Contrary to the practice in some countries, access to flexible and integrated forms of psychiatric care (FIT models) is limited in Germany. Several legislations have been introduced to improve this situation, notably the recent §64b (flexible and integrative treatment model; FIT64b) of the German Social Code, which allows for a capitation-based accounting of fees for services. The aim of this study was to explore the effects of FIT64b implementation on various stakeholders (patients, informal caregivers and staff) in 12 psychiatric hospital departments across Germany. Structural as well as quantitative and qualitative data are included, with integration of different methodological approaches. In all departments, the implementation of the new accounting system resulted into a relatively stable set of structural and processual changes where rigid forms of mainly inpatient care shifted to more flexible and integrated types of outpatient and outreach treatments. These changes were more likely to be perceived by patients and staff, and likewise received better evaluations, in those departments showing higher level or longer duration of implementation. Patients' evaluations, furthermore, were largely influenced by the advent of continuous forms of care, better accessibility, and by their degree of autonomy in steering of their services.
Conclusion:Based on the results, we developed 3 core mechanisms of change of FIT64b models: (1) Need-adaptedness and flexibility; (2) Continuity of care; (3) Maintaining everyday life. Our findings outline and emphasize the potential a GTB approach may have for improving psychiatric hospital services.
Background
Despite evidence from other countries for its effectiveness, flexible and integrative psychiatric treatment (FIT) is not part of the German standard healthcare system. Since 2013, German legislative reform has enabled a test implementation of FIT based on a global treatment budget. Because the budget is not restricted to any particular activity, this legislation opens the possibility of enhancing linkages between inpatient-, outpatient- and day-patient treatment structures. As staff involvement is a relevant component in successful implementation, we aimed in this study to judge the degree of FIT implementation based on staff members’ experiences and evaluations of FIT.
Method
Within an exploratory study design, we administered a standardized written survey to rate experiences and evaluations of physicians, psychologists, and nurses in the first 13 FIT projects between October 2016 and February 2017. The sample consisted of 352 nurses, 127 physicians, 84 psychologists, and 132 special therapists. We identified critical factors for successful implementation from the staff perspective by logistic regression analysis.
Results
Staff evaluations of the degree of FIT implementation were generally favorable, although some staff reported no experiences with one or several FIT-specific components. We found considerable differences in the assessments between the occupational groups. The only common factor for successful FIT implementation shared by physicians, psychologists, and nurses was the opportunity to join training programs on the objectives of FIT. Other critical factors for successful implementation were work conditions, the number of nurses/special therapists per physician/psychologist, and project duration. These factors together explained 49% of the variance of physician/psychologist evaluations and 34% for nurse evaluations. Individual staff members’ characteristics were less important than structural- or FIT characteristics as explanatory factors for the degree of FIT implementation.
Implications
Results point to the importance of new forms of multi-professional cooperation, training programs, improvement of work conditions, and guidance of the implementation process by systematic Change Management for future implementations of FIT. Our exploratory findings require further validation to guide practical improvements in FIT implementation. Longitudinal observations and a multilevel analysis should yield a better understanding of the relevant variables from different organization levels and their possible interactions.
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