Clinical informatics

BACKGROUND: Diagnosis can often be recorded in electronic medical records (EMRs) as free-text or using a term with a diagnosis code. Researchers, governments, and agencies, including organisations that deliver incentivised primary care quality improvement programs, frequently utilise coded data only and often ignore free-text entries. Diagnosis data are reported for population healthcare planning including resource allocation for patient care. This study sought to determine if diagnosis counts based on coded diagnosis data only, led to under-reporting of disease prevalence and if so, to what extent for six common or important chronic diseases...

BACKGROUND: Learning of burn patient assessment is very important, but heart-breaking for nursing students. This study aimed to compare the effects of feedback lecture method with a serious game (BAM Game) on nursing students' knowledge and skills in the assessment of burn patients. METHOD: In this randomized controlled clinical trial, 42 nursing students in their 5th semester at Mashhad University of Medical Sciences School of Nursing and Midwifery, were randomly assigned to intervention (BAM game, available for two weeks) and control (feedback lecture method presented in two 90-minute sessions) groups...

Research algorithms are seldom externally validated or integrated into clinical practice, leaving unknown challenges in deployment. In such efforts, one needs to address challenges related to data harmonization, the performance of an algorithm in unforeseen missingness, automation and monitoring of predictions, and legal frameworks. We here describe the deployment of a high-dimensional data-driven decision support model into an EHR and derive practical guidelines informed by this deployment that includes the necessary processes, stakeholders and design requirements for a successful deployment...

BACKGROUND:  Clinical informatics (CI) has reshaped how medical information is shared, evaluated, and utilized in health care delivery. The widespread integration of electronic health records (EHRs) mandates proficiency among physicians and practitioners, yet medical trainees face a scarcity of opportunities for CI education. OBJECTIVES:  We developed a CI rotation at a tertiary pediatric care center to teach categorical pediatric, pediatric-neurology, and medicine-pediatric residents foundational CI knowledge and applicable EHR skills...

BACKGROUND:  Studies have shown that documentation burden experienced by clinicians may lead to less direct patient care, increased errors, and job dissatisfaction. Implementing effective strategies within health care systems to mitigate documentation burden can result in improved clinician satisfaction and more time spent with patients. However, there is a gap in the literature regarding evidence-based interventions to reduce documentation burden. OBJECTIVES:  The objective of this review was to identify and comprehensively summarize the state of the science related to documentation burden reduction efforts...

OBJECTIVE: This study aims to investigate the association between social determinants of health (SDoH) and clinical research recruitment outcomes and recommends evidence-based strategies to enhance equity. MATERIALS AND METHODS: Data were collected from the internal clinical study manager database, clinical data warehouse, and clinical research registry. Study characteristics (e.g., study phase) and sociodemographic information were extracted. Median neighborhood income, distance from the study location, and Area Deprivation Index (ADI) were calculated...

Objective: To evaluate the impact of PDMP integration in the EHR on provider query rates within twelve primary care clinics in one academic medical center. Methods: Using linked data from the EHR and state PDMP program, we evaluated changes in PDMP query rates using a stepped-wedge observational design where integration was implemented in three waves (four clinics per wave) over a five-month period (May, July, September 2019). Multivariable negative binomial general estimating equations (GEE) models assessed changes in PDMP query rates, overall and across several provider and clinic-level subgroups...

BACKGROUND: In the rush to develop health technologies for the COVID-19 pandemic, the unintended consequence of digital health inequity or the inability of priority communities to access, use, and receive equal benefits from digital health technologies was not well examined. OBJECTIVE: This scoping review will examine tools and approaches that can be used during digital technology innovation to improve equitable inclusion of priority communities in the development of digital health technologies...

BACKGROUND: This study aimed to investigate the relationships between adiposity and circadian rhythm and compare the measurement of circadian rhythm using both actigraphy and a smartphone app that tracks human-smartphone interactions. OBJECTIVE: We hypothesized that the app-based measurement may provide more comprehensive information, including light-sensitive melatonin secretion and social rhythm, and have stronger correlations with adiposity indicators. METHODS: We enrolled a total of 78 participants (mean age 41...

PURPOSE: Identification of those at risk of hereditary cancer syndromes using electronic health record (EHR) data sources is important for clinical care, quality improvement, and research. We describe diagnostic processes, previously seldom reported, for a common hereditary cancer syndrome, Lynch syndrome (LS), using EHR data within a community-based, multicenter, demographically diverse health system. METHODS: Within a retrospective cohort enrolled between 2015 and 2020 at Kaiser Permanente Northern California, we assessed electronic diagnostic domains for LS including (1) family history of LS-associated cancer; (2) personal history of LS-associated cancer; (3) LS screening via mismatch repair deficiency (MMRD) testing of newly diagnosed malignancy; (4) germline genetic test results; and (5) clinician-entered diagnostic codes for LS...

Using the electronic health record to address the underdiagnosis of Lynch syndrome.

Lysine-specific demethylase 1 (LSD1), a highly sophisticated epigenetic regulator, orchestrates a range of critical cellular processes, holding promising therapeutic potential for treating diverse diseases. However, the clinical research progress targeting LSD1 is very slow. After 20 years of research, only one small-molecule drug, BEA-17, targeting the degradation of LSD1 and CoREST has been approved by the U.S. Food and Drug Administration. The primary reason for this may be the lack of abundant structural data regarding its intricate functions...

Non-invasive prenatal testing (NIPT) is a quite popular approach for detecting fetal genomic aneuploidies. However, due to the limitations on sequencing read length and coverage, NIPT suffers a bottleneck on further improving performance and conducting earlier detection. The errors mainly come from reference biases and population polymorphism. To break this bottleneck, we proposed NIPT-PG, which enables the NIPT algorithm to learn from population data. A pan-genome model is introduced to incorporate variant and polymorphic loci information from tested population...

BACKGROUND: The problem list (PL) is a repository of diagnoses for patients' medical conditions and health-related issues. Unfortunately, over time, our PLs have become overloaded with duplications, conflicting entries, and no-longer-valid diagnoses. The lack of a standardized structure for review adds to the challenges of clinical use. Previously, our default electronic health record (EHR) organized the PL primarily via alphabetization, with other options available, for example, organization by clinical systems or priority settings...

OBJECTIVE: The COVID-19 pandemic was associated with a reduction in the incidence of myocardial infarction (MI) diagnosis, in part because patients were less likely to present to hospital. Whether changes in clinical decision making with respect to the investigation and management of patients with suspected MI also contributed to this phenomenon is unknown. METHODS: Multicentre retrospective cohort study in three UK centres contributing data to the National Institute for Health Research Health Informatics Collaborative...

OBJECTIVES: Telemedical applications are solutions to challenges in the healthcare system. However, it is unclear what intensive care unit healthcare professionals expect from such solutions. This study investigated the expectations and concerns of nurses and physicians when implementing telemedicine tools in intensive care units (tele-ICU). METHODS: The study was conducted in intensive care units in 2020 during the second wave of the COVID-19 pandemic. It used a mixed-methods approach targeted at physicians and nurses and involved 14 qualitative interviews and 63 quantitative questionnaires...

BACKGROUND: Extracting research of domain criteria (RDoC) from high-risk populations like those with post-traumatic stress disorder (PTSD) is crucial for positive mental health improvements and policy enhancements. The intricacies of collecting, integrating, and effectively leveraging clinical notes for this purpose introduce complexities. METHODS: In our study, we created a natural language processing (NLP) workflow to analyze electronic medical record (EMR) data and identify and extract research of domain criteria using a pre-trained transformer-based natural language model, all-mpnet-base-v2...

INTRODUCTION: None of the studies of type 2 diabetes (T2D) subtyping to date have used linked population-level data for incident and prevalent T2D, incorporating a diverse set of variables, explainable methods for cluster characterization, or adhered to an established framework. We aimed to develop and validate machine learning (ML)-informed subtypes for type 2 diabetes mellitus (T2D) using nationally representative data. RESEARCH DESIGN AND METHODS: In population-based electronic health records (2006-2020; Clinical Practice Research Datalink) in individuals ≥18 years with incident T2D (n=420 448), we included factors (n=3787), including demography, history, examination, biomarkers and medications...

BACKGROUND: The method of documentation during a clinical encounter may affect the patient-physician relationship. OBJECTIVES: Evaluate how the use of ambient voice recognition, coupled with natural language processing and artificial intelligence (DAX™) affects the patient-physician relationship is not known. METHODS: A prospective observational study within a community teaching health system. The primary aim was evaluating any difference on the PDQR-9 scale between primary care encounters in which DAX™ was utilized for documentation as compared to those that did not...

BACKGROUND: Asynchronous outpatient patient-to-provider communication is expanding in UK health care, requiring evaluation. During the pandemic, Aberdeen Royal Infirmary in Scotland expanded its outpatient asynchronous consultation service from dermatology (deployed in May 2020) to gastroenterology and pain management clinics. OBJECTIVE: We conducted a mixed methods study using staff, patient, and public perspectives and National Health Service (NHS) numerical data to obtain a rounded picture of innovation as it happened...