Clinical
Predictive analytics in EHRs aren't yet effective enough for clinical decision support at the point of care.
While understanding and reconciling drugs after discharge from the hospital can be challenging, it's a necessity for greater efficacy of care delivery. HL7's Da Vinci project can help.
AHRQ is helping the transition towards evidence-based recommendations to guide clinical decision-making that incorporates patients' needs and preferences.
While traditionally deeply skeptical of artificial intelligence in clinical settings, in today's fast-changing care delivery landscape many physicians are thinking more proactively about how AI can improve quality and patient experience.
CIOs need to look beyond just EHRs and explore stand-alone platforms to enhance care delivery – keeping focused on reliable patient data and streamlined clinical workflows.
The clinical manifestations of COVID-19 are varied, and patients are known to have rapidly changing signs and symptoms that must be tracked with laboratory testing.
CMS requirements for approved clinical decision support mechanisms could cause extra burden and more keystrokes for physicians attempting to meet appropriate use criteria.
COVID-19 appeared in late 2019 and its epicentre has been moving with alarming speed from the far east toward Europe and now more toward the Americas.
Penn Medicine’s Mike Restuccia explains why instituting an end user survey is such an important, and eye-opening, step to take.
Why is now the time they’ll finally join together? Patients expectations are evolving, the tech is now mature enough, and apps are emerging to integrate with legacy clinical systems.
