International journal of medical informatics
-
Randomized Controlled Trial
Use of the FITT framework to understand patients' experiences using a real-time medication monitoring pill bottle linked to a mobile-based HIV self-management app: A qualitative study.
The purpose of this work was to conduct an in-depth analysis to understand patients' experiences using a real-time medication monitoring pill bottle linked to an HIV self-management app. ⋯ This study demonstrated that tracking medication adherence and receiving push-notification medication reminders through the electronic pill bottle connected to the app encourages and supports PLWH in adhering to their medication regimens. Findings from this work highlight the importance of adequate consideration of the needs of intended users in designing customizable mobile health technology, including HIV-related stigma, disclosure of HIV status and antiretroviral therapy regimens.
-
Severity of illness scores used in critical care for benchmarking, quality assurance and risk stratification have been mainly created in high-income countries. In low and middle-income countries (LMICs), they cannot be widely utilized due to the demand for large amounts of data that may not be available (e.g. laboratory results). We attempt to create a new severity prognostication model using fewer variables that are easier to collect in an LMIC. ⋯ Our study proposes a new ICU mortality prediction model using simple logistic regression on a small set of easily collected variables may be better suited than currently available models for use in low and middle-income countries.
-
To assess the role of speech recognition (SR) technology in clinicians' documentation workflows by examining use of, experience with and opinions about this technology. ⋯ While concerns about SR usability and accuracy persist, clinicians expressed positive opinions about its impact on workflow and efficiency. Faster and better approaches are needed for clinical documentation, and SR is likely to play an important role going forward.
-
Pain gained recognition as a vital sign in the early 2000s, underscoring the importance of accurate documentation, characterization, and treatment of pain. No prior studies have demonstrated the utility of the 0-10 pain scale with respect to discharge opioid prescriptions, nor characterized the most influential factors in discharge prescriptions. ⋯ Pain scale was significantly negatively correlated with discharge MMEs in the ED and positively correlated in the inpatient population. Individual prescriber characteristics were the more influential variable, with prolific high prescribers writing for the largest MME amounts. The inverse association of pain and MMEs at discharge in the ED, and the large effect pre-existing prescriber patterns exhibited, both improved methodology for assessing and appropriately treating pain, and effective prescriber-targeted interventions, must be a priority.
-
Nursing triage documentation is the first free-form text data created at the start of an emergency department (ED) visit. These 1-3 unstructured sentences reflect the clinical impression of an experienced nurse and are key in gauging a patient's illness. We aimed to predict final ED disposition using three commonly-employed natural language processing (NLP) techniques of nursing triage notes in isolation from other data. ⋯ Nursing triage notes can be used to predict final ED patient disposition, even when used separately from other clinical information. These findings have substantial implications for future studies, suggesting that free text from medical records may be considered as a critical predictor in research of patient outcomes.