Poor sleep is common in critically ill patients and is characterized by frequent awakenings and approximately 50% of sleep occurring during daytime hours (1–4). Patients consistently report worse sleep quality in the ICU compared with home (2) and rank poor sleep as an important source of ICU-related anxiety and stress (5). Although poor sleep can be attributed to modifiable factors, such as noise (1, 2, 6–8), light (2, 6), patient care interactions (9), and medications (3, 10), few large-scale ICU sleep improvement studies have been attempted, possibly due to challenges with sleep measurement in this setting (11).
Nevertheless, interest in improving ICU sleep quality has increased, given its possible association with ICU delirium (12) and post-ICU neuropsychological sequelae (13). Efforts to address these sequelae currently include avoiding deep sedation, preventing delirium, and introducing early physical rehabilitation (13); whether improving ICU sleep quality may be beneficial remains unknown. Thus, this project evaluated the effect of a multifaceted intervention to improve sleep and delirium/cognition in a medical ICU (MICU).
MATERIALS AND METHODS
Project Setting and Design
This quality improvement (QI) project was undertaken in the Johns Hopkins MICU, which has a 1:2 registered nurse-to-patient ratio and 16 private rooms. This MICU-wide, pre–post evaluation was developed by a multidisciplinary team with expertise in critical care, sleep, nursing, psychiatry, neuropsychology, and pharmacology. The multifaceted QI intervention targeted modifiable factors affecting sleep quality (1, 2, 4, 14) and was implemented in three additive stages (described below), using a previously employed QI framework (15–17).
Baseline (January–February 2010): usual MICU care.
Stage 1 (starting March 2010): To decrease sleep disruptions, nighttime environmental interventions were implemented, including minimizing overhead pages, turning off patient televisions, dimming hallway lights, and grouping care activities (14, 18). Daytime interventions to promote normal circadian rhythms and nighttime sleep included raising window blinds, preventing excessive napping, encouraging mobilization, and minimizing prebedtime caffeine.
Stage 2 (starting April 2010): In addition to Stage 1 interventions, previously studied nonpharmacological sleep aids were offered to nondelirious (as measured by a negative Confusion Assessment Method for the ICU [CAM-ICU (19)] assessment) patients, including earplugs (20, 21), eye masks (21), and soothing music (22).
Stage 3 (May–July 2010): A pharmacologic guideline was implemented for patients unable to sleep despite the Stage 1 and 2 interventions. This guideline discouraged the use of commonly prescribed sedating medications known to alter sleep and precipitate delirium (i.e., benzodiazepines, opiates, diphenhydramine, trazodone [12, 23, 24]), and recommended readily available alternatives: zolpidem for patients without delirium, and haloperidol or an atypical antipsychotic for patients with delirium.
In this pre–post analysis, we decided a priori to compare patient outcomes during the baseline stage vs. Stage 3, after all QI interventions had been incrementally adopted into routine practice. All involved MICU staff received extensive training regarding this project. A daily checklist (available from authors) reminded staff to perform sleep-promoting interventions (16).
ICU Outcome Measures
All patients spending more than or equal to one full night in the MICU were eligible for outcome measurement. There were two domains for the primary ICU outcomes: perceived sleep quality and noise ratings, and patient cognition.
Perceived sleep quality was measured using the Richards-Campbell Sleep Questionnaire (RCSQ) (25), a five-item questionnaire, validated against polysomnography in MICU patients (25), evaluating these aspects of nighttime sleep: 1) depth, 2) latency (time to fall asleep), 3) number of awakenings, 4) efficiency (percent of time awake), and 5) quality. Responses are recorded on a 100-millimeter visual-analogue scale (VAS), with higher scores representing better sleep and the mean of these five items representing the overall RCSQ score (primary RCSQ measure). As in other studies (26, 27), the RCSQ also included a sixth item, not included in the overall score, evaluating perceived nighttime noise (VAS range: 0 for “very noisy” to 100 for “very quiet”).
Each morning, MICU nurses asked patients to complete the RCSQ. If patients were “comatose” (i.e., Richmond Agitation-Sedation Scale [RASS] score of –4 or –5 ) overnight, the RCSQ was not completed due to inability to evaluate perceived sleep quality. For noncomatose patients with delirium (i.e., having a positive CAM-ICU assessment ), inability to complete the survey (e.g., did not understand English), or with major communication barriers (e.g., unable to write or point to answers), the patient’s nightshift nurse completed the RCSQ, based on previous studies demonstrating high patient–nurse agreement on the RCSQ (26, 29).
Patient cognition was assessed using ICU delirium/coma-free status, based on nurses’ twice daily CAM-ICU (19) and RASS (28) assessment. As in prior studies (30, 31), delirium/coma-free status was selected to provide a gross, but feasible, daily evaluation of the incidence of “normal” cognition following each night’s sleep. Secondary ICU outcomes included MICU and hospital length of stay and mortality.
Within the context of the MICU’s ongoing QI efforts, and in accordance with Office for Human Research Protections (OHRP) standards, this project was deemed “quality improvement” by the institutional review board (IRB) chair at Johns Hopkins University (32). The Standards for Quality Improvement Reporting Excellence guidelines were followed in reporting this QI project (33).
Post-ICU Outcome Measures
Shortly after ICU discharge, a sample of MICU patients present during the QI project and meeting eligibility criteria (below) were evaluated for perceived sleep quality and cognition. Because this post-ICU evaluation was not part of routine care, it was considered human subjects research and approved by the Johns Hopkins University IRB, with informed consent obtained from all participating patients or their proxies (if patient incapable of consent).
Inclusion criteria for the post-ICU evaluation were age ≥ 18 yrs, more than or equal to one night in MICU, and discharge to an inpatient ward bed or pending discharge directly from the ICU. Exclusion criteria were 1) more than or equal to one night in another ICU during the hospitalization; 2) pre-existing cognitive impairment in the medical record (including dementia, stroke, traumatic brain injury, hepatic encephalopathy, or sustained alcohol or drug abuse ); 3) inability to speak or understand English; 4) visual or hearing impairment; 5) inability to read or use a writing instrument; 6) cardiac arrest during the hospitalization; 7) moribund; 8) discharge from the MICU more than 96 hrs prior to assessment; and 9) prior enrollment.
As soon as possible after ICU discharge, a trained investigator (B.B.K. or D.M.N.) administered the post-ICU evaluation. Perceived MICU sleep quality was assessed using an abbreviated Sleep in the ICU Questionnaire, a previously published instrument (2) addressing ICU sleep quality and disturbances using a 1–10 scale. Cognition was measured using the CAM-ICU, along with these standardized tests: 1) Digit Span Forward and Backward to assess attention and short-term memory (35), and 2) Trail Making Tests A and B to assess attention and executive function (36). Education- and/or age-scaled cognitive test scores (35, 37, 38) were presented as standardized T-scores (mean = 50, sd = 10 ). Cognitive test scores were qualitatively classified as “mild to moderate” impairment if ≥1 and <2 sd below norm, and “severe” if ≥2 sd below norm.
Demographic and ICU Variables
Demographic and ICU data obtained for this project included age, gender, race, ICU admission diagnosis, nightly mechanical ventilation status, daily administration of benzodiazepine and/or opiates via infusion and/or bolus, and nightly administration of pharmacological sleep aids. MICU patients (or proxy if patient incapable) completed a brief one-time home sleep quality survey (adapted from the Pittsburgh Sleep Quality Index ), inquiring about the presence of pre-existing sleep problems, home sleep quality, and frequency of sleep medication use. Data collection for the post-ICU patient subset included years of education, Charlson Comorbidity Index (41) and other relevant comorbidities, and ICU admission Sequential Organ Failure Assessment (SOFA) score (42).
Data were summarized using median and interquartile range (IQR) for continuous variables and proportions for categorical variables. Unadjusted baseline vs. sleep QI comparisons were performed using Wilcoxon rank-sum, chi-squared, and Fisher’s exact tests, as appropriate. For patients with repeat MICU admissions, only the first MICU admission was included in statistical analyses.
ICU Outcomes. Adjusted baseline vs. sleep QI differences for the overall RCSQ and nighttime noise scores were determined using multivariable linear regression. All available covariates potentially influencing daily MICU sleep quality ratings were included in the regression model, including age, gender, home sleep survey responses, RCSQ rater (patient vs. nurse), location prior to ICU admission, ICU admission diagnosis, and mechanical ventilation status (measured each night). Because nurse raters performing sleep QI interventions may have influenced their own RCSQ responses, we created an interaction term for rater and project stage (i.e., baseline vs. QI) in the regression models, which was not significant and therefore not included in final models.
Analyses comparing ICU cognitive and secondary outcomes were conducted using multivariable logistic (delirium/coma-free status and mortality) and Poisson regression (length of stay), with adjustment for age, gender, overnight mechanical ventilation status, and four variables for bolus and infusion of benzodiazepines and narcotics. The Poisson models included standard error corrections for overdispersion based on the scaled deviance. Generalized estimating equations were used in regression models incorporating repeated daily outcomes (RCSQ scores, delirium/coma-free status) to account for within-patient correlation of time-varying measures (43). Each of the two distinct primary outcome variables was evaluated using a significance level of 0.05. All other analyses of secondary outcomes were considered hypothesis generating; hence, the p-value threshold used for statistical significance was not adjusted for multiple comparisons.
Post-ICU Outcomes. Normality of post-ICU raw data was determined using Shapiro–Wilk tests. The Digit Span results were normally distributed and analyzed using linear regression. A transformed Trail Making Test B variable was calculated by subtracting raw time values from 180 to produce a right-skewed variable. The Sleep in the ICU Questionnaire responses, Trail Making Test A, and transformed Trail Making Test B results were right-skewed and analyzed using multivariable regression assuming a gamma distribution. To avoid overfitting the post-ICU regression models, we included covariates in the multivariable model based on bivariable association (at p < 0.10) of the outcome and potentially relevant covariates, as selected, a priori, during design of the study based on prior research and consensus of the multidisciplinary QI team.
For all regression analyses, multicollinearity was assessed using variance inflation factors (44), and addressed, when necessary, by recategorizing or omitting less-relevant collinear variables. A two-sided p < 0.05 defined statistical significance. All analyses were performed using STATA version 11.2 (College Station, TX).
Sample Size Calculation. The post-ICU evaluation sample size was calculated using the Digit Span test. A sample size of 38 patients in each of the baseline and sleep QI stages was selected to detect a moderate effect size of the intervention (45) (defined as a difference in Digit Span test score of 1.5 (46) given an expected sd of 2.3 ), with 80% power and a two-sided p = 0.05. Based on historical MICU admission rates, we calculated that the desired sample size was attainable within 8 weeks, the allotted time for the baseline and sleep QI stages.
During the baseline and sleep QI stages, respectively, 122 and 178 patients spent more than or equal to one night in the MICU and were therefore eligible for ICU outcomes analysis (Table 1). Overall, 34 baseline and 38 QI patients were enrolled in the post-ICU outcomes evaluation, with consent rates of 100% and 97%, respectively. There were no significant between-group differences in demographic characteristics, home sleep habits, or ICU admission diagnoses (Table 1). However, compared with the baseline group, fewer QI patients received mechanical ventilation during their ICU stay. In the post-ICU subset, there were no significant between-group differences in the additional covariates: years of education (median [IQR]: 11[13–15] vs. 12[13–16]; p = 0.67), ICU admission SOFA score (6[4–9] vs. 5[3–7]; p = 0.15), Charlson Comorbidity Index score (2[1–4] vs. 1[0–3]; p = 0.16), and history of prior or current heavy drug and/or alcohol use (n = 10 (29%) vs. n = 10 (26%); p = 0.77).
During the sleep QI stage, the daytime environmental, nighttime environmental, and nighttime nonpharmacologic intervention checklist items were completed for 86%, 89%, and 94% of patient-days, respectively (summary in Table 2). Medications for sleep were given 60 times (9% of patient-days) during the baseline stage and 133 times (16%) during the QI stage after implementation of the pharmacologic sleep aid guideline (p < 0.001). Of medications administered for sleep during the baseline and QI stages, respectively, 45% (n = 27) vs. 60% (n = 80, p = 0.050) were guideline-promoted medications given alone, 52% (n = 31) vs. 34% (n = 45, p = 0.02) were guideline-discouraged medications given alone, and 3% (n = 2) and 6% (n = 8, p = 0.44) were given in combination.
Sleep Quality. During 634 and 826 patient-days in the baseline and sleep QI stages, respectively, 110 (90%) and 160 (90%) patients completed at least one RCSQ assessment. During noncomatose days, 440 (89%) and 615 (87%) RCSQs were completed in the baseline and QI stages, respectively, of which nurse raters completed 193 (44%) and 279 (45%).
During the baseline vs. sleep QI stages, mean (sd) ratings for RCSQ overall sleep quality were 54.5 (27.1) vs. 53.2 (27.3; p = 0.46), with no significant improvement in multivariable regression models (adjusted difference = 2.37; 95% confidence interval [CI] –1.66 to 6.40; p = 0.25; Table 3). However, mean RCSQ noise ratings were 60.5 (26.3) vs. 65.9 (26.6; p = 0.002), respectively, and were significantly improved in multivariable models (7.06; 95% CI 2.80–11.33; p = 0.001; Table 3). Similar adjusted differences for the RCSQ overall and noise ratings were observed in multivariable regression analyses stratified by patient (2.51 [p = 0.38] and 6.75 [p = 0.02], respectively) and nurse (2.09 [p = 0.47] and 8.28 [p < 0.001], respectively) raters. Patients with “somewhat or very bad” (vs. “very good”) home sleep quality had substantially worse RCSQ overall scores and noise ratings (Table 3).
Delirium/Coma. Fewer patient-days of delirium/coma-free status were observed during the baseline (272, 43%) vs. sleep QI (399, 48%) stage (unadjusted p = 0.04), with an adjusted odds ratio of 1.64 (95% CI 1.04–2.58; p = 0.03; Table 4). Among the 110 and 175 patients whose entire ICU stay occurred during the baseline or QI stage, respectively, 76 (69%) vs. 86 (49%) had incident delirium/coma during their ICU stay (unadjusted p = 0.001), with an adjusted odds ratio of 0.46 (95% CI 0.23–0.89; p = 0.02; Table 4). To investigate whether differences in administration of pharmacologic sleep aids (as recommended by the pharmacologic guideline for insomnia) influenced this result, we included these medications in post hoc multivariable regression analyses and observed no material change in these results.
Secondary Outcomes. In multivariable regression, there was no significant reduction in ICU or hospital length of stay or mortality (Table 4).
The mean (sd) time to post-ICU testing after MICU discharge for the baseline and sleep QI groups was 23.3 (37.7) vs. 7.8 (26.7) hrs, respectively (p = 0.046; Table 5). On the Sleep in the ICU Questionnaire, QI patients recorded higher median ratings, representing better perceived sleep quality and disruptions, for 8 of 9 items (Table 5). In multivariable regression analysis, only ratings for disruptions due to medication administration were significantly improved (p = 0.009) in the QI stage.
For neurocognitive testing, all but one patient (in the sleep QI group) were not delirious. Cognitive impairment was observed in almost all baseline and QI patients, with no significant differences in severity: no impairment, 12% vs. 21%; mild/moderate, 38% vs. 29%; and severe, 50% vs. 50% (p = 0.54). Median (IQR) T-scores for the baseline vs. sleep QI groups were as follows: Digit Forward: 49 (41–58) vs. 49 (44–57), p = 0.96; Digit Backward: 37 (33–41) vs. 41 (33–48), p = 0.13; Trail Making A: 36 (1–44) vs. 33 (16–53), p = 0.31; and Trail Making B: 35 (25–43) vs. 40 (26–53), p = 0.27. In multivariable models, neurocognitive test results were not significantly improved (Table 5), with no material change in a post hoc sensitivity analysis adjusting for time to post-ICU testing
Using a structured QI process, this single-site project involved a multifaceted intervention for critically ill patients, with pre–post evaluation of its effect on perceived sleep quality and delirium/cognitive outcomes in the ICU and following ICU discharge. Implementation of sleep-promoting interventions as part of routine care was feasible and associated with significant improvements in perceived nighttime noise, incidence of ICU delirium/coma, and daily delirium/coma-free status in the ICU, along with nonsignificant improvements in sleep disruption ratings in a small post-ICU subset. Numeric differences reflecting improved perceived sleep quality in the ICU and post-ICU cognitive function in the QI stage were not statistically significant in multivariable regression models.
Given that interventions to improve ICU sleep have only recently gained widespread scientific interest (4), to our knowledge, there have been no previously published large-scale, multifaceted QI projects in this area. This project followed other successful QI interventions within our MICU (47) and was conceived as a part of our ongoing efforts to change routine practice to reduce ICU-acquired functional impairments (13). Development of this sleep intervention was guided by prior studies demonstrating the feasibility of environmental noise and light reduction strategies (7, 18, 27, 29), use of earplugs, eye masks, and music (20–22), and pharmacologic sleep aid interventions (48, 49). Despite prior studies being limited by sample size (18, 22, 27, 29, 48, 49), use of simulated ICU settings (20, 21), or lack of well-recognized sleep measurement tools (7), they highlighted a spectrum of modifiable ICU sleep factors considered for this project.
Prior to QI implementation, sleep and noise ratings, prevalence of delirium/coma within our MICU, and post-ICU cognitive performance and noise ratings closely matched those of prior studies (2, 8, 14, 25–27, 30, 34, 50–52). Following implementation, the MICU sleep-promoting interventions were associated with noise rating improvements paralleling those of a similar study (27). Furthermore, our QI effort was associated with delirium/coma reductions on par with those observed in a randomized clinical trial of dexmedetomidine (31). Despite these findings, however, we did not demonstrate a significant improvement in perceived ICU sleep quality, in contrast to two previous intervention studies (27, 51), for several reasons. In contrast to our study, which included all patients spending more than one full night in the MICU, these prior studies selectively included postoperative patients with a lower acuity of illness (<4% received mechanical ventilation) and excluded patients receiving sedation, having pre-existing sleep problems, and/or an ICU length of stay more than 3 days. Consequently, these patients may have experienced fewer sleep disruptions inherent to critical illness and been more sensitive to sleep-promoting interventions. Furthermore, both studies had smaller sample sizes, did not adjust for potential confounders, and collected sleep ratings only once, on ICU day 3 (27) or after ICU discharge (51).
This QI project had several potential limitations. First, without a significant improvement in perceived sleep quality, we cannot necessarily attribute improvements in delirium/coma specifically to sleep. Instead, this improvement may have resulted from aspects of the multifaceted interventions that could affect delirium, such as the pharmacologic guideline for insomnia, provision of daytime sunlight (53), and promotion of daytime activity (47, 53). However, because all aspects of the intervention are generally inexpensive, feasible to implement, and potentially beneficial, we suggest that all aspects of the entire multifaceted intervention can be considered together until further research is available. Second, given this pre–post design, we cannot be certain that the QI interventions caused the observed baseline vs. QI differences. Other factors, not adjusted for in our analysis, including temporal or seasonal differences, could have influenced the results. Third, sleep was evaluated using the RCSQ instead of polysomnography (PSG), which is difficult to interpret and implement on a large-scale basis in the ICU (11). We selected the RCSQ in part because it had been validated against PSG in a MICU population (25). Fourth, there was no objective measure of noise, and it is unclear whether the observed improvement in perceived noise was clinically important. However, in post hoc multivariable regression analysis, there was a significant association between the RCSQ noise score and the overall RCSQ sleep ratings that excluded the noise question (0.38 point improvement in overall score for 1 point improvement in noise, p < 0.001), suggesting that improvements in perceived noise correlated with improvements in perceived sleep. We also have many anecdotal reports of marked reductions in overhead pages, unnecessary alarms, and nighttime television watching. However, we cannot demonstrate that improvements in perceived noise correlated with objective measurement and were clinically important. Fifth, it is possible that nurses’ RCSQ ratings and delirium/coma assessments were biased by their own sleep-promoting actions (i.e., minimizing alarms, turning off televisions). However, RCSQ regression models including an interaction term for rater and project stage were not significant, suggesting no influence of the intervention stage on nurse RCSQ ratings. Furthermore, confounding of the delirium/coma outcome was minimized because the 8AM assessments were completed by daytime nurses not performing nighttime sleep-promoting interventions, and the 8PM assessments were completed before the implementation of sleep-promoting interventions. Sixth, the post-ICU evaluation may have been underpowered to detect significant improvements in sleep quality and cognitive function. Moreover, despite efforts to perform the post-ICU evaluation immediately following ICU discharge, a longer time to cognitive testing in the baseline group may have allowed for recovery from ICU-acquired deficits (54), thus biasing the result toward the null. However, a post hoc sensitivity analysis did not demonstrate any important differences in the results. Seventh, as a single-site study, generalizability of our findings may be limited. However, by having no exclusion criteria for the QI portion of the project, we examined a heterogeneous ICU patient population that included 161 mechanically ventilated patients, and observed baseline sleep quality ratings and cognitive outcomes similar to other ICU studies. Finally, as a multifaceted QI project, we could not determine which specific sleep-promoting interventions were associated with the observed results. However, all facets of the intervention were inexpensive, easy to implement, and low risk. For this reason, and potential synergy between the interventions, we suggest the QI intervention remain bundled if implemented elsewhere.
In conclusion, using a structured process, we implemented a multifaceted, multistage quality improvement intervention to promote sleep, demonstrating that such efforts were feasible as part of routine ICU care and were associated with significant reductions in perceived nighttime noise levels and a substantial decrease in delirium/coma.
We thank the dedicated Johns Hopkins MICU nurses and other staff. Additionally, we thank Pooja Shah, Amanda Le, BS, Preeya Nandkumar, BA, Farah Rahman, BA, and Melinda Christie, BS for assistance with data collection, entry, and cleaning.
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