Publications

Scholarly Journals--Published

  • Tabisula, B., & Uwaoma, C. (2022, July). The Need for an Adaptive Sociotechnical Model for Managing Mental Health in a Pandemic. In 2022 IEEE International Conference on Digital Health (ICDH) (pp. 66-68). IEEE. Abstract: Many people experienced an increase in mental health distress due to the isolation requirements arising from the COVID-19 pandemic. The pandemic and the resulting isolation protocols to control the spread of the virus no doubt, sparked researchers' interest in seeking solutions to address the impact on people's mental health in different situations. One of such solutions is the use of technologies to cope with mental health challenges. Though a plethora of technology exists for communication and socialization with several others proposed to deal with mental health breakdown during the pandemic, there is no ‘one-size fits all’ technology that has been identified to address every individual's distress level and coping strategy. This study thus, examines the existing technologies that have been used by people to manage their mental health distress, and proposes a sociotechnical model that can be used to identify current technologies and the effectiveness of such technologies in addressing an individual's mental health distress and symptoms. (07/2022) (link)
  • Tabisula, B., & Uwaoma, C. (2022). A Sociotechnical Model for Managing Mental Health Distress Among College Students During and After a Pandemic: Development and Usability Study. Iproceedings, 8(1), e39341. (06/2022) (link)
  • Tabisula, B. (2021). Association rules in heart failure readmission rates and patient experience scores. Perspectives in Health Information Management, 18(3). Abstract Objective: Thirty-day readmission rates are closely monitored in today’s healthcare ecosystem to prevent higher-than-average rates in inpatient settings. Excess readmission rates result in decreased reimbursement for healthcare facilities. Additionally, feedback from patients about their hospital experience may indicate areas of improvement for healthcare facilities. This feedback is a national survey that collects data on patient experience through a standardized survey called Hospital Consumer Assessment of Healthcare Providers and Systems (HCAHPS). The objective of this study is to identify significant patterns between readmission rates and HCAHPS survey data through the application of association rules. Materials and Methods: Publically accessible HCAHPS survey data and 30-day readmission rates provided by the Centers for Medicare and Medicaid Services (CMS) were utilized for this study. Through the implementation of association rules using SAS Enterprise Miner, significant rules were identified in the data. Results: Association rules were developed in SAS Enterprise Miner and produced three significant rules associated with high heart failure (HF) readmission as the right-hand rule. The rules indicated that a high pneumonia readmission, a low cleanliness star rating, and a low medication communication star rating were associated with a high readmission rate for heart failure. Conclusions: The rules provided strong associations between HCAHPS star ratings and determining a high readmission rate for HF. It was interesting to find that pneumonia readmissions exist as well with a high HF readmission. Hospitals should work on improving their star ratings for the HCAHPS domains identified and work on lowering pneumonia readmissions to lower their HF readmissions. Keywords: hcahps, readmission rate, heart failure, association rules, patient satisfaction (08/2021) (link)
  • Tabisula, B. (2021). Looking at data analytics in the him curriculum: what students are learning. CHIA Journal, 73(2), 8-9. (08/2021)
  • Alismail, A., Tabisula, B. M., & López, D. (2021). Designing a Clinical Education Tracking System: An Innovative Approach. Advances in medical education and practice, 12, 539–546. https://doi.org/10.2147/AMEP.S312734 Abstract In clinical education, there is a need for constant evaluation, assessment, and at times immediate feedback for students to recognize areas of success, learning, and areas for improvement. The clinical educator is expected to manage the number of student evaluations and assess their performance, regularly, as needed, and over time. This allows appropriate and timely formative, as well as summative feedback to students and the program. Clinical programs face challenges in finding innovative and efficient methods to track and manage this large volume of seemingly disparate needed and required data. Traditional solutions entail paper-based systems or a paid proprietary clinical tracking system. However, both of these options have their own unique challenges. This perspective article proposes an innovative approach of collecting data electronically via online forms, processing and storing data in cloud-based databases and providing appropriate visualizations for the end users (i.e., students and educators) to analyze and assess the information. Migrating data to be collected in this manner allows for the integration of business intelligence (BI) techniques that provide data mining and machine learning in various user needed methods. This article presents a perspective and an innovative guide for clinical educators on how to develop and design a system that leads to positive sentiments and immediate student feedback regarding their progress to improve student outcomes. Keywords: business intelligence; BI; clinical education tracking system; health education; information systems. (05/2021) (link)

Non-Scholarly Journals

  • Simiplifying Your Data Visualizations (05/2018)
  • Data Analytics and Informatics are Two Separate Disciplines (and Why It Matters to HIM) Journal of AHIMA (10/2017)
  • Loma Linda University opens new Master's Program (06/2013)

Book Review - Scholarly Journals--Published

  • Management and the Health Information Management Professional (Janette Richard Kelly, MBA, RHIA and Pamela S. Greenstone, M.Ed., RHIA) (08/2015)
  • Healthcare Code Sets, Clinical Terminologies, and Classification Systems, Second Edition (Kathy Giannangelo, MA, RHIA, CCS, CPHIMS, FAHIMA) (04/2014)