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Nonvalvular atrial fibrillation (NVAF) affects almost 6 million Americans and is a major contributor to stroke but is significantly undiagnosed and undertreated despite explicit guidelines for oral anticoagulation.

The aim of this study is to investigate whether the use of semisupervised natural language processing (NLP) of electronic health record's (EHR) free-text information combined with structured EHR data improves NVAF discovery and treatment and perhaps offers a method to prevent thousands of deaths and save billions of dollars.

We abstracted 96,681 participants from the University of Buffalo faculty practice's EHR. NLP was used to index the notes and compare the ability to identify NVAF, congestive heart failure, hypertension, age ≥75 years, diabetes mellitus, stroke or transient ischemic attack, vascular disease, age 65 to 74 years, sex category (CHA

DS

-VASc), and Hypertension,Abnormal liver/renal function,Stroke history,Bleeding history or predisposition,Labile INR,Elderly,Drug/alcohol usag of strokes, and saves lives and funds. This method is applicable to many disorders with profound public health consequences.

Artificial intelligence-informed bio-surveillance combining NLP of free-text information with structured EHR data improves data completeness, prevents thousands of strokes, and saves lives and funds. This method is applicable to many disorders with profound public health consequences.

Clinical reasoning (CR) is a fundamental skill for all medical students. In our medical education system, however, there are shortcomings in the conventional methods of teaching CR. New technology is needed to enhance our CR teaching, especially as we are facing an influx of new health trainees. China Medical University (CMU), in response to this need, has developed a computer-based CR training system (CMU-CBCRT).

We aimed to find evidence of construct validity of the CMU-CBCRT.

We recruited 385 students from fifth year undergraduates to postgraduate year (PGY) 3 to complete the test on CMU-CBCRT. The known-groups technique was used to evaluate the construct validity of the CBCRT by comparing the test scores among 4 training levels (fifth year MD, PGY-1, PGY-2, and PGY-3).

We found that test scores increased with years of training. Significant differences were found in the test scores on information collection, diagnosis, and treatment and total scores among different training years of participants. However, significant results were not found for treatment errors.

We provided evidence of construct validity of the CMU-CBCRT, which could determine the CR skills of medical students at varying early stage in their careers.

We provided evidence of construct validity of the CMU-CBCRT, which could determine the CR skills of medical students at varying early stage in their careers.

High-frequency patient-reported outcome (PRO) assessments are used to measure patients' symptoms after surgery for surgical research; however, the quality of those longitudinal PRO data has seldom been discussed.

The aim of this study was to determine data quality-influencing factors and to profile error trajectories of data longitudinally collected via paper-and-pencil (P&P) or web-based assessment (electronic PRO [ePRO]) after thoracic surgery.

We extracted longitudinal PRO data with 678 patients scheduled for lung surgery from an observational study (n=512) and a randomized clinical trial (n=166) on the evaluation of different perioperative care strategies. PROs were assessed by the MD Anderson Symptom Inventory Lung Cancer Module and single-item Quality of Life Scale before surgery and then daily after surgery until discharge or up to 14 days of hospitalization. Patient compliance and data error were identified and compared between P&P and ePRO. Generalized estimating equations model and 2-pted in a provincial hospital (P&P OR 3.34, 95% CI 2.10-5.33; P<.001; ePRO OR 4.73, 95% CI 2.18-10.25; P<.001), and with severe disease (P&P OR 1.63, 95% CI 1.33-1.99; P<.001; ePRO OR 2.70, 95% CI 1.53-4.75; P<.001). Errors peaked on postoperative day (POD) 1 for P&P, and on POD 2 for ePRO.

It is possible to improve data quality of longitudinally collected PRO through ePRO, compared with P&P. However, ePRO-related sampling bias needs to be considered when designing clinical research using longitudinal PROs as major outcomes.

It is possible to improve data quality of longitudinally collected PRO through ePRO, compared with P&P. However, ePRO-related sampling bias needs to be considered when designing clinical research using longitudinal PROs as major outcomes.Data integration, the processes by which data are aggregated, combined, and made available for use, has been key to the development and growth of many technological solutions. In health care, we are experiencing a revolution in the use of sensors to collect data on patient behaviors and experiences. Yet, the potential of this data to transform health outcomes is being held back. Deficits in standards, lexicons, data rights, permissioning, and security have been well documented, less so the cultural adoption of sensor data integration as a priority for large-scale deployment and impact on patient lives. The use and reuse of trustworthy data to make better and faster decisions across drug development and care delivery will require an understanding of all stakeholder needs and best practices to ensure these needs are met. The Digital Medicine Society is launching a new multistakeholder Sensor Data Integration Tour of Duty to address these challenges and more, providing a clear direction on how sensor data can fulfill its potential to enhance patient lives.

As chronic cardiac and pulmonary diseases often coexist, there is a need for combined physical home-based rehabilitation programs, specifically addressing older patients with advanced disease stages.

The primary aim of this study is to evaluate the completion and adherence rates of an 8-week, home-based exercise program for patients with advanced cardiopulmonary disease. The secondary end points include patient satisfaction; adverse events; and program efficacy in terms of change in functional capacity, level of dyspnea, and health-related quality of life.

The participants received a goal-oriented, home-based exercise program, and they used a wrist-worn activity tracker to record their exercise sessions. Activity tracker data were made visible on a digital platform, which was also equipped with several other features such as short instruction videos on how to perform specific exercises. The participants received weekly coaching by a physiotherapist and an occupational therapist through video communicatieasible in terms of high completion and satisfaction rates. Nevertheless, a decrease in adherence during the program was observed, and some of the participants reported difficulties with the technology, indicating the importance of the integration of behavior change techniques, using appropriate technology.

Netherlands Trial Register NL9182; https//www.trialregister.nl/trial/9182.

Netherlands Trial Register NL9182; https//www.trialregister.nl/trial/9182.

Mobile health (mHealth) interventions have been shown to effectively improve the quality of life (QOL) among people living with HIV. However, little is known about the long-term effects of mHealth interventions.

This study aims to explore the intervention mechanisms of a social media-based intervention, Run4Love, on the QOL of people with HIV over across a 9-month follow-up period.

We recruited people living with HIV who were concurrently experiencing elevated depressive symptoms from an HIV outpatient clinic in South China. A total of 300 eligible participants were randomized either to the intervention group or the control group in a 11 ratio after they provided informed consent and completed a baseline survey. The intervention group received a 3-month WeChat-based intervention, comprising cognitive-behavioral stress management (CBSM) courses and physical activity promotion. The control group received a printed brochure on nutrition guidelines in addition to the usual care for HIV treatment. Neither paHIV, especially social media-based interventions that can address HIV-related stigma and alleviate depressive symptoms.

Chinese Clinical Trial Registry ChiCTR-IPR-17012606; https//www.chictr.org.cn/showproj.aspx?proj=21019.

Chinese Clinical Trial Registry ChiCTR-IPR-17012606; https//www.chictr.org.cn/showproj.aspx?proj=21019.

Cirrhosis, or scarring of the liver, is a debilitating condition that affects millions of US adults. Early identification, linkage to care, and retention of care are critical for preventing severe complications and death from cirrhosis.

The purpose of this study is to conduct a preimplementation formative evaluation to identify factors that could impact implementation of the Population-Based Cirrhosis Identification and Management System (P-CIMS) in clinics serving patients with cirrhosis. P-CIMS is a web-based informatics tool designed to facilitate patient outreach and cirrhosis care management.

Semistructured interviews were conducted between January and May 2016 with frontline providers in liver disease and primary care clinics at 3 Veterans Health Administration medical centers. Atuveciclib CDK inhibitor A total of 10 providers were interviewed, including 8 physicians and midlevel providers from liver-related specialty clinics and 2 primary care providers who managed patients with cirrhosis. The Consolidated Framework for Iequired leadership support, time, and staffing. Providers also cited the need for more intuitive interface elements to enhance usability.

P-CIMS shows promise as a powerful tool for identifying, linking, and retaining care in patients living with cirrhosis. The current evaluation identified several improvements and advantages of P-CIMS over current care processes and provides lessons for others implementing similar population-based identification and management tools in populations with chronic disease.

P-CIMS shows promise as a powerful tool for identifying, linking, and retaining care in patients living with cirrhosis. The current evaluation identified several improvements and advantages of P-CIMS over current care processes and provides lessons for others implementing similar population-based identification and management tools in populations with chronic disease.

Work-related stress in the construction industry increases the prevalence of depression and anxiety among personnel. In low-resource settings such as Nigeria, construction personnel face high demands and severe working conditions but only have a few services to address their mental health needs. With emerging research showing that digital interventions can be used to self-manage mental health across diverse settings, there may be new opportunities to support construction personnel in the construction industry.

This study aims to determine the use of digital interventions for mental health management among construction personnel in Nigeria and to explore the factors that facilitate or impede the use of these interventions.

This qualitative study explored the perspectives of a convenience sample of 62 construction personnel. The data were subjected to inductive content analysis.

A total of 6 barrier and 3 motivator themes were identified and categorized into 2 groups. The barrier themes were subcategorized into barriers to adoption and barriers to persistent use, whereas the motivator themes were subcategorized into intrinsic and extrinsic motivators.

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