OBJECTIVE: To explore and describe the everyday practices (Work-As-Done) that hinder and facilitate patient care transitions from the intensive care unit (ICU) to the ward.
METHODS: Multiple qualitative case studies in the ICU and various specialized wards of three Dutch hospitals. Adult patients planned to be transferred were purposively sampled on a variety of characteristics along with their relative (if present), and the ICU and ward nurses who were involved in the transition process. Data were collected by using multiple sources (i.e., observations, semi-structured interviews and a qualitative survey) and then systematically analyzed using the thematic analysis approach until saturation was reached.
RESULTS: Twenty-six cases were studied. For each case, the actual transfer was observed. Sixteen patients, five relatives and 36 nurses were interviewed. Two patients completed the survey. Fifteen themes emerged from the data, showing that the quality of transitions is influenced by the extent to which nurses anticipate to patient-specific needs (e.g., providing timely and adequate information, orientation, mental support and aftercare) and to the needs of the counterpart to continue care (e.g., by preparing handovers) besides following standard procedures. Data also show that procedures sometimes interfere with what works best in practice (e.g., communication via a liaison service instead of direct communication between ICU and ward nurses).
CONCLUSIONS: Subtle, non-technical nursing skills play an important role in comforting patients and in the coordination of care when patients are transferred from the ICU to the ward.
CONCLUSIONS: These Work-As-Done findings and their underlying narratives, that are often overlooked when focusing on quality improvement, can be used as material to reflect on own practice and raise awareness for its impact on patients. They may stimulate healthcare staff in crafting interventions for optimizing the transition process.

BACKGROUND: Traditionally, wards in acute care hospitals consist predominately of multioccupancy bays with some single rooms. There is an increasing global trend towards a higher proportion of single rooms in hospitals, with the UK National Health Service (NHS) advocating for single-room provision in all new hospital builds. There is limited evidence on the impact of a ward environment incorporating mostly single and some multioccupancy bays on patient care and organisational outcomes.
METHODS: This study will assess the impact of a newly designed 28-bedded ward environment, with 20 single rooms and two four-bedded bays, on patient and staff experiences and outcomes in an acute NHS Trust in East England. The study is divided into two work packages (WP)-WP1 is a quantitative data extraction of routinely collected patient and staff data while WP2 is a mixed-methods process evaluation consisting of one-to-one, in-depth, semistructured interviews with staff, qualitative observations of work processes on the ward and a quantitative data evaluation of routinely collected process evaluation data from patients and staff.
BACKGROUND: Ethical approval was obtained from the UK Health Research Authority (IRAS ID: 334395). Study findings will be shared with key stakeholders, published in peer-reviewed high-impact journals and presented at relevant conferences.

UNASSIGNED: The hospital\'s physical environment can impact health and well-being. Patients spend most of their time in their hospital rooms. However, little experimental evidence supports specific physical design variables in these rooms, particularly for people poststroke. The study aimed to explore the influence of patient room design variables modeled in virtual reality using a controlled experimental design.
UNASSIGNED: Adults within 3 years of stroke who had spent >2 nights in hospital for stroke and were able to consent were included (Melbourne, Australia). Using a factorial design, we immersed participants in 16 different virtual hospital patient rooms in both daytime and nighttime conditions, systematically varying design attributes: patient room occupancy, social connectivity, room size (spaciousness), noise (nighttime), greenery outlook (daytime). While immersed, participants rated their affect (Pick-A-Mood Scale) and preference. Mixed-effect regression analyses were used to explore participant responses to design variables in both daytime and nighttime conditions. Feasibility and safety were monitored throughout. Australian New Zealand Clinical Trials Registry, Trial ID: ACTRN12620000375954.
UNASSIGNED: Forty-four adults (median age, 67 [interquartile range, 57.3-73.8] years, 61.4% male, and a third with stroke in the prior 3-6 months) completed the study in 2019-2020. We recorded and analyzed 701 observations of affective responses (Pick-A-Mood Scale) in the daytime (686 at night) and 698 observations of preference responses in the daytime (685 nighttime) while continuously immersed in the virtual reality scenarios. Although single rooms were most preferred overall (daytime and nighttime), the relationship between affective responses differed in response to different combinations of nighttime noise, social connectivity, and greenery outlook (daytime). The virtual reality scenario intervention was feasible and safe for stroke participants.
UNASSIGNED: Immediate affective responses can be influenced by exposure to physical design variables other than room occupancy alone. Virtual reality testing of how the physical environment influences patient responses and, ultimately, outcomes could inform how we design new interventions for people recovering after stroke.
UNASSIGNED: URL: https://anzctr.org.au; Unique identifier: ACTRN12620000375954.

UNASSIGNED: The frequency at which patients should have their vital signs (e.g. blood pressure, pulse, oxygen saturation) measured on hospital wards is currently unknown. Current National Health Service monitoring protocols are based on expert opinion but supported by little empirical evidence. The challenge is finding the balance between insufficient monitoring (risking missing early signs of deterioration and delays in treatment) and over-observation of stable patients (wasting resources needed in other aspects of care).
UNASSIGNED: Provide an evidence-based approach to creating monitoring protocols based on a patient\'s risk of deterioration and link these to nursing workload and economic impact.
UNASSIGNED: Our study consisted of two parts: (1) an observational study of nursing staff to ascertain the time to perform vital sign observations; and (2) a retrospective study of historic data on patient admissions exploring the relationships between National Early Warning Score and risk of outcome over time. These were underpinned by opinions and experiences from stakeholders.
UNASSIGNED: Observational study: observed nursing staff on 16 randomly selected adult general wards at four acute National Health Service hospitals. Retrospective study: extracted, linked and analysed routinely collected data from two large National Health Service acute trusts; data from over 400,000 patient admissions and 9,000,000 vital sign observations.
UNASSIGNED: Observational study found a variety of practices, with two hospitals having registered nurses take the majority of vital sign observations and two favouring healthcare assistants or student nurses. However, whoever took the observations spent roughly the same length of time. The average was 5:01 minutes per observation over a \'round\', including time to locate and prepare the equipment and travel to the patient area. Retrospective study created survival models predicting the risk of outcomes over time since the patient was last observed. For low-risk patients, there was little difference in risk between 4 hours and 24 hours post observation.
UNASSIGNED: We explored several different scenarios with our stakeholders (clinicians and patients), based on how \'risk\' could be managed in different ways. Vital sign observations are often done more frequently than necessary from a bald assessment of the patient\'s risk, and we show that a maximum threshold of risk could theoretically be achieved with less resource. Existing resources could therefore be redeployed within a changed protocol to achieve better outcomes for some patients without compromising the safety of the rest. Our work supports the approach of the current monitoring protocol, whereby patients\' National Early Warning Score 2 guides observation frequency. Existing practice is to observe higher-risk patients more frequently and our findings have shown that this is objectively justified. It is worth noting that important nurse-patient interactions take place during vital sign monitoring and should not be eliminated under new monitoring processes. Our study contributes to the existing evidence on how vital sign observations should be scheduled. However, ultimately, it is for the relevant professionals to decide how our work should be used.
UNASSIGNED: This study is registered as ISRCTN10863045.
UNASSIGNED: This award was funded by the National Institute for Health and Care Research (NIHR) Health and Social Care Delivery Research programme (NIHR award ref: 17/05/03) and is published in full in Health and Social Care Delivery Research; Vol. 12, No. 6. See the NIHR Funding and Awards website for further award information.
Patient recovery in hospital is tracked by measuring heart rate, blood pressure and other ‘vital signs’ and converting them into a score. These are ‘observed’ regularly by nursing staff so that deterioration can be spotted early. However, taking observations can disturb patients, and taking them too often causes extra work for staff. More frequent monitoring is recommended for higher scores, but evidence is lacking. To work out how often patients should be monitored, we needed to know how likely it is for patients to become more unwell between observations. We analysed over 400,000 patient records from two hospitals to understand how scores change with time. We looked at three of the most serious risks for patients in hospital. These risks are dying, needing intensive care or having a cardiac arrest. We also looked at the risk that a patient’s condition would deteriorate significantly before their measurements were taken again. We identified early signs of deterioration and how changes in vital signs affected the risk of a patient’s condition becoming worse. From this we calculated a maximum risk of deterioration. We then calculated different monitoring schedules that keep individual patients below this risk level. Some of those would consume less staff time than current National Health Service guidelines suggest. We also watched staff record patients’ vital signs. We learnt it takes about 5 minutes to take these measurements from each patient. This information helped us calculate how costs would change if patients’ vital signs were taken more or less often. We found that patients with a low overall score could have their vital signs monitored less often without being in danger of serious harm. This frees up nursing time so that patients with a higher score can be monitored more often. Importantly, this can be achieved without employing more staff.

OBJECTIVE: There is limited data on the effects of discontinuing single-room isolation while maintaining contact precautions, such as the use of gowns and gloves. In April 2021, our hospital ceased single-room isolation for patients with vancomycin-resistant enterococci (VRE) because of single-room unavailability. This study assessed the impact of this policy by examining the incidence of hospital-acquired VRE bloodstream infections (HA-VRE BSI).
METHODS: This retrospective quasi-experimental study was conducted at a tertiary-care hospital in Seoul, South Korea. Time-series analysis was used to evaluate HA-VRE BSI incidence at the hospital level and in the haematology unit before (phase 1) and after (phase 2) the policy change.
RESULTS: At the hospital level, HA-VRE BSI incidence level (VRE BSI per 1000 patient-days per month) and trend did not change significantly between phase 1 and phase 2 (coefficient -0.015, 95% confidence interval (CI): -0.053 to 0.023, P=0.45 and 0.000, 95% CI: -0.002 to 0.002, P=0.84, respectively). Similarly, HA-VRE BSI incidence level and trend in the haematology unit (-0.285, 95% CI: -0.618 to 0.048, P=0.09 and -0.018, 95% CI: -0.036 to 0.000, P = 0.054, respectively) did not change significantly across the two phases.
CONCLUSIONS: Discontinuing single-room isolation of VRE-colonized or infected patients was not associated with an increase in the incidence of VRE BSI at the hospital level or among high-risk patients in the haematology unit. Horizontal intervention for multi-drug-resistant organisms, including measures such as enhanced hand hygiene and environmental cleaning, may be more effective at preventing VRE transmission.

The limitations of current early warning scores have prompted the development of deep learning-based systems, such as deep learning-based cardiac arrest risk management systems (DeepCARS). Unfortunately, in South Korea, only two institutions operate 24-hour Rapid Response System (RRS), whereas most hospitals have part-time or no RRS coverage at all. This study validated the predictive performance of DeepCARS during RRS operation and nonoperation periods and explored its potential beyond RRS operating hours.
Retrospective cohort study.
In this 1-year retrospective study conducted at Yonsei University Health System Severance Hospital in South Korea, DeepCARS was compared with conventional early warning systems for predicting in-hospital cardiac arrest (IHCA). The study focused on adult patients admitted to the general ward, with the primary outcome being IHCA-prediction performance within 24 hours of the alarm.
We analyzed the data records of adult patients admitted to a general ward from September 1, 2019, to August 31, 2020.
None.
Performance evaluation was conducted separately for the operational and nonoperational periods of the RRS, using the area under the receiver operating characteristic curve (AUROC) as the metric. DeepCARS demonstrated a superior AUROC as compared with the Modified Early Warning Score (MEWS) and the National Early Warning Score (NEWS), both during RRS operating and nonoperating hours. Although the MEWS and NEWS exhibited varying performance across the two periods, DeepCARS showed consistent performance.
The accuracy and efficiency for predicting IHCA of DeepCARS were superior to that of conventional methods, regardless of whether the RRS was in operation. These findings emphasize that DeepCARS is an effective screening tool suitable for hospitals with full-time RRS, part-time RRS, and even those without any RRS.

Currently, many hospitals use vital signs-based criteria such as modified early warning score (MEWS) and national early warning score (NEWS) to classify high-risk patients for cardiac arrest, but there are limitations in selecting high-risk patients with a possibility of cardiac arrest. The purpose of this study is to develop a cardiac arrest classification model to identify patients at high risk of cardiac arrest based on the patient family and past history, and blood test results after hospitalization, rather than vital signs. This study used electronic medical record (EMR) data from A university hospital, and patients in the high-risk group for cardiac arrest were defined as those who underwent cardio-pulmonary resuscitation (CPR) after cardiac arrest. Considering the use of the rapid response team of A university hospital, patients hospitalized in intensive care units (ICU), emergency medicine departments, psychiatric departments, pediatric departments, cardiology departments, and palliative care wards were excluded. This study included 325,534 patients, of which 3291 low-risk and 382 high-risk patients were selected for study. Data were split into training and validation data sets and univariate analysis was performed for 13 candidate risk factors. Then, multivariate analysis was performed using a bivariate logistic regression model, and an optimal model was selected using simulation analysis. In the training data set, it was calculated as sensitivity 75.25%, precision 21.59%, specificity 66.89%, accuracy 67.79%, F1 score 33.56, area under curve (AUC) 71.1 (95% confidence interval [CI] = 68.9-73.1 P value=<.001). In the validation data set, sensitivity 73.37%, precision 25.81%, specificity 75.03%, accuracy 74.86%, F1 score 38.19, AUC 74.2 (95% CI = 72.1-76.2, P value=<.001) were calculated. A model for classifying the high-risk group of cardiac arrest should be developed from various perspectives. In the future, in order to classify patients with high risk of cardiac arrest, a prospective study on the combined use of the model developed by this study and NEWS or MEWS should be conducted.

OBJECTIVE: To identify the characteristics of device-related pressure injuries (DRPI) in general ward inpatients, and to confirm the DRPI risk factors by examining differences between a DRPI and non-DRPI group.
METHODS: This study is a retrospective case-control study. High-risk adult patients for pressure injuries (rated at 16 points or less on the Braden scale) who were admitted to a general ward of a tertiary general hospital in South Korea from January 1 to September 30, 2021 were enrolled in this study. Among them, participants were selected by matching the patients with DRPI (n = 50) to the non-DRPI patient group (n = 100) in a ratio of 1:2.
RESULTS: As for risk factors, longer hospitalization periods and the presence of oedema increased DRPI risk. In blood tests, higher glucose levels increased the risk by 1.03 times, and lower albumin levels increased the risk by 0.08 times. Furthermore, the risk of developing DRPI was 7.89 times higher when sedatives were administered.
CONCLUSIONS: Based on the DRPI risk factors identified in this study, patients who have oedema, who have long hospital stays, use sedatives and devices, have a low albumin level, and whose blood glucose is not well controlled should be recognized as having a high risk of developing DRPI. In order to prevent the development of DRPI, it is necessary to recognize risk factors at an early stage, increase actively preventive interventions. The results of this study contribute to recognizing the risk of DRPI in patients and evaluating risk factors for DRPI prevention.

Patient transfer from intensive care units (ICUs) to general wards is a routine part of hospital care. However, if the transfer is not optimal, it can result in increased readmissions to the ICU, increased stress and discomfort for the patient and, thus, a threat to patient safety. The aim of this study was to explore how general ward nurses experience patient safety during patient transfers from ICUs to general wards.
A qualitative design based on a phenomenological approach was used.
Two focus group interviews were conducted with a total of eight nurses from a medical ward and a surgical ward at one hospital in Norway. The data were analysed using systematic text condensation.
The nurses\' experiences of patient safety during patient transfer had four themes: (1) the importance of preparedness; (2) the importance of the handover of information; (3) stress and a lack of resources and (4) a feeling of two different worlds.
In order to promote patient safety, the informants highlighted the importance of being well prepared for transfer, and to have optimal handover of information. Stress, lack of resources and a feeling of two different worlds may pose threats to patient safety.
We suggest several intervention studies testing the effect of intervention improving patient safety during the transfer process are designed, and that increased knowledge in this area is used to develop local practice recommendations.
The participants of this study were nurses and this contribution has been explained in the Data collection section. There was no patient contribution in this study.

The study describes the feasibility and short-to-medium-term efficacy of an evidence-based proton pump inhibitor (PPI) de-prescribing initiative undertaken as part of routine clinical care during acute admissions in a general medical unit. Of the 44 (median (IQR) age 75.5 (13.75) years; females 25 (57%)) who participated in the study, de-prescription was maintained in 29 (66%) and 27 (61%) patients at 12 and 26 weeks respectively.