The World Series just wrapped up, and a Bay Area team won, but not mine. I am an Oakland Athletics fan, and the A’s were eliminated in the playoffs this year by the Detroit Tigers, who played opposite the San Francisco Giants, the new World Series champions.
The Oakland A’s are best known over the past fifteen years as a team that maximizes outcomes given a relatively meager budget, at least compared to its competition. The A’s base their personnel decisions and execution on sabermetrics, an intense statistical analysis of individual player performance and potential. Michael Lewis’ book, Moneyball, portrayed sabermetrics in action; you may have seen the Best Picture-nominated feature film a couple years ago. The A’s have applied information to systematically better identify baseball talent, an otherwise subjective and imprecise activity, and outperform the majority of baseball clubs since around 2000. It could be argued the A’s are the most value-driven ball club.
Healthcare, and healthcare design, are now entrenched in their own sabermetrics era. Across healthcare, smart organizations are utilizing collected data to inform decisions on outcomes, payments and billing, safety and infection control, and throughput. Patients now have “portals” where they can be more proactive in managing their own care, integrating with electronic health records (EHR) and other analytics.
Following healthcare’s information revolution, is healthcare design. The days of guestimating how many treatment rooms are needed, how much storage space is required, or how many people might use a waiting area at any given time are gone. Simulation now helps determine ideal spatial adjacencies, patient and treatment flow, and room sizes and layouts. If an adverse event floods the ED with patients, hospitals can have a verified protocol in place, based on projected outcomes from simulation. Growth is dictated by data.
Winners and losers in the healthcare market will also be determined by data. Successful future healthcare design will be led by information: access to it, speed of its acquisition, notifications of its changes. Hospitals and healthcare designers will need systems that provide feedback, immediate and real-time in some cases, so designs can be optimized even after layouts were supposedly settled. Healthcare data and project design management systems will trump the individual input of Directors and C-level administrators who change over time. Currently, architects charge hospitals extra for the man hours to make those adjustments, whereas design-build’s flexibility has in the past, and will continue to absorb, process and accommodate change with much less time and expense.
Hospitals without a working knowledge of evidence-based design will be searching blindly for project success. To optimize project outcomes, design-builders will ask for a hospital’s counterpart who is conversant in evidence-based design, Lean and Six Sigma. Hospitals cannot afford to rely on their legacy architects to design how they have always designed a department, because that is changing. Much like the subjectivity of scouting ball players, ‘they way they always did it’ did not work for Oakland; it will not work for healthcare design.
The need for better design is a GIGO (garbage in, garbage out) scenario. Hospitals without clinical innovation centers that collect and parse data in new ways for benchmarking, analysis, best practices—and thus to guide design—will fall behind because their project designs will fall behind. Healthcare architects will request departmental performance numbers, key metrics and patient satisfaction surveys in order to proceed with design. Where data is lacking, RFID tags on providers and patients will generate paths of travel, stop times and process behavior that will inform Lean and Six Sigma goals.
Today’s healthcare IT investment is seen primarily in hardware, software and consultants. Soon it will be in personnel to gather, intepret and act—or help others act—on the data. The Information Age has only begun in healthcare design.