Objectives To determine nurse-sensitive outcomes in district nursing care for community-living older people. Nurse-sensitive outcomes are defined as patient outcomes that are relevant based on nurses’ scope and domain of practice and that are influenced by nursing inputs and interventions. Design A Delphi study following the RAND/UCLA Appropriateness Method with two rounds of data collection. Setting District nursing care in the community care setting in the Netherlands. Participants Experts with current or recent clinical experience as district nurses as well as expertise in research, teaching, practice, or policy in the area of district nursing. Main outcome measures Experts assessed potential nurse-sensitive outcomes for their sensitivity to nursing care by scoring the relevance of each outcome and the ability of the outcome to be influenced by nursing care (influenceability). The relevance and influenceability of each outcome were scored on a nine-point Likert scale. A group median of 7 to 9 indicated that the outcome was assessed as relevant and/or influenceable. To measure agreement among experts, the disagreement index was used, with a score of <1 indicating agreement. Results In Delphi round two, 11 experts assessed 46 outcomes. In total, 26 outcomes (56.5%) were assessed as nurse-sensitive. The nurse-sensitive outcomes with the highest median scores for both relevance and influenceability were the patient’s autonomy, the patient’s ability to make decisions regarding the provision of care, the patient’s satisfaction with delivered district nursing care, the quality of dying and death, and the compliance of the patient with needed care. Conclusions This study determined 26 nurse-sensitive outcomes for district nursing care for community-living older people based on the collective opinion of experts in district nursing care. This insight could guide the development of quality indicators for district nursing care. Further research is needed to operationalise the outcomes and to determine which outcomes are relevant for specific subgroups.
Background: A new selective preventive spinal immobilization (PSI) protocol was introduced in the Netherlands. This may have led to an increase in non-immobilized spinal fractures (NISFs) and consequently adverse patient outcomes. Aim: A pilot study was conducted to describe the adverse patient outcomes in NISF of the PSI protocol change and assess the feasibility of a larger effect study. Methods: Retrospective comparative cohort pilot study including records of trauma patients with a presumed spinal injury who were presented at the emergency department of a level 2 trauma center by the emergency medical service (EMS). The pre-period 2013-2014 (strict PSI protocol), was compared to the post-period 2017-2018 (selective PSI protocol). Primary outcomes were the percentage of records with a NISF who had an adverse patient outcome such as neurological injuries and mortality before and after the protocol change. Secondary outcomes were the sample size calculation for a larger study and the feasibility of data collection. Results: 1,147 records were included; 442 pre-period, and 705 post-period. The NISF-prevalence was 10% (95% CI 7-16, n = 19) and 8% (95% CI 6-11, n = 33), respectively. In both periods, no neurological injuries or mortality due to NISF were found, by which calculating a sample size is impossible. Data collection showed to be feasible. Conclusions: No neurological injuries or mortality due to NISF were found in a strict and a selective PSI protocol. Therefore, a larger study is discouraged. Future studies should focus on which patients really profit from PSI and which patients do not.
Background: Adverse outcome pathway (AOP) networks are versatile tools in toxicology and risk assessment that capture and visualize mechanisms driving toxicity originating from various data sources. They share a common structure consisting of a set of molecular initiating events and key events, connected by key event relationships, leading to the actual adverse outcome. AOP networks are to be considered living documents that should be frequently updated by feeding in new data. Such iterative optimization exercises are typically done manually, which not only is a time-consuming effort, but also bears the risk of overlooking critical data. The present study introduces a novel approach for AOP network optimization of a previously published AOP network on chemical-induced cholestasis using artificial intelligence to facilitate automated data collection followed by subsequent quantitative confidence assessment of molecular initiating events, key events, and key event relationships. Methods: Artificial intelligence-assisted data collection was performed by means of the free web platform Sysrev. Confidence levels of the tailored Bradford-Hill criteria were quantified for the purpose of weight-of-evidence assessment of the optimized AOP network. Scores were calculated for biological plausibility, empirical evidence, and essentiality, and were integrated into a total key event relationship confidence value. The optimized AOP network was visualized using Cytoscape with the node size representing the incidence of the key event and the edge size indicating the total confidence in the key event relationship. Results: This resulted in the identification of 38 and 135 unique key events and key event relationships, respectively. Transporter changes was the key event with the highest incidence, and formed the most confident key event relationship with the adverse outcome, cholestasis. Other important key events present in the AOP network include: nuclear receptor changes, intracellular bile acid accumulation, bile acid synthesis changes, oxidative stress, inflammation and apoptosis. Conclusions: This process led to the creation of an extensively informative AOP network focused on chemical-induced cholestasis. This optimized AOP network may serve as a mechanistic compass for the development of a battery of in vitro assays to reliably predict chemical-induced cholestatic injury.
