Recycling components in medical devices

A non-transitory computer readable medium comprising instructions to be executed in a processor, the instructions when executed in the processor perform an operation, the operation comprising:

• registering a one-time use medical device in a database, wherein a device entry in the database for the medical device includes at least one component entry for a recyclable component in the medical device;
• tracking a usage of the medical device by a patient;
• updating a remaining life of the recyclable component based on the usage of the medical device;
• upon determining the patient is finished with the medical device, determining whether the recyclable component has sufficient remaining life to be recycled based on a threshold;
• upon determining the recyclable component has sufficient remaining life, outputting instructions to remove the recyclable component from the medical device;
• and
• outputting instructions to transport the recyclable component to be placed in a new medical device;
• and
• predicting a number of medical devices that will be available for recycling at a future date using a machine learning (ML) model, wherein the ML model comprises at least one of a neural network, and is trained by:
• tracking an amount of time each of a first plurality of patients used a first plurality of medical devices;
• receiving medical information, including at least a diagnosis, for each of the first plurality of patients;
• and
• using the amount of time and the medical information to correlate the amount of time and the medical information.

A system, comprising:

• a processor;
• and
• memory storing code which, when executed by the processor, performs an operation, the operation comprising:
• registering a one-time use medical device in a database, wherein a device entry in the database for the medical device includes at least one component entry for a recyclable component in the medical device;
• tracking a usage of the medical device by a patient;
• updating a remaining life of the recyclable component based on the usage of the medical device;
• upon determining the patient is finished with the medical device, determining whether the recyclable component has sufficient remaining life to be recycled based on a threshold;
• upon determining the recyclable component has sufficient remaining life, outputting instructions to remove the recyclable component from the medical device;
• and
• outputting instructions to transport the recyclable component to be placed in a new medical device;
• and
• predicting a number of medical devices that will be available for recycling at a future date using a machine learning (ML) model, wherein the ML model comprises at least one of a neural network, and is trained by:
• tracking an amount of time each of a first plurality of patients used a first plurality of medical devices;
• receiving medical information, including at least a diagnosis, for each of the first plurality of patients;
• and
• using the amount of time and the medical information to correlate the amount of time and the medical information.