Evaluation of ATP bioluminescence for rapid determination of farrowing room cleanliness after pressure washing at a commercial sow farm.

Rotavirus and other pathogenic microorganisms are known to cause scours, respiratory infection, and increased mortality, spread from pig to pig via contaminated equipment, insuffcient washing, and improper disinfection processes in farrowing rooms on commercial sow farms. Pig producers have adopted cleaning procedures and biosecurity policies as an attempt to ensure farrowing rooms are free of infectious organisms before the next group of sows is introduced. Adenosine triphosphate () bioluminescence has been used in other industries to provide real-time feedback on surface cleanliness through the detection of ATP from organic sources.

Network analysis to reveal the most commonly detected compounds in predator-prey pairs in freshwater and marine mammals and fish in Europe.

Marine and freshwater mammalian predators and fish samples, retrieved from environmental specimen banks (ESBs), natural history museum (NHMs) and other scientific collections, were analysed by LIFE APEX partners for a wide range of legacy and emerging contaminants (2545 in total). Network analysis was used to visualize the chemical occurrence data and reveal the predominant chemical mixtures for the freshwater and marine environments. For this purpose, a web tool was created to explore these chemical mixtures in predator-prey pairs.

Automating detection of diagnostic error of infectious diseases using machine learning.

Diagnostic error, a cause of substantial morbidity and mortality, is largely discovered and evaluated through self-report and manual review, which is costly and not suitable to real-time intervention. Opportunities exist to leverage electronic health record data for automated detection of potential misdiagnosis, executed at scale and generalized across diseases. We propose a novel automated approach to identifying diagnostic divergence considering both diagnosis and risk of mortality.

Evaluation of ATP bioluminescence for rapid determination of cleanliness of livestock trailers after a commercial wash.

Pathogens such as porcine epidemic diarrhea virus (PEDV), porcine reproductive and respiratory syndrome (PRRSV), and are known to spread by contaminated vehicles and equipment. Pork producers have adopted trailer wash policies where each trailer is washed, disinfected, and dried before it can return to a farm. Cleanliness of livestock trailers after washing is determined by visual inspection rather than any objective method.

Building the Future of Infectious Diseases: A Call to Action for Quality Improvement Research and Measurement.

Quality is central to value-based care, and measurement is essential for assessing performance and understanding improvement over time. Both value-based care and methods for quality measurement are evolving. Infectious diseases (ID) has been less engaged than other specialties in quality measure development, and ID providers must seize the opportunity to engage with quality measure development and research.

A Linguistic Analysis Examining the Impact of COVID-19 on Pneumonia Diagnosis and Disease Models.

Written clinical language embodies and reflects the clinician's mental models of disease. Prior to the COVID-19 pandemic, pneumonia was shifting away from concern for healthcare-associated pneumonia and toward recognition of heterogeneity of pathogens and host response. How these models are reflected in clinical language or whether they were impacted by the pandemic has not been studied.

How Safe are Outpatient Electronic Health Records? An Evaluation of Medication-Related Decision Support using the Ambulatory Electronic Health Record Evaluation Tool.

Background: The purpose of the Ambulatory Electronic Health Record (EHR) Evaluation Tool is to provide outpatient clinics with an assessment that they can use to measure the ability of the EHR system to detect and prevent common prescriber errors. The tool consists of a medication safety test and a medication reconciliation module.

Objectives: The goal of this study was to perform a broad evaluation of outpatient medication-related decision support using the Ambulatory EHR Evaluation Tool.

Improving Sepsis Outcomes in the Era of Pay-for-Performance and Electronic Quality Measures: A Joint IDSA/ACEP/PIDS/SHEA/SHM/SIDP Position Paper.

The Centers for Medicare & Medicaid Services (CMS) introduced the Severe Sepsis/Septic Shock Management Bundle (SEP-1) as a pay-for-reporting measure in 2015 and is now planning to make it a pay-for-performance measure by incorporating it into the Hospital Value-Based Purchasing Program. This joint IDSA/ACEP/PIDS/SHEA/SHM/SIPD position paper highlights concerns with this change. Multiple studies indicate that SEP-1 implementation was associated with increased broad-spectrum antibiotic use, lactate measurements, and aggressive fluid resuscitation for patients with suspected sepsis but not with decreased mortality rates.

Healthcare-associated infections and conditions in the era of digital measurement.

As the third edition of the is released with the latest recommendations for the prevention and management of healthcare-associated infections (HAIs), a new approach to reporting HAIs is just beginning to unfold. This next generation of HAI reporting will be fully electronic and based largely on existing data in electronic health record (EHR) systems and other electronic data sources. It will be a significant change in how hospitals report HAIs and how the Centers for Disease Control and Prevention (CDC) and other agencies receive this information.

How can artificial intelligence decrease cognitive and work burden for front line practitioners?

Artificial intelligence (AI) has tremendous potential to improve the cognitive and work burden of clinicians across a range of clinical activities, which could lead to reduced burnout and better clinical care. The recent explosion of generative AI nicely illustrates this potential. Developers and organizations deploying AI have a responsibility to ensure AI is designed and implemented with end-user input, has mechanisms to identify and potentially reduce bias, and that the impact on cognitive and work burden is measured, monitored, and improved.

Risk Factors for Severe COVID-19 Among Health Care Workers.

Objective: Evaluate potential risk factors for severe coronavirus disease 2019 (COVID-19) among health care workers (HCWs) at the University of Virginia Medical Center in Charlottesville, Virginia.

Methods: We conducted a retrospective manual chart review of data from HCWs who were diagnosed with COVID-19 from March 2020 to March 2021. Using data from patient medical histories, we ascertained risk factors for COVID-19-related emergency department encounter, hospitalization, or death.

The importance of in-year seasonal fluctuations for biomonitoring of apex predators: A case study of 14 essential and non-essential elements in the liver of the common buzzard (Buteobuteo) in the United Kingdom.

Trace elements are chemical contaminants spread in the environment by anthropogenic activities and threaten wildlife and human health. Many studies have investigated this contamination in apex raptors as sentinel birds. However, there is limited data for long-term biomonitoring of multiple trace elements in raptors.

Examining medication ordering errors using AHRQ network of patient safety databases.

Background: Studies examining the effects of computerized order entry (CPOE) on medication ordering errors demonstrate that CPOE does not consistently prevent these errors as intended. We used the Agency for Healthcare Research and Quality (AHRQ) Network of Patient Safety Databases (NPSD) to investigate the frequency and degree of harm of reported events that occurred at the ordering stage, characterized by error type.

Materials And Methods: This was a retrospective observational study of safety events reported by healthcare systems in participating patient safety organizations from 6/2010 through 12/2020.

Development and evaluation of an interoperable natural language processing system for identifying pneumonia across clinical settings of care and institutions.

Objective: To evaluate the feasibility, accuracy, and interoperability of a natural language processing (NLP) system that extracts diagnostic assertions of pneumonia in different clinical notes and institutions.

Materials And Methods: A rule-based NLP system was designed to identify assertions of pneumonia in 3 types of clinical notes from electronic health records (EHRs): emergency department notes, radiology reports, and discharge summaries. The lexicon and classification logic were tailored for each note type.

Bending the patient safety curve: how much can AI help?

This paper reviews the current state of patient safety and the application of artificial intelligence (AI) techniques to patient safety. This paper defines patient safety broadly, not just inpatient care but across the continuum of care, including diagnostic errors, misdiagnosis, adverse events, injuries, and measurement issues. It outlines the major current uses of AI in patient safety and the relative adoption of these techniques in hospitals and health systems.

Assessment of contaminants of emerging concern in European apex predators and their prey by LC-QToF MS wide-scope target analysis.

Apex predators are good indicators of environmental pollution since they are relatively long-lived and their high trophic position and spatiotemporal exposure to chemicals provides insights into the persistent, bioaccumulative and toxic (PBT) properties of chemicals. Although monitoring data from apex predators can considerably support chemicals' management, there is a lack of pan-European studies, and longer-term monitoring of chemicals in organisms from higher trophic levels. The present study investigated the occurrence of contaminants of emerging concern (CECs) in 67 freshwater, marine and terrestrial apex predators and in freshwater and marine prey, gathered from four European countries.

A flexible framework for visualizing and exploring patient misdiagnosis over time.

Diagnosis is a complex and ambiguous process and yet, it is the critical hinge point for all subsequent clinical reasoning and decision-making. Tracking the quality of the patient diagnostic process has the potential to provide valuable insights in improving the diagnostic accuracy and to reduce downstream errors but needs to be informative, timely, and efficient at scale. However, due to the rate at which healthcare data are captured on a daily basis, manually reviewing the diagnostic history of each patient would be a severely taxing process without efficient data reduction and representation.

Fate of C-labelled ionic organic chemicals in a water-sediment system and surface water.

The persistence assessment of organic chemicals is based on neutral reference substances. Therefore, our study aimed at investigating the influence of a chemical charge on the degradation of organic compounds in a water-sediment system (OECD 308) and surface water (OECD 309). We used radiolabelled 4-n-dodecylbenzenesulfonic acid sodium salt (C-DS, anionic), 4-n-dodecylbenzyltrimethylammonium chloride (C-DA, cationic) and 4-n-dodecylphenol (C-DP, non-ionic) which are structurally similar except their charges.