Association between intrahospital transfer and hospital-acquired infection in the elderly: a retrospective case-control study in a UK hospital network

Role of admission rapid antigen testing (RATs) for COVID-19 on patients transferred from acute hospitals to a post-acute rehabilitation setting

BACKGROUND

Rapid antigen tests (RATs) are suitable for point-of -care testing, require no laboratory time and give immediate results. However, are RATs useful for detecting asymptomatic COVID-19 infection when compared with polymerase chain reaction (PCR) testing in healthcare settings?

AIM

The aim of this study was to implement a reliable testing system utilising RATs to promptly detect COVID-19 infection in predominantly asymptomatic patients transferred from acute hospitals to a post-acute rehabilitation unit (PARU).

METHODS

RAT testing was carried out on all new admissions without a history of confirmed Covid-19 infection within three months of admission. PCR testing was carried out on all patients with a positive RAT for confirmation purposes. The cycle threshold (Ct) values of COVID-19 detected results on PCR testing were examined to determine the utility of the RATs.

RESULTS

A total of 1,403 patients were transferred to the PARU from January to December 2023. The results of the study revealed an 85% accuracy of RATs with a 15% rate of false negative results at the time of admission. All patients that had a positive RAT at the time of admission also had a positive PCR test.

CONCLUSION

This testing algorithm resulted in early detection and prompt isolation of positive cases reducing the likely spread of COVID-19 infection, hospital outbreaks and bed/ward closures.

Estimating the impact on patient safety of enabling the digital transfer of patients' prescription information in the English NHS

OBJECTIVES

To estimate the number and burden of medication errors associated with prescription information transfer within the National Health Service (NHS) in England and the impact of implementing an interoperable prescription information system (a single digital prescribing record shared across NHS settings) in reducing these errors.

METHODS

We constructed a probabilistic mathematical model. We estimated the number of transition medication errors that would be undetected by standard medicines reconciliation, based on published literature, and scaled this up based on the annual number of hospital admissions. We used published literature to estimate the proportion of errors that lead to harm and applied this to the number of errors to estimate the associated burden (healthcare resource use and deaths). Finally, we used reported effect sizes for electronic prescription information sharing interventions to estimate the impact of implementing an interoperable prescription information system on number of errors and resulting harm.

RESULTS

Annually, around 1.8 million (95% credibility interval (CrI) 1.3 to 2.6 million) medication errors were estimated to occur at hospital transitions in England, affecting approximately 380 000 (95% CrI 260 397 to 539 876) patient episodes. Harm from these errors affects around 31 500 (95% CrI 22 407 to 42 906) patients, with 36 500 (95% CrI 25 093 to 52 019) additional bed days of inpatient care (costing around £17.8 million (95% CrI £12.4 to £24.9 million)) and >40 (95% CrI 9 to 146) deaths. Assuming the implementation of an interoperable prescription information system could reduce errors by 10% and 50%, there could be 180 000-913 000 fewer errors, 3000-15 800 fewer people who experience harm and 4-22 lives saved annually.

CONCLUSIONS

An interoperable prescription information system could provide major benefits for patient safety. Likely additional benefits include healthcare professional time saved, improved patient experience and care quality, quicker discharge and enhanced cross-organisational medicines optimisation. Our findings provide vital safety and economic evidence for the case to adopt interoperable prescription information systems.

Predisposing Factors of Nosocomial Infections in Hospitalized Patients in the United Kingdom: Systematic Review

BACKGROUND

Nosocomial infections are infections incubating or not present at the time of admission to a hospital and manifest 48 hours after hospital admission. The specific factors contributing to the risk of infection during hospitalization remain unclear, particularly for the hospitalized population of the United Kingdom.

OBJECTIVE

The aim of this systematic literature review was to explore the risk factors of nosocomial infections in hospitalized adult patients in the United Kingdom.

METHODS

A comprehensive keyword search was conducted through the PubMed, Medline, and EBSCO CINAHL Plus databases. The keywords included "risk factors" or "contributing factors" or "predisposing factors" or "cause" or "vulnerability factors" and "nosocomial infections" or "hospital-acquired infections" and "hospitalized patients" or "inpatients" or "patients" or "hospitalized." Additional articles were obtained through reference harvesting of selected articles. The search was limited to the United Kingdom with papers written in English, without limiting for age and gender to minimize bias. The above process retrieved 377 articles, which were further screened using inclusion and exclusion criteria following the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines. The retained 9 studies were subjected to critical appraisal using the Critical Appraisal Skills Programme (cohort and case-control studies) and Appraisal Tool for Cross-Sectional Studies (cross-sectional studies) checklists. Finally, 6 eligible publications were identified and used to collect the study findings. A thematic analysis technique was used to analyze data extracted on risk factors of nosocomial infections in hospitalized patients in the United Kingdom.

RESULTS

The risk factors for nosocomial infections that emerged from the reviewed studies included older age, intrahospital transfers, cross-infection, longer hospital stay, readmissions, prior colonization with opportunistic organisms, comorbidities, and prior intake of antibiotics and urinary catheters. Nosocomial infections were associated with more extended hospital stays, presenting with increased morbidity and mortality. Measures for controlling nosocomial infections included the use of single-patient rooms, well-equipped wards, prior screening of staff and patients, adequate sick leave for staff, improved swallowing techniques and nutritional intake for patients, improved oral hygiene, avoiding unnecessary indwelling plastics, use of suprapubic catheters, aseptic techniques during patient care, and prophylactic use.

CONCLUSIONS

There is a need for further studies to aid in implementing nosocomial infection prevention and control.

Carbapenem-resistant Acinetobacter baumannii infections: Antimicrobial resistance patterns and risk factors for acquisition in a Kenyan intensive care unit

Objectives

Multidrug-resistant (MDR) Acinetobacter baumannii (AB), especially carbapenem-resistant (CR) strains, presents a significant challenge in intensive care units (ICUs) but surveillance data in many resource-constrained countries is inadequate. Here, we determined the prevalence of MDRAB and risk factors for infection and mortality in ICU-admitted patients.

Methods

A cross-sectional study among 132 consecutive patients between July 2019 and July 2020, with infected patients followed for 30 days from sample collection to ICU discharge/death. Blood, urine, and tracheal aspirate samples were processed following the standard bacteriological procedures. Isolate identity and antimicrobial susceptibility were elucidated by VITEK 2 Compact system.

Results

The prevalence of MDRAB was 22.7% (30/132), mostly from urine samples (12.1%, 16/132), and dominated by CRAB (83.3%) that were colistin-nonresistant and exhibited high multiple antibiotic resistance indices, ranging from 0.64-0.91. Risk factors for infection were occupation (adjusted odds ratio = 4.41, P = 0.016) and interhospital referral status (adjusted odds ratio = 0.14, P = 0.001). ICU mortality was 20% (6/30).

Conclusion

Our findings underpin the need for strict adherence to and evaluation of infection prevention and control, and continuous surveillance of CRAB in ICU, especially among the risk groups, in the current study setting and beyond.

The impact of atypical intrahospital transfers on patient outcomes: a mixed methods study

The architectural design of hospitals worldwide is centred around individual departments, which require the movement of patients between wards. However, patients do not always take the simplest route from admission to discharge, but can experience convoluted movement patterns, particularly when bed availability is low. Few studies have explored the impact of these rarer, atypical trajectories. Using a mixed-method explanatory sequential study design, we firstly used three continuous years of electronic health record data prior to the Covid-19 pandemic, from 55,152 patients admitted to a London hospital network to define the ward specialities by patient type using the Herfindahl-Hirschman index. We explored the impact of 'regular transfers' between pairs of wards with shared specialities, 'atypical transfers' between pairs of wards with no shared specialities and 'site transfers' between pairs of wards in different hospital site locations, on length of stay, 30-day readmission and mortality. Secondly, to understand the possible reasons behind atypical transfers we conducted three focus groups and three in-depth interviews with site nurse practitioners and bed managers within the same hospital network. We found that at least one atypical transfer was experienced by 12.9% of patients. Each atypical transfer is associated with a larger increase in length of stay, 2.84 days (95% CI 2.56-3.12), compared to regular transfers, 1.92 days (95% CI 1.82-2.03). No association was found between odds of mortality, or 30-day readmission and atypical transfers after adjusting for confounders. Atypical transfers appear to be driven by complex patient conditions, a lack of hospital capacity, the need to reach specific services and facilities, and more exceptionally, rare events such as major incidents. Our work provides an important first step in identifying unusual patient movement and its impacts on key patient outcomes using a system-wide, data-driven approach. The broader impact of moving patients between hospital wards, and possible downstream effects should be considered in hospital policy and service planning.

Nursing Home Residents' Use of Radiography in New Brunswick: A Case for Mobile Radiography?

Introduction

Identifying ways to eliminate unnecessary transfer of nursing home (NH) residents to hospitals provides an opportunity to improve outcomes and use scarce healthcare resources more efficiently. This study's goal was to better understand where NH residents access X-ray (XR) and computed tomography (CT) scans and to determine if there was a case for mobile radiography policies in New Brunswick.

Methods

A retrospective analysis of all the visits to the emergency department (ED) and outpatient imaging departments in two hospitals in Saint John, New Brunswick, in 2020, that involved XR or CT investigations was conducted.

Results

There were 521 visits by 311 unique NH residents and 920 investigations (688 XR and 232 CT scans). Most investigations were ordered in the ED (696 of 920; 75.6%; confidence interval: 72.8-78.3%). Of the NH residents who visited the ED and received either an XR or a CT scan, 33.2% received only XR imaging and were discharged back to the NH after a mean ED stay of 5.15 hours.

Discussion

The pattern of NH residents' use of the ED for their imaging needs supports the creation of mobile XR policies to deliver more safe and efficient care in a Canadian medium population urban centre.

Global prevalence of nosocomial infection: A systematic review and meta-analysis

OBJECTIVES

Hospital-acquired infections (HAIs) are significant problems as public health issues which need attention. Such infections are significant problems for society and healthcare organizations. This study aimed to carry out a systematic review and a meta-analysis to analyze the prevalence of HAIs globally.

METHODS

We conducted a comprehensive search of electronic databases including EMBASE, Scopus, PubMed and Web of Science between 2000 and June 2021. We found 7031 articles. After removing the duplicates, 5430 studies were screened based on the titles/ abstracts. Then, we systematically evaluated the full texts of the 1909 remaining studies and selected 400 records with 29,159,630 participants for meta-analysis. Random-effects model was used for the analysis, and heterogeneity analysis and publication bias test were conducted.

RESULTS

The rate of universal HAIs was 0.14 percent. The rate of HAIs is increasing by 0.06 percent annually. The highest rate of HAIs was in the AFR, while the lowest prevalence were in AMR and WPR. Besides, AFR prevalence in central Africa is higher than in other parts of the world by 0.27 (95% CI, 0.22-0.34). Besides, E. coli infected patients more than other micro-organisms such as Coagulase-negative staphylococci, Staphylococcus spp. and Pseudomonas aeruginosa. In hospital wards, Transplant, and Neonatal wards and ICU had the highest rates. The prevalence of HAIs was higher in men than in women.

CONCLUSION

We identified several essential details about the rate of HAIs in various parts of the world. The HAIs rate and the most common micro-organism were different in various contexts. However, several essential gaps were also identified. The study findings can help hospital managers and health policy makers identify the reason for HAIs and apply effective control programs to implement different plans to reduce the HAIs rate and the financial costs of such infections and save resources.

Standardized Nursing Diagnoses in a Surgical Hospital Setting: A Retrospective Study Based on Electronic Health Data

Introduction

In electronic health records (EHRs), standardized nursing terminologies (SNTs), such as nursing diagnoses (NDs), are needed to demonstrate the impact of nursing care on patient outcomes. Unfortunately, the use of NDs is not common in clinical practice, especially in surgical settings, and is rarely included in EHRs.

Objectives

The aim of the study was to describe the prevalence and trend of NDs in a hospital surgical setting by also analyzing the relationship between NDs and hospital outcomes.

Methods

A retrospective study was conducted. All adult inpatients consecutively admitted to one of the 15 surgical inpatient units of an Italian university hospital across 1 year were included. Data, including the Professional Assessment Instrument and the Hospital Discharge Register, were collected retrospectively from the hospital's EHRs.

Results

The sample included 5,027 surgical inpatients. There was a mean of 6.3 ± 4.3 NDs per patient. The average distribution of NDs showed a stable trend throughout the year. The most representative NANDA-I ND domain was safety/protection. The total number of NDs on admission was significantly higher for patient whose length of stay was longer. A statistically significant correlation was observed between the number of NDs on admission and the number of intra-hospital patient transfers. Additionally, the mean number of NDs on admission was higher for patients who were later transferred to an intensive care unit compared to those who were not transferred.

Conclusion

NDs represent the key to understanding the contribution of nurses in the surgical setting. NDs collected upon admission can represent a prognostic factor related to the hospital's key outcomes.

Challenges and recommendations for high quality research using electronic health records

Harnessing Real World Data is vital to improve health care in the 21st Century. Data from Electronic Health Records (EHRs) are a rich source of patient centred data, including information on the patient's clinical condition, laboratory results, diagnoses and treatments. They thus reflect the true state of health systems. However, access and utilisation of EHR data for research presents specific challenges. We assert that using data from EHRs effectively is dependent on synergy between researchers, clinicians and health informaticians, and only this will allow state of the art methods to be used to answer urgent and vital questions for patient care. We propose that there needs to be a paradigm shift in the way this research is conducted - appreciating that the research process is iterative rather than linear. We also make specific recommendations for organisations, based on our experience of developing and using EHR data in trusted research environments.

Prediction of hospital-onset COVID-19 infections using dynamic networks of patient contact: an international retrospective cohort study

BACKGROUND

Real-time prediction is key to prevention and control of infections associated with health-care settings. Contacts enable spread of many infections, yet most risk prediction frameworks fail to account for their dynamics. We developed, tested, and internationally validated a real-time machine-learning framework, incorporating dynamic patient-contact networks to predict hospital-onset COVID-19 infections (HOCIs) at the individual level.

METHODS

We report an international retrospective cohort study of our framework, which extracted patient-contact networks from routine hospital data and combined network-derived variables with clinical and contextual information to predict individual infection risk. We trained and tested the framework on HOCIs using the data from 51 157 hospital inpatients admitted to a UK National Health Service hospital group (Imperial College Healthcare NHS Trust) between April 1, 2020, and April 1, 2021, intersecting the first two COVID-19 surges. We validated the framework using data from a Swiss hospital group (Department of Rehabilitation, Geneva University Hospitals) during a COVID-19 surge (from March 1 to May 31, 2020; 40 057 inpatients) and from the same UK group after COVID-19 surges (from April 2 to Aug 13, 2021; 43 375 inpatients). All inpatients with a bed allocation during the study periods were included in the computation of network-derived and contextual variables. In predicting patient-level HOCI risk, only inpatients spending 3 or more days in hospital during the study period were examined for HOCI acquisition risk.

FINDINGS

The framework was highly predictive across test data with all variable types (area under the curve [AUC]-receiver operating characteristic curve [ROC] 0·89 [95% CI 0·88-0·90]) and similarly predictive using only contact-network variables (0·88 [0·86-0·90]). Prediction was reduced when using only hospital contextual (AUC-ROC 0·82 [95% CI 0·80-0·84]) or patient clinical (0·64 [0·62-0·66]) variables. A model with only three variables (ie, network closeness, direct contacts with infectious patients [network derived], and hospital COVID-19 prevalence [hospital contextual]) achieved AUC-ROC 0·85 (95% CI 0·82-0·88). Incorporating contact-network variables improved performance across both validation datasets (AUC-ROC in the Geneva dataset increased from 0·84 [95% CI 0·82-0·86] to 0·88 [0·86-0·90]; AUC-ROC in the UK post-surge dataset increased from 0·49 [0·46-0·52] to 0·68 [0·64-0·70]).

INTERPRETATION

Dynamic contact networks are robust predictors of individual patient risk of HOCIs. Their integration in clinical care could enhance individualised infection prevention and early diagnosis of COVID-19 and other nosocomial infections.

FUNDING

Medical Research Foundation, WHO, Engineering and Physical Sciences Research Council, National Institute for Health Research (NIHR), Swiss National Science Foundation, and German Research Foundation.

Effects of patient-level risk factors, departmental allocation and seasonality on intrahospital patient transfer patterns: network analysis applied on a Norwegian single-centre data set

OBJECTIVES

Describe patient transfer patterns within a large Norwegian hospital. Identify risk factors associated with a high number of transfers. Develop methods to monitor intrahospital patient flows to support capacity management and infection control.

DESIGN

Retrospective observational study of linked clinical data from electronic health records.

SETTING

Tertiary care university hospital in the Greater Oslo Region, Norway.

PARTICIPANTS

All adult (≥18 years old) admissions to the gastroenterology, gastrointestinal surgery, neurology and orthopaedics departments at Akershus University Hospital, June 2018 to May 2019.

METHODS

Network analysis and graph theory. Poisson regression analysis.

OUTCOME MEASURES

Primary outcome was network characteristics at the departmental level. We describe location-to-location transfers using unweighted, undirected networks for a full-year study period. Weekly networks reveal changes in network size, density and key categories of transfers over time. Secondary outcome was transfer trajectories at the individual patient level. We describe the distribution of transfer trajectories in the cohort and associate number of transfers with patient clinical characteristics.

RESULTS

The cohort comprised 17 198 hospital stays. Network analysis demonstrated marked heterogeneity across departments and throughout the year. The orthopaedics department had the largest transfer network size and density and greatest temporal variation. More transfers occurred during weekdays than weekends. Summer holiday affected transfers of different types (Emergency department-Any location/Bed ward-Bed ward/To-From Technical wards) differently. Over 75% of transferred patients followed one of 20 common intrahospital trajectories, involving one to three transfers. Higher number of intrahospital transfers was associated with emergency admission (transfer rate ratio (RR)=1.827), non-prophylactic antibiotics (RR=1.108), surgical procedure (RR=2.939) and stay in intensive care unit or high-dependency unit (RR=2.098). Additionally, gastrosurgical (RR=1.211), orthopaedic (RR=1.295) and neurological (RR=1.114) patients had higher risk of many transfers than gastroenterology patients (all effects: p<0.001).

CONCLUSIONS

Network and transfer chain analysis applied on patient location data revealed logistic and clinical associations highly relevant for hospital capacity management and infection control.

Percutaneous Ultrasound Guided Gastrostomy Tube Placement: A Prospective Cohort Trial

BACKGROUND

To compare the safety and efficacy of percutaneous ultrasound guided gastrostomy (PUG) tube placement with traditional fluoroscopic guided percutaneous gastrostomy tube placement (PRG).

METHODS

A prospective, observational, non-randomized cohort trial was performed comparing 25 consecutive patients who underwent PUG placement between April 2020 and August 2020 with 25 consecutive patients who underwent PRG placement between February 2020 and March 2020. Procedure time, sedation, analgesia requirements, and complications were compared between the two groups in non-inferiority analysis.

RESULTS

Technical success rates were 96% in both groups (24/25) of procedures. Ninety-two percent of patients in the PUG cohort were admitted to the ICU at the time of G-tube request. Aside from significantly more COVID-19 patients in the PUG group (P < .001), there was no other statistically significant difference in patient demographics. Intra-procedure pain medication requirements were the same for both groups, 50 micrograms of IV fentanyl (P = 1.0). Intra-procedure sedation with IV midazolam was insignificantly higher in the PUG group 1.12 mg vs 0.8 mg (P = .355). Procedure time trended toward statistical significance (P = .076), with PRG being shorter than PUG (30.5 ± 14.1 minutes vs 39.7 ± 17.9 minutes). There were 2 non-device related major complications in the PUG group and 1 major and 1 minor complication in the PRG group.

CONCLUSION

PUG is similar in terms of complications to PRG gastrostomy tube placement and a safe method for gastrostomy tube placement in the critically ill with the added benefits of bedside placement, elimination of radiation exposure, and expanded and improved access to care.