Phenobarbital versus benzodiazepines in alcohol withdrawal syndrome.

AIM: Phenobarbital, a long-acting barbiturate, presents an alternative to conventional benzodiazepine treatment for alcohol withdrawal syndrome (AWS). Currently, existing research offers only modest guidance on the safety and effectiveness of phenobarbital in managing AWS in hospital settings. The study objective was to assess if a phenobarbital protocol for the treatment of AWS reduces respiratory complications when compared to a more traditionally used benzodiazepine protocol. METHODS: A retrospective cohort study analyzing adults who received either phenobarbital or benzodiazepine-based treatment for AWS over a 4-year period, 2015-2019, in a community teaching hospital in a large academic medical system. RESULTS: A total of 147 patient encounters were included (76 phenobarbital and 71 benzodiazepine). Phenobarbital was associated with a significantly decreased risk of respiratory complications, defined by the occurrence of intubation (15/76 phenobarbital [20%] vs. 36/71 benzodiazepine [51%]) and decreased incidence of the requirement of six or greater liters of oxygen when compared with benzodiazepines (10/76 [13%] vs. 28/71 [39%]). There was a significantly higher incidence of pneumonia in benzodiazepine patients (15/76 [20%] vs. 33/71 [47%]). Mode Richmond Agitation Sedation Scale (RASS) scores were more frequently at goal (0 to -1) between 9 and 48 h after the loading dose of study medication for phenobarbital patients. Median hospital and ICU length of stay were significantly shorter for phenobarbital patients when compared with benzodiazepine patients (5 vs. 10 days and 2 vs. 4 days, respectively). CONCLUSION: Parenteral phenobarbital loading doses with an oral phenobarbital tapered protocol for AWS resulted in decreased risk of respiratory complications when compared to standard treatment with benzodiazepines.

Implementation of a telehealth videoconference to improve hospital-to-skilled nursing care transitions: Preliminary data.

BACKGROUND: Transition-related patient safety errors are high among patients discharged from hospitals to skilled nursing facilities (SNFs), and interventions are needed to improve communication between hospitals and SNF providers. Our objective was to describe the implementation of a pilot telehealth videoconference program modeled after Extension for Community Health Outcomes-Care Transitions and examine patient safety errors and readmissions. METHODS: A multidisciplinary telehealth videoconference program was implemented at two academic hospitals for patients discharged to participating SNFs. Process measures, patient safety errors, and hospital readmissions were evaluated retrospectively for patients discussed at weekly conferences between July 2019-January 2020. Results were mapped to the constructs of the Reach, Effectiveness, Adoption, Implementation, Maintenance (RE-AIM) model. Descriptive statistics were reported for the conference process measures, patient and index hospitalization characteristics, and patient safety errors. The primary clinical outcome was all-cause 30-day readmissions. An intention-to-treat (ITT) analysis was conducted using logistic regression models fit to compare the probability of 30-day hospital readmission in patients discharged to participating SNFs across 7 months prior to after telehealth project implementation. RESULTS: There were 263 patients (67% of eligible patients) discussed during 26 telehealth videoconferences. Mean discussion time per patient was 7.7 min and median prep time per patient was 24.2 min for the hospital pharmacist and 10.3 min for the hospital clinician. A total of 327 patient safety errors were uncovered, mostly related to communication (54%) and medications (43%). Differences in slopes (program period vs. pre-implementation) of the probability of readmission across the two time periods were not statistically significant (OR 0.95, [95% CI 0.75, 1.19]). CONCLUSIONS: A pilot care innovations telehealth videoconference between hospital-based and SNF provider teams was successfully implemented within a large health system and enhanced care transitions by optimizing error-prone transitions. Future work is needed to understand process flow within nursing homes and its impact on clinical outcomes.