Salient beliefs towards the application of an algorithm for pain relief in ICU
- D Beaulieu1
© BioMed Central Ltd 2002
Published: 1 March 2002
The negative effects of pain on ICU patients' recuperation has been reported in many studies, prolonging their length of stay and increasing the cost of hospitalisation. It was demonstrated that the application of an algorithm reduced pain scores.
The aim of this study was to identify the salient beliefs of ICU nurses toward the application of an algorithm for pain relief.
This information was assessed using a questionnaire answered by 24 ICU nurses recruited during work, as a convenience sample. Ajzen's theoretical framework was used as a basis for the questionnaire and as a guide for the qualitative analysis of the data.
The respondents found that the application of an algorithm for pain relief increased autonomy and efficacy, ensured a better follow-up and was easy to use. However, it was found to be time consuming and not adapted to all patients, was a rigid framework and did not take into consideration the subjectivity of pain. The main barriers were lack of time, fear of side effects, inaccessibility of the algorithm, the morphine or the pain scale. Also, patients' fear of the drug and refusal of the analgesia offered, physicians' fear of side effects and unwillingness to adhere to the algorithm, the inability of patient to use or understand the pain scale and the chart not adapted were mentioned as barriers.
Although the application of an algorithm seems to be successful in pain relief, this study has identified numerous objectives of intervention to be considered before the official implementation of an algorithm as a protocol for pain relief in ICU. Specific points have been identified to facilitate its integration and reduce workload for nurses already burdened with many aspects of patient care. Information concerning pain is the first step towards its relief but a more integrated psychosocial approach such as increasing the feeling of self-efficacy of the nursing and medical team needs to be considered in order to improve the quality of care and cut down on health expenses.