The perioperative handoff protocol: evaluating impacts on handoff defects and provider satisfaction in adult perianesthesia care units.

STUDY OBJECTIVE: To evaluate a new perioperative handoff protocol in the adult perianesthesia care units (PACUs). DESIGN: Prospective, unblinded cross-sectional study. SETTING: Perianesthesia care unit in a tertiary care facility serving 55,000 patients annually. PATIENTS: One hundred three surgery patients. INTERVENTIONS: During a 4-week preintervention phase, 53 perioperative handoffs were observed, and data were collected daily by a trained observer. Educational sessions were conducted to train perioperative practitioners on the new protocol. Two weeks after implementation, 50 consecutive handoffs were observed, and practitioners were surveyed with the same methodology as in the preintervention phase. MEASUREMENTS: Type of information shared, type and duration of procedure, total duration of handoff, number and type of providers at the bedside, number of report interruptions, environmental distractions, and any other disruptive events. Observers also tracked technical/equipment problems to include malfunctioning or compromised operation of medical equipment, such as the cardiac monitor, transducer, oxygen tank, and pulse oximeter. MAIN RESULTS: A total of 103 handoffs were observed (53 preintervention and 50 postintervention). The mean number of defects per handoff decreased from 9.92 to 3.68 (P < .01). The mean number of missed information items from the surgery report decreased from 7.57 to 1.2 items per handoff and from 2.02 to 0.94 (P < .01) for the anesthesia report. Technical defects reported by unit nurses decreased from 0.34 to 0.10 (P = .04). Verbal reports delivered by surgeons increased from 21.2% to 83.3%. Although the mean duration of handoffs increased by 2 minutes (P = .01), the average time from patient arrival at PACU to handoff start was reduced by 1.5 minutes (P = .01). Satisfaction with the handoff improved significantly among PACU nurses. CONCLUSIONS: The perioperative handoff protocol implementation was associated with improved information sharing and reduced handoff defects.

Lifetime cigarette smoking and breast cancer prognosis in the After Breast Cancer Pooling Project.

BACKGROUND: There is controversy on whether former smokers have increased risk for breast cancer recurrence or all-cause mortality, regardless of how much they smoked. METHODS: Data were from three US cohorts in the After Breast Cancer Pooling Project, with detailed information on smoking among 9975 breast cancer survivors. Smoking was assessed an average of 2 years after diagnosis. Delayed entry Cox proportional hazards models were used to examine the relationships of smoking status, cigarettes per day, years of smoking, and pack years with breast cancer prognosis. Endpoints included breast cancer recurrence (n = 1727), breast cancer mortality (n = 1059), and overall mortality (n = 1803). RESULTS: Compared with never smokers, former smokers with less than 20 pack-years of exposure had no increased risk of any outcome. However, former smokers with 20 to less than 34.9 pack-years of exposure had a 22% increased risk of breast cancer recurrence (hazard ratio [HR] = 1.22; 95% confidence interval [CI] = 1.01 to 1.48) and a 26% increased risk of all-cause mortality (HR = 1.26; 95% CI = 1.07 to 1.48). For former smokers with 35 or more pack-years of exposure, the probability of recurrence increased by 37% (HR = 1.37; 95% CI = 1.13 to 1.66), breast cancer mortality increased by 54% (HR = 1.54; 95% CI = 1.24 to 1.91), and all-cause mortality increased by 68% (HR = 1.68; 95% CI = 1.44 to 1.96). Current smoking increased the probability of recurrence by 41% (HR = 1.41; 95% CI = 1.16 to 1.71), increased breast cancer mortality by 60% (HR = 1.61; 95% CI = 1.28 to 2.03), and doubled the risk of all-cause mortality (HR = 2.17; 95% CI = 1.85 to 2.54). CONCLUSIONS: Lifetime cigarette smoking was statistically significantly associated with a poor prognosis among women diagnosed with breast cancer, dose-dependent increased risks of recurrence, and breast cancer and all-cause mortality.

Pilot implementation of a perioperative protocol to guide operating room-to-intensive care unit patient handoffs.

OBJECTIVES: Perioperative handoffs are a particularly high-risk period given patients' postprocedural physiology, their physical transport through the hospital, and the triad transfer of personnel, information, and technology. The authors piloted a new perioperative handoff process to guide patient transfers from the cardiac operating room (OR) to the cardiac surgical intensive care unit (CSICU). The aim of the study was to evaluate the impact of a standardized handoff process on patient care and provider satisfaction. DESIGN: A prospective, unblinded intervention study. SETTING: A CSICU in a teaching hospital. PARTICIPANTS: Two hundred thirty-eight health care practitioners during the transfer of care of 60 patients. INTERVENTIONS: The implementation of a standardized handoff protocol and checklist. MEASUREMENTS AND MAIN RESULTS: After the protocol's implementation, the presence of all handoff core team members at the bedside increased from 0% at baseline to 68% after intervention. The percentage of missed information in the surgery report decreased from 26% to 16% (p = 0.03), but the percentage of missed information in the anesthesia report showed no significant change (19% to 17%, p > 0.05). Handoff satisfaction scores among intensive care unit (ICU) nurses increased from 61% to 81%. On average, the duration of handoff increased by 1 minute. CONCLUSIONS: A standardized handoff protocol that guides the transfer of care from the OR team to the CSICU team can reduce the risk of missed information and improve satisfaction among perioperative providers.

Predictors of habitual snoring and obstructive sleep apnea risk in patients with asthma.

BACKGROUND: A high prevalence of obstructive sleep apnea (OSA) symptoms was reported in patients with asthma. Our goal was to evaluate factors associated with habitual snoring and OSA risk in these patients. METHODS: Patients with asthma were surveyed at specialty clinics with the Sleep Apnea scale of the Sleep Disorders Questionnaire (SA-SDQ) and questions about the frequency of asthma symptoms (National Asthma Education and Prevention Program guidelines), followed by medical record review. SA-SDQ scores >or= 36 for men and >or= 32 for women defined high OSA risk. Logistic regression was used to model associations with habitual snoring and high OSA risk. RESULTS: Among 244 patients, 37% snored habitually and 40% demonstrated high OSA risk. Independent predictors of habitual snoring included gastroesophageal reflux disease (GERD) [odds ratio (OR), 2.19; 95% confidence interval (CI), 1.19 to 4.02] and use of an inhaled corticosteroid (ICS) [OR, 2.66; 95% CI, 1.05 to 6.72]. High OSA risk was predicted by asthma severity step (OR, 1.59; 95% CI, 1.23 to 2.06), GERD (OR, 2.70; 95% CI, 1.51 to 4.83), and ICS use (OR, 4.05; 95% CI, 1.56 to 10.53). Linear, dose-dependent relationships of ICS with habitual snoring and high OSA risk were seen (p = 0.004 and p = 0.0006, respectively). Women demonstrated a 2.11 times greater odds for high OSA risk (95% CI, 1.10 to 4.09) when controlling for the above covariates. CONCLUSIONS: Symptoms of OSA in patients with asthma are predicted by asthma severity, coexistent GERD, and use of an ICS in a dose-dependent fashion. The well-recognized male gender predominance for OSA symptoms is not apparent in these patients. Further exploration of these relationships may help to explain the increased prevalence of OSA in asthma and provide new insights into the reported female predominance of asthma morbidity.

Correlates of daytime sleepiness in patients with asthma.

BACKGROUND AND PURPOSE: Patients with asthma often complain of daytime sleepiness, which is usually attributed to a direct effect of asthma on nocturnal sleep quality. We investigated this and other potential explanations for daytime sleepiness among asthmatics. PATIENTS AND METHODS: One hundred fifteen adult asthmatics were assessed for perceived daytime sleepiness (one question item), subjective sleepiness (Epworth Sleepiness Scale score, ESS), obstructive sleep apnea risk (Sleep Apnea scale score within Sleep Disorders Questionnaire, SA-SDQ), asthma severity step, relevant comorbid conditions, and current asthma medications. RESULTS: Among all subjects, 55% perceived excessive daytime sleepiness and 47% had ESS>10. Most subjects reported snoring (n=99, or 86%) and many snored habitually (n=44, 38%). The ESS correlated with SA-SDQ (P<0.0001), male gender (P=0.01), and asthma severity step (P=0.04). In a multiple regression model, the ESS was independently associated with SA-SDQ (P=0.0003) and male gender (P=0.02), but not with asthma severity step (P=0.51). There were no correlations between ESS and age, body mass index (BMI), forced expiratory volume in one second as percent of predicted value (FEV(1)%), comorbidities, or medication used to treat asthma. CONCLUSIONS: Sleepiness is common in asthmatics and may reflect occult obstructive sleep apnea more often than effects of asthma itself, other comorbid conditions, or asthma medications.