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Audit and Feedback (A&F) is an effective multidimensional strategy for improving the quality of care. The optimal methods for its implementation remain unclear. This study aimed to map the state of art of A&F strategies in the hospitals involved in a time-dependent emergency network. For these purposes, a structured questionnaire was defined and discussed within the research group. This consists of 29 questions in three sections: (1) characteristics of the structure, (2) internal feedback systems, and (3) external feedback systems. All structures involved in the network were invited to participate in the e-survey by indicating a Health Management representative and a clinical representative for the Cardiovascular (CaV) and/or for the Cerebrovascular area (CeV). Of 20 structures invited, a total of 13 (65%) responded to the survey, 11 for the CaV area and 8 for the CeV area. A total of 10 of 11 (91%) facilities for the CaV area and 8/11 (75%) for the CeV area reported that they perform A&F activities. All facilities perform at least one of the activities defined as “assimilating A&F procedures.” The most frequent is the presentation and discussion of clinical cases (82% CaV and 88% CeV) and the least is the identification of responsible for improvement actions (45% CaV and 38% CeV). In 4/10 (40%) facilities for the CaV area and 4/8 (50%) for the CEV area, corrective actions are suggested or planned when the feedback is returned. These results confirm the need to define, in a synergistic way with the relevant stakeholders, an effective and agreed A&F intervention to improve the level of implementation of A&F strategies.

Background The promotion of safer healthcare interventions in hospitals is a relevant public health topic. This study is aimed to investigate predictors of Adverse Events (AEs) taking into consideration the Charlson Index in order to control for confounding biases related to comorbidity. Methods The study was a retrospective cohort study based on a two-stage assessment tool which was used to identify AEs. In stage 1, two physicians reviewed a random sample of patient records from 2008 discharges. In stage 2, reviewers independently assessed each screened record to confirm the presence of AEs. A univariable and multivariable analysis was conducted to identify prognostic factors of AEs; socio-demographic and some main organizational variables were taken into consideration. Charlson comorbidity Index was calculated using the algorithm developed by Quan et al. Results A total of 1501 records were reviewed; mean patients age was 60 (SD: 19) and 1415 (94.3%) patients were Italian. Forty-six (3.3%) AEs were registered; they most took place in medical wards (33, 71.7%), followed by surgical ones (9, 19.6%) and intensive care unit (ICU) (4, 8.7%). According to the logistic regression model and controlling for Charlson Index, the following variables were associated to AEs: type of admission (emergency vs elective: OR 3.47, 95% CI: 1.60-7.53), discharge ward (surgical and ICU vs medical wards: OR 2.29, 95% CI: 1.00-5.21 and OR 4.80, 95% CI: 1.47-15.66 respectively) and length of stay (OR 1.03, 95% CI 1.01-1.04). Among patients experiencing AEs a higher frequency of elderly (≥65 years) was shown (58.7% vs 49.3% among patients without AEs) but this difference was not statistically significant. Interestingly, a higher percentage of patients admitted through emergency department was found among patients experiencing AEs (69.7% vs 55.1% among patients without AEs). Conclusions The incidence of AEs was associated with length of stay, type of admission and unit of discharge, independ

The short stay unit (SSU) is a ward providing targeted care for patients requiring brief hospitalization and dischargeable as soon as clinical conditions are resolved. Therefore, SSU is an alternative to the ordinary ward (OW) for the treatment of selected patients. The SSU model has been tested in only a few hospitals, and the literature lacks systematic evaluation of the impact of SSU use. The aim of our study was to evaluate the use of SSUs in terms of length of hospital stay, mortality and readmission rate. A random effect meta-analysis was carried out by consulting electronic databases. Studies were se- lected that focused on comparison between use of SSUs and OWs. Mean difference of length of stay was calculated within 95% confidence intervals. Six articles were selected, for a total of 21 264 patients. The estimated mean difference was 3.06 days (95% CI 4.71, 1.40) in favor of the SSU. The selected articles did not show any differences in terms of mortality and readmission rate. Use of SSUs could reduce patient length of stay in hospital, representing an alternative to the ordinary ward for selected patients. A shorter period of hospitalization could reduce the risk of hospital-acquired infections, increase patient satisfaction and yield more efficient use of hospital beds. Findings of this study are useful for institutional, managerial and clinical decision-makers regarding the implementation of the SSU in a hospital setting, and for better management of continuity of care.

Among risk management initiatives, systematic safety processes (SSPs), implemented within health care organizations, could be useful in managing patient safety. The purpose of this article is to conduct a systematic literature review assessing the impact of SSPs on different error categories. Articles that investigated the relation between SSPs, clinical and organizational outcomes were selected from scientific literature. The proportion and impact of proactive and reactive SSPs were calculated among five error categories. Proactive interventions impacted more positively than reactive ones in reducing medication errors, technical errors and errors due to personnel. PSSPs and RSSPs had similar effects in reducing errors related to a wrong procedure. A single reactive study influenced non-positively communication errors. A relevant prevalence of the impact of proactive processes on reactive ones is reported. This article can help decision makers in identifying which SSP can be the most appropriate against specific error categories.