Organization Efficiencies with an IoT System

By Madison Pittman

Using IoT to Measure Patient Interactions

Many facilities have wondered about disparities between shifts. Are patients visited at the same rate at all hours of the day? Are certain days busier than others? This information has previously been unavailable to hospital leadership and has been left to guessing, estimation, and other outdated and inaccurate methods. With an IoT (Internet of Things) platform, facilities can now gain insight into shifts and make decisions based on the collected data.

Clean Hands – Safe Hands has been providing this valuable data to their customers. Many facilities suspect that night shift is slightly slower than day shift, but the actual data speaks loudly. Patients are visited much less during night shift compared to day shift, and Wednesday tends to be the busiest day for patient interactions.

It can also be stated that patients are visited more regularly at the start of a day shift, when the clinicians are the most fresh. Clinical visits peak at 8:00 am as healthcare workers are greeting their patients for the day and getting familiar with their individual needs. Then visits drop a bit until right before lunchtime when patients are checked on again. In the afternoon, there’s a lull as clinicians may be getting tired and visiting patients less frequently. Activity rises again a bit before dinner, and then especially as clinicians are saying goodbye and clocking out…but late day activity never reaches even the lowest point from the morning.

This data gives hospital leadership critical insight that can be used to make decisions around staffing.

Better Nurse Rounding with Critical Insights

Many facilities have nurse rounding policies. Providers are typically expected to check on their patients once every hour, but that’s not always the case. It can be difficult for hospitals to measure their nurse rounding, much less, measure it in an affective and efficient way. The Clean Hands – Safe Hands system can provide insight into patient visit rates.

In this real data example, Nurse Susan is the primary provider for the patient. While she checked on the patient frequently, she did not check on the patient every hour. A summary of her visits is below. Nurse Susan actually only checked on this particular patient about half the time she was supposed to.

Data that has previously been unavailable to hospital leadership is now being used to make critical decisions and interventions for patient care. As facilities are transitioning to value-based care, these insights can save facilities time and money.

If you are interested in learning more about your facility’s clinical patterns, contact Clean Hands – Safe Hands to schedule a quick call.

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