Building a Time-Series Model to Predict Hospitalization Risks in Home Health Care: Insights Into Development, Accuracy, and Fairness.

Objectives: Home health care (HHC) serves more than 5 million older adults annually in the United States, aiming to prevent unnecessary hospitalizations and emergency department (ED) visits. Despite efforts, up to 25% of patients in HHC experience these adverse events. The underutilization of clinical notes, aggregated data approaches, and potential demographic biases have limited previous HHC risk prediction models.

An evolutionary concept analysis of depression in Black mothers.

Background: Depression is a common mental health disorder but can be difficult to diagnose. Its prevalence in Black mothers is nine times the national rate, possibly due to barriers in receiving care. In addition, depression may present differently in this group.

Applying natural language processing to understand symptoms among older adult home healthcare patients with urinary incontinence.

Introduction: Little is known about the range and frequency of symptoms among older adult home healthcare patients with urinary incontinence, as this information is predominantly contained in clinical notes. Natural language processing can uncover symptom information among older adults with urinary incontinence to promote holistic, equitable care.

Design: We conducted a secondary analysis of cross-sectional data collected between January 1, 2015, and December 31, 2017, from the largest HHC agency in the Northeastern United States.

Secondary Qualitative Analysis of Stigmatizing and Nonstigmatizing Language Used in Hospital Birth Settings.

Objective: To more clearly understand the use of stigmatizing and nonstigmatizing language in electronic health records in hospital birth settings and to broaden the understanding of discrimination and implicit bias in clinical care.

Design: A secondary qualitative analysis of free-text clinical notes from electronic health records.

Setting: Two urban hospitals in the northeastern United States that serve patients with diverse sociodemographic characteristics during the perinatal period.

Identifying stigmatizing and positive/preferred language in obstetric clinical notes using natural language processing.

Objective: To identify stigmatizing language in obstetric clinical notes using natural language processing (NLP).

Materials And Methods: We analyzed electronic health records from birth admissions in the Northeast United States in 2017. We annotated 1771 clinical notes to generate the initial gold standard dataset.

Machine learning-based infection diagnostic and prognostic models in post-acute care settings: a systematic review.

Objectives: This study aims to (1) review machine learning (ML)-based models for early infection diagnostic and prognosis prediction in post-acute care (PAC) settings, (2) identify key risk predictors influencing infection-related outcomes, and (3) examine the quality and limitations of these models.

Materials And Methods: PubMed, Web of Science, Scopus, IEEE Xplore, CINAHL, and ACM digital library were searched in February 2024. Eligible studies leveraged PAC data to develop and evaluate ML models for infection-related risks.

Developing a clinical decision support framework for integrating predictive models into routine nursing practices in home health care for patients with heart failure.

Background: The healthcare industry increasingly values high-quality and personalized care. Patients with heart failure (HF) receiving home health care (HHC) often experience hospitalizations due to worsening symptoms and comorbidities. Therefore, close symptom monitoring and timely intervention based on risk prediction could help HHC clinicians prevent emergency department (ED) visits and hospitalizations.

Social Determinants Documented Across Individuals from Different Racial and Ethnic Groups in Home Healthcare.

Home healthcare (HHC) enables patients to receive health services within their homes. Social determinants of health (SDOH) influence a patient's health and may disproportionately affect patients from racially and ethnically minoritized groups. This study describes differences in SDOH documentation in clinical notes among individuals from different racial or ethnic groups from one HHC agency in the northeastern United States.

Documentation of social determinants of health across individuals from different racial and ethnic groups in home healthcare.

Introduction: Home healthcare (HHC) enables patients to receive healthcare services within their homes to manage chronic conditions and recover from illnesses. Recent research has identified disparities in HHC based on race or ethnicity. Social determinants of health (SDOH) describe the external factors influencing a patient's health, such as access to care and social support.

Comorbidities of community-dwelling older adults with urinary incontinence: A scoping review.

Background: Identifying comorbidities is a critical first step to building clinical phenotypes to improve assessment, management, and outcomes.

Objectives: 1) Identify relevant comorbidities of community-dwelling older adults with urinary incontinence, 2) provide insights about relationships between conditions.

Methods: PubMed, Cumulative Index of Nursing and Allied Health Literature, and Embase were searched.

Characterising symptom clusters in patients with atrial fibrillation undergoing catheter ablation.

Objective: This study aims to leverage natural language processing (NLP) and machine learning clustering analyses to (1) identify co-occurring symptoms of patients undergoing catheter ablation for atrial fibrillation (AF) and (2) describe clinical and sociodemographic correlates of symptom clusters.

Methods: We conducted a cross-sectional retrospective analysis using electronic health records data. Adults who underwent AF ablation between 2010 and 2020 were included.

Machine learning applied to electronic health record data in home healthcare: A scoping review.

Objective: Despite recent calls for home healthcare (HHC) to integrate informatics, the application of machine learning in HHC is relatively unknown. Thus, this study aimed to synthesize and appraise the literature describing the application of machine learning to predict adverse outcomes (e.g.

Do nurses document all discussions of patient problems and nursing interventions in the electronic health record? A pilot study in home healthcare.

Objective: To assess the overlap of information between electronic health record (EHR) and patient-nurse verbal communication in home healthcare (HHC).

Methods: Patient-nurse verbal communications during home visits were recorded between February 16, 2021 and September 2, 2021 with patients being served in an organization located in the Northeast United States. Twenty-two audio recordings for 15 patients were transcribed.

Insulin acts as a repressive factor to inhibit the ability of PAR2 to induce islet cell transdifferentiation.

Recently, we showed that pancreatitis in the context of profound β-cell deficiency was sufficient to induce islet cell transdifferentiation. In some circumstances, this effect was sufficient to result in recovery from severe diabetes. More recently, we showed that the molecular mechanism by which pancreatitis induced β-cell neogenesis by transdifferentiation was activation of an atypical GPCR called Protease-Activated Receptor 2 (PAR2).

Executive Summary of IPITA-TTS Opinion Leaders Report on the Future of β-Cell Replacement.

The International Pancreas and Islet Transplant Association (IPITA), in conjunction with the Transplantation Society (TTS), convened a workshop to consider the future of pancreas and islet transplantation in the context of potential competing technologies that are under development, including the artificial pancreas, transplantation tolerance, xenotransplantation, encapsulation, stem cell derived beta cells, beta cell proliferation, and endogenous regeneration. Separate workgroups for each topic and then the collective group reviewed the state of the art, hurdles to application, and proposed research agenda for each therapy that would allow widespread application. Herein we present the executive summary of this workshop that focuses on obstacles to application and the research agenda to overcome them; the full length article with detailed background for each topic is published as an online supplement to Transplantation.

Simultaneous silencing of multiple RB and p53 pathway members induces cell cycle reentry in intact human pancreatic islets.

Background: Human pancreatic islet structure poses challenges to investigations that require specific modulation of gene expression. Yet dissociation of islets into individual cells destroys cellular interactions important to islet physiology. Approaches that improve transient targeting of gene expression in intact human islets are needed in order to effectively perturb intracellular pathways to achieve biological effects in the most relevant tissue contexts.

Encapsulated islets for diabetes therapy: history, current progress, and critical issues requiring solution.

Insulin therapy became a reality in 1921 dramatically saving lives of people with diabetes, but not protecting them from long-term complications. Clinically successful free islet implants began in 1989 but require life long immunosuppression. Several encapsulated islet approaches have been ongoing for over 30 years without defining a clinically relevant product.

Islet isolation from human pancreas with extended cold ischemia time.

The general consensus among transplant centers is that a cold ischemia time (CIT) beyond 8 hours results in reduced yields and quality of human islets. We sought to optimize the isolation process and enzymes for pancreata with extended CIT. We processed 16 extended CIT pancreata (13.