Patient-initiated device removal in intensive care units: a national prevalence study

Information is needed about patient-initiated device removal to guide quality initiatives addressing regulations aimed at minimizing physical restraint use. Research objectives were to determine the prevalence of device removal, describe patient contexts, examine unit-level adjusted risk factors, and describe consequences.

Prospective prevalence.

Total of 49 adult intensive care units (ICUs) from a random sample of 39 hospitals in five states.

Data were collected daily for 49,482 patient-days by trained nurses and included unit census, ventilator days, restraint days, and days accounted for by men and by elderly. For each device removal episode, data were collected on demographic and clinical variables.

Patients removed 1,623 devices on 1,097 occasions: overall rate, 22.1 episodes/1000 patient-days; range, 0-102.4. Surgical ICUs had lower rates (16.1 episodes) than general (23.6 episodes) and medical (23.4 episodes) ICUs. ICUs with fewer resources had fewer all-type device removal relative to ICUs with greater resources (relative risk, 0.76; 95% confidence interval, 0.66-0.87) but higher self-extubation rates (relative risk, 1.27; 95% confidence interval, 1.07-1.52). Men accounted for 57% of the episodes, 44% were restrained at the time, and 30% had not received any sedation, narcotic, or psychotropic drug in the previous 24 hrs. There was no association between rates of device removal with restraint rates, proportion of men, or elderly. Self-extubation rates were inversely associated with ventilator days (rs = -0.31, p = .03). Patient harm occurred in 250 (23%) episodes; ten incurred major harm. No deaths occurred. Reinsertion rates varied by device: 23.5% of surgical drains to 88.9% of monitor leads. Additional resources (e.g., radiography) were used in 58% of the episodes.

Device removal by ICU patients is common, resulting in harm in one fourth of patients and significant resource expenditure. Further examination of patient-, unit-, and practitioner-level variables may help explain variation in rates and provide direction for further targeted interventions.