Having a reliable power source is something many of us take for granted. It is particularly important for healthcare facilities to have a consistent, reliable power source to ensure that vulnerable patients – specifically those who rely on electricity to sustain their lives – are not disrupted. In rural Sub-Saharan Africa, however, it’s estimated that only about 28% of hospitals have reliable electricity.
Hospitals that adopt electronic health records (EHR) to optimize clinical workflows face the decision of how to integrate EHR alerts into their workflows. The rationale is to surface actionable data from EHR systems and present healthcare providers with this information to supplement their day-to-day clinical decisions.
Effective communication in nursing is central to providing top-quality patient care. Nurses communicate with patients to understand their health issues, and they provide them with the care and compassion needed for recovery. Accomplishing effective communication with patients directly impacts patient health outcomes, and it has far-fetched implications when carried out ineffectively. As such, effective communication in nursing drives patient-centered care.
Healthcare providers are under more pressure than ever to provide better care and improve patient outcomes despite clinical resource scarcity, high turnover, and burn-out. Staffing shortages of physicians and nurses, growing populations in need of care, and rising costs create real barriers to exceptional care.
A team of data scientists from the University of Pittsburgh School of Medicine in the US, and neurotrauma surgeons from the University of Pittsburgh Medical Centre, has developed the first automated brain scans and machine-learning techniques to inform outcomes for patients who have severe traumatic brain injuries. The advanced machine-learning algorithm can analyse vast volumes of data from brain scans and relevant clinical data from patients.
A new study shows that it is possible to use the genetic sequences of a person’s antibodies to predict what pathogens those antibodies will target. Reported in the journal Immunity, the new approach successfully differentiates between antibodies against influenza and those attacking SARS-CoV-2, the virus that causes COVID-19.
