Ten Things You Learn from Medical Machine Data Analytics

Puneet Pandit

A critical component of healthcare delivery continues to be the precision and efficacy of diagnostic equipment and devices used to create and monitor treatment programs. Digitizing the diverse array of machines from a variety of manufacturers was an important innovation. Today healthcare organizations are taking the next steps – implementing platforms to analyze distributed and diverse data to create insights that will optimize process, workflow and the collaboration of machines and people. The result is reliable automation that improves the delivery of care and patient experience.

Glassbeam is in the business of analyzing machine data. We have decades of experience in the art and science of collecting data and analyzing the data to enable decision support. We’ve applied our experience and science to manage the service and utilization of machines used by every healthcare provider. In 2019 the data showed that healthcare expenditures expanded to over $9 trillion dollars and the number is still increasing. The number of connected medical devices and machines utilizing Internet of Things (IoT) technologies was 23 MILLION in 2020 and analysts project the number will grow to 100 MILLION by 2026. During a typical hospital visit the patient comes in contact with 75 of these devices!

What can you learn from machine data analytics? Here are just TEN of the many things you can learn and what you can do with the insights:

> By analyzing key machine parameters like helium levels and magnet pressure you can prevent unplanned machine downtime.

> You can predict when to remove machines from service, improving uptime and the reliability of your capital budget forecasts.

> Staffing gets easier – schedule staffing of all personnel and especially top of license radiologists based on patient demand.

> Schedule staff for training by reviewing statistics on “retesting” due to operator error.

> Negotiate better rates on service contracts with major vendors.

> Create an inventory of parts for high demand equipment to lower cost of parts replacement and speed up mean time to repair (MTTR).

> By integrating Glassbeam Clinsights with patient CMS data you can evaluate the impact machine availability on the wellness of vulnerable populations.

> Provide referring physicians and insurers with protocol usage.

> Improve machine inventory utilization and staffing by using the data to correlate patient demand and machine availability

> Develop service plans and scheduling protocols that engender confidence from sometime overworked staff and provide a resilient response to the most challenging healthcare crisis.

Organizations often find that valuable insights remain hidden due to the overwhelming volume of data. The Glassbeam Clinsights platform liberates the information interactions from a diverse array of machines by applying sophisticated algorithms and machine learning. Glassbeam is a pioneer in machine data management models, and we are applying our expertise in analytics to connected medical equipment with Clinsights. Clinsights hides the science and reveals the meaningful and usable information on dashboards and in reports that staff, licensed  professionals, and business executives can use to improve collaboration, optimize service and workflows, and make decisions.

Today regional healthcare systems are growing to improve purchasing power and provide consistent options to diverse populations – to deliver the best care at the lowest cost. Already large healthcare corporations are expanding. This means that the machine landscape is increasingly comprised of multiple brands having different network standards and approaches for how they are imbedding intelligence in the machines. This has presented hurdles for organizations recognizing the value of machine data analytics to optimize service and utilization.

Clinsights represents a shift in thinking from collecting and analyzing data to how integration of data from costly machines will improve the efficiency and utilization of top of license staff and improve the scheduling and servicing of physical systems for better healthcare outcomes. Clinsights becomes indispensable for organizations that prioritize automation, have a vision and strategy to be a smart hospital. Smart hospitals rely on real-time networked data and orchestrated information that integrates all the people, assets and facility systems involved in health delivery and patient experience.