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.
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.
Authors: Burgunda V Sweet; Katherine A Kelley; Kristin K Janke; Sarah E Kuba; Kimberly S Plake; Luke D Stanke; Gary C Yee Journal: Am J Pharm Educ Date: 2015-08-25 Impact factor: 2.047