Additional file 1 of The effectiveness and efficiency of asymptomatic SARS-CoV-2 testing strategies for patient and healthcare workers within acute NHS hospitals during an omicron-like period

Supplementary Material

The National One Week Prevalence Audit of Universal Meticillin-Resistant <i>Staphylococcus aureus</i> (MRSA) Admission Screening 2012

<div><p>Introduction</p><p>The English Department of Health introduced universal MRSA screening of admissions to English hospitals in 2010. It commissioned a national audit to review implementation, impact on patient management, admission prevalence and extra yield of MRSA identified compared to “high-risk” specialty or “checklist-activated” screening (CLAS) of patients with MRSA risk factors.</p> <p>Methods</p><p>National audit May 2011. Questionnaires to infection control teams in all English NHS acute trusts, requesting number patients admitted and screened, new or previously known MRSA; MRSA point prevalence; screening and isolation policies; individual risk factors and patient management for <i>all</i> new MRSA patients and random sample of negatives.</p> <p>Results</p><p>144/167 (86.2%) trusts responded. Individual patient data for 760 new MRSA patients and 951 negatives. 61% of emergency admissions (median 67.3%), 81% (median 59.4%) electives and 47% (median 41.4%) day-cases were screened. MRSA admission prevalence: 1% (median 0.9%) emergencies, 0.6% (median 0.4%) electives, 0.4% (median 0%) day-cases. Approximately 50% all MRSA identified was new. Inpatient MRSA point prevalence: 3.3% (median 2.9%). 104 (77%) trusts pre-emptively isolated patients with previous MRSA, 63 (35%) pre-emptively isolated admissions to “high-risk” specialties; 7 (5%) used PCR routinely. Mean time to MRSA positive result: 2.87 days (±1.33); 37% (219/596) newly identified MRSA patients discharged before result available; 55% remainder (205/376) isolated post-result. In an average trust, CLAS would reduce screening by 50%, identifying 81% of all MRSA. “High risk” specialty screening would reduce screening by 89%, identifying 9% of MRSA.</p> <p>Conclusions</p><p>Implementation of universal screening was poor. Admission prevalence (new cases) was low. CLAS reduced screening effort for minor decreases in identification, but implementation may prove difficult. Cost effectiveness of this and other policies, awaits evaluation by transmission dynamic economic modelling, using data from this audit. Until then trusts should seek to improve implementation of current policy and use of isolation facilities.</p> </div

Additional file 1 of Model-based evaluation of admission screening strategies for the detection and control of carbapenemase-producing Enterobacterales in the English hospital setting

Additional file 1: Supplemental information: §1. Parameterisation (§1.a. Patient population and movements: §1.a.i. Patient source geography and associated prevalence on admission, §1.a.ii. Length of Stay, Maximum number of admissions per patient, Time between admissions; §1.b. CPE natural history : §1.b.i. Definitions used in test data analysis for CPE natural history parameters, §1.b.ii. Transmission estimation, §1.b.iii. Clearance estimation; §1.c. CPE infection prevention and control : §1.c.i Screening, contact tracing and clinical tests sensitivity and specificity), §2 Additional parameters, §3 Model validation, §4 Simulation results for region-typical hospitals

System-wide approaches to antimicrobial therapy and antimicrobial resistance in the UK: the AMR-X framework

Antimicrobial resistance (AMR) threatens human, animal, and environmental health. Acknowledging the urgency of addressing AMR, an opportunity exists to extend AMR action-focused research beyond the confines of an isolated biomedical paradigm. An AMR learning system, AMR-X, envisions a national network of health systems creating and applying optimal use of antimicrobials on the basis of their data collected from the delivery of routine clinical care. AMR-X integrates traditional AMR discovery, experimental research, and applied research with continuous analysis of pathogens, antimicrobial uses, and clinical outcomes that are routinely disseminated to practitioners, policy makers, patients, and the public to drive changes in practice and outcomes. AMR-X uses connected data-to-action systems to underpin an evaluation framework embedded in routine care, continuously driving implementation of improvements in patient and population health, targeting investment, and incentivising innovation. All stakeholders co-create AMR-X, protecting the public from AMR by adapting to continuously evolving AMR threats and generating the information needed for precision patient and population care.</p