.979, and the Word2Vec inversion to be 90.03% with an AUC of 0.905.ConclusionsOur results suggest that a shallow neural network with CUIs and random forests with both CUIs and BOWs are the best classifiers for this lupus phenotyping task. The Word2Vec inversion method failed to significantly beat the ICD-9 code classification, but yielded promising results. This method does not require explicit features and is more adaptable to non-binary classification tasks. The Word2Vec inversion is hypothesized to become more powerful with access to more data. Therefore, currently, the shallow neural networks and random forests are the desirable classifiers.

A Comprehensive View of Frequent Emergency Department Users Based on Data from a Regional HIE.

Objectives A small but significant number of patients make frequent emergency department (ED) visits to multiple EDs within a region. We have a unique health information exchange (HIE) that includes every ED encounter in all hospital systems in our region. Using our HIE we were able to characterize all frequent ED users in our region, regardless of hospital visited or payer class. The objective of our study was to use data from an HIE to characterize patients in a region who are frequent ED users (FEDUs). Methods We constructed a database from a cohort of adult patients (18 years old or older) with information in a regional HIE for a 1-year period beginning in April 2012. Patients were defined as FEDUs (those who made four or more visits during the study period) and non-FEDUs (those who made fewer than four ED visits during the study period). Predictor variables included age, race, sex, payer class, county of residence, and International Classification of Diseases, Ninth Revision codes. Bivariate (&khgr;2) and multivariate (logistic regression) analyses were performed to determine associations between predictor variables and the outcome of being a FEDU. Results The database contained 127,672 patients, 12,293 (9.6%) of whom were FEDUs. Logistic regression showed the following patient characteristics to be significantly associated with the outcome of being a FEDU: age 35 to 44 years; African American race; Medicaid, Medicare, and dual-pay payer class; and International Classification of Diseases, Ninth Revision codes 630 to 679 (complications of pregnancy, childbirth, and puerperium), 780 to 799 (ill-defined conditions), 280 to 289 (diseases of the blood), 290–319 (mental disorders), 680 to 709 (diseases of the skin and subcutaneous tissue), 710 to 739 (musculoskeletal and connective tissue disease), 460 to 519 (respiratory disease), and 520 to 579 (digestive disease). No significant differences were noted between men and women. Conclusions Data from an HIE can be used to describe all of the patients within a region who are FEDUs, regardless of the hospital system they visited. This information can be used to focus care coordination efforts and link appropriate patients to a medical home. Future studies can be designed to learn the reasons why patients become FEDUs, and interventions can be developed to address deficiencies in health care that result in frequent ED visits.

Teleconsent: A Novel Approach to Obtain Informed Consent for Research.

Lack of recruitment of qualified research participants continues to be a significant bottleneck in clinical trials, often resulting in costly time extensions, underpowered results, and in some cases early termination. Some of the reasons for suboptimal recruitment include laborious consent processes and access to participants at remote locations. While new electronic consents technologies (eConsent) help overcome challenges related to readability and consent management, they do not adequately address challenges related to remote access. To address this, we have developed an innovative solution called “teleconsent”, which embeds the informed consent process into a telemedicine session. Teleconsent allows a researcher to remotely video conference with a prospective research participant, display and interactively guide participants in real-time through a consent form. When finished, the researcher and participant can electronically sign the consent form and print or download the signed document for archiving. This process can eliminate challenges related to travel and management of personnel at remote sites. Teleconsent has been successfully implemented in several clinical trials. Teleconsent can improve research recruitment by reducing the barriers related to informed consent, while preserving human interaction.

A biomedical research permissions ontology: cognitive and knowledge representation considerations

In designing a comprehensive mechanism for managing informed consents and permissions for biomedical research involving human participants, a significant effort is dedicated to the development of standardized classification of these consents and permissions. In this paper, we describe the considerations and implications of this effort that should be addressed during the development of a Biomedical Research Permissions Ontology (RPO). It is hoped that this standardization will allow disparate research institutions to pool research data and associated consents and permissions in order to facilitate collaborative translational research projects across multiple institutions and subsequent new breakthroughs in medicine while providing: 1) essential built in protections for privacy and confidentiality of research participants and 2) a mechanism for insuring that researchers adhere to patients intent whether to participate in research or not.

A population-based approach for implementing change from opt-out to opt-in research permissions

Due to recently proposed changes in the Common Rule regarding the collection of research preferences, there is an increased need for efficient methods to document opt-in research preferences at a population level. Previously, our institution developed an opt-out paper-based workflow that could not be utilized for research in a scalable fashion. This project was designed to demonstrate the feasibility of implementing an electronic health record (EHR)-based active opt-in research preferences program. The first phase of implementation required creating and disseminating a patient questionnaire through the EHR portal to populate discreet fields within the EHR indicating patients’ preferences for future research study contact (contact) and their willingness to allow anonymised use of excess tissue and fluid specimens (biobank). In the second phase, the questionnaire was presented within a clinic nurse intake workflow in an obstetrical clinic. These permissions were tabulated in registries for use by investigators for feasibility studies and recruitment. The registry was also used for research patient contact management using a new EHR encounter type to differentiate research from clinical encounters. The research permissions questionnaire was sent to 59,670 patients via the EHR portal. Within four months, 21,814 responses (75% willing to participate in biobanking, and 72% willing to be contacted for future research) were received. Each response was recorded within a patient portal encounter to enable longitudinal analysis of responses. We obtained a significantly lower positive response from the 264 females who completed the questionnaire in the obstetrical clinic (55% volunteers for biobank and 52% for contact). We demonstrate that it is possible to establish a research permissions registry using the EHR portal and clinic-based workflows. This patient-centric, population-based, opt-in approach documents preferences in the EHR, allowing linkage of these preferences to health record information.

Scientific retreats with ‘speed dating’: networking to stimulate new interdisciplinary translational research collaborations and team science

To stimulate the formation of new interdisciplinary translational research teams and innovative pilot projects, the South Carolina Clinical and Translational Research (SCTR) Institute (South Carolina Clinical and Translational Science Award, CTSA) initiated biannual scientific retreats with ‘speed dating’ networking sessions. Retreat themes were prioritized based on the following criteria; cross-cutting topic, unmet medical need, generation of novel technologies and methodologies. Each retreat begins with an external keynote speaker followed by a series of brief research presentations by local researchers focused on the retreat theme, articulating potential areas for new collaborations. After each session of presentations, there is a 30 min scientific ‘speed dating’ period during which the presenters meet with interested attendees to exchange ideas and discuss collaborations. Retreat attendees are eligible to compete for pilot project funds on the topic of the retreat theme. The 10 retreats held have had a total of 1004 participants, resulted in 61 pilot projects with new interdisciplinary teams, and 14 funded projects. The retreat format has been a successful mechanism to stimulate novel interdisciplinary research teams and innovative translational research projects. Future retreats will continue to target topics of cross-cutting importance to biomedical and public health research.