For 60 years, clinical decision support systems (CDSS) have helped clinicians solve their daily chores. Initially, CDSSs were computer-assisted aids for diagnosing individual patient cases. The newest version of CDSS is using artificial intelligence, machine learning, deep learning, artificial neural networks, and genetic algorithms to solve the complex problems of health care. This dissertation is about the developed CDSSs of the key processes in the implementation of a new integrated mental and addiction care clinic (MTPA).

The previous separately organized service systems of mental health and addiction care were fragmented and inefficient. A redesign of the service systems and effective implementation methods was needed. The developed CDSSs offered an efficient way to implement a new clinic within a narrow time frame. The CDSSs of adult ADHD, the evaluation of the working ability of psychiatric patients, and the opioid substitution therapy were the key processes designed in focus groups of multi-professional teams to align the various duties of different mental and addiction care professionals in the southeast of Finland.

Process and systems thinking, organizational development and systems science were the background theories of this dissertation. These manufacture-originated theories were applied in a joint team effort in a real work-life situation to the core processes of the new clinic. The results of using these theories were mostly successful. The CDSS-assisted key processes eliminated long waiting lists altogether and facilitated new patient groups entering the clinic. The clinic achieved a benchmarking status in integrated mental and addiction care in Finland. The CDSS-assisted key processes of the clinic formed an agile, efficient, and productive way of reorganizing and implementing psychiatric and addiction care operations. This dissertation contributes similar efforts to reorganizing and developing health care service systems.