TY - JOUR
T1 - The past, present and future of opioid withdrawal assessment
T2 - A scoping review of scales and technologies
AU - Nuamah, Joseph K.
AU - Sasangohar, Farzan
AU - Erranguntla, Madhav
AU - Mehta, Ranjana K.
N1 - Funding Information:
The open access publishing fees for this article have been covered by the Texas A&M University Open Access to Knowledge Fund (OAKFund), supported by the University Libraries and the Office of the Vice President for Research.
Funding Information:
This independent work was supported by the Texas A&M Triads for Transformation. The funding body was not involved in any aspects of the study design, analysis, or dissemination.
Publisher Copyright:
© 2019 The Author(s).
PY - 2019/6/18
Y1 - 2019/6/18
N2 - Background: A common challenge with all opioid use disorder treatment paths is withdrawal management. When withdrawal symptoms are not effectively monitored and managed, they lead to relapse which often leads to deadly overdose. A prerequisite for effective opioid withdrawal management is early identification and assessment of withdrawal symptoms. Objective: The objective of this research was to describe the type and content of opioid withdrawal monitoring methods, including surveys, scales and technology, to identify gaps in research and practice that could inform the design and development of novel withdrawal management technologies. Methods: A scoping review of literature was conducted. PubMed, EMBASE and Google Scholar were searched using a combination of search terms. Results: Withdrawal scales are the main method of assessing and quantifying opioid withdrawal intensity. The search yielded 18 different opioid withdrawal scales used within the last 80 years. While traditional opioid withdrawal scales for patient monitoring are commonly used, most scales rely heavily on patients' self-report and frequent observations, and generally suffer from lack of consensus on the criteria used for evaluation, mode of administration, type of reporting (e.g., scales used), frequency of administration, and assessment window. Conclusions: It is timely to investigate how opioid withdrawal scales can be complemented or replaced with reliable monitoring technologies. Use of noninvasive wearable sensors to continuously monitor physiologic changes associated with opioid withdrawal represents a potential to extend monitoring outside clinical setting.
AB - Background: A common challenge with all opioid use disorder treatment paths is withdrawal management. When withdrawal symptoms are not effectively monitored and managed, they lead to relapse which often leads to deadly overdose. A prerequisite for effective opioid withdrawal management is early identification and assessment of withdrawal symptoms. Objective: The objective of this research was to describe the type and content of opioid withdrawal monitoring methods, including surveys, scales and technology, to identify gaps in research and practice that could inform the design and development of novel withdrawal management technologies. Methods: A scoping review of literature was conducted. PubMed, EMBASE and Google Scholar were searched using a combination of search terms. Results: Withdrawal scales are the main method of assessing and quantifying opioid withdrawal intensity. The search yielded 18 different opioid withdrawal scales used within the last 80 years. While traditional opioid withdrawal scales for patient monitoring are commonly used, most scales rely heavily on patients' self-report and frequent observations, and generally suffer from lack of consensus on the criteria used for evaluation, mode of administration, type of reporting (e.g., scales used), frequency of administration, and assessment window. Conclusions: It is timely to investigate how opioid withdrawal scales can be complemented or replaced with reliable monitoring technologies. Use of noninvasive wearable sensors to continuously monitor physiologic changes associated with opioid withdrawal represents a potential to extend monitoring outside clinical setting.
KW - Opioid use disorder
KW - Physiological monitoring
KW - Questionnaires
KW - Scales
KW - Surveys
KW - Wearable sensor
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U2 - 10.1186/s12911-019-0834-8
DO - 10.1186/s12911-019-0834-8
M3 - Article
C2 - 31215431
AN - SCOPUS:85067605085
VL - 19
JO - BMC Medical Informatics and Decision Making
JF - BMC Medical Informatics and Decision Making
SN - 1472-6947
IS - 1
M1 - 113
ER -