title: Factors affecting the unmet demand for pharmacists: state-level analysis.
abstract: 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.
  
  
  METHODS
  Cross-sectional time series analysis using state-level data.
  
  
  METHODS
  U.S. labor market for pharmacists, from 2001 to 2010.
  
  
  METHODS
  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.
  
  
  METHODS
  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.
  
  
  CONCLUSIONS
  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.affiliation: Eugene Applebaum College of Pharmacy & Health Sciences, Wayne State University, Detroit, MI, USA.
authors.forename: Thomas N
authors.initials: TN
authors.lastname: Taylor
authors.forename: Katherine K
authors.initials: KK
authors.lastname: Knapp
authors.forename: Mitchell J
authors.initials: MJ
authors.lastname: Barnett
authors.forename: Bijal M
authors.initials: BM
authors.lastname: Shah
authors.forename: Laura
authors.initials: L
authors.lastname: Miller
mesh_terms: D003430:Cross-Sectional Studies; D011307:Drug Prescriptions; D004651:Employment / Q000706:statistics & numerical data; D006301:Health Services Needs and Demand / Q000706:statistics & numerical data; D006801:Humans; D054524:Medicare Part D; D015233:Models, Statistical; D010593:Pharmaceutical Services / Q000706:statistics & numerical data; D010594:Pharmacies / Q000706:statistics & numerical data; D010595:Pharmacists / Q000706:statistics & numerical data / Q000600:supply & distribution*; D013997:Time Factors; D014478:Unemployment; D014481:United States; D000078329:Workforce; D016526:Workload