ObjectivesIt is disputed whether the time a patient waits for surgery after hip fracture increases the risk of in-hospital death. This uncertainty matters as access to surgery following hip fracture may be underprioritised due to a lack of definitive evidence. Uncertainty in the available evidence may be due to differences in characteristics of patients, their injury and their care. We summarised the literature on patients and system factors associated with time to surgery, and collated proposed mechanisms for the associations.MethodsWe used the framework developed by Arksey and O’Malley and Levac et al for synthesis of factors and mechanisms of time to surgery after hip fracture in adults aged >50 years, published in English, between 1 January 2000 and 28 February 2017, and indexed in MEDLINE, EMBASE, CINAHL or Ageline. Proposed mechanisms for reported associations were extracted from discussion sections.ResultsWe summarised evidence from 26 articles that reported on 24 patient and system factors of time to surgery post hip fracture. In total, 16 factors were reported by only one article. For 16 factors we found proposed mechanisms for their association with time to surgery which included surgical readiness, available resources, prioritisation and out-of-hours admission.ConclusionsWe identified patient and system factors associated with time to surgery after hip fracture. This new knowledge will inform evaluation of the putative timing–death association. Future interventions should be designed to influence factors with modifiable mechanisms for delay.

Inappropriate prescribing in older people is frequent, and is mainly associated with long-acting benzodiazepines. There are diabetic patients who do not have statins prescribed. Multiple medication is associated with PPI and OP.

Introduction Adverse Events (AE) are one of the main problems in healthcare. Therefore, many policies have been developed worldwide to mitigate their impact. The Patient Safety Incident Study in Hospitals in the Community of Madrid (ESHMAD) measures the results of them in the region. Methods Cross‐sectional study, conducted in May 2019, in hospitalised patients in 34 public hospitals using the Harvard Medical Practice Study methodology. A logistic regression model was carried out to study the association of the variables with the presence of AE, calibrated and adjusted by patient. Results A total of 9975 patients were included, estimating a prevalence of AE of 11.9%. A higher risk of AE was observed in patients with surgical procedures (OR[CI95%]: 2.15[1.79 to 2.57], vs. absence), in Intensive Care Units (OR[CI95%]: 1.60[1.17 to 2.17], vs. Medical) and in hospitals of medium complexity (OR[CI95%]: 1.45[1.12 to 1.87], vs. low complexity). A 62.6% of AE increased the length of the stay or it was the cause of admission, and 46.9% of AE were considered preventable. In 11.5% of patients with AE, they had contributed to their death. Conclusions The prevalence of AE remains similar to the previously estimated one in studies developed with the same methodology. AE keep leading to longer hospital stays, contributing to patient's death, showing that it is necessary to put focus on patient safety again. A detailed analysis of these events has enabled the detection of specific areas for improvement according to the type of care, centre and patient.

Objectives Previous research reports numerous factors of post-operative mortality in patients undergoing isolated coronary artery bypass graft surgery. However, this evidence has not been mapped to the conceptual framework of care improvement. Without such mapping, interventions designed to improve care quality remain unfounded. Methods We identified reported factors of in-hospital mortality post isolated coronary artery bypass graft surgery in adults over the age of 19, published in English between January 1, 2000 and December 31, 2019, indexed in PubMed, CINAHL, and EMBASE. We grouped factors and their underlying mechanism for association with in-hospital mortality according to the augmented Donabedian framework for quality of care. Results We selected 52 factors reported in 83 articles and mapped them by case-mix, structure, process, and intermediary outcomes. The most reported factors were related to case-mix (characteristics of patients, their disease, and their preoperative health status) (37 articles, 27 factors). Factors related to care processes (27 articles, 12 factors) and structures (11 articles, 6 factors) were reported less frequently; most proposed mechanisms for their mortality effects. Conclusions Few papers reported on factors of in-hospital mortality related to structures and processes of care, where intervention for care quality improvement is possible. Therefore, there is limited evidence to support quality improvement efforts that will reduce variation in mortality after coronary artery bypass graft surgery.

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