title: Explaining primary healthcare pharmacy expenditure using classification of medications for chronic conditions.
abstract: BACKGROUND
  The Valencian Autonomous Community (Spain) has implemented a scheme of purchasing services with the participation of public and private providers. Five districts are managed using public-private partnership. The financing model is capitation and inter-center invoice. The pharmaceutical benefits are not included in the per capita assignment.
  
  
  OBJECTIVE
  Modeling and explaining pharmacy expenditure using electronic prescriptions drug data.
  
  
  METHODS
  A database of electronic prescription corresponding to 625,246 patients between November 2008 and October 2009 was used to run four linear models that explain the pharmaceutical expenditures. We take as dependent variable the neperian log of total pharmacy annual cost per patient in the primary health setting. The independent variables used combined demographics with revised classification in 18 chronic conditions obtained from the anatomical therapeutic chemical classification index (ATC).
  
  
  RESULTS
  The retrospective model selected included: gender, pharmaceutical co-payment status and 8 dummy variables for the number of chronic conditions of each patient from 1 to 8 or more. The goodness-of-fit achieved is measured in R(2) of 57%.
  
  
  CONCLUSIONS
  These models must be considered in the current capitation system for pharmaceutical budgeting in a primary care setting established at regional level, as is the case in the Valencian Autonomous Community. The use of diagnostics and information regarding hospital encounters appears to be a complementary option for refining models of capitation of pharmaceutical and total health expenditure.
authors.affiliation: Research Centre for Health Care Economic and Management, Universitat Politècnica de València, Cno de Vera s/n, Valencia, Spain. dvivas@upv.es
authors.forename: David
authors.initials: D
authors.lastname: Vivas
authors.forename: Natividad
authors.initials: N
authors.lastname: Guadalajara
authors.forename: Isabel
authors.initials: I
authors.lastname: Barrachina
authors.forename: José-Luis
authors.initials: JL
authors.lastname: Trillo
authors.forename: Ruth
authors.initials: R
authors.lastname: Usó
authors.forename: Elena
authors.initials: E
authors.lastname: de-la-Poza
mesh_terms: D000293:Adolescent; D000328:Adult; D000367:Age Factors; D000368:Aged; D000369:Aged, 80 and over; D002648:Child; D002675:Child, Preschool; D002908:Chronic Disease / Q000145:classification / Q000188:drug therapy*; D016527:Drug Costs / Q000706:statistics & numerical data; D005260:Female; D006801:Humans; D007223:Infant; D008297:Male; D008875:Middle Aged; D018803:Models, Economic; D009313:National Health Programs / Q000191:economics / Q000706:statistics & numerical data; D055553:Prescription Drugs / Q000145:classification / Q000191:economics / Q000627:therapeutic use; D011320:Primary Health Care / Q000191:economics* / Q000706:statistics & numerical data; D013030:Spain; D055815:Young Adult
chemical_list: D055553:Prescription Drugs