title: Semi-online patient scheduling in pathology laboratories.
abstract: OBJECTIVE
  Nowadays, effective scheduling of patients in clinics, laboratories, and emergency rooms is becoming increasingly important. Hospitals are required to maximize the level of patient satisfaction, while they are faced with lack of space and facilities. An effective scheduling of patients in existing conditions is vital for improving healthcare delivery. The shorter waiting time of patients improves healthcare service quality and efficiency. Focusing on real settings, this paper addresses a semi-online patient scheduling problem in a pathology laboratory located in Tehran, Iran, as a case study.
  
  
  METHODS
  Due to partial precedence constraints of laboratory tests, the problem is formulated as a semi-online hybrid shop scheduling problem and a mixed integer linear programming model is proposed. A genetic algorithm (GA) is developed for solving the problem and response surface methodology is used for setting GA parameters. A lower bound is also calculated for the problem, and several experiments are conducted to estimate the validity of the proposed algorithm.
  
  
  RESULTS
  Based on the empirical data collected from the pathology laboratory, comparison between the current condition of the laboratory and the results obtained by the proposed approach is performed through simulation experiments. The results indicate that the proposed approach can significantly reduce waiting time of the patients and improve operations efficiency.
  
  
  CONCLUSIONS
  The proposed approach has been successfully applied to scheduling patients in a pathology laboratory considering the real-world settings including precedence constraints of tests, constraint on the number of sites or operators for taking tests (i.e. multi-machine problem), and semi-online nature of the problem.
authors.affiliation: School of Industrial Engineering and Centre of Excellence for Intelligent Experimental Mechanics, College of Engineering, University of Tehran, PO Box 515-14395, Tehran, Iran. Electronic address: aazadeh@ut.ac.ir.
authors.forename: Ali
authors.initials: A
authors.lastname: Azadeh
authors.affiliation: Department of Industrial and Systems Engineering, Virginia Polytechnic Institute and State University, Blacksburg, VA, USA.
authors.forename: Milad
authors.initials: M
authors.lastname: Baghersad
authors.affiliation: School of Industrial Engineering and Centre of Excellence for Intelligent Experimental Mechanics, College of Engineering, University of Tehran, PO Box 515-14395, Tehran, Iran.
authors.forename: Mehdi Hosseinabadi
authors.initials: MH
authors.lastname: Farahani
authors.affiliation: School of Industrial Engineering and Centre of Excellence for Intelligent Experimental Mechanics, College of Engineering, University of Tehran, PO Box 515-14395, Tehran, Iran.
authors.forename: Mansour
authors.initials: M
authors.lastname: Zarrin
mesh_terms: D000465:Algorithms; D001071:Appointments and Schedules; D003198:Computer Simulation; D003695:Delivery of Health Care; D017598:Efficiency, Organizational; D006801:Humans; D020407:Internet; D007753:Laboratories / Q000458:organization & administration*; D016014:Linear Models; D009862:Online Systems / Q000458:organization & administration*; D010336:Pathology / Q000458:organization & administration*; D010561:Personnel Staffing and Scheduling; D013997:Time Factors; D014850:Waiting Lists; D057188:Workflow
keywords: Genetic algorithm; Health care operations management; Pathology laboratory; Patients scheduling; Response surface methodology