Improving patient care transitions from the intensive care unit to the ward by learning from everyday practice. A multicenter qualitative study.

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. RESEARCH METHOD/DESIGN: 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. FINDINGS: 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. IMPLICATIONS FOR CLINICAL PRACTICE: 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.

Evaluating the impact of a ward environment with 20 single occupancy rooms and two four-bedded bays on patient and staff experiences and outcomes in an acute NHS Trust: a mixed-methods study protocol.

INTRODUCTION: 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 AND ANALYSES: 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. ETHICS AND DISSEMINATION: 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.

Risk of nosocomial coronavirus disease 2019: comparison between single- and multiple-occupancy rooms.

BACKGROUND: There is an ongoing controversy regarding whether single-occupancy rooms are superior to multiple-occupancy rooms in terms of infection prevention. We investigated whether treatment in a multiple-occupancy room is associated with an increased incidence of nosocomial coronavirus disease 2019 (COVID-19) compared with treatment in a single-occupancy room. METHODS: In this retrospective cohort study, every hospitalization period of adult patients aged ≥ 18 years at a tertiary hospital in Korea from January 1, 2022, to December 31, 2022, was analyzed. If COVID-19 was diagnosed more than 5 days after hospitalization, the case was classified as nosocomial. We estimated the association between the number of patients per room and the risk of nosocomial COVID-19 using a Cox proportional hazards regression model. RESULTS: In total, 25,143 hospitalizations per room type were analyzed. The incidence rate of nosocomial COVID-19 increased according to the number of patients per room; it ranged from 3.05 to 38.64 cases per 10,000 patient-days between single- and 6-bed rooms, respectively. Additionally, the hazard ratios of nosocomial COVID-19 showed an increasing trend according to the number of patients per room, ranging from 0.14 (95% confidence interval 0.001-1.03) to 2.66 (95% confidence interval 1.60-4.85) between single- and 6-bed rooms, respectively. CONCLUSIONS: We demonstrated that the incidence of nosocomial COVID-19 increased according to the number of patients per room. To reduce nosocomial infections by respiratory viruses, the use of multiple-occupancy rooms should be minimized.

Microbial ecology of protective isolation room: Air and Surfaces.

INTRODUCTION: Healthcare-associated infections pose a significant public health burden, leading to morbidity, mortality, prolonged hospital stays, and substantial social and economic costs. Immunocompromised patients are at a heightened risk of nosocomial infections. AIM: This prospective study conducted at Mohammed VI University Hospital of Oujda aimed to assess the microbial ecology of surfaces and air in an immunosuppressed patient room compared to a double hospitalization room. METHODS: Microbiological air purity tests were conducted employing both the sedimentation method and the collision method with the assistance of Microflow Alpha. The sedimentation method used Mueller Hinton with 5% human blood, facilitating the free fall of contaminated dust particles. The collection program employed was set for 10 minutes per 1 m3. For surface sampling, swabs were taken from a 25 cm2 surface. The swabs were immediately forwarded to the Microbiology Laboratory. We carried out both macroscopic and microscopic identification of colonies, followed by definitive biochemical identification using the BD phoenixTM system. Antibiotic susceptibility was assessed through agar diffusion on Muller Hinton medium coupled with the determination of the minimum inhibitory concentration. RESULTS: The results revealed a decreased bacterial count within the protective isolation room, in contrast to the standard hospital room. We noted the predominance of coagulase-negative Staphylococcus spp and Bacillus spp. Staphylococcus aureus and Aspergillus spp, common pathogens in healthcare-associated infections, were notably absent in the protective isolation room. The findings underline the pivotal role of hospital environments in the transmission of healthcare-associated infections. CONCLUSION: The protective isolation room demonstrated effective control of microbial contamination, with fewer and less resistant germs. The study highlighted the significance of air treatment systems in preventing the spread of opportunistic infections. Our study underscored the critical role of microbiological cleanliness in preventing nosocomial infections.

Impact of terminal cleaning in rooms previously occupied by patients with healthcare-associated infections.

Healthcare associated infections (HAIs) are costly but preventable. A limited understanding of the effects of environmental cleaning on the riskiest HAI associated pathogens is a current challenge in HAI prevention. This project aimed to quantify the effects of terminal hospital cleaning practices on HAI pathogens via environmental sampling in three hospitals located throughout the United States. Surfaces were swabbed from 36 occupied patient rooms with a laboratory-confirmed, hospital- or community-acquired infection of at least one of the four pathogens of interest (i.e., Acinetobacter baumannii (A. baumannii), methicillin resistant Staphylococcus aureus (MRSA), vancomycin resistant Enterococcus faecalis/faecium (VRE), and Clostridioides difficile (C. difficile)). Six nonporous, high touch surfaces (i.e., chair handrail, bed handrail, nurse call button, desk surface, bathroom counter near the sink, and a grab bar near the toilet) were sampled in each room for Adenosine Triphosphate (ATP) and the four pathogens of interest before and after terminal cleaning. The four pathogens of interest were detected on surfaces before and after terminal cleaning, but their levels were generally reduced. Overall, C. difficile was confirmed on the desk (n = 2), while MRSA (n = 24) and VRE (n = 25) were confirmed on all surface types before terminal cleaning. After cleaning, only MRSA (n = 6) on bed handrail, chair handrail, and nurse call button and VRE (n = 5) on bathroom sink, bed handrail, nurse call button, toilet grab bar, and C. difficile (n = 1) were confirmed. At 2 of the 3 hospitals, pathogens were generally reduced by >99% during terminal cleaning. One hospital showed that VRE increased after terminal cleaning, MRSA was reduced by 73% on the nurse call button, and VRE was reduced by only 50% on the bathroom sink. ATP detections did not correlate with any pathogen concentration. This study highlights the importance of terminal cleaning and indicates room for improvement in cleaning practices to reduce surface contamination throughout hospital rooms.

The Experiences of Hospital Admission in a Single Room for Older Persons With Dementia and Their Families: A Scoping Review.

INTRODUCTION: When older persons with dementia are admitted to hospital, they often feel disoriented and confused and their cognitive impairment may worsen, purely due to the sudden change in their environment. As such hospital design is recognised as an important aspect in the care and well-being of older persons with dementia. As the number of persons with dementia is increasing, the experience of admission to a hospital with, for example, single rooms is more relevant than ever. AIM AND METHODS: This scoping review aimed to identify, explore and conceptually map the literature reporting on what older people with dementia and their families experienced during admission to a hospital with single room accommodation. We followed the Joanna Briggs Institute recommendations for undertaking a scoping review. In addition, we used the Preferred Reporting Items for Systematic reviews (PRISMA-ScR) Checklist, which assisted the development and reporting of this scoping review. RESULTS: We included 10 sources within a time frame of 23 years (1998-2021). The sources originate from Europe, Australia and Canada. We identified three conceptual maps: Safety and security, Privacy and dignity and Sensorial stimulation. Our review demonstrates that the themes of the three conceptual maps are experienced as mutually interdependent for the older persons with dementia and their families. CONCLUSION: We conclude that it is not merely the single room design that determines what the older persons with dementia and their families experience as important; the exposure to sensorial stimulation and the presence of well-trained staff taking a dignified patient-centred approach are also crucial for their experience of high-quality nursing care.

Secondary attack rate following on-site isolation of patients with suspected COVID-19 in multiple-bed rooms.

The implementation of isolation precautions for patients with suspected Coronavirus Disease 2019 (COVID-19) and pending test results is resource intensive. Due to the limited availability of single-bed rooms at our institution, we isolated patients with suspected COVID-19 together with patients without suspected COVID-19 on-site in multiple-bed rooms until SARS-CoV-2-test results were available. We evaluated the likelihood of SARS-CoV-2 transmission to individuals sharing the room with patients isolated on-site. This observational study was performed at the University Hospital Basel, Switzerland, from 03/20 - 11/20. Secondary attack rates were compared between patients hospitalized in multiple-bed rooms and exposed to individuals subjected to on-site isolation precautions (on-site isolation group), and patients exposed to individuals initially not identified as having COVID-19, and not placed under isolation precautions until the diagnosis was suspected (control group). Transmission events were confirmed by whole-genome sequencing. Among 1,218 patients with suspected COVID-19, 67 (5.5%) tested positive for SARS-CoV-2. Of these, 21 were isolated on-site potentially exposing 27 patients sharing the same room. Median contact time was 12 h (interquartile range 7-18 h). SARS-CoV-2 transmission was identified in none of the patients in the on-site isolation group vs. 10/63 (15.9%) in the control group (p = 0.03). Isolation on-site of suspected COVID-19-patients in multiple-bed rooms avoided single-room occupancy and subsequent in-hospital relocation for many patients without confirmed SARS-CoV-2-infection. The absence of secondary transmission among the exposed patients in the on-site isolation group allows for assessment of the risk/benefit ratio of this strategy given the limitation of a small sample size.

Re-Imagining Hospital Patient Room Design for People After stroke: A Randomized Controlled Study Using Virtual Reality.

BACKGROUND: 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. METHODS: 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. RESULTS: 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. CONCLUSIONS: 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. REGISTRATION: URL: https://anzctr.org.au; Unique identifier: ACTRN12620000375954.

The silent threat: investigating sleep disturbances in hospitalized patients.

Sleep disruptions in the hospital setting can have adverse effects on patient safety and well-being, leading to complications like delirium and prolonged recovery. This study aimed to comprehensively assess the factors influencing sleep disturbances in hospital wards, with a comparison of the sleep quality of patients staying in single rooms to those in shared rooms. A mixed-methods approach was used to examine patient-reported sleep quality and sleep disruption factors, in conjunction with objective noise measurements, across seven inpatient wards at an acute tertiary public hospital in Sydney, Australia. The most disruptive factor to sleep in the hospital was noise, ranked as 'very disruptive' by 20% of patients, followed by acute health conditions (11%) and nursing interventions (10%). Patients in shared rooms experienced the most disturbed sleep, with 51% reporting 'poor' or 'very poor' sleep quality. In contrast, only 17% of the patients in single rooms reported the same. Notably, sound levels in shared rooms surpassed 100 dB, highlighting the potential for significant sleep disturbances in shared patient accommodation settings. The results of this study provide a comprehensive overview of the sleep-related challenges faced by patients in hospital, particularly those staying in shared rooms. The insights from this study offer guidance for targeted healthcare improvements to minimize disruptions and enhance the quality of sleep for hospitalized patients.

Visibility-based layout of a hospital unit - An optimization approach.

A patient fall is one of the adverse events in an inpatient unit of a hospital that can lead to disability and/or mortality. The medical literature suggests that increased visibility of patients by unit nurses is essential to improve patient monitoring and, in turn, reduce falls. However, such research has been descriptive in nature and does not provide an understanding of the characteristics of an optimal inpatient unit layout from a visibility-standpoint. To fill this gap, we adopt an interdisciplinary approach that combines the human field of view with facility layout design approaches. Specifically, we propose a bi-objective optimization model that jointly determines the optimal (i) location of a nurse in a nursing station and (ii) orientation of a patient's bed in a room for a given layout. The two objectives are maximizing the total visibility of all patients across patient rooms and minimizing inequity in visibility among those patients. We consider three different layout types, L-shaped, I-shaped, and Radial; these shapes exhibit the section of an inpatient unit that a nurse oversees. To estimate visibility, we employ the ray casting algorithm to quantify the visible target in a room when viewed by the nurse from the nursing station. The algorithm considers nurses' horizontal visual field and their depth of vision. Owing to the difficulty in solving the bi-objective model, we also propose a Multi-Objective Particle Swarm Optimization (MOPSO) heuristic to find (near) optimal solutions. Our findings suggest that the Radial layout appears to outperform the other two layouts in terms of the visibility-based objectives. We found that with a Radial layout, there can be an improvement of up to 50% in equity measure compared to an I-shaped layout. Similar improvements were observed when compared to the L-shaped layout as well. Further, the position of the patient's bed plays a role in maximizing the visibility of the patient's room. Insights from our work will enable understanding and quantifying the relationship between a physical layout and the corresponding provider-to-patient visibility to reduce adverse events.

The impact of discontinuing single-room isolation of patients with vancomycin-resistant enterococci: a quasi-experimental single-centre study in South Korea.

OBJECTIVES: 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.

Safer and more efficient vital signs monitoring protocols to identify the deteriorating patients in the general hospital ward: an observational study.

Background: 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). Objective: 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. Design: 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. Setting and participants: 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. Results: 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. Conclusions: 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. Study registration: This study is registered as ISRCTN10863045. Funding: 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.

Effectiveness of Implementing Modified Early Warning System and Rapid Response Team for General Ward Inpatients.

This retrospective study assessed the effectiveness and impact of implementing a Modified Early Warning System (MEWS) and Rapid Response Team (RRT) for inpatients admitted to the general ward (GW) of a medical center. This study included all inpatients who stayed in GWs from Jan. 2017 to Feb. 2022. We divided inpatients into GWnon-MEWS and GWMEWS groups according to MEWS and RRT implementation in Aug. 2019. The primary outcome, unexpected deterioration, was defined by unplanned admission to intensive care units. We defined the detection performance and effectiveness of MEWS according to if a warning occurred within 24 h before the unplanned ICU admission. There were 129,039 inpatients included in this study, comprising 58,106 GWnon-MEWS and 71,023 GWMEWS. The numbers of inpatients who underwent an unplanned ICU admission in GWnon-MEWS and GWMEWS were 488 (.84%) and 468 (.66%), respectively, indicating that the implementation significantly reduced unexpected deterioration (p < .0001). Besides, 1,551,525 times MEWS assessments were executed for the GWMEWS. The sensitivity, specificity, positive predicted value, and negative predicted value of the MEWS were 29.9%, 98.7%, 7.09%, and 99.76%, respectively. A total of 1,568 warning signs accurately occurred within the 24 h before an unplanned ICU admission. Among them, 428 (27.3%) met the criteria for automatically calling RRT, and 1,140 signs necessitated the nursing staff to decide if they needed to call RRT. Implementing MEWS and RRT increases nursing staff's monitoring and interventions and reduces unplanned ICU admissions.

Wireless continuous single-lead ST-segment monitoring to detect new-onset myocardial injury at the general ward-An exploratory subanalysis.

Patients admitted for acute medical conditions and major noncardiac surgery are at risk of myocardial injury. This is frequently asymptomatic, especially in the context of concomitant pain and analgesics, and detection thus relies on cardiac biomarkers. Continuous single-lead ST-segment monitoring from wireless electrocardiogram (ECG) may enable more timely intervention, but criteria for alerts need to be defined to reduce false alerts. This study aimed to determine optimal ST-deviation thresholds from wireless single-lead ECG for detection of myocardial injury following major abdominal cancer surgery and during acute exacerbation of chronic obstructive pulmonary disease. Patients were monitored with a wireless single-lead ECG patch for up to 4 days and had daily troponin measurements. Single-lead ST-segment deviations of <0.255 mV and/or >0.245 mV (based on previous study comparison with 0.1 mV 12-lead ECG and variation in single-lead ECG) were analyzed for relation to myocardial injury defined as hsTnT elevation of 20-64 ng/L with an absolute change of ≥5 ng/L, or a hsTnT level ≥ 65 ng/L. In total, 528 patients were included for analysis, of which 15.5% had myocardial injury. For corrected ST-thresholds lasting ≥10 and ≥ 20 min, we found specificities of 91% and 94% and sensitivities of 17% and 13% with odds ratios of 2.0 (95% CI: 1.1; 3.9) and 2.4 (95% CI: 1.1; 5.1) for myocardial injury. In conclusion, wireless single-lead ECG monitoring with corrected ST thresholds detected patients developing myocardial injury with specificities >90% and sensitivities <20%, suggesting increased focus on sensitivity improvement.

Is it possible to estimate the number of patients with COVID-19 admitted to intensive care units and general wards using clinical and telemedicine data?

BACKGROUND: Gabaldi et al. utilized telemedicine data, web search trends, hospitalized patient characteristics, and resource usage data to estimate bed occupancy during the COVID-19 pandemic. The results showcase the potential of data-driven strategies to enhance resource allocation decisions for an effective pandemic response. OBJECTIVE: To develop and validate predictive models to estimate the number of COVID-19 patients hospitalized in the intensive care units and general wards of a private not-for-profit hospital in São Paulo, Brazil. METHODS: Two main models were developed. The first model calculated hospital occupation as the difference between predicted COVID-19 patient admissions, transfers between departments, and discharges, estimating admissions based on their weekly moving averages, segmented by general wards and intensive care units. Patient discharge predictions were based on a length of stay predictive model, assessing the clinical characteristics of patients hospitalized with COVID-19, including age group and usage of mechanical ventilation devices. The second model estimated hospital occupation based on the correlation with the number of telemedicine visits by patients diagnosed with COVID-19, utilizing correlational analysis to define the lag that maximized the correlation between the studied series. Both models were monitored for 365 days, from May 20th, 2021, to May 20th, 2022. RESULTS: The first model predicted the number of hospitalized patients by department within an interval of up to 14 days. The second model estimated the total number of hospitalized patients for the following 8 days, considering calls attended by Hospital Israelita Albert Einstein's telemedicine department. Considering the average daily predicted values for the intensive care unit and general ward across a forecast horizon of 8 days, as limited by the second model, the first and second models obtained R² values of 0.900 and 0.996, respectively and mean absolute errors of 8.885 and 2.524 beds, respectively. The performances of both models were monitored using the mean error, mean absolute error, and root mean squared error as a function of the forecast horizon in days. CONCLUSION: The model based on telemedicine use was the most accurate in the current analysis and was used to estimate COVID-19 hospital occupancy 8 days in advance, validating predictions of this nature in similar clinical contexts. The results encourage the expansion of this method to other pathologies, aiming to guarantee the standards of hospital care and conscious consumption of resources. BACKGROUND: Developed models to forecast bed occupancy for up to 14 days and monitored errors for 365 days. BACKGROUND: Telemedicine calls from COVID-19 patients correlated with the number of patients hospitalized in the next 8 days.

Pioneering the Use of Tracker Data to Evaluate Lean-Led Hospital Design.

OBJECTIVE: This study aims to examine how we can effectively and affordably evaluate the impact of design concepts such as Lean-Led Hospital Design (LLHD) on the allocation of nurses' time spent at different locations. Particularly in patient rooms, as this can be seen as value-adding time. BACKGROUND: LLHD aims to create a hospital environment that supports value creation for patients and reduces waste. However, only a few studies measure its' effects. One of the reasons for this absence is the lack of an adequate and affordable way to evaluate. METHOD: Nurses' time spent in patient rooms was used as a proxy for value-adding time. Through studying a pioneering case of LLHD, and drawing on a pre-/postoccupancy evaluation approach, this study used an innovative methodology utilizing mobile tracking devices to adequately provide reliable data about the time nurses spend at specific locations. RESULTS: Our analysis reveals that the answer to the question concerning the impact of LLHD, as advocated by its proponents, on nurses' allocation of time for value-adding activities versus waste time remains inconclusive. Our findings indicate no discernible difference in the amount of value-adding time nurses spent in the old facility compared to the new one. CONCLUSION: Our experience suggests that mobile tracking devices offer an affordable, efficient means of collecting data that produces objective measurements. Nevertheless, the interpretation of this time-based data necessitates the inclusion of supplementary qualitative information.

External Validation of Deep Learning-Based Cardiac Arrest Risk Management System for Predicting In-Hospital Cardiac Arrest in Patients Admitted to General Wards Based on Rapid Response System Operating and Nonoperating Periods: A Single-Center Study.

OBJECTIVES: 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. DESIGN: Retrospective cohort study. SETTING: 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. PATIENTS: We analyzed the data records of adult patients admitted to a general ward from September 1, 2019, to August 31, 2020. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: 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. CONCLUSIONS: 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.

[Hypercalcaemia: intensive care or general ward]. / Die Hyperkalzämie ­ Intensivmedizin oder Normalstation.

Hypercalcaemia is a life-threatening electrolyte imbalance, which not only occurs in the context of an endocrinological disease but is also frequently associated with a tumour. Its severity is determined by the level of deviation from normal, acuity of occurrence, and severity of the symptoms. These are unspecific, can affect any organ system and ultimately result in a life-threatening hypercalcaemic crisis characterised by cardiac arrhythmia, metabolic acidosis, exsiccosis, fever, psychotic states and, ultimately, coma. Endocrinological disorders, drugs such as vitamin D3, vitamin A, checkpoint inhibitors, but also malignancies can be causative for the development of hypercalcaemia. Up to 30% of tumour patients are affected by hypercalcaemia. It is associated with a poor prognosis and a high tumour burden. Malignant hypercalcaemia is mainly caused by PTHrP (parathormone-related peptide), which is secreted by the tumour cells. In oncological patients, serum calcium (ionised calcium and non-ionised calcium) should be evaluated regularly. As the level of serum calcium depends on the albumin concentration, the latter should also be evaluated. Treatment consists of increasing the intravasal volume, increasing calcium excretion and inhibiting calcium reabsorption.

Development of a deep learning model that predicts critical events of pediatric patients admitted to general wards.

Early detection of deteriorating patients is important to prevent life-threatening events and improve clinical outcomes. Efforts have been made to detect or prevent major events such as cardiopulmonary resuscitation, but previously developed tools are often complicated and time-consuming, rendering them impractical. To overcome this problem, we designed this study to create a deep learning prediction model that predicts critical events with simplified variables. This retrospective observational study included patients under the age of 18 who were admitted to the general ward of a tertiary children's hospital between 2020 and 2022. A critical event was defined as cardiopulmonary resuscitation, unplanned transfer to the intensive care unit, or mortality. The vital signs measured during hospitalization, their measurement intervals, sex, and age were used to train a critical event prediction model. Age-specific z-scores were used to normalize the variability of the normal range by age. The entire dataset was classified into a training dataset and a test dataset at an 8:2 ratio, and model learning and testing were performed on each dataset. The predictive performance of the developed model showed excellent results, with an area under the receiver operating characteristics curve of 0.986 and an area under the precision-recall curve of 0.896. We developed a deep learning model with outstanding predictive power using simplified variables to effectively predict critical events while reducing the workload of medical staff. Nevertheless, because this was a single-center trial, no external validation was carried out, prompting further investigation.

[Changes in Patient Safety Culture Attitudes Among Emergency, Intensive Care, and General Ward Nurses During the COVID-19 Pandemic].

BACKGROUND: Patient safety culture is an indicator of healthcare quality and a topic of global importance in medical care. PURPOSE: In this study, the attitudes towards patient safety culture of nursing staff working in the emergency, intensive care, and general wards are compared before and during the COVID-19 pandemic. METHODS: A retrospective research design was utilized and an anonymous questionnaire survey conducted on the Taiwan Patient Safety Culture Survey web-based platform system was used to collect the data. The survey was administered in a regional hospital in northern Taiwan between 2018 and 2020. The 1,540 nursing personnel who participated in this study worked in the emergency, intensive care units, or general adult ward. The analysis focused on assessing participant attitudes towards patient safety culture in terms of both the overall score and sub-dimensions. RESULTS: The participants were mostly female and between 21 and 30 years old. A majority had completed a diploma or university education. The two analyses revealed the highest and lowest average scores were earned, respectively, in the "teamwork" and "resilience" dimensions of patient safety culture. In 2020, the average scores for all dimensions were lower than in 2018, and the average scores for the emergency and critical care group were lower than those for the general adult ward group. Sub-dimension analysis showed that the general adult ward group earned significantly higher scores in "teamwork" across all three sub-dimensions compared to the emergency and critical care groups. The general ward group exhibited the most significant score decline between the two surveys. CONCLUSIONS / IMPLICATIONS FOR PRACTICE: Overall scores were found to have decreased during the COVID-19 pandemic period (2020). Notably, emergency and intensive care nurses earned consistently lower scores, likely due to the severity of patient conditions and increased pandemic-related workloads and stress. "Resilience" scores were the lowest among all nursing staff, with the most significant drop seen in general ward nurses. Enhancing nursing staff education and training as well as addressing their psychological well-being will be crucial to improving patient safety culture attitudes. Managers should provide infection control, resilience training, and psychological counseling to help nurses manage the challenges posed by infectious diseases effectively and enhance patient safety culture.