“Big data” is defined as information produced through computer modeling at high volume and high velocity that’s used to analyze variability and complexity. The availability of big data today is influencing healthcare delivery, reimbursement rates, and—increasingly—architectural design.

Specifically, under the Affordable Care Act, providers are now being measured against national metrics, with patient satisfaction, length of stay, readmissions, staff retention, and infection rates affecting the bottom line of our hospitals in a pay-for-value system. A health system must demonstrate payment incentives to providers who show quality improvement as measured against national results. For example, a hospital that implemented a new lighting and acoustic environment at medication areas may report a 20 percent error reduction. This improvement, if it meets a stated goal, will result in an overall increase in the reimbursement rate for the year.

Understanding the goals a client has for improvement metrics can inform the design process. An institution may focus on improved patient satisfaction through decreasing the amount of time spent on non-value-added activities such as waiting. Early project phases might include computer simulation models that test patient movement through the building. These models can tell architects how long it takes to park and walk to the facilities, and then how many greeters, kiosks, or check-in staff are required to keep the wait time below the set goal. The availability of this data offers the ability to predict bottlenecks in the flow of patients through a given building configuration, and design changes can be made to optimize the time that any patient spends within the facility.

Access to computer modeling means design teams can offer greater service to clients by integrating a scientific approach within a framework of humanistic values—what is it that the users touch, hear, smell, and see? These values are hard to measure but integral to creating a sense of well-being, so it’s important that they’re considered in concert with efficiency, safety, and infection control. Big data is beginning to provide metrics to back up design intuition tied to these variables: The room with a view of nature is now shown by data to be healthier for a patient.

There are three different ways that design processes change as a result of data and integrated technology, with modeling answering questions once relegated to theory and intuition.

Client and design team communication
Architects continually explore ways to better communicate to ensure informed and confident client decisions. With client groups often varied—including hospital management, clinical leadership, building users, and the surrounding community—the challenge is to build consensus among these constituents around a complex project proposal.

Virtual tools (digital simulations of reality) are used by design and construction firms to tackle the process of describing building options and facilitating consensus. For example, a 3-D virtual model allows designers and stakeholders to experience the space and configuration of equipment, while newer hands-on tools like virtual reality glasses and gloves allow a full-sensory spatial experience. Users can test in real time whether operating room booms and lights will interfere with one another; owners can preview the effectiveness of lighting and sight lines.

An animated walk-through of the entry sequence to a new hospital lobby can assure clients that the architectural team delivered an arrival space that provides the appropriate first impression, security control, and key wayfinding cues. The accuracy of these visual models is tied to the amount of real data that can be utilized: Specific building and environmental information as well as an overlay of occupant tracking data are required. Who’s coming through the door and at what rate? Where are they going and where do they stop for help? This is where the work becomes dependent on larger quantities of data to really understand the human experience within a facility.

The evolution of BIM
Construction documentation is changing with the use of building information modeling (BIM), affecting team structure, information flow, and document standards. All work on a project is tied to a live model where all design information is available to export, measure, test, and manipulate. While BIM alone isn’t big data, it provides a platform of data to utilize for new lines of inquiry. For example, architects and engineers can push BIM to new levels to provide optimization, predictive modeling, and operational and statistical analyses.

Sustainability issues can be explored, such as how to control heat gain or increase thermal comfort through façade design. Parametric modeling—producing a series of options based on a combination of fixed relationships that respond to a finite set of variables—can be employed to enhance traditional ways architects study building solutions. For instance, if an architect proposes a façade treatment using external shading devices, parametric modeling can be used to illustrate a sophisticated response, such as window shading louvers outside patient rooms on the west side of a building. One can model, perhaps with a 3-D printer, the variations required for other exposures of the building and the sun angle.

There’s also potential to run an analysis examining financial patterns that cross building parameters, such as the efficacy of different exam room-to-clinician ratios. Or if accidents are mapped to floor plans, including variables such as the age of patients, types of accidents, and times of day, it might be possible to find trends to inform design that prevents falls.

These types of inquiries are possible given the robust infrastructure of the BIM model and how data can be pulled from it and conversely input to generate graphic relationships. Moreover, these investigations can show how effectively an organization is addressing quality controls in the environment and help answer the larger question of how well a system is responding to the challenges of delivering high-quality care at a lower cost.

Research and design
Architects propose, measure, track, and evaluate alternate design solutions with a scientific eye. There are several prominent methodologies being used to bring research to healthcare design, including Lean/process development, evidence-based design (EBD), patient safety metrics, and the WELL Building Standard. All of these methodologies are grounded in setting objectives and measuring end results.

For instance, an EBD project may try to decrease the prevalence of slips and falls by introducing a new flooring surface. Measuring the current state and then re-measuring after the flooring is installed may show a significant decrease in incidents. That decrease can be measured monetarily in savings to the hospital through shorter lengths of stay and fewer medical interventions.

The complexity of an investigation and how many variables are tracked tie back to the threshold of “big data.” Are patient age, diagnosis, time of day, unit location, status of “accompanied” or “alone,” cleaning schedules, and medication all being tracked for a richer understanding of slips and falls? This will help determine if incidents are due to floor conditions or something beyond the environment of care. For example, the change in flooring may be part of a solution but also help to reveal a second relationship that ties slips and falls to a particular rhythm of the nursing shift. These types of layered investigations studying multiple variables can lead to more complex strategies in addressing operational challenges.

The future
Looking forward to the next 10 years, healthcare architecture will continue to transform. The trends outlined here will grow, and it’s probable that building design will be tied to population-based medicine. The issues are huge—where will healthcare occur? Will it be at home, at work, or in traditional healthcare environments? Will patients interact with healthcare providers in person or via telemedicine? And what role will buildings play?

Much of the process of healthcare design, for the design team and the users, is to cover all the possibilities—all the what-ifs. The tasks are to understand the current state, predict human behavior, and anticipate change. Data and analysis will provide a stronger foundation for addressing these variables. A balance of technical sophistication and design leadership will create the great healthcare spaces of the future.

Milly Baker, AIA, ACHA, LEED AP, is an associate at Payette (Boston). She can be reached at mbaker@payette.com.