RESUMO
Background: Opioid-related inpatient hospital stays are increasing at alarming rates. Unidentified and poorly treated opioid withdrawal may be associated with inpatients leaving against medical advice and increased health care utilization. To address these concerns, we developed and implemented a clinical pathway to screen and treat medical service inpatients for opioid withdrawal. Methods: The pathway process included a two-item universal screening instrument to identify opioid withdrawal risk (Opioid Withdrawal Risk Assessment [OWRA]), use of the validated Clinical Opiate Withdrawal Scale (COWS) to monitor opioid withdrawal symptoms and severity, and a 72-h buprenorphine/naloxone-based treatment protocol. Implementation outcomes including adoption, fidelity, and sustainability of this new pathway model were measured. To assess if there were changes in nursing staff acceptability, appropriateness, and adoption of the new pathway process, a cross-sectional survey was administered to pilot four hospital medical units before and after pathway implementation. Results: Between 2016 and 2018, 72.4% (77,483/107,071) of admitted patients received the OWRA screening tool. Of those, 3.0% (2,347/77,483) were identified at risk for opioid withdrawal. Of those 2,347 patients, 2,178 (92.8%) were assessed with the COWS and 29.6% (645/2,178) were found to be in active withdrawal. A total of 49.5% (319/645) patients were treated with buprenorphine/naloxone. Fifty-seven percent (83/145) of nurses completed both the pre- and post-pathway implementation surveys. Analysis of the pre/post survey data revealed that nurse respondents were more confident in their ability to determine which patients were at risk for withdrawal (p = .01) and identify patients currently experiencing withdrawal (p < .01). However, they cited difficulty working with the patient population and coordinating care with physicians. Conclusions: Our study demonstrates a process for successfully implementing and sustaining a clinical pathway to screen and treat medical service inpatients for opioid withdrawal. Standardizing care delivery for patients in opioid withdrawal can also improve nursing confidence when working with this complex population.
RESUMO
BACKGROUND: Increasing adoption of electronic health records (EHRs) with integrated alerting systems is a key initiative for improving patient safety. Considering the variety of dynamically changing clinical information, it remains a challenge to design EHR-driven alerting systems that notify the right providers for the right patient at the right time while managing alert burden. The objective of this study is to proactively develop and evaluate a systematic alert-generating approach as part of the implementation of an Early Warning Score (EWS) at the study hospitals. METHODS: We quantified the impact of an EWS-based clinical alert system on quantity and frequency of alerts using three different alert algorithms consisting of a set of criteria for triggering and muting alerts when certain criteria are satisfied. We used retrospectively collected EHRs data from December 2015 to July 2016 in three units at the study hospitals including general medical, acute care for the elderly and patients with heart failure. RESULTS: We compared the alert-generating algorithms by opportunity of early recognition of clinical deterioration while proactively estimating alert burden at a unit and patient level. Results highlighted the dependency of the number and frequency of alerts generated on the care location severity and patient characteristics. CONCLUSION: EWS-based alert algorithms have the potential to facilitate appropriate alert management prior to integration into clinical practice. By comparing different algorithms with regard to the alert frequency and potential early detection of physiological deterioration as key patient safety opportunities, findings from this study highlight the need for alert systems tailored to patient and care location needs, and inform alternative EWS-based alert deployment strategies to enhance patient safety.