March 3, 2022By Lance Baily

Medical Simulation Research: Costs & Value of Modeling-Based Healthcare Delivery Design

In many ways, the push for increased use of healthcare simulation was expedited by the COVID-19 pandemic, but some elements were slowed or halted. For example, during this time many medical simulation professionals were left in a unique position, one where they were unable to physically attend clinicals or meet with learners face-to-face. Reallocating their time and resources, some simulationists instead chose to further existing research efforts. One such clinical simulation leader, Professor TP Young, FBCS, of Datchet Consulting Ltd., seized this opportunity during lockdown to bring the past 20 years of his research alive. This article shares highlights from his research.

Having been shortlisted for an Operational Research Society Medal in 2020 (with Sada Soorapanth), he won Griffiths Medal last November (with Sada Soorapanth, Jim Wilkerson, Lance Millburg, Todd Roberts, and David Morgareidge) for a research paper that measured both the costs and benefits of health design projects. According to Young, this research enabled healthcare simulation leaders to say with real numbers how much a center or program should spend in design to avoid how much catastrophe downstream or to design in how much benefit for later. Yet, he believes his converse to be true as well-meaning that simulationists can choose not to model services and they know roughly how much they are leaving for someone to sort out later. The paper addresses computer-based models, but other forms of simulation should yield similar benefits.

“The early evidence (and we are at the start of really establishing the methods) is that every £1 spent in modeling is worth between £10 and £1,000 or more downstream. The cost of failure is particularly high in care services,” Young said. “It doesn’t really matter what sort of synthetic world you are using to design your new system, we can help you to work out the link between what gets spent upfront in design and what is gained (or must be recovered) later.”

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The foundation for this research began In the 1990s and early 2000s when Hollocks surveyed the use of Discrete Event Simulation (DES) in industry and listed (although he could not quantify the value of) benefits. When Young and colleagues surveyed the scene (e.g.: Simulation in health-care: lessons from other sectors) a decade later, they observed how little progress had been made in pinning down the benefits, so he set out to develop a value-for-money case with a protocol for collecting information. The costs and value of modeling-based design in healthcare delivery: five case studies from the U.S.

To do so, they presented a set of five DES case studies from the United State healthcare system and, following Hollocks, focused more on modeling as part of a rigorous design process. They ultimately captured as many of the benefits as possible. Although healthcare offers the possibility of ascribing value to health improvement, in these cases the value is primarily the operational benefits of a better service that are reported and monetized.

Of the five case studies presented, three were by an internal design team within a U.S. health system, and two by an architectural practice serving healthcare users. The benefits and savings were then estimated on the basis of the models where there is no further evidence of impact, but where there is, this is cited. Here is more information on the case studies:

  • Case study 1: extra elevator for OR patient flows | This project analyzed the floor usage and flow for all aspects of a design for a two-story operating room. Design process within which case studies 1–3 were conducted.
  • Case study 2: redesign of patient flows to CT | This 2014 study was to reduce patient waits for a CT in the Emergency Department (ED). Initial requests included the addition of a second CT in the ED to increase the throughput.
  • Case study 3: redesign of patient flows from ED towards | This 2015 program was designed to reduce the delay in placing a patient from ED in an appropriate inpatient bed, by setting a target of 2 h from request to occupation.
  • Case study 4: general practice clinic replacement | This study was undertaken for an affiliated practice of 8 General Practitioners (GPs) whose offices were collocated on three adjacent floors of a building, with a total combined clinic space of more than 50,000 square feet (4,700 m2 ), not including circulation and other common spaces.
  • Case study 5: operating room (OR) expansion | This 6-month study was commissioned when the hospital concerned was facing an increase of 29.4% in the volume of surgical cases and wanted to know whether its 12 ORs with a total of almost 8,000 square feet (740m2 ) of surgical procedure space (not including corridors, storage, air circulation, etc.) would suffice or whether new ORs would be required.

The authors thereby conclude that with a protocol for collecting information and a discussion of methods by which different types of benefit may be captured. When answering the question, “How far along the trajectory followed by other sectors has healthcare come?” the researchers note that, although they have focused on “industrialized” healthcare environments, they can still identify many features that Hollocks observed in earlier ecosystems, as modeling is being applied in operations, to facilities, and to productivity.

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The modeling is also being used by central teams or by groups with a responsibility to a central team, and for related reasons (a combination of cost and risk); selection of experiments is still a matter of judgment and there is evidence of design frameworks within which such choices are being made. They add that:

“However, where the cost of modeling itself was an issue 30–40 years ago, it is now minimal. Also greater than the cost of modeling are the costs of making decisions and then, on a different scale altogether, the cost of implementing the preferred options modeled. The perceived cost of failure (buying an unnecessary scanner, or lacking elevator capacity) appears to be driving demand.”

Responding to a second question, “What progress has been made in articulating the value-for-money case?” they share that on the immediate front, they found cases where, with good hospital data and with good business models (eg, how much a patient costs per minute in the system) comparing options and to monetize the value of the improvement becomes easy. Additionally, they report that sometimes the business case is particularly clear: do not build the extra OR or install the extra scanner. They conclude that the value-for-money case in such examples is now exceptionally easy to monetize.

They also identified benefits which are now possible to monetize, but which they have not been assessed, principally because there is a lack of conversion factors to convert the benefit, for instance, of earlier scanning or swifter allocation to award (or even treatment at home) into a health premium for a return on investment calculation. Ultimately, they recommend the further development of economic evaluation theory and production of approximate conversation factors to fill this gap.

This type of analysis is really only available in healthcare, where epidemiology provides precise information on the number of patients with each condition and their progression under different treatments, while health economics provides a way to convert the utility of different health states into cash. Whether it is possible to spend such currency or not, it has to be accounted for before we can have truly efficient outcomes-based healthcare.


Terry Young, Sada Soorapanth, Jim Wilkerson, Lance Millburg, Todd Roberts & David Morgareidge (2020) The costs and value of modelling-based design in healthcare delivery: five case studies from the US, Health Systems, 9:3, 253-262, DOI: 10.1080/20476965.2018.1548255

Read the Full Research Article Here

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