Integrated Process Mining & Simulation-Optimization Framework For Healthcare Design

Farouq Halawa, Alice Gittler, Sreenath Chalil Madathila, Mohammad T. Khasawneh 

Department of Systems Science and Industrial Engineering,     

Binghamton University, New York  EwingCole, New York


  • Simulation-optimization is an underutilized methodology to test and better inform healthcare facility programming and design1.• 17% of hospital design projects have applied simulation modeling during facility planning and design in the US2.
  • The average age of healthcare facilities in the US exceeds 30 years, and growth in new building projects is expected for both inpatient and outpatient facilities3.
  • Challenges for timely application of simulation during healthcare design projects include:
    Highly variable workflows and lack of electronic health records (EHR) data matched to locations.
  • Time required for detailed observation and data collection/processing.
  • ISE/OR methods still in nascent phase in architecture.



  • Improve healthcare facility layout planning by adopting data-driven approaches to account for variability in patient pathways and volumes in the early stages of the design process.



  • Three-phase framework for healthcare facility layout planning.
    • Phase 1: Probabilistic deterministic automata4 to extract significant patient pathways.
    • Phase 2: Discrete-event simulation for right-sizing and space programming.
    • Phase 3: Automated layout planning using Facility Layout Problem1 solved by Genetic Algorithm.
  • Apply framework during the programming and design of a heart and vascular clinic to validate the approach.



Setting: New Outpatient Heart and Vascular
Timing: Schematic Design and Spatial Program Reconciliation



  • Determine optimal number of spaces (exam, imaging, procedural) to reach an acceptable level of utilization (60-80%) and minimize patient waiting time.
  • Optimize spatial layout to maximize efficiency of patient and staff flows.



  • Real-time decision support and collaboration with facilities, operational, and clinical leadership.
  • Data-driven approach required limited on-site timestamp documentation.
  • Process mining allowed identification of significant flows (reduced noise in the data).
  • 8 significant out of 90 variants for Heart and Vascular Clinic.
  • Discovered total cost saving of $242,250.
  • Developed optimal spatial layout informed by flow-frequency analysis and genetic algorithm.



  • The practice of healthcare, particularly in the clinic setting, involves highly variable patient flows, however only a few are significant and can be extracted using process mining.
  • Simulation modeling optimizes space requirements in the context of operational objectives and can identify significant cost savings.
  • Outputs of simulation and process mining can enable automated layout planning based on significant flows.
  • OR methods have great potential to ensure facility designs actively support better care quality and efficiency.
  • This research will develop further algorithms for layout automation.



  1. Vahdatzad, V., et al. (2019) ‘Improving patient timeliness of care through efficient outpatient clinic layout design using data-driven simulation and optimization Improving patient timeliness of care through efficient outpatient’, Health Systems, pp. 1–22.
  2. Health Facilities Management/ASHE 2017 Hospital Construction Survey.
  3. Healthcare Design Magazine.
  4. Arnolds, I. V. and Gartner, D. (2018) ‘Improving hospital layout planning through clinical pathway mining’, Annals of Operations Research. Springer, 263(1–2), pp. 453–477.