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Design Experience, Experience Design: Design Experience, Experience Design: Results and Implications from a Multi-Hospital Post-Occupancy Evaluation

Design Experience, Experience Design
Design Experience, Experience Design: Results and Implications from a Multi-Hospital Post-Occupancy Evaluation
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  1. Design Experience, Experience Design: Results and Implications from a Multi-Hospital Post-Occupancy Evaluation

Design Experience, Experience Design: Results and Implications from a Multi-Hospital Post-Occupancy Evaluation

Nicholas Watkins (Gensler)

The ongoing confluence of technological and nontechnological forces continues to radically redefine the global economy. The healthcare industry has responded with numerous advances in population health, personalized medicine, telehealth, mobile health, outpatient surgery, among others. Through cycles of scientific experimentation and continuous process improvement, these advances are being refined to augment optimal care provider-patient interactions and patient experiences, many times creating new roles and responsibilities. Though the healthcare industry is an innovation leader in the global economic shift, healthcare organizations' facility portfolios are often fragmented from the larger organization's performance metrics, considered a liability, and pose significant risk. A recent study of more than 2,000 patients from 13 Cleveland Clinic inpatient facilities revealed that this is a mistake and an opportunity. The study found that facility design had a profound impact on patients' loyalty behavior and likelihood to recommend. To understand what accounted for the impact, the facilities were assessed in aggregate and in comparison on a variety of facility design and patient experience measures. The assessment revealed the importance of specific design interventions and other opportunities for optimal patient experience and return-on-investment. Most importantly, the study's key finding underscored a need to leverage the often overlooked and underutilized advances in computational design tools. These tools can effectively integrate and visualize data streams from facilities, patient experience, care quality, demographic, and real estate data. Using predictive analytics and machine learning, computational design tools integrate multiple streams of data into intelligible and quantifiable indicators of performance, often not detectable through contemporary dashboards and the naked eye. This “spatial intelligence,” in turn, allows healthcare organizations to take an agile and informed stance toward their near and long-term strategy decisions by nimbly balancing their portfolio with shifts in care delivery, patient expectations, demographics, technology, and numerous other forces.

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Design & Advocacy: Abstracts
CC BY-NC-ND 4.0 | Proceedings of the Environmental Design Research Association 50th Conference
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