From managing appointments to admittance and coordination of treatments to billing – patient management is a complex field in which everything revolves around the patient. Keep reading for the latest developments and application examples.
An ultrasound examination performed by a robot can cause distress in some patients. Munich researchers have now developed a VR avatar system that makes the process feel more human.
Currently, cancer treatment evaluation focuses heavily on survival outcomes, but doesn't adequately consider how treatments affect quality of life. A new policy review aims to change this.
Hospitalists face a dual challenge when a critically ill pregnant patient is admitted to a hospital: providing safe and effective treatment for both mother and fetus. Pregnancy causes physiologic changes as well as anatomical ones, which complicates the assessment and medical management of pregnant women. At the annual meeting of the Society of Hospital Medicine (SHM) in Las Vegas, an expert…
Lower income, higher BMI, less time and fewer resources to improve their health: A new study links social and environmental factors in patients from deprived areas to poorer outcomes in surgery.
‘Intelligent bedside terminals’ installed at the upcoming NHS National Rehabilitation Centre in Loughborough are designed to help patients engage in their ongoing rehabilitation.
When should preventive mastectomy be offered for women at higher risk of breast cancer? A new evaluation model defines thresholds at which risk reducing surgery should be recommended.
Saving money, at a cost: To undergo bariatric and weight reduction surgery, more and more patients turn to institutions outside their home country – potentially putting their health at risk.
Too many medicines, too many hospital visits: Inappropriate polypharmacy is a major driver of emergency hospital admissions among adults aged 65 and over, according to a new study.
A virtual medical receptionist named “Cassie,” developed through research at Texas A&M University, is designed to transform the way patients interact with health care providers.
Machine learning (ML) for personalised care, large language models for empathy training of cardiologists, wearable sensor data for better screening, and more: Digital technologies hold great potential to improve diagnosis and treatment of patients with atrial fibrillation (AF). At the ESC 2024 cardiology congress in London, four experts explored the benefits of new solutions and pointed out…
Childhood cancer diagnosis times span from immediate to delays of several years, according to a new study. Young bone tumor patients are among the most affected by these delays.
A new method for predicting the risks of severe injuries during childbirth could improve care and reduce long-term complications for women.
When it comes to breast cancer, ethnic differences matter, putting some women at a significantly higher risk, a new study finds. Genetic ancestry should therefore be considered as a risk factor.
Multiple sclerosis often transitions from a relapsing-remitting to secondary progressive form, which requires different treatment. Now, an AI model can determine this change with 90% certainty.
Discovering knowledge about side effects needs to be faster and better. In her oration, Prof. Dr. Agnes Kant, Professor by special appointment of Innovation of Pharmacovigilance, calls for more research on side effects. She also pleads for a fund for independent research on side effects.
Arginine vasopressin deficiency (AVP-D) is a rare condition affecting the body's water management. However, it is also known under a different name – this can lead to fatal mix-ups.
A large new study of more than 40,000 patients finds that a zero coronary artery calcium score continues to be an accurate indicator of a low risk for a coronary heart event even as a person ages.
Screening for colorectal cancer has proven effective for reducing mortality, but response rates are lacking. A new study finds that putting on the pressure can provide the necessary encouragement.
Generative AI can detect and quantify cognitive biases of human caregivers during medical emergency situations. This way, LLMs could help reduce the impact of bias based on gender, age, or ethnicity.
