Clinical Research Directory

AI Tool to Reduce Clinician Documentation Burden

This study looks at whether a clinician-facing artificial intelligence (AI) tool can help outpatient doctors spend less time reviewing medical records and documenting care. The tool creates brief summaries of existing medical record information to support routine clinical work. This study examines how use of this tool affects clinicians' workload, time spent in the electronic health record, and overall experience with documentation. The goal is to better understand whether AI documentation support tools can improve efficiency and reduce burden for clinicians in outpatient specialty practice. Eligible UNC outpatient specialists may be invited to complete surveys and, if they qualify, are randomly assigned either to receive access to the tool (Evidently) at the beginning of the study period or to continue their usual workflow for eight weeks before receiving access. The study does not recruit patients and does not change medical care for patients.

The Role of Framing and Choice Architecture in Patients' Reactions and EHR Error Discovery and Reporting

The first goal of our research is to understand the effects of different wordings of certain messages on patients' engagement in reviewing their electronic health records (EHRs). These messages will be about EHR errors and their potential consequences, as well as the benefits that might accrue from reviewing EHRs. The second goal is to understand the effects of different wordings of certain messages on patients' discovery and reporting of potential errors in their electronic health records (EHRs). The main questions it aims to answer are: 1. Does focusing on the negative OR positive consequences of EHR errors in the investigator's messages to people, increase their likelihood of reviewing their EHRs? 2. Does focusing on the negative OR positive consequences of EHR errors in the investigators' messages to people, increase their likelihood of discovery and reporting of potential errors in their EHRs? First, participants will take an initial short online survey (for about 5 minutes). Next, participants will be asked to log into their patient portal and review their EHRs, a process that should take around 10 minutes. Finally, they will proceed with the same survey for an additional 5 minutes, providing responses about their healthcare provider, patient portals, EHR errors, and some basic demographic details.

#AWARE.HIV Europe: Supporting Healthcare Professionals to Find Undiagnosed HIV in European Hospitals: An Effectiveness-implementation Trial.

The #aware.hiv Europe study is a real-world, multicenter, stepped-wedge cluster randomized, effectiveness-implementation trial designed to evaluate whether the introduction of dedicated HIV teams in hospitals can improve HIV testing rates among patients presenting with HIV indicator conditions across ten European countries. Study Design: The study employs a stepped-wedge design, whereby clusters of hospitals transition sequentially from a control phase (routine care) to an intervention phase. All patient data are collected retrospectively from routine care, while prospective data are gathered at the healthcare professional level. The project spans four years and involves hospitals from the Netherlands, Belgium, United Kingdom, Germany, Spain, France, Italy, Romania, Poland, and Ukraine. This design allows for comparison of HIV testing rates and related outcomes before and after the implementation across different settings and time points. Intervention: The core intervention involves the establishment of hospital-based HIV teams. Each team is led by an HIV specialist and supported by nurses and data collectors. Their responsibilities include: Identification and Surveillance: Screening routine electronic health records for HIV indicator conditions using predefined ICD-10 codes and verifying cases that warrant HIV testing. Audit \& Feedback: Providing targeted recommendations to treating physicians when an HIV test is indicated but has not been performed, thereby prompting action. Education \& Training: Delivering training sessions to healthcare professionals to improve their knowledge and attitudes towards HIV testing, prevention, and care. Enabling Environment: Implementing digital solutions and other support mechanisms to streamline testing processes, reduce stigma, and enhance overall guideline adherence. Linkage to prevention: Improving linkage to the locally available preventive services. The intervention is intended to integrate seamlessly into routine hospital care, thereby reinforcing existing guidelines while addressing the current diagnostic testing gap. Endpoints and Outcome Measures: Primary Endpoint: The change in HIV testing rate among patients diagnosed with HIV indicator conditions before and after the implementation of HIV teams. Key Secondary Endpoints: The change in the incidence of new HIV diagnoses among patients with HIV indicator conditions. Variations in HIV testing rates across different countries, medical specialties, and types of indicator conditions, as well as over time. Assessment of the cascade of HIV diagnosis, including the proportion of patients identified with an indicator condition, the offer and acceptance of HIV testing, and documented reasons for non-testing. Evaluation of the cascade of HIV care and prevention, including linkage to HIV care, achievement of viral suppression, and referral and uptake of preventive services. Changes in healthcare professionals' knowledge, attitudes, and levels of stigma towards HIV. Implementation outcomes such as fidelity of HIV team activities, resource utilization, cost-effectiveness, and sustainability of the intervention. Analysis of contextual factors, barriers, and facilitators impacting the implementation process, using established frameworks like CFIR and RE-AIM. Impact: By introducing HIV teams and systematically monitoring their effect on HIV testing practices, the study aims to enhance early HIV diagnosis and improve patient outcomes. The findings will contribute to evidence-based guidelines and may promote the adoption of similar interventions across European healthcare settings, ultimately reducing HIV-associated morbidity, mortality, and transmission rates. This project not only addresses a critical diagnostic gap in HIV care but also provides valuable insights into the effective implementation of complex interventions in routine clinical practice.

throMboembolic Risk Associated To High atrIal Fibrillation riSk

Cardiovascular diseases are the leading cause of mortality from treatable conditions in the European Union and the second from preventable causes, with a standardized mortality rate of 257.8 deaths per 100,000 inhabitants. In 2022, more than 1.11 million deaths in individuals under 75 years could have been avoided. Atrial fibrillation (AF) and major adverse cardiovascular events (MACE) are highly prevalent in the elderly and generate substantial healthcare costs. AF significantly increases the risk of MACE and is projected to rise markedly in the coming decades. In Europe, AF prevalence is expected to increase 2.5-fold over the next 50 years, with a lifetime risk of 1 in 3-5 individuals after age 55. AF-related strokes are projected to increase by 34%, and ischemic strokes in individuals over 80 are expected to triple between 2016 and 2060. Additionally, a 27% increase is anticipated among stroke survivors who subsequently develop AF or related conditions. AF substantially impacts morbidity, mortality, and disease progression, and early detection and treatment are crucial to prevent severe outcomes. European action plans (2018-2030) and the 2024 ESC/ESO guidelines emphasize early detection and management of AF in primary care. Although several AF prediction models exist, their integration into clinical practice remains challenging. AF represents a clinical continuum, with thrombotic risk present even before arrhythmia onset. High-risk patients for AF also show a high incidence of MACE, defined as a composite of myocardial infarction, stroke, systemic embolic events, and cardiovascular death. The proposed strategy involves developing and clinically validating an Artificial Intelligence (AI) model to improve early thrombotic risk prediction in patients at high risk of AF, using MACE as the primary outcome. This model aims to outperform the traditional CHA₂DS₂-VASc score by incorporating both classical and emerging clinical factors. The estimated timeline from clinical validation to commercialization is approximately 48 months. AI-based prediction is expected to enable personalized treatment, reduce the incidence of MACE, hospitalizations, and disability, and improve cost-effectiveness, ultimately decreasing the social and economic burden of AF and stroke in Europe.

SPIDER: A Research & QI Collaboration Supporting Practices in Improving Care for Complex Elderly Patients

Elders living with multiple chronic conditions often take many drugs (polypharmacy); some of the drugs may not benefit them or may be harmful. The Canadian Institute for Health Information has reported that about one-quarter of Canadian seniors are prescribed ten or more different drugs each year. Polypharmacy can result in poorer health, reduced quality of life and high healthcare costs. Choosing Wisely Canada and the Canadian Deprescribing Network have suggested wiser uses for the following four Potentially Inappropriate Prescriptions (PIPs): drugs that reduce stomach acid; reduce anxiety and induce sleep; treat agitation; and treat type 2 diabetes but have a high risk of low blood sugar. To improve care for elderly patients living with polypharmacy, we propose SPIDER: a Structured Process Informed by Data, Evidence and Research. Using quality improvement (QI) and supported by Electronic Medical Record (EMR) data, SPIDER will invite family doctors, nurses, pharmacists and front desk staff to participate in Learning Collaboratives and learn from each other. The practice teams will work with a QI Coach to identify areas to improve, develop strategies and implement changes tailored to the local practice context. The objective of this study is to determine whether SPIDER will reduce PIPs for patients 65 years or older who are on ten or more different drugs. The study will also explore patient experience and provider satisfaction with SPIDER and assess the cost of running SPIDER. The study will first be tested for feasibility in Toronto, Edmonton and Montreal. Findings will then guide a Randomized Controlled Trial (RCT) in Calgary, Winnipeg, Ottawa, Montreal and Halifax where practices enrolled in the SPIDER intervention will be compared with those in usual care.

Automatic Feedback Indicator to Enhance the Hospital Discharge Communication Between Acute Care and Primary Care.

This study, titled "Automated Indicator Feedback for Improving the Quality of Discharge Letters: A Cluster-Randomized Controlled Trial" (FIAQ-LS), aims to evaluate whether continuous real-time feedback to hospital teams can improve the quality of discharge letters. Discharge letters are critical for ensuring continuity of care and reducing adverse events by providing detailed information about a patient's hospital stay to both the patient and their primary care physician. The study will be conducted at Grenoble Alpes University Hospital and involve 40 hospital services across three campuses. The trial design includes two parallel arms: an intervention group receiving monthly performance feedback through automated dashboards and a control group with no additional intervention. Services are randomized into these groups using a stratified cluster approach. The primary objective is to assess whether this intervention increases the proportion of discharge letters validated on the day of discharge compared to usual care. Secondary objectives include evaluating patient satisfaction, rates of unplanned 30-day readmissions, and completeness of discharge letter content. The study will include data from approximately 132,000 patient stays over two phases: a pre-implementation observational period (12 months) and an intervention phase (12 months). All data will be collected and analyzed anonymously, with findings expected to inform the broader implementation of quality improvement strategies in French hospitals.