Grant gives scientists chance to advance tools to predict readmission in diabetic patients


Credit: Temple University Health System

(Philadelphia, PA) – Each year in the United States, more than 1 million patients with diabetes make return trips to the hospital for diabetes-related illness, often being readmitted within 30 days of their initial hospitalization. The costs of these return visits add up, in terms of dollars and in terms of the toll on patient health that comes with prolonged or chronic illness and repeated hospitalization.

Some patients are especially prone to hospital readmission, and now, with $2.5 million in funding from the National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK), researchers at the Lewis Katz School of Medicine at Temple University (LKSOM) are poised to better predict which patients with diabetes are most likely to experience additional hospital visits. Building from a model previously generated at Temple and known as the Diabetes Early Readmission Risk Indicator (DERRITM), the researchers aim to develop improved models that accurately and automatically predict 30-day readmission risk among patients with diabetes, based on electronic health record (EHR) data.

“The DERRITM app originally was developed for point-of-care use, with patients manually inputting information on a small number of variables, such as insulin use, co-existing conditions and recent hospital discharge,” explained Daniel J. Rubin, MD, MSc, FACE, Associate Professor of Medicine at LKSOM, Chair of the Glycemic Control Taskforce at Temple University Hospital and lead investigator on the new five-year NIDDK grant. “Now, we want to upgrade DERRITM to build models that bypass manual input and instead draw directly on EHR data, allowing for faster and more accurate prediction.”

Dr. Rubin’s collaborators on the project include Dr. Zoran Obradovic, Laura H. Carnell Professor of Data Analytics, Director of the Center for Data Analytics and Biomedical Informatics and Professor in the Computer and Information Sciences Department at Temple University; and Anuradha Paranjape, MD, MPH, FACP, Vice Chair for Clinical Affairs in the Department of Medicine and Professor of Medicine and Professor of Clinical Sciences at LKSOM.

The new models, named eDERRITM, will incorporate data from the PaTH Clinical Data Research Network (CDRN), a multi-center, 40-plus hospital member of the National Patient-Centered Clinical Research Network, of which Temple University Health System is a member. With Dr. Obradovic’s expertise, the researchers will be able to apply state-of-the-art deep-learning methods to optimize predictive modeling.

Once the optimized eDERRITM models are completed, the researchers aim to translate them into a readmission risk prediction tool that automatically captures EHR data. Using this data, the researchers anticipate that the tool will accurately identify risk factors for individual patients with diabetes and thereby predict readmission risk. Dr. Rubin’s team plans to validate the eDERRITM models with PaTH CDRN data collected subsequent to the model’s development. The eDERRITM tool additionally will be tested in patients with diabetes who are admitted to Temple University Hospital.

The novel tool stands to greatly advance the care and treatment of patients with diabetes who are especially vulnerable to severe illness.

“Our proposed eDERRITM tool could be widely used for predicting risks, reducing costs and improving care,” Dr. Rubin said. “We are building and testing it at Temple, but the EHR component will be built in EPIC, which is used at numerous institutions across the country. Our tool could be rolled out to any hospital or treatment center that uses EPIC systems.”


Other collaborators on the grant include Jeremiah Brown, PhD, of the Department of Epidemiology at the Dartmouth Geisel School of Medicine; H. Lester Kirchner, PhD, of the Division of Medicine at Geisinger Medical Center; Nestoras Nicolas Mathioudakis, MD, MHS, Associate Professor of Medicine and Clinical Director of Endocrinology, Diabetes & Metabolism at Johns Hopkins University; Mary Korytkowski, MD, Professor of Medicine and Director of Quality Improvement in the Division of Endocrinology at the University of Pittsburgh Department of Medicine; Wenke Hwang, MA, PhD, Associate Professor in the Department of Public Health Sciences at Penn State University; and Mark Weiner, MD, of Weill Cornell Medical College.

About Temple Health

Temple University Health System (TUHS) is a $2.2 billion academic health system dedicated to providing access to quality patient care and supporting excellence in medical education and research. The Health System consists of Temple University Hospital (TUH); TUH-Episcopal Campus; TUH-Jeanes Campus; TUH-Northeastern Campus; The Hospital of Fox Chase Cancer Center and Affiliates, an NCI-designated comprehensive cancer center; Temple Transport Team, a ground and air-ambulance company; Temple Physicians, Inc., a network of community-based specialty and primary-care physician practices; and Temple Faculty Practice Plan, Inc., TUHS’s physician practice plan comprised of more than 500 full-time and part-time academic physicians in 20 clinical departments. TUHS is affiliated with the Lewis Katz School of Medicine at Temple University.

Temple Health refers to the health, education and research activities carried out by the affiliates of Temple University Health System (TUHS) and by the Katz School of Medicine. TUHS neither provides nor controls the provision of health care. All health care is provided by its member organizations or independent health care providers affiliated with TUHS member organizations. Each TUHS member organization is owned and operated pursuant to its governing documents.

It is the policy of Temple University Health System that there shall be no exclusion from, or participation in, and no one denied the benefits of, the delivery of quality medical care on the basis of race, ethnicity, religion, sexual orientation, gender, gender identity/expression, disability, age, ancestry, color, national origin, physical ability, level of education, or source of payment.

Media Contact
Jennifer Reardon
[email protected]

Original Source