Relevance of intra-hospital patient movements for the spread of healthcare-associated infections within hospitals - a mathematical modeling study

Repercussions of moving patients on the context of practice: perspectives of the nursing team

OBJECTIVE

to examine the nursing team's view of the repercussions of moving patients (admissions, transfers and discharges) on the organization of work and the delivery of care.

METHOD

this is a qualitative study using the focus group technique, conducted with 23 professionals - 12 nurses, eight nurse technicians and three nurse assistants working in three inpatient units at a teaching hospital in the countryside of Sao Paulo. Four meetings took place between November 2021 and March 2022. The reports were analyzed thematically using MAXQDA software.

RESULTS

two thematic categories emerged: the influence of structural factors and work organization on the intra-hospital moving of patients; it demands time, generates work overload and interferes with the delivery of care.

CONCLUSION

the volume of moving patient associated with unforeseen demands, care complexity and insufficient staff and resources have a negative impact on the delivery of care, with clinical risks and work overload. The findings make it possible to improve the regulation of patients entering and leaving the units, work organization and care management, avoiding clinical risks, delays, omissions and work overload.

BACKGROUND

(1) Moving patients around the hospital requires structure and work organization.

BACKGROUND

(2) Nursing estimates dedicating 10-15 minutes to 2-3 hours of work on these interventions.

BACKGROUND

(3) Frequency, unpredictability and complexity of care have a negative impact on care.

BACKGROUND

(4) Unfavorable conditions for moving generate care and occupational risks.

Hub and Spoke: Next level in regional networks for infection prevention

The threat of multidrug-resistant organisms (MDROs) and antimicrobial resistance (AMR) are real and increasing every day. They affect not only healthcare systems but also communities, causing economic and public health concerns. Governments must take action to tackle AMR and prevent the spread of MDROs and regional hubs have a critical role to play in achieving this outcome. Furthermore, bacteria have no borders, consequently, cooperation networks should be extended between countries as a crucial strategy for achieving the success of infection control. Euregions, which are a specific form of cooperation between local authorities of two or more bordering European countries, can help solve common problems and improve the lives of people living on both sides of the border. Regional collaboration strategies can enhance infection control and build resilience against antimicrobial resistance. This review identifies risk factors and the correct approaches to infection prevention and control, including education and awareness programs for healthcare professionals, appropriate prescribing practices, and infection prevention control measures. These measures can help reduce the incidence of antimicrobial resistance in the region and save lives. It is therefore essential to take concrete actions and foster the creation of more effective regional and cross-border centers to ensure the success of infection control policies and the management of healthcare-associated infections. This work sheds light on the issue of MDRO infections within healthcare settings, while also acknowledging the crucial role of the One Health concept in understanding the broader context of these infections. By recognizing the interdependence of human and animal health and the environment, we can take constructive steps toward mitigating the risks of these infections and promoting better health outcomes for all.

Regional patient transfer patterns matter for the spread of hospital-acquired pathogens

Pathogens typically responsible for hospital-acquired infections (HAIs) constitute a major threat to healthcare systems worldwide. They spread via hospital (or hospital-community) networks by readmissions or patient transfers. Therefore, knowledge of these networks is essential to develop and test strategies to mitigate and control the HAI spread. Until now, no methods for comparing healthcare networks across different systems were proposed. Based on healthcare insurance data from four German federal states (Bavaria, Lower Saxony, Saxony and Thuringia), we constructed hospital networks and compared them in a systematic approach regarding population, hospital characteristics, and patient transfer patterns. Direct patient transfers between hospitals had only a limited impact on HAI spread. Whereas, with low colonization clearance rates, readmissions to the same hospitals posed the biggest transmission risk of all inter-hospital transfers. We then generated hospital-community networks, in which patients either stay in communities or in hospitals. We found that network characteristics affect the final prevalence and the time to reach it. However, depending on the characteristics of the pathogen (colonization clearance rate and transmission rate or even the relationship between transmission rate in hospitals and in the community), the studied networks performed differently. The differences were not large, but justify further studies.

Effectiveness of methicillin-resistant Staphylococcus aureus surveillance among exposed roommates in community hospitals: Conventional culture versus direct PCR

BACKGROUND

Roommates of unrecognized nosocomial methicillin-resistant Staphylococcus aureus (MRSA) cases are at a higher acquisition risk; however, optimal surveillance strategies are unknown.

METHODS

Using simulation, we analyzed surveillance testing and isolation strategies for MRSA among exposed hospital roommates. We compared isolating exposed roommates until conventional culture testing on day 6 and a nasal polymerase chain reaction test on day 3 (PCR3) with/without day 0 culture testing (Cult0). The model represents MRSA transmission in medium-sized hospitals using data and recommends best practices from the literature and Ontario community hospitals.

RESULTS

Cult0 + PCR3 incurred a slightly lower number of MRSA colonizations and 38.9% lower annual cost in the base case compared to Cult0 + culture testing on day 6 because the reduced isolation cost compensated for the increased testing cost. The reduction in MRSA colonizations was due to a 54.5% drop in MRSA transmissions during isolation as PCR3 reduced the exposure of MRSA-free roommates to new MRSA carriers. Removing the day 0 culture test from Cult0 + PCR3 increased total cost, the number of MRSA colonization, and missed cases by $1,631, 4.3%, and 50.9%, respectively. Improvements were higher under aggressive MRSA transmission scenarios.

DISCUSSION AND CONCLUSIONS

Adopting direct nasal polymerase chain reaction testing for determining post-exposure MRSA status reduces transmission risk and costs. Day 0 culture would still be beneficial.

Transmission of drug-resistant bacteria in a hospital-community model stratified by patient risk

A susceptible-infectious-susceptible (SIS) model for simulating healthcare-acquired infection spread within a hospital and associated community is proposed. The model accounts for the stratification of in-patients into two susceptibility-based risk groups. The model is formulated as a system of first-order ordinary differential equations (ODEs) with appropriate initial conditions. The mathematical analysis of this system is demonstrated. It is shown that the system has unique global solutions, which are bounded and non-negative. The basic reproduction number ([Formula: see text]) for the considered model is derived. The existence and the stability of the stationary solutions are analysed. The disease-free stationary solution is always present and is globally asymptotically stable for [Formula: see text], while for [Formula: see text] it is unstable. The presence of an endemic stationary solution depends on the model parameters and when it exists, it is globally asymptotically stable. The endemic state encompasses both risk groups. The endemic state within only one group only is not possible. In addition, for [Formula: see text] a forward bifurcation takes place. Numerical simulations, based on the anonymised insurance data, are also presented to illustrate theoretical results.

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.

A survey on agents applications in healthcare: Opportunities, challenges and trends

BACKGROUND AND OBJECTIVE

The agent abstraction is a powerful one, developed decades ago to represent crucial aspects of artificial intelligence research. The meaning has transformed over the years and now there are different nuances across research communities. At its core, an agent is an autonomous computational entity capable of sensing, acting, and capturing interactions with other agents and its environment. This review examines how agent-based techniques have been implemented and evaluated in a specific and very important domain, i.e. healthcare research.

METHODS

We survey key areas of agent-based research in healthcare, e.g. individual and collective behaviours, communicable and non-communicable diseases, and social epidemiology. We propose a systematic search and critical review of relevant recent works, introduced by an exploratory network analysis.

RESULTS

Network analysis enables to devise out 5 main research clusters, the most active authors, and 4 main research topics.

CONCLUSIONS

Our findings support discussion of some future directions for increasing the value of agent-based approaches in healthcare.

Network Analysis Examining Intrahospital Traffic of Patients With Traumatic Hip Fracture

INTRODUCTION

Increased intrahospital traffic (IHT) is associated with adverse events and infections in hospitalized patients. Network science has been used to study patient flow in hospitals but not specifically for patients with traumatic injuries.

METHODS

This retrospective analysis included 103 patients with traumatic hip fractures admitted to a level I trauma center between April 2021 and September 2021. Associations with IHTs (moves within the hospital) were analyzed using R (4.1.2) as a weighted directed graph.

RESULTS

The median (interquartile range) number of moves was 8 (7-9). The network consisted of 16 distinct units and showed mild disassortativity (-0.35), similar to other IHT networks. The floor and intensive care unit (ICU) were central units in the flow of patients, with the highest degree and betweenness. Patients spent a median of 20-28 hours in the ICU, intermediate care unit, or floor. The number of moves per patient was mildly correlated with hospital length of stay (ρ = 0.26, p = .008). Intrahospital traffic volume was higher on weekdays and during daytime hours. Intrahospital traffic volume was highest in patients aged <65 years ( p = .04), but there was no difference in IHT volume by dependent status, complications, or readmissions.

CONCLUSIONS

Network science is a useful tool for trauma patients to plan IHT, flow, and staffing.

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.

A prospective multicentre screening study on multidrug-resistant organisms in intensive care units in the Dutch-German cross-border region, 2017 to 2018: the importance of healthcare structures

Background

Antimicrobial resistance poses a risk for healthcare, both in the community and hospitals. The spread of multidrug-resistant organisms (MDROs) occurs mostly on a local and regional level, following movement of patients, but also occurs across national borders.

Aim

The aim of this observational study was to determine the prevalence of MDROs in a European cross-border region to understand differences and improve infection prevention based on real-time routine data and workflows.

Methods

Between September 2017 and June 2018, 23 hospitals in the Dutch (NL)–German (DE) cross-border region (BR) participated in the study. During 8 consecutive weeks, patients were screened upon admission to intensive care units (ICUs) for nasal carriage of meticillin-resistant Staphylococcus aureus (MRSA) and rectal carriage of vancomycin-resistant Enterococcus faecium/E. faecalis (VRE), third-generation cephalosporin-resistant Enterobacteriaceae (3GCRE) and carbapenem-resistant Enterobacteriaceae (CRE). All samples were processed in the associated laboratories.

Results

A total of 3,365 patients were screened (median age: 68 years (IQR: 57–77); male/female ratio: 59.7/40.3; NL-BR: n = 1,202; DE-BR: n = 2,163). Median screening compliance was 60.4% (NL-BR: 56.9%; DE-BR: 62.9%). MDRO prevalence was higher in DE-BR than in NL-BR, namely 1.7% vs 0.6% for MRSA (p = 0.006), 2.7% vs 0.1% for VRE (p < 0.001) and 6.6% vs 3.6% for 3GCRE (p < 0.001), whereas CRE prevalence was comparable (0.2% in DE-BR vs 0.0% in NL-BR ICUs).

Conclusions

This first prospective multicentre screening study in a European cross-border region shows high heterogenicity in MDRO carriage prevalence in NL-BR and DE-BR ICUs. This indicates that the prevalence is probably influenced by the different healthcare structures.