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Related Experiment Videos

Administrative receivership and troika management

J A Talbott, P Goodman, N Shapiro

    Administration in Mental Health
    |January 1, 1977
    PubMed
    Summary

    This study explored troika management and administrative receivership to improve a state mental hospital unit. The approach involved a three-person leadership team and collective decision-making processes.

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    Area of Science:

    • Healthcare Management
    • Organizational Psychology
    • Psychiatric Services

    Background:

    • State mental hospitals face challenges in unit management and patient care.
    • Previous management models may not fully address the complexities of psychiatric units.
    • The need for innovative administrative and leadership strategies is evident.

    Purpose of the Study:

    • To evaluate the effectiveness of troika management and administrative receivership in enhancing a state mental hospital unit.
    • To assess the impact of a three-person unit chief structure on unit operations.
    • To examine the role of transitional leadership and collective decision-making in organizational change within a mental health setting.

    Main Methods:

    • Implementation of a troika management system involving three key leaders.
    • Introduction of administrative receivership for oversight and resource allocation.
    • Establishment of transitional leadership to guide the change process.
    • Facilitation of collective decision-making among unit staff.

    Main Results:

    • The study demonstrated the application of a novel management structure in a clinical setting.
    • Key components included a tripartite leadership and collaborative problem-solving.
    • The model aimed to optimize unit functioning and administrative efficiency.

    Conclusions:

    • Troika management and administrative receivership offer a potential framework for upgrading state mental hospital units.
    • Transitional leadership and collective decision-making are crucial elements for successful implementation.
    • Further research is warranted to explore the scalability and long-term impact of this model.

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