title: Cost prediction of antipsychotic medication of psychiatric disorder using artificial neural network model.
abstract: BACKGROUND
  Antipsychotic monotherapy or polypharmacy (concurrent use of two or more antipsychotics) are used for treating patients with psychiatric disorders (PDs). Usually, antipsychotic monotherapy has a lower cost than polypharmacy. This study aimed to predict the cost of antipsychotic medications (AM) of psychiatric patients in Iran.
  
  
  METHODS
  For this purpose, 790 patients with PDs who were discharged between June and September 2010 were selected from Razi Psychiatric Hospital, Tehran, Iran. For cost prediction of AM of PD, neural network (NN) and multiple linear regression (MLR) models were used. Analysis of data was performed with R 2.15.1 software.
  
  
  RESULTS
  Mean ± standard deviation (SD) of the duration of hospitalization (days) in patients who were on monotherapy and polypharmacy was 31.19 ± 15.55 and 36.69 ± 15.93, respectively (P < 0.001). Mean and median costs of medication for monotherapy (n = 507) were $8.25 and $6.23 and for polypharmacy (n =192) were $13.30 and $9.48, respectively (P = 0.001). The important variables for cost prediction of AM were duration of hospitalization, type of treatment, and type of psychiatric ward in the MLR model, and duration of hospitalization, type of diagnosed disorder, type of treatment, age, Chlorpromazine dosage, and duration of disorder in the NN model.
  
  
  CONCLUSIONS
  Our findings showed that the artificial NN (ANN) model can be used as a flexible model for cost prediction of AM.
authors.affiliation: Department of Psychiatric, Social Determinants of Health Research Center, University of Social Welfare and Rehabilitation Sciences (USWRS), Tehran, Iran.
authors.forename: Arash
authors.initials: A
authors.lastname: Mirabzadeh
authors.affiliation: Department of Biostatistics, University of Social Welfare and Rehabilitation Sciences (USWRS), Tehran, Iran.
authors.forename: Enayatollah
authors.initials: E
authors.lastname: Bakhshi
authors.affiliation: Department of Psychiatric, University of Social Welfare and Rehabilitation Sciences (USWRS), Tehran, Iran.
authors.forename: Mohamad Reza
authors.initials: MR
authors.lastname: Khodae
authors.affiliation: Master of Sciences of Psychology, Pediatric Neurorehabilitation Research Center, University of Social Welfare and Rehabilitation Sciences (USWRS), Tehran, Iran.
authors.forename: Mohamad Reza
authors.initials: MR
authors.lastname: Kooshesh
authors.affiliation: Master of Sciences of Psychology, Family Clinic, Shahid Beheshti University of Medical Sciences and Health Services, Tehran, Iran.
authors.forename: Bibi Riahi
authors.initials: BR
authors.lastname: Mahabadi
authors.affiliation: Master of Industrial Psychology, Tehran, Iran.
authors.forename: Hossein
authors.initials: H
authors.lastname: Mirabzadeh
authors.affiliation: Department of Biostatistics, University of Social Welfare and Rehabilitation Sciences (USWRS), Tehran, Iran.
authors.forename: Akbar
authors.initials: A
authors.lastname: Biglarian
keywords: Linear regression; neural networks; psychiatric disorders; treatment cost