Development and alarm threshold evaluation of a side rail integrated sensor technology for the prevention of falls.

OBJECTIVE

Patient falls constitute a serious problem both for the persons fallen and for the institutions involved. Bed-exit alarm systems are used to reduce patient falls. Existing bed-exit alarm systems have several disadvantages depending on the technology used. As in "Evaluation of Bed-Exit Alarms" stated, restless, light weighted, uncooperative, incontinent and confused patients require different systems. The aim of this work is to present the research and development process of the integrated, universally applicable BUCINATOR bed-exit-alarm system.

METHODS

The use-case technique was applied to capture the functional requirements for the development of the new integrated bed-exit alarm system. An experimental study was carried out to collect data regarding preliminary sensitivity and specificity for alarm set-off.

RESULTS

Major identified requirements for an optimized bed-exit alarm system were usability, wide range usage, low costs, hygiene factors, integration into nursing beds and nurse call systems and an adequate alarm/false alarm ratio with early alarm trigger functionality. On the basis of the criteria mentioned above, a sensor system was developed, comprising tubes with an air-filled passageway attached on the top of side rails. These tubes are coupled via lines to transducers which trigger an alarm when a predetermined level of pressure is reached. Both the preliminary sensitivity (96.0%) and the specificity (>or=95.5%) of the trigger level indicate a satisfactory alarm/false alarm ratio which is now to be evaluated in a clinical trial.

CONCLUSIONS

After experimental testing, BUCINATOR shows great potential to be a reliable bed-exit alarm system. In general, bed-exit alarm systems with extended features could play a major role in ambient assisted living technologies.

LIMITATIONS

Besides the theoretical evaluation, it will be imperative to perform more tests and to gather more data about the effect on fall rates and resulting injuries.