The BIGDATA Methodologic Core collaborates with faculty, fellows, and students through one-on-one consultations to methodologic rigor in ongoing rheumatic and musculoskeletal diseases (RMDs) research. Our team also offers assistance with  data analysis, graph development, results interpretation, and manuscript writing. We offer One-on-One Biostatistics and Methodology  Consultation via weekly office hours or by Appointment.  Please contact (recommend an e-mail to someone in the Administrative Core) to arrange a collaborative meeting.

Through the newly proposed biweekly Design and Analysis Studios (DAS), the Methodologic Core in conjunction with our Data Capture and Integration (DCI) Core will meet with the CCCR research base investigators to implement existing/new Data Capture and Integration approaches, design real time data management approaches, implement data visualization and analysis approaches, as well as facilitate the design and implementation of future BIGDATA supported research projects  including NIH (R01, R21, K, etc.), NSF, and DOD, as well as other extramural and intramural funding opportunities.  Please contact us HERE, to schedule a Design and Analysis Studio.

The proposed topics that the BIGDATA Methodologic Core focus on cutting edge approaches and software. The proposed courses will mainly focus on the application of data capture, data integration, and data analysis focusing on RA and other RMDs.

Among the proposed topics for upcoming mini-courses are:

• data visualization using software tools/languages (e.g. Tableau, Python, Datawrapper); b) utilization of DCI developed platforms (Kaizen, READY, StudyBuddy App, UAB SkinSelfie, UAB Patient Reported Outcome software),

• cohort identification and integration with the UAB Cerner Millenium® EHR,

• a practical guide to unstructured data and natural language processing;

• machine learning and other data-driven analytic methods ( K-nearest neighbor, Quadratic Discrimination Analysis, K-fold cross-validation, unsupervised learning methods, support vector machines, random forests and bagging, deep learning)

• use of natural language processing pipelines for unstructured data, i2b2 queries,

• single cell sequencing, ‘omics’ data integration,

• novel clinical trial designs. Content for these courses and other seminars will be created jointly with the DCI Core, and will be administratively overseen by the Administrative Core.

We offer multiple venues for BIGDATA support including face-to-face (office hours, consultations) and self-taught (BIGDATA-related videos on our CCTS YouTube channel and the R2T game on our Kaizen learning platform).

Bring us your statistical and methodological questions about research projects, manuscripts in progress, responses to peer reviewers, and data management concerns. All are welcome! Currently, drop-in clinics are by virtual meeting only. 

We also offer appointments for one-on-one study design consultations. A team of methodologists, including experts in epidemiology, biostatistics, and statistical genetics, is available to collaborate in the design of pilot and feasibility proposals as well as in their review. If other methodological expertise is required in the project design, we will recruit that expertise on your behalf.

Our popular R2T game, built on a Kaizen web-based platform developed members of the BIGDATA DCI Core, helps investigators meet an NIH policy requiring formal training in rigor, reproducibility, and transparency (R2T). Kaizen has been successfully used by the UAB Schools of Medicine, Nursing, Dentistry, and Public Health to enhance learner engagement and increase retention. R2T gamers can play alone or compete on teams. Learn more

Help us spread the word about Kaizen by downloading our flyer.

Auburn University: Investigators at Auburn University conduct ground-breaking research in the areas of digital health, medical decision making, patient preference elicitation, and implementation science. This expertise and related resources are available to researchers seeking collaboration and consultation to advance projects in these areas of inquiry.

Dr. Chris Loughnane is available for consultation, project planning, and support for digital work. His research interests include haptic media studies, digital humanities, and exploring embodiment and immersive multimodalities through virtual reality (VR) and augmented reality (AR) technologies.

Gary Hawkins is a technology specialist with extensive experience in 3D computer graphics and 3D printing. He has been involved in creating VR scenarios most recently and has been creating models for 3D printing for a decade. Extended reality, electronics, microcomputing, Internet of Things (IoT,) artificial intelligence (AI) and machine learning (ML) are areas that he is currently researching. His skills can be adapted for medical research as needed.

Dr. Kimberly Garza is a health behavior scientist with expertise in value of the future, risk communication, and judgement and decision-making. She has conducted intervention studies that leverage incentives for health behavior change and has used innovative technologies, including VR, to influence perceived risk of chronic disease.

Dr. Surachat Ngorsuraches’s research area is patient-centered value assessment. Primarily, he uses discrete choice experiments (DCE) to determine patients’ preferences and willingness-to-pay for prescription drugs and healthcare services.

Dr. Natalie Hohmann is a health services researcher with expertise in decision science. Her research goal is to develop point-of-care tools that help patients, family caregivers, and providers make better healthcare decisions by improving risk communication, shared decision-making, and quality of care. Her research portfolio focuses on patient-centered studies investigating social and behavioral aspects of health, including chronic disease self-management, cancer treatment preferences, and dementia care for older adults.

The goal of Dr. Salisa Westrick’s lab is to improve the quality of health care and patient outcomes by promoting the uptake of evidence-base innovations into practice. Using implementation science principles, she has studied the adoption, implementation and evaluation of various types of healthcare innovations, including pharmacy-based immunization services, medication therapy management services and naloxone dispensing services.

PRO Software, accesses the MAS API instrument library to facilitate the collection of patient-reported data at the point of care. The highly flexible PRO Software has been adapted to capture data in multiple care settings, including HIV, palliative, viral hepatitis, social work and pediatric spinal bifida clinics, among others. Patients typically report preference for computerized screening over human interviews for sensitive subjects such as sexual function, drug use, suicidal thoughts, etc. In addition to using our MAS API to support the capture of sensitive patient data, PRO Software can also send alerts (e.g., automatically pages clinic personnel in charge of response) to pre-determined team members in response to patient reported findings that can be used to trigger appropriate clinical responses (e.g., reported suicidal ideation, intimate partner violence, etc.), or to identify those meeting self-reported study enrollment criteria. With a successful track record spanning many outpatient clinical settings at UAB, the PRO Software powered by our MAS API can be adapted to facilitate NIAMS research.

Kaizen, Our popular R2T game, built on a Kaizen web-based platform developed members of the BIGDATA DCI Core, helps investigators meet an NIH policy requiring formal training in rigor, reproducibility, and transparency (R2T). Kaizen has been successfully used by the UAB Schools of Medicine, Nursing, Dentistry, and Public Health to enhance learner engagement and increase retention. R2T gamers can play alone or compete on teams.  Kaizen software platform consists of a player app and an educator game manager toolset to build games. This platform uses principles of gamification to enhance learner participation, longitudinal engagement and knowledge retention. We have successfully used Kaizen in diverse settings, including graduate medical education (Internal Medicine, Otorhinolaryngology, etc.), undergraduate and graduate nursing education (over 6 courses currently use Kaizen in our School of Nursing), training for translational science principles for the CTSA consortium, patient education for chronic disease management and assessment of competency-based educational programs. Kaizen uses a mixture of intrinsic (e.g., self-efficacy, personal challenge, socialization, etc.) and extrinsic motivators (e.g., achievements – points/levels/badges, reputation – leaderboard position, etc.) to engage learners in multiple-choice question-based knowledge competitions.

REDCap (Research Electronic Data Capture) is a secure, web application designed to support data capture for research studies, providing user-friendly web-based case report forms, real-time data entry validation (e.g. for data types and range checks), audit trails and a de-identified data export mechanism to common statistical packages (SPSS, SAS, Stata, R/S-Plus). REDCap also provides a powerful tool for building and managing online surveys. The research team can create and design surveys in a web browser and engage potential respondents using various notification methods. REDCap data collection projects rely on a thorough study-specific data dictionary defined in an iterative self-documenting process by all research team members with planning assistance from the system owner. The iterative development and testing process result in a well-planned data collection strategy for individual studies. REDCap provides a secure, web-based application that is flexible enough to be used for a variety of types of research, provides an intuitive interface for users to enter data and have real-time validation rules at the time of entry. The system was developed at Vanderbilt University but is now part of an international and multi-institutional consortium, which includes The University of Alabama at Birmingham (UAB).

MyCap makes it easy for researchers to capture participant/patient-reported outcomes using mobile devices. MyCap leverages REDCap, ResearchKit, and ResearchStack to capture participant/patient-reported outcomes via mobile devices. REDCap is used to define tasks/instruments/surveys to be completed by participants. MyCap translates REDCap task metadata into a structure compatible with ResearchKit and ResearchStack. When a project participant completes a task, MyCap converts the results into a format compatible with REDCap before synchronizing back to the REDCap project.