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Clinical and organizational factors predicting readmission for mental health patients across Italy
Federico Tedeschi1, V Donisi2, D Salazzari2
1Section of Psychiatry, Department of Neurosciences, Biomedicine and Movement Sciences, Ospedale Policlinico "G.B. Rossi", University of Verona, P.le L.A. Scuro, 10, 37134, Verona, Italy. federico.tedeschi@univr.it.
Purpose:
The aims of our study are: to explore rehospitalization in mental health services across Italian regions, Local Health Districts (LHDs), and hospitals; to examine the predictive power of different clinical and organizational factors.
Methods:
The data set included adult patients resident in Italy discharged from a general hospital episode with a main psychiatric diagnosis in 2012. Independent variables at the individual, hospital, LHD, and region levels were used. Outcome variables were individual-level readmission and LHD-level readmission rate to any hospital at 1-year follow-up. The association with readmission of each variable was assessed through both single- and multi-level logistic regression; descriptive statistics were provided to assess geographical variation. Relevance of contextual effects was investigated through a series of random-effects regressions without covariates.
Results:
The national 1-year readmission rate was 43.0%, with a cross-regional coefficient of variation of 6.28%. Predictors of readmission were: admission in the same LHD as residence, psychotic disorder, higher length of stay (LoS), higher rate of public beds in the LHD; protective factors were: young age, involuntary admission, and intermediate number of public healthcare staff at the LHD level. Contextual factors turned out to affect readmission only to a limited degree.
Conclusions:
Homogeneity of readmission rates across regions, LHDs, hospitals, and groups of patients may be considered as a positive feature in terms of equity of the mental healthcare system. Our results highlight that readmission is mainly determined by individual-level factors. Future research is needed to better explore the relationship between readmission and LoS, discharge decision, and resource availability.
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