BACKGROUND: The health system must develop effective solutions to the growing challenges it faces with respect to individuals who suffer with mental health disorders and addictions. The purpose of this study was to evaluate the usability and potential impact on outcomes of a knowledge translation system aimed at improving client-centered, evidence-based care for hospitalized individuals with schizophrenia. METHODOLOGY: A pre-posttest design was used. The e-Volution-TREAT system was implemented on two inpatient units at a large mental health facility. Thirty-seven nurses, allied health workers, and physicians participated from two units. Data collection involved questionnaires, semistructured interviews, and observations. Thirty-eight consenting clients' outcome data were collected from organizational records. RESULTS: Overall, staff participants were very satisfied with the functions of the e-Volution-TREAT system. Barriers to using the system were identified by participants related to the work environment, to understaffing, equipment problems, discomfort with technology, and a focus on short-term rather than long-term goals. There was moderate uptake of guidelines related to social issues, and low uptake of guidelines related to family support and addictions. There were significant improvements in four client outcomes over time, specifically aggressive behavior, depression, withdrawal, and psychosis. CONCLUSIONS: In conclusion, users were overall satisfied with the e-Volution-TREAT system, although expressed challenges related to workload that interfered with time to utilize the system. It would be premature to conclude the change in client outcomes was related to the e-Volution-TREAT system without a randomized controlled trial with outcomes compared to a control group. Future research needs to incorporate strategies for modifying the context and engage clinicians who are in a position of influence to model change.
BACKGROUND: The health system must develop effective solutions to the growing challenges it faces with respect to individuals who suffer with mental health disorders and addictions. The purpose of this study was to evaluate the usability and potential impact on outcomes of a knowledge translation system aimed at improving client-centered, evidence-based care for hospitalized individuals with schizophrenia. METHODOLOGY: A pre-posttest design was used. The e-Volution-TREAT system was implemented on two inpatient units at a large mental health facility. Thirty-seven nurses, allied health workers, and physicians participated from two units. Data collection involved questionnaires, semistructured interviews, and observations. Thirty-eight consenting clients' outcome data were collected from organizational records. RESULTS: Overall, staff participants were very satisfied with the functions of the e-Volution-TREAT system. Barriers to using the system were identified by participants related to the work environment, to understaffing, equipment problems, discomfort with technology, and a focus on short-term rather than long-term goals. There was moderate uptake of guidelines related to social issues, and low uptake of guidelines related to family support and addictions. There were significant improvements in four client outcomes over time, specifically aggressive behavior, depression, withdrawal, and psychosis. CONCLUSIONS: In conclusion, users were overall satisfied with the e-Volution-TREAT system, although expressed challenges related to workload that interfered with time to utilize the system. It would be premature to conclude the change in client outcomes was related to the e-Volution-TREAT system without a randomized controlled trial with outcomes compared to a control group. Future research needs to incorporate strategies for modifying the context and engage clinicians who are in a position of influence to model change.
Authors: Christalla Pithara; Michelle Farr; Jeremy Horwood; Sarah A Sullivan; Hannah B Edwards; William Hall; Caroline Gadd; Julian Walker; Nick Hebden Journal: J Med Internet Res Date: 2020-03-19 Impact factor: 5.428