Mapping Patient Journeys and Optimising Hospital Designs for People Flow:
Agent-Based Modelling Techniques
R Hayward, D Brocklehurst, S B Sharma
a
Buro Happold Ltd, Camden Mill, Lower Bristol Road, Bath BA2 3DQ, UK
a
Associate Director, Email: [email protected], Tel: +44-1225-320600, Fax: +44-870-7874148
Abstract
In this article, a methodology is introduced to simulate, analyse and optimise hospital designs using agentbased simulation techniques. These powerful simulation techniques are increasingly used in the design of
airports, transport hubs, sport stadia, and schools but rarely for the healthcare sector.
Hospitals are complex dynamic systems, with management, buildings, facilities and processes that can be
difficult to understand from a quantified and holistic viewpoint. They are also systems that often experience
under-resourcing, long waiting, queuing, bed/equipment shortages, and process constraints. Using efficient
dynamic simulation models help assess the performance and bottlenecks of hospital designs taking into account
the related variables. Our overall goal of utilising the simulation is to help achieve buildings that are as
sustainable and efficient as possible whilst maximising patient comfort.
This article shows the development and application of a high level methodology for simulating and optimising
hospital designs. The methodology involves the consideration of the following elements:
Hospital Location and Typology (e.g. Emergency, Outpatients or Inpatients)
Patient Needs and Goals
Processes
Staffing
Hospital resources
Building Design (overall layout as well as lifts and stairs)
Each of the elements is accounted for within a holistic agent-based model, designed to aid understanding of the
hospital system. Two case studies are presented, clearly demonstrating the value of agent-based simulation
techniques within the building industry. The first case-study is used to inform an existing Accident & Emergency
Department, with the second case study informing a proposed Orthopaedics Hospital design optioneering.
Background and previous work
There is a strong need for a reliable and validated modelling method for analysing the performance of hospitals
from patient and staff experience perspectives, evidenced by several problems in new and existing hospitals.
A significant amount of literature exists on the modelling and simulation of hospital movements (Abdur Rais,
2010; Pidd, 2010). Studies typically focus on optimising efficiency indicators such as length of stay, waiting
times, and throughput by changing processes or altering the allocation of human and technical resources (S C
Brailsford, 2009). There is very little work to date that attempts to understand the relationship between
building design and hospital operational efficiency / effectiveness despite evidence suggesting that
conventional design practices over-estimate building occupancy and thus space is inappropriately designed and
thus allocated (Bacon, 2012; Zhengwei Li, 2009).
Spatial analysis including agent based modelling method should be able to contribute to the improvement of
efficiency and effectiveness of hospitals by helping to design spaces that more closely meet their functional
requirements with respect to accessibility, way-finding and safety (F. Pascale, 2012). These analyses may be
able to identify opportunities to reduce wasted space, unnecessary movement and improve the conditions
people experience whilst waiting or moving around a hospital.
In this paper we demonstrate an implementation of dynamic agent based simulation (Sharma, 2007) to
evaluate, benchmark and enhance patient, staff and visitor movements within the hospitals.
Implementation and case study examples
The paper presents a developing agent-based methodology for analysing and informing in-patient and outpatient hospitals. We present two case studies that illustrate how the methodology and software
implementations can be applied to improving the efficiency of existing hospital processes/management as well
as proposed new hospitals.
1.
Queen’s Hospital Accident &Emergency (A&E) department
With an aim to capturing and resolving key bottlenecks in this existing A&E department to improve patient
waiting times and processing efficiency, the work included modelling of existing operations as well as “what-if”
scenarios of increased patient numbers (due to the planned closure of a local A&E department) and different
combinations of staff resourcing (Rapid Assessment Treatment vs Triage) within current and proposed designs.
2.
An orthopaedic hospital
We used agent based simulations to support optioneering of the design proposals for this state of art
orthopaedic hospital. By modelling the detailed activity patterns and movements of patients, medical staff, FM
staff and visitors we were able to predict likely occupancy and densities throughout the day. The output was
interactively used to assess the performance of the designs as they evolved, optimising the building layout, bedroom locations, corridor and stair widths and lift size/numbers and locations against parameters such as travel
distances, waiting times, queues and bed-bed conflicts in corridors.
References:
Abdur Rais, A. V. (2010). Operations Research in Healthcare: a survey. International Transactions in Operational Research , 1-31.
Bacon, M. (2012). Occupancy analytics - a new science for energy efficient hospital design. Health and Care Infrastructure and Innovation
Centre Conference 2012, (pp. 67-75). Cardiff.
F. Pascale, N. A. (2012). Evaluation, analysis and benchmarking of the design of emergency departments in Italy. Health and Care
Infrastructures and Innovation Centre International Conference 2012 (pp. 93-99). Cardiff.
Pidd, M. M. (2010). Discrete event simulation for performance modelling in health care: a review of the literature. Journal of Simulation.
S C Brailsford (2009). An analysis of the academic literature on simulation and modelling in health care. Journal of Simulation , 130-140.
Zhengwei Li, Y. H. (2009). HVAC Design Informed By Organizational Simulation. Building Simulation, (pp. 2198-2203). Glasgow.
Sharma, S B. A static-dynamic network model for crowd flow simulation. In: 6th International Symposium on Space Syntax, 12-15 Jun 2007,
Istanbul, Turkey.