title: Predicting the demand of physician workforce: an international model based on "crowd behaviors".
abstract: BACKGROUND
  Appropriateness of physician workforce greatly influences the quality of healthcare. When facing the crisis of physician shortages, the correction of manpower always takes an extended time period, and both the public and health personnel suffer. To calculate an appropriate number of Physician Density (PD) for a specific country, this study was designed to create a PD prediction model, based on health-related data from many countries.
  
  
  METHODS
  Twelve factors that could possibly impact physicians' demand were chosen, and data of these factors from 130 countries (by reviewing 195) were extracted. Multiple stepwise-linear regression was used to derive the PD prediction model, and a split-sample cross-validation procedure was performed to evaluate the generalizability of the results.
  
  
  RESULTS
  Using data from 130 countries, with the consideration of the correlation between variables, and preventing multi-collinearity, seven out of the 12 predictor variables were selected for entry into the stepwise regression procedure. The final model was: PD = (5.014 - 0.128 × proportion under age 15 years + 0.034 × life expectancy)2, with R2 of 80.4%. Using the prediction equation, 70 countries had PDs with "negative discrepancy", while 58 had PDs with "positive discrepancy".
  
  
  CONCLUSIONS
  This study provided a regression-based PD model to calculate a "norm" number of PD for a specific country. A large PD discrepancy in a country indicates the needs to examine physician's workloads and their well-being, the effectiveness/efficiency of medical care, the promotion of population health and the team resource management.
authors.affiliation: Department of Pediatrics, E-Da Hospital, Kaohsiung City, Taiwan, Republic of China. tsaitc2003@gmail.com
authors.forename: Tsuen-Chiuan
authors.initials: TC
authors.lastname: Tsai
authors.forename: Misha
authors.initials: M
authors.lastname: Eliasziw
authors.forename: Der-Fang
authors.initials: DF
authors.lastname: Chen
mesh_terms: D001723:Birth Rate; D003441:Crowding; D005260:Female; D059066:Gross Domestic Product; D005102:Health Expenditures; D006305:Health Status Indicators; D006801:Humans; D008017:Life Expectancy; D016014:Linear Models; D008297:Male; D009026:Mortality / Q000639:trends; D010820:Physicians / Q000600:supply & distribution*; D011156:Population Density; D011237:Predictive Value of Tests; D017678:Sex Distribution; D012923:Social Class; D014944:World Health Organization