Contextualized race and ethnicity annotations for clinical text from MIMIC-III.

Observational health research often relies on accurate and complete race and ethnicity (RE) patient information, such as characterizing cohorts, assessing quality/performance metrics of hospitals and health systems, and identifying health disparities. While the electronic health record contains structured data such as accessible patient-level RE data, it is often missing, inaccurate, or lacking granular details. Natural language processing models can be trained to identify RE in clinical text which can supplement missing RE data in clinical data repositories.

Auditing Learned Associations in Deep Learning Approaches to Extract Race and Ethnicity from Clinical Text.

Complete and accurate race and ethnicity (RE) patient information is important for many areas of biomedical informatics research, such as defining and characterizing cohorts, performing quality assessments, and identifying health inequities. Patient-level RE data is often inaccurate or missing in structured sources, but can be supplemented through clinical notes and natural language processing (NLP). While NLP has made many improvements in recent years with large language models, bias remains an often-unaddressed concern, with research showing that harmful and negative language is more often used for certain racial/ethnic groups than others.

Can Patient Contributed Data (PCD) Leverage Connected Health Technology for Cardiac Rehabilitation in Austria?

New technologies such as devices, apps, smartphones, and sensors not only enable people to self-monitor their health but also share their health data with healthcare professionals. Data collection and dissemination occur across a wide variety of environments and settings, tracking everything from biometric data to mood and behavior, which has been termed Patient Contributed Data (PCD). In this work, we created a patient journey, enabled by PCD, to shape a connected health model for Cardiac Rehabilitation (CR) in Austria.

A guiding framework for creating a comprehensive strategy for mHealth data sharing, privacy, and governance in low- and middle-income countries (LMICs).

With the numerous advances and broad applications of mobile health (mHealth), establishing concrete data sharing, privacy, and governance strategies at national (or regional) levels is essential to protect individual privacy and data usage. This article applies the recent Health Data Governance Principles to provide a guiding framework for low- and middle-income countries (LMICs) to create a comprehensive mHealth data governance strategy. We provide three objectives: (1) establish data rights and ownership to promote equitable benefits from health data, (2) protect people through building trust and addressing patients' concerns, and (3) promote health value by enhancing health systems and services.

The messiness of the menstruator: assessing personas and functionalities of menstrual tracking apps.

Objective: The aim of this study was to examine trends in the intended users and functionalities advertised by menstrual tracking apps to identify gaps in personas and intended needs fulfilled by these technologies.

Materials And Methods: Two types of materials were collected: a corpus of scientific articles related to the identities and needs of menstruators and a corpus of images and descriptions of menstrual tracking apps collected from the Google and Apple app stores. We conducted a scoping review of the literature to develop themes and then applied these as a framework to analyze the app corpus, looking for alignments and misalignments between the 2 corpora.

Divided We Stand: The Collaborative Work of Patients and Providers in an Enigmatic Chronic Disease.

In chronic conditions, patients and providers need support in understanding and managing illness over time. Focusing on endometriosis, an enigmatic chronic condition, we conducted interviews with specialists and focus groups with patients to elicit their work in care specifically pertaining to dealing with an enigmatic disease, both independently and in partnership, and how technology could support these efforts. We found that the work to care for the illness, including reflecting on the illness experience and planning for care, is significantly compounded by the complex nature of the disease: enigmatic condition means uncertainty and frustration in care and management; the multi-factorial and systemic features of endometriosis without any guidance to interpret them overwhelm patients and providers; the different temporal resolutions of this chronic condition confuse both patients and provides; and patients and providers negotiate medical knowledge and expertise in an attempt to align their perspectives.

Data Quality of Chemotherapy-Induced Nausea and Vomiting Documentation.

Objective: The objective of the study was to characterize the completeness and concordance of the electronic health record (EHR) documentation of cancer symptoms among multidisciplinary health care professionals.

Methods: We examined the EHRs of children, adolescents, and young adults who received highly emetogenic chemotherapy and characterized the completeness and concordance of chemotherapy-induced nausea and vomiting (CINV) documentation by clinician type and by the International Classification of Diseases 10th Revision (ICD-10) coding choice.

Results: The EHRs of 127 patients, comprising 870 patient notes, were abstracted and reviewed.

Augmenting the Clinical Data Sources for Enigmatic Diseases: A Cross-Sectional Study of Self-Tracking Data and Clinical Documentation in Endometriosis.

Background: Self-tracking through mobile health technology can augment the electronic health record (EHR) as an additional data source by providing direct patient input. This can be particularly useful in the context of enigmatic diseases and further promote patient engagement.

Objectives: This study aimed to investigate the additional information that can be gained through direct patient input on poorly understood diseases, beyond what is already documented in the EHR.

Eye-tracking retrospective think-aloud as a novel approach for a usability evaluation.

Objective: To report on the use of an eye-tracking retrospective think-aloud for usability evaluation and to describe its application in assessing the usability of a mobile health app.

Materials And Methods: We used an eye-tracking retrospective think-aloud to evaluate the usability of an HIV prevention mobile app among 20 young men (15-18 years) in New York City, NY; Birmingham, AL; and Chicago, IL. Task performance metrics, critical errors, a task completion rate per participant, and a task completion rate per task, were measured.

A Mobile Health Intervention for HIV Prevention Among Racially and Ethnically Diverse Young Men: Usability Evaluation.

Background: Mobile health (mHealth) apps have the potential to be a useful mode of delivering HIV prevention information, particularly for young men (13-24 years) who account for 21% of new HIV diagnoses in the United States. We translated an existing evidence-based, face-to-face HIV prevention curriculum into a portable platform and developed a mobile Web app: MyPEEPS Mobile.

Objective: The purpose of this study was to assess the usability of MyPEEPS Mobile from both expert and end user perspectives.

Usability Testing of a mHealth App to Support Self-Management of HIV-Associated Non-AIDS Related Symptoms.

Mobile health (mHealth) applications (apps) are uniquely poised to offer the information that persons living with HIV (PLWH) need to manage the symptoms associated with their chronic condition. The purpose of this study was to assess the usability of a mHealth app designed to help PLWH self-man-age the symptoms associated with their HIV and HIV-associated non-AIDS (HANA) conditions. We conducted a heuristic evaluation with five experts in informatics and end-user testing with 20 PLWH.

Mobile Health Technology for Improving Symptom Management in Low Income Persons Living with HIV.

Persons living with HIV (PLWH) are living longer but experiencing more adverse symptoms associated with the disease and its treatment. This study aimed to examine the impact of a mHealth application (app) comprised of evidence-based self-care strategies on the symptom experience of PLWH. We conducted a 12-week feasibility study with 80 PLWH who were randomized (1:1) to a mHealth app, mobile Video Information Provider (mVIP), with self-care strategies for improving 13 commonly experienced symptoms in PLWH or to a control app.