Healthcare IoT analytics have a lot in common with manufacturing IoT analytics. The accuracy of reported values is extremely important, and the age of the unit is a key factor linked to multiple health issues. However, unlike manufacturing, which strives to make consistent and repeatable processes, nature values variation in the units (people).

This makes environmental factors, location, and population demographics more important. Maybe counter-intuitively, it also makes the production period (when people are born) less important. In manufacturing, a change in the process could affect everything immediately. In life, variation protects against this, and trends take longer to affect the full population. This makes the detection of problems more difficult and complex statistical techniques more valuable to health care analytics.

The more accurate the IoT device records values and the more consistent the data sampling period, the better the performance of advanced analytics. Pay extra attention to the data value distributions compared to what would be expected for the population of people being measured.