Mitchell J. Barnett

The Anabolic 500 Survey: Characteristics of Male Users versus Nonusers of Anabolic-Androgenic Steroids for Strength Training

Study Objective. To contrast the characteristics of two groups of men who participated in strength‐training exercise—those who reported anabolic‐androgenic steroid (AAS) use versus those who reported no AAS use.

Psychological and Physical Impact of Anabolic-Androgenic Steroid Dependence

To contrast the characteristics of two groups of anabolic‐androgenic steroid (AAS) users—those with versus those without AAS dependence.

Medication regimen complexity and readmissions after hospitalization for heart failure, acute myocardial infarction, pneumonia, and chronic obstructive pulmonary disease.

Objectives: Readmission rate is increasingly being viewed as a key indicator of health system performance. Medication regimen complexity index scores may be predictive of readmissions; however, few studies have examined this potential association. The primary objective of this study was to determine whether medication regimen complexity index is associated with all-cause 30-day readmission after admission for heart failure, acute myocardial infarction, pneumonia, or chronic obstructive pulmonary disease. Methods: This study was an institutional review board–approved, multi-center, case–control study. Patients admitted with a primary diagnosis of heart failure, acute myocardial infarction, pneumonia, or chronic obstructive pulmonary disease were randomly selected for inclusion. Patients were excluded if they discharged against medical advice or expired during their index visit. Block randomization was utilized for equal representation of index diagnosis and site. Discharge medication regimen complexity index scores were compared between subjects with readmission versus those without. Medication regimen complexity index score was then used as a predictor in logistic regression modeling for readmission. Results: Seven hundred and fifty-six patients were randomly selected for inclusion, and 101 (13.4%) readmitted within 30 days. The readmission group had higher medication regimen complexity index scores than the no-readmission group (p < 0.01). However, after controlling for demographics, disease state, length of stay, site, and medication count, medication regimen complexity index was no longer a significant predictor of readmission (odds ratio 0.99, 95% confidence interval 0.97–1.01) or revisit (odds ratio 0.99, 95% confidence interval 0.98–1.02). Conclusion: There is little evidence to support the use of medication regimen complexity index in readmission prediction when other measures are available. Medication regimen complexity index may lack sufficient sensitivity to capture an effect of medication regimen complexity on all-cause readmission.

The Effect of Trazodone on Standardized Field Sobriety Tests

To evaluate the effects of a single dose of trazodone on the standardized field sobriety test (SFST).

Factors affecting the unmet demand for pharmacists: State-level analysis

OBJECTIVE To describe the relationship between state-level Aggregate Demand Index (ADI) data and market factors reflecting both supply and demand: unemployment rates, pharmacy graduates, community pharmacy prescription growth rates, and Medicare Part D. DESIGN Cross-sectional time series analysis using state-level data. SETTING U.S. labor market for pharmacists, from 2001 to 2010. INTERVENTION Model ADI data for states (dependent variable) against five independent variables: previous year ADI, unemployment rates, pharmacy graduates, prescription growth rates, and Medicare Part D. MAIN OUTCOME MEASURES Significance and predictive ability of the model, sign of the variables studied, and R2. RESULTS In the two-way (state and time) fixed-effects model, all variables were significant and R2 was 0.79. Contributions to state-level ADIs were, in rank order, previous year ADI, unemployment rates, pharmacy graduates, and prescription growth rates. The model predicted 2010 ADI values for 44 of 51 states within ±10%. The model depicts the independent contributions of each variable for the short (∼1 year) and longer term. Although the nature of ADI data precludes quantitative predictions about the pharmacist job market, the model results show marketplace directions (up or down) and comparative impacts. CONCLUSION The model demonstrated that unemployment rates, pharmacy graduates, prescription growth rates, and Medicare Part D contributed significantly to state-level ADIs between 2001 and 2010. The relationships uncovered should be monitored and reexamined as new data emerge in order to anticipate the directions of the pharmacist job market.

Transitions of Care Pilot Programs—We Have Your Missing Positive Results

We read with great enthusiasm the recent article published in your journal entitled, “Implementation of a Cardiac Transitions of Care Pilot Program: A Prospective Study of Inpatient and Outpatient Clinical Pharmacy Services for Patients with Heart Failure (HF) Exacerbation or Acute Myocardial Infarction (AMI).” Murphy et al’s article details results of their pharmacist-lead, multidisciplinary Transitions of Care (TOC) Program tailored to cardiac patients. Specifically, the authors compared 30-day readmission rates for HF and AMI patients after implementation of their TOC Program relative to historical data as their primary outcome. They considered 72-hour emergency department (ED) visit rates, 30-day mortality, and compliance with follow-up medication therapy management (MTM) appointments as secondary outcomes. The study period ran approximately 2 years from 2013 through 2015 at a single facility in the Midwest and was comprised of 193 (100 HF and 93 AMI) patients. Unfortunately, the authors found no significant improvement in 30-day readmission rates, 72-hour ED visit rates, or 30-day mortality rates for either the HF or AMI group in unadjusted comparisons. Rates for 30-day readmission and 72-hour ED visits were actually equal or trended higher for both patient cohorts, while rates for follow-up MTM appointments appeared too low for meaningful comparisons. The authors did not report attempts to adjust for patient mix pre(historical) or post(study) TOC program, although no evidence was given to suggest that patient mix had changed from historical to study time period. The authors’ reasoning for lack of “positive findings” included possibility of clinicians diverting more challenging or sicker HF patients into the TOC program, the relative small sample of patients in the TOC program, limited amount of patients’ time, and possible patient geographical barriers. Despite the lack of evidence, the authors remained upbeat toward the potential of pharmacist-led TOC programs for HF and AMI patients to improve 30-day readmission rates and other outcomes. We wish to provide encouragement by briefly highlighting findings from our pharmacist-led TOC program, resulting from collaboration between pharmacy academia and a community hospital. It should be noted that highlights presented are from a similar period as Murphy et al’s study, namely a 2011 to 2015 time frame. In 2011, Touro University California College of Pharmacy (TUCCOP) and Sharp Memorial Hospital (Sharp) embarked on a collaborative relationship to expand the provision of novel pharmacy services at Sharp. It was thought that efficiency of Sharp’s TOC program or Continuum of Care Network (CCN) might be improved by making wider use of advanced pharmacy practice experience (APPE) students, along with cosponsored residents and faculty member. Studies from this collaboration include Backes and Truong, who reported a 50% reduction in readmission rates among 632 (162 CCN and 470 non-CCN patients) HF patients who received pharmacist-led TOC services, relative to those who did not (12% vs 24%, respectively; P < .001). Additionally, HF compliance rates improved from the 80th percentile to the 90th percentile. Since 2015, the CCN has worked to further prevent HF readmissions. A recent retrospective review by Bradford et al conducted on HF patients admitted to Sharp since 2008 identified patient and care characteristics that likely contribute to a heightened readmission risk. Results showed the majority of patients readmit beyond 7 days from the index visit discharge— suggesting ample patient time or availability for TOC programs. Lastly, results from Abou-Karam et al comprised of 756 patients with 5 diagnostic groups, including HF and AMI patients. Results demonstrated that medication complexity was significantly higher among readmission patients— suggesting a role for pharmacist-led TOC to help manage patients with complex medication regimens to reduce readmissions.

The impact of work-life balance on intention to stay in academia: Results from a national survey of pharmacy faculty

Purpose: Border‐Crossing theory suggests work‐life balance and career satisfaction are inter‐related and disappointment in work‐life balance may predict changes in ones career path. Application of this theory to health profession faculty is plausible but has not been fully explored. The purpose of this study is to examine factors related to reported career change intention among United States pharmacy school faculty and to determine if Border‐Crossing theory fits these observations. Methods: Results from a national web‐based survey administered via Qualtrics® to American Association of Colleges of Pharmacy (AACP) members were utilized. Bivariate analyses were conducted to compare differences among faculty stating an intention to stay or leave academia. A logistic multivariate model was used to determine if work‐life balance remains significant when controlling for other variables and if survey results support the Border‐Crossing theory. Results: Nearly all (seven hundred of 811 responders, or 86.3%) stated a desire to stay in academia. Faculty with higher work‐life balance were more likely to report an intent to remain in academia. Male, older, full‐professor and non‐pharmacy practice faculty (social or administrative science, pharmacology, medicinal chemistry and others) were more likely to state an intention to remain in academia relative to their counterparts. Lower stress, as measured by the validated Perceived Stress Scale (PSS) scores, was seen among faculty stating a desire to remain in academia. Work‐life balance remained significantly inversely related to career change intention after controlling for all other factors. Conclusion: A significant factor related to pharmacy facultys stated intention to remain in academia was work‐life balance. Other factors such as gender, age, rank, stress level and department may also play a role. These results support the application of the Border‐Crossing theory in health profession faculty and may provide pharmacy school administrators and stakeholders with insight to foster faculty retention and decrease faculty turnover.