Nurse-Controlled Sedation Protocols in the Intensive Care Unit: An Evidence-Based Traditional Review
Year: 2026
Type: article
Abstract: Sedation and analgesia management in intensive care units is one of the fundamental care processes that directly affects mechanical ventilation duration, patient safety, and clinical outcomes. Sedation levels are determined based on criteria such as the patient's level of consciousness, preservation of airway reflexes, adequacy of spontaneous ventilation, and cardiovascular stability. The dose and rate of administration of sedative and analgesic agents, as well as patient-specific clinical characteristics, determine the depth of sedation; inadequate or excessive sedation is associated with patient-ventilator mismatch, hemodynamic instability, and prolonged mechanical ventilation. Therefore, clinical guidelines recommend that sedation management be goal-oriented, protocol-based, and conducted within a framework of systematic assessment. In Turkey, sedation management is carried out according to a plan determined by the physician, but the effectiveness of the process largely depends on the continuous assessment and decision-making process carried out by the nurse at the bedside. Nurses titrate medications by assessing the patient's immediate clinical condition and depth of sedation, detect potential side effects early, and actively manage the achievement of goals. In this context, nurses are not merely implementers; they are healthcare professionals who play a central role in ensuring that sedation is safe, effective, and individualized. This review examines the effects of nurse-controlled sedation protocols on the mechanical ventilation process and the contribution of nurses' clinical knowledge and practices in sedation management to patient outcomes, based on findings from the current literature.
Authors: Funda Akduran, Dilek Kaya
Institution: Sakarya University
Language: English
Subfield: Anesthesiology and Pain Medicine
Field: Medicine
Domain: Health Sciences
Open Access status: hybrid
OpenAlex ID: W7162954966