Background: The delivery of effective phototherapy to patients with psoriasis living in areas devoid of dermatologists is difficult. Telemedicine has proven useful in the delivery of health care in such locations.
Objective: This evidence-based study sought to investigate the use of telemedicine in the monitoring of phototherapy of psoriasis patients located in a Nova Scotia region with no dermatologist.
Methods: Psoriatic patients were reviewed six months before and after protocols and monitoring were instituted. First, charts of 23 patient treated with phototherapy were reviewed from the Aberdeen Hospital in New Glasgow. Patients were either self-referred or referred by a family physician and occasionally a dermatologist. Treatments were not monitored by a specialist. Second, a group of 33 patients receiving treatment were supervised via telemedicine by a dermatologist 250 km away in Halifax.
Results: During the study period, treatment time decreased from 140 to 37 days. In the monitored group, 40% more patients were clear of psoriasis at time of discharge. The number of patients with side effects decreased. The number of self-and family practice-referred patients dropped; the clinic became a referral center for dermatologists.
Conclusion: Telemedicine provided an excellent way to monitor patients receiving phototherapy in an area without a dermatologist. Overall, patient care improved: More patients were treated effectively with better outcomes and fewer side effects.
Download full-text PDF |
Source |
---|---|
http://dx.doi.org/10.1007/s10227-005-0145-9 | DOI Listing |
JMIR Form Res
January 2025
Larner College of Medicine, University of Vermont, Burlington, VT, United States.
Background: Social media has become a widely used way for people to share opinions about health care and medical topics. Social media data can be leveraged to understand patient concerns and provide insight into why patients may turn to the internet instead of the health care system for health advice.
Objective: This study aimed to develop a method to investigate Reddit posts discussing health-related conditions.
JMIR Form Res
January 2025
Northwestern Medicine, Chicago, IL, United States.
Background: Patient recruitment and data management are laborious, resource-intensive aspects of clinical research that often dictate whether the successful completion of studies is possible. Technological advances present opportunities for streamlining these processes, thus improving completion rates for clinical research studies.
Objective: This paper aims to demonstrate how technological adjuncts can enhance clinical research processes via automation and digital integration.
JMIR Serious Games
January 2025
School of Computing, Engineering and Mathematical Sciences, Optus Chair Digital Health, La Trobe University, Melbourne, Australia.
Background: This review explores virtual reality (VR) and exercise simulator-based interventions for individuals with attention-deficit/hyperactivity disorder (ADHD). Past research indicates that both VR and simulator-based interventions enhance cognitive functions, such as executive function and memory, though their impacts on attention vary.
Objective: This study aimed to contribute to the ongoing scientific discourse on integrating technology-driven interventions into the management and evaluation of ADHD.
JMIR AI
January 2025
Department of Information Systems and Business Analytics, Iowa State University, Ames, IA, United States.
Background: In the contemporary realm of health care, laboratory tests stand as cornerstone components, driving the advancement of precision medicine. These tests offer intricate insights into a variety of medical conditions, thereby facilitating diagnosis, prognosis, and treatments. However, the accessibility of certain tests is hindered by factors such as high costs, a shortage of specialized personnel, or geographic disparities, posing obstacles to achieving equitable health care.
View Article and Find Full Text PDFJMIR Med Inform
January 2025
Department of Systems Design Engineering, Faculty of Engineering, University of Waterloo, Waterloo, ON, Canada.
Background: While expert optometrists tend to rely on a deep understanding of the disease and intuitive pattern recognition, those with less experience may depend more on extensive data, comparisons, and external guidance. Understanding these variations is important for developing artificial intelligence (AI) systems that can effectively support optometrists with varying degrees of experience and minimize decision inconsistencies.
Objective: The main objective of this study is to identify and analyze the variations in diagnostic decision-making approaches between novice and expert optometrists.
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!