Adverse events (AEs) seriously affect patient safety and quality of care, and remain a pressing global issue. This study had three objectives: (1) to describe the proportions of patients affected by in-hospital AEs; (2) to explore the types and consequences of observed AEs; and (3) to estimate the preventability of in-hospital AEs. We applied a scoping review method and concluded a comprehensive literature search in PubMed and CINAHL in May 2017 and in February 2018. Our target was retrospective medical record review studies applying the Harvard method–or similar methods using screening criteria–conducted in acute care hospital settings on adult patients (≥18 years). We included a total of 25 studies conducted in 27 countries across six continents. Overall, a median of 10% patients were affected by at least one AE (range: 2.9–21.9%), with a median of 7.3% (range: 0.6–30%) of AEs being fatal. Between 34.3 and 83% of AEs were considered preventable (median: 51.2%). The three most common types of AEs reported in the included studies were operative/surgical related, medication or drug/fluid related, and healthcare-associated infections. Evidence regarding the occurrence of AEs confirms earlier estimates that a tenth of inpatient stays include adverse events, half of which are preventable. However, the incidence of in-hospital AEs varied considerably across studies, indicating methodological and contextual variations regarding this type of retrospective chart review across health care systems. For the future, automated methods for identifying AE using electronic health records have the potential to overcome various methodological issues and biases related to retrospective medical record review studies and to provide accurate data on their occurrence.

Objectives 12 h shifts are becoming increasingly common for hospital nurses but there is concern that long shifts adversely affect nurses’ well-being, job satisfaction and intention to leave their job. The aim of this study is to examine the association between working long shifts and burnout, job dissatisfaction, dissatisfaction with work schedule flexibility and intention to leave current job among hospital nurses. Methods Cross-sectional survey of 31 627 registered nurses in 2170 general medical/surgical units within 488 hospitals across 12 European countries. Results Nurses working shifts of ≥12 h were more likely than nurses working shorter hours (≤8) to experience burnout, in terms of emotional exhaustion (adjusted OR (aOR)=1.26; 95% CI 1.09 to 1.46), depersonalisation (aOR=1.21; 95% CI 1.01 to 1.47) and low personal accomplishment (aOR=1.39; 95% CI 1.20 to 1.62). Nurses working shifts of ≥12 h were more likely to experience job dissatisfaction (aOR=1.40; 95% CI 1.20 to 1.62), dissatisfaction with work schedule flexibility (aOR=1.15; 95% CI 1.00 to 1.35) and report intention to leave their job due to dissatisfaction (aOR=1.29; 95% CI 1.12 to 1.48). Conclusions Longer working hours for hospital nurses are associated with adverse outcomes for nurses. Some of these adverse outcomes, such as high burnout, may pose safety risks for patients as well as nurses.

Background: Despite concerns as to whether nurses can perform reliably and effectively when working longer shifts, a pattern of two 12- to 13-hour shifts per day is becoming common in many hospitals to reduce shift to shift handovers, staffing overlap, and hence costs. Objectives: To describe shift patterns of European nurses and investigate whether shift length and working beyond contracted hours (overtime) is associated with nurse-reported care quality, safety, and care left undone. Methods: Cross-sectional survey of 31,627 registered nurses in general medical/surgical units within 488 hospitals across 12 European countries. Results: A total of 50% of nurses worked shifts of ≤8 hours, but 15% worked ≥12 hours. Typical shift length varied between countries and within some countries. Nurses working for ≥12 hours were more likely to report poor or failing patient safety [odds ratio (OR)=1.41; 95% confidence interval (CI), 1.13–1.76], poor/fair quality of care (OR=1.30; 95% CI, 1.10–1.53), and more care activities left undone (RR=1.13; 95% CI, 1.09–1.16). Working overtime was also associated with reports of poor or failing patient safety (OR=1.67; 95% CI, 1.51–1.86), poor/fair quality of care (OR=1.32; 95% CI, 1.23–1.42), and more care left undone (RR=1.29; 95% CI, 1.27–1.31). Conclusions: European registered nurses working shifts of ≥12 hours and those working overtime report lower quality and safety and more care left undone. Policies to adopt a 12-hour nursing shift pattern should proceed with caution. Use of overtime working to mitigate staffing shortages or increase flexibility may also incur additional risk to quality.

Objectives The purpose of this study was to provide normative data on fall prevalence in U.S. hospitals by unit type and to determine the 27-month secular trend in falls before the implementation of the Centers for Medicare and Medicaid Service (CMS) rule, which does not reimburse hospitals for care related to injury resulting from hospital falls. Methods We used data from the National Database of Nursing Quality Indicators (NDNQI) collected between July 1, 2006, and September 30, 2008, to estimate prevalence and secular trends of falls occurring in adult medical, medical-surgical, and surgical nursing units. More than 88 million patient days (pd) of observation were contributed from 6100 medical, surgical, and medical-surgical nursing units in 1263 hospitals across the United States. Results A total of 315,817 falls occurred (rate = 3.56 falls/1000 pd) during the study period, of which, 82,332 (26.1%) resulted in an injury (rate = 0.93/1000 pd). Both total fall and injurious fall rates were highest in medical units (fall rate = 4.03/1000 pd; injurious fall rate = 1.08/1000 pd) and lowest in surgery units (fall rate = 2.76/1000 pd; injurious fall rate = 0.67/1000 pd). Falls (0.4% decrease per quarter, P < 0.0001) and injurious falls (1% decrease per quarter, P < 0.0001) both decreased over the 27-month study. Conclusions In this large sample, fall and injurious fall prevalence varied by nursing unit type in U.S. hospitals. Over the 27-month study, there was a small, but statistically significant, decrease in falls (P < 0.0001) and injurious falls (P < 0.0001).

Background: Understanding how comorbidity measures contribute to patient mortality is essential both to describe patient health status and to adjust for risks and potential confounding. The Charlson and Elixhauser comorbidity indices are well-established for risk adjustment and mortality prediction. Still, a different set of comorbidity weights might improve the prediction of in-hospital mortality. The present study, therefore, aimed to derive a set of new Swiss Elixhauser comorbidity weightings, to validate and compare them against those of the Charlson and Elixhauser-based van Walraven weights in an adult in-patient population-based cohort of general hospitals.Methods: Retrospective analysis was conducted with routine data of 102 Swiss general hospitals (2012–2017) for 6.09 million inpatient cases. To derive the Swiss weightings for the Elixhauser comorbidity index, we randomly halved the inpatient data and validated the results of part 1 alongside the established weighting systems in part 2, to predict in-hospital mortality. Charlson and van Walraven weights were applied to Charlson and Elixhauser comorbidity indices. Derivation and validation of weightings were conducted with generalized additive models adjusted for age, gender and hospital types.Results: Overall, the Elixhauser indices, c-statistic with Swiss weights (0.867, 95% CI, 0.865–0.868) and van Walraven’s weights (0.863, 95% CI, 0.862–0.864) had substantial advantage over Charlson’s weights (0.850, 95% CI, 0.849–0.851) and in the derivation and validation groups. The net reclassification improvement of new Swiss weights improved the predictive performance by 1.6% on the Elixhauser-van Walraven and 4.9% on the Charlson weights.Conclusions: All weightings confirmed previous results with the national dataset. The new Swiss weightings model improved slightly the prediction of in-hospital mortality in Swiss hospitals. The newly derive weights support patient population-based analysis of in-hospital mortality and seek country or specific cohort-based weightings.