Comparison of 3 Surveillance Methods to Detect Potential Controlled Substance Diversion in an Academic Medical Center.

Objectives: To compare 3 methods of detecting potential diversion of controlled substances (CS) by health care personnel from inpatient units in a large, academic medical center. Methods: Three different reports were retrospectively analyzed and evaluated to determine which employees are "high-risk" for diversion over a 30-day period using defined criteria. Reports were derived from automated dispensing machines (ADMs), purchased third-party software (TPS), and the electronic health record (EHR). The primary outcome was the percentage of employees in each report who were deemed to be high-risk for CS diversion (positive predictive value [PPV]). Secondary outcomes included the number of false positives and description of high-risk users on each report. Descriptive statistics were used to analyze differences between methods. Results: The PPV was highly variable between reports. The PPVs among the ADM, TPS, and EHR reports were 3.28%, 6.82%, and 23.88%, respectively. False positives were high among all reports (96.72%, 93.18%, and 76.12% for the ADM, TPS, and EHR reports, respectively). Conclusions: A report from the EHR has the highest PPV to detect high-risk employees who may be diverting CS. However, false positives were high for all reports, indicating that significant improvements are needed in the development of accurate and reliable software to detect potential and actual CS diversion.

Implementation of a prioritized scoring tool to improve time to pharmacist intervention.

PURPOSE: The implementation of a prioritized scoring tool to improve time to pharmacist intervention is described. SUMMARY: At the Ohio State University Wexner Medical Center, pharmacists are accepted providers of therapeutic drug monitoring of vancomycin and aminoglycosides. At the onset of this initiative and despite the implementation of an integrated electronic medical record (EMR), management of pharmacokinetically monitored medications was conducted using a paper monitoring form. The potential for transcription errors during this process provided an opportunity for improvement. For these reasons, the department of pharmacy focused its initial efforts for a patient scoring system on the pharmacokinetics scoring module. Adjustment of associated medications based on pharmacokinetic values was a core function of pharmacists of the institution and was expected to be conducted without fail. Vancomycin was used as the index surrogate pharmacokinetically monitored medication within the module for testing and validation because of the clear expectations and standardized resources available to pharmacists to complete the task. The pharmacokinetics scoring module was designed specifically for the function of dosing management, searching throughout the EMR and concisely displaying the information a pharmacist needs to make a clinical decision. Importantly, integration of the scoring module reduced the time to intervention from hours to minutes. The median time to intervention was reduced to within a clinical working shift (8 hours) with the scoring module versus 24 hours or longer with the paper monitoring system. CONCLUSION: The implementation of an internally developed pharmacokinetics scoring module built into the EMR substantially reduced the time to clinical intervention for pharmacokinetic monitoring of vancomycin drug levels.

Factors Associated With Burnout Among US Hospital Clinical Pharmacy Practitioners: Results of a Nationwide Pilot Survey.

Background: In health care, burnout has been defined as a psychological process whereby human service professionals attempting to positively impact the lives of others become overwhelmed and frustrated by unforeseen job stressors. Burnout among various physician groups who primarily practice in the hospital setting has been extensively studied; however, no evidence exists regarding burnout among hospital clinical pharmacists. Objective: The aim of this study was to characterize the level of and identify factors independently associated with burnout among clinical pharmacists practicing in an inpatient hospital setting within the United States. Methods: We conducted a prospective, cross-sectional pilot study utilizing an online, Qualtrics survey. Univariate analysis related to burnout was conducted, with multivariable logistic regression analysis used to identify factors independently associated with the burnout. Results: A total of 974 responses were analyzed (11.4% response rate). The majority were females who had practiced pharmacy for a median of 8 years. The burnout rate was high (61.2%) and largely driven by high emotional exhaustion. On multivariable analysis, we identified several subjective factors as being predictors of burnout, including inadequate administrative and teaching time, uncertainty of health care reform, too many nonclinical duties, difficult pharmacist colleagues, and feeling that contributions are underappreciated. Conclusions: The burnout rate of hospital clinical pharmacy providers was very high in this pilot survey. However, the overall response rate was low at 11.4%. The negative effects of burnout require further study and intervention to determine the influence of burnout on the lives of clinical pharmacists and on other health care-related outcomes.