Guest post by Will Hayles, technical writer and blogger, Outscale.
We tend to conceive of the Internet as a place of human communication. In reality, a significant proportion of the traffic carried over the networks that comprise the Internet is generated by machines talking to other machines. For the most part, there is no human in the loop of these so called machine-to-machine (M2M) interactions. Data is gathered from sensors attached to devices which are connected to the Internet. That data it is stored and analyzed in the cloud. Only at the end of the process is a human involved, once the deluge of data generated by machines has been squeezed down to extract useful information.
To take a simple example of how machine-to-machine processes can deliver useful information to human decision makers and system designers, consider a pet store that specializes in selling tropical fish. The store has several dozen aquariums filled with sensors that report the nutrient content and chemical composition of the water — data that is stored on a cloud platform. Another system records the store’s purchases, stock levels and waste. An analytics solution designed by the store’s developers takes both sets of data and tries to develop feeding and water treatment regimens that reduce waste (dead fish) and increase yield (fish growth). Every day, workers at the store get a list of tasks generated by the system — perhaps one of the aquariums is slightly too acidic and action needs to be taken or waste will increase.
The bulk of the communication is machines talking to machines, the culmination of which could be a text message that instructs the fish store owner to add three drops of a particular chemical to a specific tank.
Now that you have a basic grasp of the fundamental idea of M2M communication, let’s focus on how it is being used in the healthcare sector to improve patient outcomes and increase spending efficiency.
Healthcare treatments often involve many different professionals, from general practitioners to specialists, and from radiologists to physiotherapists. Complex cases can require input and decisions from a dozen or more individuals across several institutions. To be effective, it’s essential that healthcare professionals have access to up-to-date and comprehensive information about the case. With paper record keeping, it’s all too easy for information to fail to reach the right person at the right time. M2M systems, in which relevant data, including test results and real-time monitoring, are made available to all stakeholders simultaneously and automatically can make a real difference to healthcare outcomes, radically increasing the efficiency and efficacy of treatment regimes.
Remote Patient Monitoring
Remote patient monitoring is the classic case for M2M communication. With the advent of sensor-equipped medical devices with internet connectivity, patient status can be monitored in realtime, with physicians and other healthcare professionals receiving alerts when a decision or action needs to be taken.
Equipment maintenance is directly related to patient outcomes. Malfunctioning equipment can lead to death or other failures to provide adequate treatment. As industrial applications of M2M technologies to equipment maintenance programs have shown to be extremely effective in reducing failure rates, healthcare organizations can leverage sensor-equipped technology to gather data that allows them to determine the status of equipment and whether it requires maintenance.
Of course, the potential for M2M equipment monitoring goes well beyond maintenance, with the scope to use sensors directly attacked to medical devices like pacemakers and prosthetics to improve the management of care.
Machine-to-machine communication is still in its infancy in the healthcare sector, but in the coming years we can expect to see healthcare providers, device manufacturers, and software vendors working towards ever more effective solutions to the problems we’ve looked at here.