Quantcast

Solution To Help Disabled Make Better Wheelchair Selections

May 23, 2012

A Wayne State University researcher has introduced computer technology that makes it easier for people who need wheelchairs to select one that best suits their needs.

In “Remote Decision Support for Wheeled Mobility and Seating Devices,” recently published online and set to appear in the June edition of Expert Systems with Applications, Kyoung-Yun Kim, Ph.D., associate professor of industrial and systems engineering in WSU’s College of Engineering, introduces a Web-based decision support system for remotely selecting wheelchairs.

According to the 2010 U.S. Census, 3.3 million people age 15 and older use wheelchairs; 10 million use walking aids, such as canes, crutches or walkers. Eleven million people age 6 and older need personal assistance with everyday activities, including such tasks as getting around inside the home, taking a bath or shower, preparing meals and performing light housework.

Many people with disabilities live outside large metropolitan areas and lack access to experienced clinicians who can help them decide what kind of device is best for them. Such help has become more necessary with changes implemented by the U.S. Centers for Medicare and Medicaid Services in the Healthcare Common Procedures Coding System (HCPCS) for wheeled mobility devices. Those changes included expanding the number of device identification codes from four to 64, making it difficult to understand where a product falls within the new structure.

“Disabled patients almost always have a unique situation, so for something that looks like a simple device, making an optimal decision is not that simple,” Kim said. “It requires doctors’ and clinicians’ assessments, as well as those of patients and their families. Combined with testing time, these are significant factors that lead to an increasingly expensive selection process.”

In a study supported by the National Institute on Disability and Rehabilitation Research of the U.S. Department of Education, Kim’s team reviewed current research in telerehabilitation, an emerging field that aims to deliver rehabilitation services over telecommunication networks and the Internet, and complements in-person clinical assessment and therapy in underserved areas.

His system improves the selection and evaluation processes by enabling remote assessment of appropriate wheelchair alternatives with advanced queries and selection criteria. It also provides a reusable information repository and enables systematic evaluation.

HCPCS coding changes have increased the gap in decision-making abilities of less experienced clinicians in underserved areas and their more experienced peers in larger population centers, Kim said. In an effort to minimize that gap, the teleconsultation model gives the former group access to the latter, ultimately allowing clinicians to make better selections.

A study based on the Technology Acceptance Model was conducted with three groups of clinicians: just graduated, moderately experienced and senior level, via the Rehabilitation Engineering Research Center. The model is a formal research tool for evaluating technological support of a given task.

As a control, Kim’s team tested face-to-face patient-clinician interactions. It also set up remote assessments using webcams so that patients and less experienced clinicians in one location could consult with more expert clinicians in another location.

Subjects said the remote wheelchair selection system generally was very user friendly and made it easy to find quality information, but they were neutral on whether they wanted to use it in their clinical decision making. Kim and his team plan to work with other medical facilities, such as U.S. Department of Veterans Affairs hospitals, to encourage wider use of the teleconsultation model with this remote wheelchair selection system.

“The goal of this study is to create a portal that gives clinicians easy and timely access to the information they need to make the best decisions for their patients,” Kim said. “We also aim to reduce the gaps in knowledge and human bias between experienced and inexperienced clinicians.

“We believe these improvements can also reduce the time needed to select a wheeled mobility device and eventually reduce the cost of the process as well.”

On The Net:


Source: Wayne State University



comments powered by Disqus