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Development of a method for quantifying biomechanical risk factors associated with manual and mechanically assisted patient handling
RS2002/03-DG23
Final Report Date: June 2005
| Principal Investigator: |
Annalee Yassi (University of British Columbia) |
| Co-investigators: | Silvia Raschke (British Columbia Institute of Technology); Yvette Jones (Simon Fraser University / British Columbia Institute of Technology); Daniel Robinson (Occupational Health & Safety Agency for Healthcare) |
For more information about this development grant project, please contact Dan Robinson.
Issue
Overexertion from patient handling activities is the most common cause of injury among healthcare workers in BC and elsewhere. The use of mechanical lifting devices has reduced the injuries associated with patient transfers but has not had the same impact on repositioning tasks. There is a need for scientific data on how the use of overhead lifts compares with other methods for various patient handling tasks.
This project developed methods for estimating the biomechanical risk associated with patient handling activities, and tested these approaches by using them to compare the forces associated with manual and mechanically assisted methods for repositioning patients in bed.
Key findings
- A novel method for quantifying biomechanical risk factors (shoulder moments and lumbar spine loading) associated with specific patient handling techniques has been developed. The method is sensitive to movement patterns and level of exertion throughout a patient handling activity.
- The use of an overhead lift to reposition a patient in bed was associated with lower peak compressive forces at the lower spine than the slider sheet (manual) method, but took longer and resulted in greater cumulative load at the low back.
- Eliminating the need to turn a patient to install a repositioning sling or slider sheet reduced the time required to reposition a patient, and reduced the exposure to peak shoulder movements, lumbar spine loads, and the cumulative loading of tissue associated with repositioning. This suggests it would be beneficial to install a repositioning sling or slider sheet as a component of bed linen replacement for patients who are dependent on a caregiver for repositioning in bed.
Objectives
- To develop methods for biomechanical estimation of tissue loading in the shoulder and low back during simulated patient handling activities.
- To compare the effectiveness of two different biomechanical modeling approaches that utilize either a ‘top-down' (reaction forces input at the hand from force-matching simulations) or a ‘bottom-up' (reaction forces input at the feet from measurement with a force platform) analytical method.
- To evaluate the effectiveness of these methods by preliminary analysis of manual and mechanically assisted patient repositioning tasks.
Method
Two commonly occurring patient repositioning tasks were evaluated (reposition up in bed; reposition laterally in bed) and two different techniques were evaluated for each of these tasks (manual technique using a repositioning sheet; mechanically assisted technique using an overhead lift) for a total of four conditions. Each technique was repeated three times by each of the study's five participants.
Two biomechanical measurement approaches were developed, using either measurement of forces beneath the caregiver's feet (ground reaction forces — force platform method) or forces at the caregiver's hands (hand reaction forces — force matching method) as input variables to a linked segment model of the human body. The dynamic position of each body segment was captured using an eight-camera digital motion analysis system.
Both approaches provide an estimate of compressive and shear loading of the lumbar spine, which are indicators of injury risk to the back.
In addition to peak tissue loads, the cumulative load was estimated by the duration of the activity. Larger cumulative loads have been associated with increased risk of back injury.
Results
A novel method for quantifying biomechanical risk factors (shoulder moments and lumbar spine loading) associated with specific patient handling techniques has been developed. This method is sensitive to movement patterns and level of exertion throughout a patient handling activity.
The older method of estimating hand reaction forces using a force matching simulation underestimates the compressive loading of the lumbar spine compared to the more direct measurement of ground reaction forces using a force platform. Use of a force platform or other real-time force measurement is therefore preferred for estimating spinal stress, where practical.
The peak compressive forces at the lumbar spine are lower when using an overhead lift to reposition a patient in bed than when using a slider sheet. However, using an overhead lift takes longer and results in greater cumulative load at the low back.
Eliminating the need to turn a patient to install a repositioning sling or slider sheet reduces exposure to peak shoulder moments and lumbar spine loads, reduces the amount of time required to reposition a patient, and reduces the cumulative loading of tissue associated with repositioning.
Conclusions
The findings suggest that it would be beneficial to install a repositioning sling or slider sheet as a component of bed linen replacement for patients who are dependent on a caregiver for repositioning in bed.
The use of an overhead lift method was associated with lower peak compressive forces at the lumbar spine than the slider sheet method, but took longer and resulted in a greater cumulative load. Further research is needed to better understand whether instantaneous loading or cumulative loading presents the greater risk of injury.
Future directions
The findings of this development grant project should be validated with a larger sample of subjects, and the biomechanical modeling approaches require further refinement.
With further development, there is potential for this approach to enable systematic quantitative risk assessment for patient handling tasks. This would enable the development of evidence-based best practices for patient handling in the health care sector.