Stevens, Penn Nursing receive RWJF grant to determine effectiveness of transitional care model

NewsGuard 100/100 Score

Stevens Institute of Technology (Stevens) and the University of Pennsylvania School of Nursing (Penn Nursing) were recently funded by the Robert Wood Johnson Foundation (RWJF) to use policy flight simulators - pioneered by Stevens--to simulate use of the Transitional Care Model, developed by Penn Nursing. Through this collaborative project, Stevens and Penn Nursing will use floor-to-ceiling surround screens to interactively estimate health benefits and delivery costs, and create an evidence-based model to aid decision-making. The goal is to accelerate decisions to implement the TCM.

The Transitional Care Model addresses the negative effects associated with common breakdowns in care when older adults with complex needs move from an acute care setting to their home or other care setting. It also prepares patients and family caregivers to more effectively manage changes in health associated with multiple chronic illness. Despite much evidence showing the effectiveness of the transitional care model to reduce costs and increase quality of care, health systems, payers and purchasers have been slow to adopt it.

"Chronic illness is a major health challenge confronting millions of older adults and their family caregivers, and will continue to have a major impact on healthcare delivery for the foreseeable future," said Mary Naylor, PhD, FAAN, RN, the Marian S. Ware Professor in Gerontology, and Director of the NewCourtland Center for Transitions and Health at Penn Nursing." Our team hopes to show through this simulation the efficiency and effectiveness of the transitional care model in response to the challenges faced by health care organizations in the United States."

Policy flight simulators fuse aspects of multiple scientific disciplines with visualization to provide decision makers with a comprehensive understanding of the consequences of interventions on each major stakeholder. By actively engaging a diverse range of decision makers in the design and pilot testing of the simulation, researchers will create a model that anticipates and aligns with emerging health care delivery and payment models, and is customizable to local contextual factors.

"Our modeling and simulation methods will enable payers to fly the future before they invest," said William B. Rouse, PhD, the Alexander Crombie Humphreys Professor in the School of Systems and Enterprises and Director of the Center for Complex Systems and Enterprises at Stevens. "Our experience has been that once decision makers get to 'live' the capabilities of TCM, they will willingly participate in the program, resulting in enormous healthcare benefits."

Despite TCM's proven value, it has been difficult to convince decision makers to implement this model. Major barriers to widespread implementation include:

  • perceptions that the model works only in randomized clinical trials;
  • it is complex and costly;
  • the model requires upfront investment that benefit others downstream; and
  • it is not adaptable to local issues.

"Time and time again we struggle with the challenge of spreading evidence-based models that have the potential to improve health and healthcare," said RWJF director Lori Melichar. "By combining cutting-edge design and technology with the science of decision-making, the Foundation is exploring the question of whether simulation tools can accelerate the spread of programs like the Transitional Care Model that are proven to work."

This project will provide a robust case study on the development and application of the simulation, which will generate key lessons to aid decision making in diverse organizations to adopt or adapt a range of evidence-based interventions.

Comments

The opinions expressed here are the views of the writer and do not necessarily reflect the views and opinions of News Medical.
Post a new comment
Post

While we only use edited and approved content for Azthena answers, it may on occasions provide incorrect responses. Please confirm any data provided with the related suppliers or authors. We do not provide medical advice, if you search for medical information you must always consult a medical professional before acting on any information provided.

Your questions, but not your email details will be shared with OpenAI and retained for 30 days in accordance with their privacy principles.

Please do not ask questions that use sensitive or confidential information.

Read the full Terms & Conditions.

You might also like...
UofL receives two federal grants to help increase Kentuckians' access to health care