● What factors affect the length of stay (LOS) for patients, such as staff-to-patient ratio, equipment readiness, bed turnover, etc., and to what extent
● Whether the right asset is available in the right place at the right time for efficient load balancing of assets
● The bottlenecks in your hospital that impact the patient flow, e.g., the average wait time for shared services
● Predicting the need or time to transfer patients from one department to another and anticipating the necessary equipment and staff to transport patients efficiently
The next step is to discover the “unknowns” that can be known, such as:
● What other patterns or bottlenecks can be identified when analyzing inpatient data – from admission to discharge – and more so getting predictions and recommendations for optimization
● What are the questions that we never thought to ask but should
● What additional data should we gather to further identify patterns and opportunities
Once you begin this process, some opportunities present themselves almost immediately. For example, by predicting when the patient will be discharged, hospitals can automate room sanitation and preparation workflows to reduce turnaround time. By integrating EHR, you may discover that patients with certain ailments are consistently above the Geometric Mean Length of Stay (GMLOS). Now drill down the data by time or compare it against other facilities – you will surface correlation factors that explain why the LOS is higher. The potential is limitless once you start conversing with your data and transforming it into impactful and value-creating decisions.
The waste, inefficiency, and frustration now part of the common patient journey should be a wake-up call for health systems. It’s time to move beyond data creation and collection to “data mobilization.” By tapping into your data with AI and ML, health systems can discover invaluable insights into the patient journey and uncover new opportunities that save costs and improve care.
About the author: Rom Eizenberg is CRO and head of product innovation at Kontakt.io, a leader in healthcare RTLS and digital transformation solutions.
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