The Many Use Cases of Real-Time Medical Equipment Data

Mobilizing Continuous Data from Medical Devices in Clinics Yields a Multitude of Actionable Insights

Too many health facilities in low-income countries can’t provide lifesaving care because basic medical equipment is absent or broken. Even when devices like infant incubators and CPAP machines are present on site, they frequently break down. Due to the lack of supply chains for consumable parts and a dearth of skilled maintenance, minor equipment problems turn into permanent failures. A recent report from PATH, covered extensively by Devex, illustrates the stakes of the crisis:

“Some countries end up with more than 80 different types of the same device that health workers aren’t trained to operate. When the equipment breaks, there are no spare parts or anyone to contact for repair, leaving health facilities no choice but to throw it away.”

At Nexleaf, we approach solving problems in low-resource health systems from the lens of gathering and operationalizing objective data. In our experience, foremost in global immunization, we’ve seen how mobilizing continuous data from equipment can reveal hidden problems and unlock solutions at every level of the system.

Nexleaf partnered with Global Health Labs (GHL) to design an IoT-based solution for gathering data on medical equipment installed in health facilities. Nexleaf and GHL worked together to select smart plugs and other monitoring hardware and, in partnership with CPHD, attached them to 108 units of equipment spread across 7 hospitals. We took readings from the equipment instruments every 1 to 5 minutes and processed the signals to determine whether the equipment was in use or sitting idle. We gathered this continuous usage data from 8 types of equipment in total, including CPAP machines, incubators, and oxygen concentrators. The result was a working prototype of a real-time medical equipment usage dashboard.

The most significant accomplishment of this project was successfully mobilizing continuous, objective data from the equipment. With off-the-shelf parts, we turned ordinary mechanical devices into smart equipment, capable of sending continuous data on their utilization status.

This type of data flow has many applications. One use case is tracking hours of utilization between routine maintenance. By keeping a running log, the system tells health workers when each unit needs maintenance – and which units are overdue – just like the dashboard on a car. Performing routine maintenance improves equipment lifespan, increasing availability and saving money.

We also saw that certain equipment was never actually in use.

When we noticed evidence of completely unused infant incubators in the data, we posed this question to health facility staff:
Why is Incubator 1 at Hospital B never utilized?
We discovered that this incubator was donated to Hospital B, but Hospital B did not yet have trained specialists on staff to use it. Project data also revealed an unutilized incubator at another site. In that case, even though the facility had trained specialists and a steady flow of patients, they did not have spare parts available to keep the incubator running.

In both cases, data on equipment disuse can inform corrective action: redistribution of critical equipment to sites with appropriate staffing, priority recruitment of trained specialists, or prompt provision of the right spare parts to get much-needed equipment back online.

Another way utilization data can yield insights in by enabling use comparison across makes and models for a given equipment type:

Why is CPAP Model B frequently in use, while CPAP Model A is never utilized? By posing this question to care providers, we learned CPAP Model B is substantially smaller and easier to move from patient to patient. In fact, CPAP Model B was designed in Africa for use in local public health facilities. By enabling planners to ask targeted questions about device utilization, medical equipment data can help health systems identify crucial selection criteria for equipment procurement.

These are only a few examples of the many systems applications of data use cases we identified from continuous automated medical equipment data.

Nexleaf views the power and potential of equipment data as the next frontier in global public health information systems. By treating medical equipment data as key public health data, just like commodity data and patient data, countries and multilateral donors – and anyone interested in improving healthcare access and equity – can approach the intractable problem of unavailable medical equipment from an information systems perspective.

Making data available means health workers at every level of the system – from the Last Mile clinic all the way to the central Ministry of Health – can collaborate to keep equipment working using tools like dashboards that display the real-time status of all equipment, located anywhere in the country.

As more smart medical equipment designed for LMIC health systems rolls off the assembly line with data transmission capacity already built in, Nexleaf is working to make sure all that critical data is poised to be as useful as possible for health systems to deliver care where and when it’s needed most.