Coylerode2385
etected by NLP, 73.8% (104/141) had documentation of substance use in at least one structured EMR field. Seventy-six patients had documentation of substance use in structured EMR fields that was not detected by NLP of clinical notes.
Among patients in an urban HIV care clinic, NLP of clinical notes identified high rates of mental illness and substance use that were often not documented in structured EMR fields. This finding has important implications for epidemiologic research and clinical care for people living with HIV.
Among patients in an urban HIV care clinic, NLP of clinical notes identified high rates of mental illness and substance use that were often not documented in structured EMR fields. This finding has important implications for epidemiologic research and clinical care for people living with HIV.
Aggressive management of blood glucose, blood pressure, and cholesterol through medication and lifestyle adherence is necessary to minimize the adverse health outcomes of type 2 diabetes. However, numerous psychosocial and environmental barriers to adherence prevent low-income, urban, and ethnic minority populations from achieving their management goals, resulting in diabetes complications. Health coaches working with clinical pharmacists represent a promising strategy for addressing common diabetes management barriers. Mobile health (mHealth) tools may further enhance their ability to support vulnerable minority populations in diabetes management.
The aim of this study is to evaluate the impact of an mHealth clinical pharmacist and health coach-delivered intervention on hemoglobin A
(HbA
, primary outcome), blood pressure, and low-density lipoprotein (secondary outcomes) in African-Americans and Latinos with poorly controlled type 2 diabetes.
A 2-year, randomized controlled crossover study will evalated behaviors, and quality of life). Data collection during the second year of study will determine the maintenance of any physiological improvement among participants receiving the intervention during the first year.
Participant enrollment began in March 2017. We have recruited 221 patients. this website Intervention delivery and data collection will continue until November 2021. The results are expected to be published by May 2022.
This is among the first trials to incorporate health coaches, clinical pharmacists, and mHealth technologies to increase access to diabetes support among urban African-Americans and Latinos to achieve therapeutic goals.
DERR1-10.2196/17170.
DERR1-10.2196/17170.
Pressure injury (PI) is a common and preventable problem, yet it is a challenge for at least two reasons. First, the nurse shortage is a worldwide phenomenon. Second, the majority of nurses have insufficient PI-related knowledge. Machine learning (ML) technologies can contribute to lessening the burden on medical staff by improving the prognosis and diagnostic accuracy of PI. To the best of our knowledge, there is no existing systematic review that evaluates how the current ML technologies are being used in PI management.
The objective of this review was to synthesize and evaluate the literature regarding the use of ML technologies in PI management, and identify their strengths and weaknesses, as well as to identify improvement opportunities for future research and practice.
We conducted an extensive search on PubMed, EMBASE, Web of Science, Cumulative Index to Nursing and Allied Health Literature (CINAHL), Cochrane Library, China National Knowledge Infrastructure (CNKI), the Wanfang database, the VIP dir effectiveness, as well as to improve the methodological quality.
There is an array of emerging ML technologies being used in PI management, and their results in the laboratory show great promise. Future research should apply these technologies on a large scale with clinical data to further verify and improve their effectiveness, as well as to improve the methodological quality.
Symptom checkers (SCs) are tools developed to provide clinical decision support to laypersons. Apart from suggesting probable diagnoses, they commonly advise when users should seek care (triage advice). SCs have become increasingly popular despite prior studies rating their performance as mediocre. To date, it is unclear whether SCs can triage better than those who might choose to use them.
This study aims to compare triage accuracy between SCs and their potential users (ie, laypersons).
On Amazon Mechanical Turk, we recruited 91 adults from the United States who had no professional medical background. In a web-based survey, the participants evaluated 45 fictitious clinical case vignettes. Data for 15 SCs that had processed the same vignettes were obtained from a previous study. As main outcome measures, we assessed the accuracy of the triage assessments made by participants and SCs for each of the three triage levels (ie, emergency care, nonemergency care, self-care) and overall, the proportion of partdeciding when to rely on self-care but it is in that very situation where SCs perform the worst. Further research is needed to determine how to best combine the strengths of humans and SCs.
Most SCs had no greater triage capability than an average layperson, although the triage accuracy of the five best SCs was superior to the accuracy of most participants. SCs might improve early detection of emergencies but might also needlessly increase resource utilization in health care. Laypersons sometimes require support in deciding when to rely on self-care but it is in that very situation where SCs perform the worst. Further research is needed to determine how to best combine the strengths of humans and SCs.
First-year university students are at an increased risk for developing mental health issues and a poor nutritional status. Self-care plays an essential role in optimizing mental health and can prevent or manage stress, anxiety, and depression. Web-based self-monitoring of diet and physical activity can lead to similar or improved health outcomes compared with conventional methods. Such tools are also popular among university students.
The primary aim of this 12-week randomized controlled trial is to assess the impact of a web-based wellness platform on perceived stress among first-year university students. The secondary aim is to assess the effects of the platform on diet quality. The exploratory objectives are to explore the effects of the platform on body composition, health-related quality of life, mindfulness, mental well-being, and physical activity.
A total of 97 first-year undergraduate students were randomized to either the intervention (n=48) or control (n=49) group. The intervention consisted of access to a web-based platform called My Viva Plan (MVP), which aims to support healthy living by focusing on the topics of mindfulness, nutrition, and physical activity.
