Transitional care models for chronic patients: preliminary results from an umbrella review

Worldwide, chronic diseases are burdening and the health systems need to be rethought to better manage this epidemiologic shift. One of the critical points in the care pathway of chronic patients is the transition from one care setting to another. Aim of this study is to provide an overview of the current evidence on the impact of transitional care programs on health and economic outcomes for chronic patients Medline, Web of Science and EMBASE were queried for relevant reviews using the Population-Intervention-Context-Outcome (PICO) model. The quality of the included articles was determined using A MeaSurement Tool to Assess systematic Reviews (AMSTAR 2). Data were analyzed using descriptive statistic, and comparison among studies carried out in European Union (EU) versus non-EU was performed (Chi-square test was used and a p < 0.05 was deemed as statistically significant) 124 reviews were assessed for eligibility and 14 were eventually included (for a total of 167 primary articles). Quality appraisal was critically low in 60% of the reviews. Both hospital readmission rate and Emergency Department (ED) visit rate were lower than those in usual care group, but this difference was significant in 40% of articles. In EU studies readmission rate was lower in 65% of cases while in non-EU ones the percentage was 51.0%, but the difference was not significant (p = 0.23). Six reviews (43%) investigated the economic impact of the transitional care: most reported an initial increase in cost due to investment in staff training and creation of organizational networks, followed by a sharp decrease in costs due to a better utilization of health services, thus leading to a reduction in overall costs. Compared with usual care, transitional care shows an overall cost reduction, even if with limited effects on re-hospitalization or ED visit rates. These findings should encourage decision makers to invest in the development of this kind of programs in order to identify models that best perform.