About this project
In progress 2019 - 2020
Pain relieving opiods are among our oldest and most common drugs. Opioids (such as heroin, morphine, codeine, fentanyl) act on opiodceptors in the brain and, in addition to pain relief, provide a sense of well-being. Addiction is fast and characterized by a pathologically recurring need for reward without the presence of pain signals.
In today's more efficient healthcare, the majority of rehabilitation and related pain relieve occur at home. As a result, the use of opiates in the home environment has increased, resulting in increased use and addiction to opiates.
Treatment with opiates is based on the average patient pain level and expected effect size and duration. This approach is static and does not take into account the large individual variation found in both patients' subjective perception of pain intensity, duration, drug half-life and patient sensitivity to the effect. The fact that tablets are only available in fixed strengths allows very little opportunity to individually adjust the dose. In addition, home treatment does not provide an opportunity to monitor how treatment is been done.
This project aims at studying the possibility of objectively, in real-time pain, evaluate if objective pain sensoring is coherent with subjective perceived pain and using this knowledge to develop an algorithm for future-dose pain relief treatment not based on historical data but on real-time individually sensored and objectively recorded pain. The goal in the long run is that such treatment should provide better pain relief with less opioid utilization and contribute to better resource utilization in health care.