Pressure ulcer risk assessment and prevention system design.

Abstract

Pressure ulcer (PU, bedsore, ischemia, decubitus ulcer) has become a global healthcare problem. In United Kingdom 412,000 people develop pressure ulcer annually and it costs the National Health Service (NHS) £1.4-£2.1 billion pounds (4% of total NHS budget). Pressure ulcers are a combined result of multiple factors such as prolonged external load applied to the skin, reduced blood flow in tissues, the patient’s physiological parameters (body mass index, age, mobility) and body support surface properties. The aetiology of pressure ulcer formation includes both mechanical and biological properties of skin and soft tissues. In order to prevent PU formation in the human body, a new type of risk predicting tool is required where identification of PU risk is based on combined effect of patient’s physiological parameters and support surface properties. Previous research suggests that interface pressure (IP) of 32 mmHg (4.2kPa) can cause PU but there is no strong evidence to show when that pressure is reached. Also IP varies from person to person due to their physiology. There are three risk assessment scales available to predict the occurrence of PU formation; however, none of these scales take interaction of body support surface material into account. Also they do not provide any information at which area a person is at risk of ulceration. In order to identify the harmful IP, biomechanical behaviour of skin and soft tissue is modelled and interaction of body support surface is studied. A mathematical model has been developed to characterise a new type of body support surface material (viscoelastic) and validated by conducting experiments. The relationship between patient’s physiological parameters and surface material are identified along with risk assessment scales for pressure ulcer prediction by conducting experiments. External load at different bony areas are measured using eleven volunteers. By measuring the external load for eleven subjects (age =33±7) and (BMI =25.0±3.01 kg/m2) at different bony areas, the relationship between IP with the total body weight and BMI was developed. A mathematical model is proposed to predict the risk of PU formation combining the Waterlow risk assessment scale and risk prediction algorithms on a user friendly interface.