Brita F Olsen1, Tone Rustøen2, Leiv Sandvik3, Christine Miaskowski4, Morten Jacobsen5, Berit T Valeberg6. 1. Østfold Hospital Trust, Fredrikstad, Norway; Oslo University Hospital, Division of Emergencies and Critical Care, Oslo, Norway. Electronic address: Brita.Fosser.Olsen@so-hf.no. 2. Oslo University Hospital, Division of Emergencies and Critical Care, Oslo, Norway; Faculty of Medicine, University of Oslo, Norway. 3. Oslo Center for Biostatistics and Epidemiology, Oslo University Hospital, Oslo, Norway. 4. School of Nursing, University of California, San Francisco, CA, USA. 5. Østfold Hospital Trust, Fredrikstad, Norway; Faculty of Medicine, University of Oslo, Norway; Norwegian University of Life Sciences, Aas, Norway. 6. Oslo and Akershus University College of Applied Sciences, Oslo, Norway.
Abstract
OBJECTIVES: To develop a pain management algorithm for intensive care unit (ICU) patients and to evaluate the psychometric properties of the translated tools used in the algorithm. BACKGROUND: Many ICU patients experience pain. However, an evidence-based algorithm for pain management does not exist. METHODS: Literature review, expert panel, and pilot testing were used to develop the algorithm. The tools were evaluated for inter-rater reliability between two nurses. Discriminant validity was evaluated by comparing pain during turning and rest. RESULTS: An algorithm was developed. The Behavioral Pain Scale (BPS) and the Behavioral Pain Scale-Non Intubated (BPS-NI) discriminated between pain scores during turning and rest. Inter-rater reliability for the BPS varied from moderate (0.46) to very good (1.00). Inter-rater reliability for the BPS-NI varied from fair (0.21) to good (0.63). CONCLUSIONS: The content of the pain management algorithm is consistent with the latest clinical practice guideline recommendations. It may be a useful tool to improve pain assessment and management in adult ICU patients.
OBJECTIVES: To develop a pain management algorithm for intensive care unit (ICU) patients and to evaluate the psychometric properties of the translated tools used in the algorithm. BACKGROUND: Many ICU patients experience pain. However, an evidence-based algorithm for pain management does not exist. METHODS: Literature review, expert panel, and pilot testing were used to develop the algorithm. The tools were evaluated for inter-rater reliability between two nurses. Discriminant validity was evaluated by comparing pain during turning and rest. RESULTS: An algorithm was developed. The Behavioral Pain Scale (BPS) and the Behavioral Pain Scale-Non Intubated (BPS-NI) discriminated between pain scores during turning and rest. Inter-rater reliability for the BPS varied from moderate (0.46) to very good (1.00). Inter-rater reliability for the BPS-NI varied from fair (0.21) to good (0.63). CONCLUSIONS: The content of the pain management algorithm is consistent with the latest clinical practice guideline recommendations. It may be a useful tool to improve pain assessment and management in adult ICU patients.
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