Symptom representations in people with multimorbidity undergoing treatment for cancer: a qualitative descriptive study.

Purpose: The symptom representations (i.e., beliefs and attitudes) that people with cancer hold about their symptom experience can impact how they self-manage their symptoms.

Predictors of Concordance between Patient-Reported and Provider-Documented Symptoms in the Context of Cancer and Multimorbidity.

Background:  The integration of patient-reported outcomes (PROs) into clinical care, particularly in the context of cancer and multimorbidity, is crucial. While PROs have the potential to enhance patient-centered care and improve health outcomes through improved symptom assessment, they are not always adequately documented by the health care team.

Objectives:  This study aimed to explore the concordance between patient-reported symptom occurrence and symptoms documented in electronic health records (EHRs) in people undergoing treatment for cancer in the context of multimorbidity.

Harnessing Natural Language Processing and High-Dimensional Clinical Notes to Detect Goals-of-Care and Surrogate-Designation Conversations.

Advance care planning, involving goals-of-care and surrogate-designation conversations, is crucial for patient-centered care. However, determining the optimal timing and participants for these conversations remains challenging. This study explored the frequency, timing, and predictors of documenting two advance care planning elements, goals-of-care and surrogate-designation conversations, in clinical notes for patients with advanced illness.

Leveraging oncology collaborative networks and biomedical informatics data resources to rapidly recruit and enroll rural residents into oncology quality of life clinical trials.

Purpose: This study assesses the feasibility of biomedical informatics resources for efficient recruitment of rural residents with cancer to a clinical trial of a quality-of-life (QOL) mobile app. These resources have the potential to reduce costly, time-consuming, in-person recruitment methods.

Methods: A cohort was identified from the electronic health record data repository and cross-referenced with patients who consented to additional research contact.

Using real-world electronic health record data to predict the development of 12 cancer-related symptoms in the context of multimorbidity.

Objective: This study uses electronic health record (EHR) data to predict 12 common cancer symptoms, assessing the efficacy of machine learning (ML) models in identifying symptom influencers.

Materials And Methods: We analyzed EHR data of 8156 adults diagnosed with cancer who underwent cancer treatment from 2017 to 2020. Structured and unstructured EHR data were sourced from the Enterprise Data Warehouse for Research at the University of Iowa Hospital and Clinics.

Factors Influencing Discharges to Hospice for Patients With Late-Stage Huntington's Disease.

Hospice services for patients with Huntington's disease (HD) are likely beneficial in relieving significant burdens and minimizing costly hospitalizations at the end of life, though there has been little study or clinical guidance on hospice enrollment for patients with HD. The primary objective of this study was to identify clinical, sociodemographic, and system-level factors associated with discharges to hospice compared to other dispositions for hospitalized patients with late-stage HD. These analyses used data from the Nationwide Inpatient Sample between the years 2007 and 2011.

Natural Language Processing Accurately Differentiates Cancer Symptom Information in Electronic Health Record Narratives.

Purpose: Identifying cancer symptoms in electronic health record (EHR) narratives is feasible with natural language processing (NLP). However, more efficient NLP systems are needed to detect various symptoms and distinguish observed symptoms from negated symptoms and medication-related side effects. We evaluated the accuracy of NLP in (1) detecting 14 symptom groups (ie, pain, fatigue, swelling, depressed mood, anxiety, nausea/vomiting, pruritus, headache, shortness of breath, constipation, numbness/tingling, decreased appetite, impaired memory, disturbed sleep) and (2) distinguishing observed symptoms in EHR narratives among patients with cancer.

Symptom-BERT: Enhancing Cancer Symptom Detection in EHR Clinical Notes.

Context: Extracting cancer symptom documentation allows clinicians to develop highly individualized symptom prediction algorithms to deliver symptom management care. Leveraging advanced language models to detect symptom data in clinical narratives can significantly enhance this process.

Objective: This study uses a pretrained large language model to detect and extract cancer symptoms in clinical notes.

Machine Learning Approaches to Predict Symptoms in People With Cancer: Systematic Review.

Background: People with cancer frequently experience severe and distressing symptoms associated with cancer and its treatments. Predicting symptoms in patients with cancer continues to be a significant challenge for both clinicians and researchers. The rapid evolution of machine learning (ML) highlights the need for a current systematic review to improve cancer symptom prediction.

Prediction of Cancer Symptom Trajectory Using Longitudinal Electronic Health Record Data and Long Short-Term Memory Neural Network.

Purpose: Ability to predict symptom severity and progression across treatment trajectories would allow clinicians to provide timely intervention and treatment planning. However, such predictions are difficult because of sparse and inconsistent assessment, and simplistic measures such as the last observed symptom severity are often used. The purpose of this study is to develop a model for predicting future cancer symptom experiences on the basis of past symptom experiences.

Social Determinants of Health and Cancer Pain in the US: Scoping Review.

Social determinants of health (SDOH) are structural factors that yield health inequities. Within the context of cancer, these inequities include screening rates and survival rates, as well as higher symptom burden during and after treatment. While pain is one of the most frequently reported symptoms, the relationship between SDOHs and cancer pain is not well understood.

Preliminary Analysis of Gut Microbiome and Gastrointestinal Symptom Burden in Breast Cancer Patients Receiving Chemotherapy Compared to Healthy Controls.

Background: Alterations in the naturally occurring bacteria of the gut, known as the gastrointestinal (GI) microbiome, may influence GI symptoms in women with breast cancer.

Objective: This work aims to describe GI symptom occurrence, duration, severity, and distress and measures of the GI microbiome among women with breast cancer receiving chemotherapy compared to age- and sex-matched healthy controls.

Interventions/methods: 22 women with breast cancer receiving chemotherapy and 17 healthy control women provided stool specimens and GI symptom data using the modified Memorial Symptom Assessment Scale (MSAS).

A qualitative exploration of goals-of-care discussions with seriously ill patients in Jordan.

Objectives: This study aims to explore seriously ill patients' experiences during goals-of-care discussions and perspectives of end-of-life (EOL) decision-making in the Middle Eastern country of Jordan.

Methods: This is a qualitative descriptive study with semi-structured, one-on-one interviews. Settings were 2 large hospitals in Jordan.

Mental toll on working women during the COVID-19 pandemic: An exploratory study using Reddit data.

COVID-19 has led to an unprecedented surge in unemployment associated with increased anxiety, stress, and loneliness impacting the well-being of various groups of people (based on gender and age). Given the increased unemployment rate, this study intends to understand if the different dimensions of well-being change across age and gender. By quantifying sentiment, stress, and loneliness with natural language processing tools and one-way, between-group multivariate analysis of variance (MANOVA) using Reddit data, we assessed the differences in well-being characteristics for age groups and gender.

Family Caregiver Challenges in Pain Management for Patients with Advanced Illnesses: A Systematic Review.

Although pain management is integral to the caregiving role, there is a paucity of evidence synthesizing specific challenges family caregivers (FCs) face when managing pain for their care partners. This review comprehensively identified and summarized such challenges in the setting of advanced illnesses. Electronic databases (PubMed, CINAHL, PsycINFO, Scopus, and Health and Psychosocial Instruments) were searched using index and keyword methods for all articles published before April 2021.

Longitudinal Subgrouping of Patients With Cancer Based on Symptom Experiences: An Integrative Review.

Problem Identification: The purpose of this integrative review is to identify literature describing (a) subgrouping patients with cancer based on symptom experiences and their patterns of symptom changes over time and (b) methodologies of subgrouping patients with cancer based on symptom experiences.

Literature Search: PubMed®, CINAHL®, and PsycINFO® were searched through January 2019.

Data Evaluation: Studies were appraised for patterns of symptom change over time and methodologic approach using the QualSyst quality rating scale.

Effect of positioning on blood pressure measurement in pregnancy.

Blood pressure is the key vital sign to detecting hypertensive disorders in pregnancy. The importance of taking blood pressure properly was recently underscored by the publication of updated ACC/AHA guidelines for measuring blood pressure in patients. However, the recommended position of seating with arms and back supported is not always feasible to achieve clinically, especially for inpatient women who are pregnant.

Missing Voices: Lessons Learned from Nonparticipating Caregivers in Palliative Care Research.

Our previous study to understand end-of-life care of adolescents and young adults (AYAs) had a suboptimal survey response rate by bereaved caregivers. To identify sociodemographic factors associated with caregiver nonparticipation. analysis of a retrospective multicenter cohort study of caregivers of deceased AYAs from 2013 to 2016.

Bereaved Caregivers Perspectives of Negative Communication Experiences Near the End of Life for Adolescents and Young Adults with Cancer.

High-quality communication is a standard of palliative care for adolescents and young adults (AYAs) with cancer. Yet, few studies have characterized the negative communication experiences of AYAs near the end of life (EOL). We performed a secondary analysis of 27 qualitative interviews with bereaved caregivers of AYAs with cancer who died between 2013 and 2016 at 1 of 3 sites.

The efficacy of web or mobile-based interventions to alleviate emotional symptoms in people with advanced cancer: a systematic review and meta-analysis.

Purpose: This review aims to critically evaluate the efficacy of web or mobile-based (WMB) interventions impacting emotional symptoms in patients with advanced cancer.

Method: Articles published from 1991 to 2019 were identified using PubMed, PsycINFO, CINAHL, and Scopus. Only interventions involving adults with advanced cancer using a WMB intervention to manage emotional symptoms were included.

"Live your life cuz everybody's terminal": Describing emotions and coping behaviors of rural advanced cancer patients.

Purpose: Culturally competent health care has led to increasing interest in how patients' identities influence the management of their health. The ways rural patients with advanced cancer process emotions and cope with their disease may be influenced by their rural context. The aims for this study were to (1) describe the emotions rural cancer patients experience, (2) describe how rural cancer patients manage their emotions within their rural context, and (3) interlace the themes related to coping with emotions.

Web and mobile-based symptom management interventions for physical symptoms of people with advanced cancer: A systematic review and meta-analysis.

Background: Symptom management is a critical aspect of comprehensive palliative care for people with advanced cancer. Web and mobile-based applications are promising e-Health modalities that can facilitate timely access to symptom management interventions for this population.

Aim: To evaluate the efficacy of web and mobile-based symptom management interventions in alleviating physical symptom burden in people with advanced cancer.

Oral Health in Adult Patients Receiving Palliative Care: A Mixed Method Study.

Background: Oral disease is highly prevalent in persons receiving palliative care (PRPC). Yet, little is known about how PRPC perceive their oral health status and related treatment needs.

Methods: This mixed-method study included 49 English-speaking PRPC (age≥18) recruited from the University of Iowa Palliative Care Clinic.

Post-treatment head and neck cancer survivors' approaches to self-management: A qualitative study.

Purpose: Post-treatment head and neck cancer (HNC) survivors contend with distinct, long-term challenges related to cancer treatments that impact their day-to-day lives. Alongside follow-up cancer care, they also must be responsible for the daily management of often intrusive physical and psychological symptoms, as well as maintaining their health and a lifestyle to promote their well-being. The purpose of this study was to identify HNC survivors' approaches toward engagement in self-management activities.