Estimated prevalence of multiple chronic conditions throughout adulthood using data from the Research Program.

Estimation of multiple chronic condition (MCC) prevalence throughout adulthood provides a critical reflection of MCC burden. We analyzed electronic health record codes for 58 conditions to estimate MCC prevalence for () Research Program adult participants (N=242,828). Approximately 76% of participants were diagnosed with MCCs, with over 40% having 6 or more conditions and prevalence increasing with age; the most frequently occurring MCC combinations varied by age category (i.

User guide for Social Determinants of Health Survey data in the All of Us Research Program.

Objectives: Integration of social determinants of health into health outcomes research will allow researchers to study health inequities. The All of Us Research Program has the potential to be a rich source of social determinants of health data. However, user-friendly recommendations for scoring and interpreting the All of Us Social Determinants of Health Survey are needed to return value to communities through advancing researcher competencies in use of the All of Us Research Hub Researcher Workbench.

Association Between Genes in the Nuclear Factor E2-Related Factor 2 Antioxidative Response Elements Pathway and Cancer-Related Fatigue in Women With Early-Stage Breast Cancer.

Objectives: To explore genes in the nuclear factor E2-related factor 2 antioxidative response elements (Nrf2-ARE) signaling pathway using a multiomics approach for associations with variability of cancer-related fatigue (CRF) in postmenopausal women with early-stage hormone receptor-positive breast cancer.

Sample & Setting: Postmenopausal women (N = 116) with early-stage hormone receptor-positive breast cancer were recruited from western Pennsylvania.

Methods & Variables: Candidate genes from the Nrf2-ARE pathway were investigated for associations with CRF occurrence and severity.

Systematic Review of Pain Research Among Limited English Proficiency Patient Populations in Health care.

Background: Pain remains a global health problem affecting all populations. There is limited knowledge, however, about the effect of limited English proficiency (LEP) on pain care and outcomes.

Aim: This systematic review determines the current state of pain research for LEP populations.

Variability of DNA Repair and Oxidative Stress Genes Associated with Worst Pain in Breast Cancer Survivors on Aromatase Inhibitors.

Pain is a problem affecting women with breast cancer (HR+BrCa) receiving aromatase inhibitor (AI) therapy. We investigated the relationship between single-nucleotide polymorphisms (SNPs) in DNA repair and oxidative stress genes and perceived worst pain after 6 months of AI therapy. We explored 39 SNPs in genes involved in DNA repair (, , , and ) and oxidative stress (, , , , and ) in women with HR+BrCa receiving adjuvant therapy (AI ± chemotherapy; = 138).

Moving beyond Table 1: A critical review of the literature addressing social determinants of health in chronic condition symptom cluster research.

Variability in the symptom experience in patients diagnosed with chronic conditions may be related to social determinants of health (SDoH). The purpose of this critical review was to (1) summarize the existing literature on SDoH and symptom clusters (i.e.

Advancing Nursing Research Through Interactive Data Visualization With R Shiny.

Scientific data visualization is a critical aspect of fully understanding data patterns and trends. To date, the majority of data visualizations in nursing research - as with other biomedical fields - have been static. The availability of electronic scientific journal articles (which are quickly becoming the norm) has created new opportunities for and data visualization which carry added cognitive benefits and support the ability to understand data more fully.

Documentation of Pain Care and Treatment for Limited English Proficiency Minority Patients With Moderate-to-Severe Pain in Primary Care.

Introduction: There are 25 million individuals in the United States with limited English proficiency (LEP). Language barriers contribute to poorer patient assessment, misdiagnosed and/or delayed treatment, and inadequate understanding of the patient condition or prescribed treatment. LEP also has been shown to result in inadequate pain control, yet there are significant gaps in our knowledge related to pain documentation and pain management in primary care settings.

Patient Race, Ethnicity, Language, and Pain Severity in Primary Care: A Retrospective Electronic Health Record Study.

Background: Patient race, ethnicity, and culture including language are intertwined and may influence patient reporting of pain severity.

Purpose: To describe documentation of patient's self-reported pain presence and severity by race, ethnicity, and language, specifically, Spanish, Hmong, Lao, or Khmer requiring an interpreter or English.

Design And Sample: Retrospective, electronic health record clinical data mining study of 79,195 patient visits with documented pain scores from one primary care clinic.

Do Limited English Proficiency and Language Moderate the Relationship Between Mental Health and Pain?

Aim: To explore whether the relationship between mental health diagnosis (i.e., mood or neurotic, stress-related, or somatoform disorder) and pain is moderated by language in patients with limited English proficiency (LEP).

Characterizing shared and distinct symptom clusters in common chronic conditions through natural language processing of nursing notes.

Data-driven characterization of symptom clusters in chronic conditions is essential for shared cluster detection and physiological mechanism discovery. This study aims to computationally describe symptom documentation from electronic nursing notes and compare symptom clusters among patients diagnosed with four chronic conditions-chronic obstructive pulmonary disease (COPD), heart failure, type 2 diabetes mellitus, and cancer. Nursing notes (N = 504,395; 133,977 patients) were obtained for the 2016 calendar year from a single medical center.

Nursing documentation of symptoms is associated with higher risk of emergency department visits and hospitalizations in homecare patients.

Background: Nurses often document patient symptoms in narrative notes.

Purpose: This study used a technique called natural language processing (NLP) to: (1) Automatically identify documentation of seven common symptoms (anxiety, cognitive disturbance, depressed mood, fatigue, sleep disturbance, pain, and well-being) in homecare narrative nursing notes, and (2) examine the association between symptoms and emergency department visits or hospital admissions from homecare.

Method: NLP was applied on a large subset of narrative notes (2.

Methylation Data Processing Protocol and Comparison of Blood and Cerebral Spinal Fluid Following Aneurysmal Subarachnoid Hemorrhage.

One challenge in conducting DNA methylation-based epigenome-wide association study (EWAS) is the appropriate cleaning and quality-checking of data to minimize biases and experimental artifacts, while simultaneously retaining potential biological signals. These issues are compounded in studies that include multiple tissue types, and/or tissues for which reference data are unavailable to assist in adjusting for cell-type mixture, for example cerebral spinal fluid (CSF). For our study that evaluated blood and CSF taken from aneurysmal subarachnoid hemorrhage (aSAH) patients, we developed a protocol to clean and quality-check genome-wide methylation levels and compared the methylomic profiles of the two tissues to determine whether blood is a suitable surrogate for CSF.

Sexual Identity and Racial/Ethnic Differences in Awareness of Heart Attack and Stroke Symptoms: Findings From the National Health Interview Survey.

Purpose: Investigate sexual identity and racial/ethnic differences in awareness of heart attack and stroke symptoms.

Design: Cross-sectional.

Setting: 2014 and 2017 National Health Interview Survey.

The State of Data Science in Genomic Nursing.

Nurse scientists are generating, acquiring, distributing, processing, storing, and analyzing greater volumes of complex omics data than ever before. To take full advantage of big omics data, to address core biological questions, and to enhance patient care, however, genomic nurse scientists must embrace data science. Intended for readership with limited but expanding data science knowledge and skills, this article aims to provide a brief overview of the state of data science in genomic nursing.

Genetic Underpinnings of Musculoskeletal Pain During Treatment With Aromatase Inhibitors for Breast Cancer: A Biological Pathway Analysis.

Background: Musculoskeletal pain (MSKP) is the most reported symptom during treatment with aromatase inhibitors (AIs) for breast cancer. The mechanisms underlying MSKP are multidimensional and not well understood. The goals of this biological pathway analysis were to (1) gain an understanding of the genetic variation and biological mechanisms underlying MSKP with AI therapy and (2) identify plausible biological pathways and candidate genes for future investigation.

Correction to: Association Between Health Literacy and Medication Adherence Among Hispanics with Hypertension.

Please note the following correction in the second paragraph of the Results section of this article, in the sentences that read, "Table 2 shows the association of health literacy level, as well as each of the included covariates with adherence.

A systematic review of natural language processing and text mining of symptoms from electronic patient-authored text data.

Objective: In this systematic review, we aim to synthesize the literature on the use of natural language processing (NLP) and text mining as they apply to symptom extraction and processing in electronic patient-authored text (ePAT).

Materials And Methods: A comprehensive literature search of 1964 articles from PubMed and EMBASE was narrowed to 21 eligible articles. Data related to purpose, text source, number of users and/or posts, evaluation metrics, and quality indicators were recorded.

Natural language processing of symptoms documented in free-text narratives of electronic health records: a systematic review.

Objective: Natural language processing (NLP) of symptoms from electronic health records (EHRs) could contribute to the advancement of symptom science. We aim to synthesize the literature on the use of NLP to process or analyze symptom information documented in EHR free-text narratives.

Materials And Methods: Our search of 1964 records from PubMed and EMBASE was narrowed to 27 eligible articles.