An Algorithm for Opioid and Barbiturate Reduction in the Acute Management of Headache in the Emergency Department.

OBJECTIVE: To develop and implement an algorithm for the management of headaches presenting to the emergency department (ED) in order to decrease the frequency of opioid and barbiturate treatment both acutely as well as on discharge. BACKGROUND: Headache is the fifth leading cause of ED visits in the United States. In the case of primary headache, particularly migraine, treatment in the ED can be highly variable. Patients with migraine continue to be treated with opioids more commonly than nonopioid, migraine specific medications. In addition, discharge plans seldom include measures to prevent recurrence or instructions to re-treat if pain persists. At this time, there is no standardized management protocol directed at acute headaches presenting to the ED. METHODS: An ED headache treatment algorithm with step-wise instructions for diagnosis, treatment, and discharge planning was piloted at Lakewood Hospital, a regional Cleveland Clinic affiliated hospital. This non-randomized interventional study compared outcomes after implementation of the algorithm to historical controls. Patient demographic data including age, gender, and payer mix was collected. Outcomes measured included the frequency of treatment with opioids or barbiturates, imaging, neurology consults, admissions, and a patient reported pain score. Data relevant to patient disposition and follow-up, including prescriptions for opioids or barbiturates given at discharge, and ensuring PCP or neurology follow-up appointments at discharge was also reviewed. RESULTS: Demographic data did not differ significantly between the pre- and post-algorithm groups. There was a significant decline in the number of patients treated with opioids and barbiturates from 66.0% pre-algorithm to 6.8% immediately after algorithm implementation (P <. 001), and to 28% (P < .001) one year after algorithm implementation, indicating both an immediate effect of the algorithm and a sustained effect. Similarly, pre-algorithm implementation, 37% of patients were discharged with a prescription for opioids or barbiturates as compared to 12% and 6% in the early post-algorithm cohort and at 1 year, respectively. There was also an increase in scheduled follow-up appointments after discharge from the ED from 59% to 98% immediately post algorithm (P < .001). Other measures including the frequency of imaging, and patient reported pain did not significantly change. There was a significant increase in neurology consults and admissions a year after the algorithm was implemented. CONCLUSIONS: A quality improvement pilot study aimed at treating headache in an Emergency Department setting was successfully implemented in a regional Cleveland Clinic Hospital. Our results demonstrated significant decrease in acute treatment with opioids or barbiturates and a decrease in prescriptions written for opioids or barbiturates on discharge. This study is limited by small sample size. More data are needed to determine the reason for 1) increased consultation and subsequent admission after algorithm implementation and 2) decreased scheduled follow-up appointments at one-year post algorithm.

Cost Analysis of the Addition of Hyperacute Magnetic Resonance Imaging for Selection of Patients for Endovascular Stroke Therapy.

BACKGROUND AND PURPOSE: Patient selection is important to determine the best candidates for endovascular stroke therapy. In application of a hyperacute magnetic resonance imaging (MRI) protocol for patient selection, we have shown decreased utilization with improved outcomes. A cost analysis comparing the pre- and post-MRI protocol time periods was performed to determine if the previous findings translated into cost opportunities. MATERIALS AND METHODS: We retrospectively identified individuals considered for endovascular stroke therapy from January 2008 to August 2012 who were ≤8 h from stroke symptoms onset. Patients prior to April 30, 2010 were selected based on results of the computed tomography/computed tomography angiography alone (pre-hyperacute), whereas patients after April 30, 2010 were selected based on results of MRI (post-hyperacute MRI). Demographic, outcome, and financial information was collected. Log-transformed average daily direct costs were regressed on time period. The regression model included demographic and clinical covariates as potential confounders. Multiple imputation was used to account for missing data. RESULTS: We identified 267 patients in our database (88 patients in pre-hyperacute MRI period, 179 in hyperacute MRI protocol period). Patient length of stay was not significantly different in the hyperacute MRI protocol period as compared to the pre-hyperacute MRI period (10.6 vs. 9.9 days, p < 0.42). The median of average daily direct costs was reduced by 24.5% (95% confidence interval 14.1-33.7%, p < 0.001). CONCLUSIONS: Use of the hyperacute MRI protocol translated into reduced costs, in addition to reduced utilization and better outcomes. MRI selection of patients is an effective strategy, both for patients and hospital systems.