A review of information sources and analysis methods for data driven decision aids in child and adolescent mental health services
International Journal of Medical Informatics, vol. 188, pp. 105479
Abstract
OBJECTIVE: Clinical data analysis relies on effective methods and appropriate data. Recognizing distinctive clinical services and service functions may lead to improved decision-making. Our first objective is to categorize analytical methods, data sources, and algorithms used in current research on information analysis and decision support in child and adolescent mental health services (CAMHS). Our secondary objective is to identify the potential for data analysis in different clinical services and functions in which data-driven decision aids can be useful. MATERIALS AND METHODS: We searched related studies in Science Direct and PubMed from 2018 to 2023(Jun), and also in ACM (Association for Computing Machinery) Digital Library, DBLP (Database systems and Logic Programming), and Google Scholar from 2018 to 2021. We have reviewed 39 studies and extracted types of analytical methods, information content, and information sources for decision-making. RESULTS: In order to compare studies, we developed a framework for characterizing health services, functions, and data features. Most data sets in reviewed studies were small, with a median of 1,176 patients and 46,503 record entries. Structured data was used for all studies except two that used textual clinical notes. Most studies used supervised classification and regression. Service and situation-specific data analysis dominated among the studies, only two studies used temporal, or process features from the patient data. This paper presents and summarizes the utility, but not quality, of the studies according to the care situations and care providers to identify service functions where data-driven decision aids may be relevant. CONCLUSIONS: Frameworks identifying services, functions, and care processes are necessary for characterizing and comparing electronic health record (EHR) data analysis studies. The majority of studies use features related to diagnosis and assessment and correspondingly have utility for intervention planning and follow-up. Profiling the disease severity of referred patients is also an important application area.
Authors 10
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Kaban Koochakpour corresponding
Norwegian University of Science and Technology
Affiliation as printed
Department of Computer Science, Norwegian University of Science and Technology (NTNU), Trondheim, Norway. Electronic address: kaban.koochakpour@ntnu.no
Department of Computer Science, Norwegian University of Science and Technology, Trondheim, Norway
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Norwegian University of Science and Technology · UiT The Arctic University of Norway
Affiliation as printed
Department of Computer Science, Norwegian University of Science and Technology (NTNU), Trondheim, Norway; Department of Computer Science, The Arctic University of Norway (UiT), Tromsø, Norway
Department of Computer Science, Norwegian University of Science and Technology, Trondheim, Norway
Department of Computer Science, The Arctic University of Norway Norway (UiT), Tromsø, Norway
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Affiliation as printed
The University of Chicago, Chicago, IL, USA
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Norwegian University of Science and Technology · St Olav's University Hospital
Affiliation as printed
Regional Centre for Child and Youth Mental Health and Child Welfare (RKBU Central Norway), Department of Mental Health, Faculty of Medicine and Health Sciences, Norwegian University of Science and Technology (NTNU), Trondheim, Norway; Department of Child and Adolescent Psychiatry, St. Olav's University Hospital, Trondheim, Norway
Department of Child and Adolescent Psychiatry, St. Olav's University Hospital, Trondheim, Norway
Regional Centre for Child and Youth Mental Health and Child Welfare (RKBU Central Norway), Department of Mental Health, Faculty of Medicine and Health Sciences, Norwegian University of Science and Technology, Trondheim, Norway
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Affiliation as printed
Vivit AS, Trondheim, Norway
Vivit AS, Norway
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UiT The Arctic University of Norway
Affiliation as printed
Regional Centre for Child and Youth Mental Health and Child Welfare (RKBU), The Arctic University of Norway (UiT), Tromsø, Norway
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Affiliation as printed
Department of Psychiatry, Psychotherapy and Psychosomatics, RWTH Aachen University, Aachen, Germany
RWTH University of Aachen, Germany
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Norwegian University of Science and Technology
Affiliation as printed
Regional Centre for Child and Youth Mental Health and Child Welfare (RKBU Central Norway), Department of Mental Health, Faculty of Medicine and Health Sciences, Norwegian University of Science and Technology (NTNU), Trondheim, Norway
Regional Centre for Child and Youth Mental Health and Child Welfare (RKBU Central Norway), Department of Mental Health, Faculty of Medicine and Health Sciences, Norwegian University of Science and Technology, Trondheim, Norway
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Norwegian University of Science and Technology
Affiliation as printed
Regional Centre for Child and Youth Mental Health and Child Welfare (RKBU Central Norway), Department of Mental Health, Faculty of Medicine and Health Sciences, Norwegian University of Science and Technology (NTNU), Trondheim, Norway
Regional Centre for Child and Youth Mental Health and Child Welfare (RKBU Central Norway), Department of Mental Health, Faculty of Medicine and Health Sciences, Norwegian University of Science and Technology, Trondheim, Norway
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Norwegian University of Science and Technology
Affiliation as printed
Regional Centre for Child and Youth Mental Health and Child Welfare (RKBU Central Norway), Department of Mental Health, Faculty of Medicine and Health Sciences, Norwegian University of Science and Technology (NTNU), Trondheim, Norway
Regional Centre for Child and Youth Mental Health and Child Welfare (RKBU Central Norway), Department of Mental Health, Faculty of Medicine and Health Sciences, Norwegian University of Science and Technology, Trondheim, Norway
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