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Creating the Foundation for Real-Time Healthcare

The successful implementation of patient monitoring initiatives that improve patient safety has long been a goal of healthcare leaders across the country. Unfortunately, parsing notifications from individual medical devices, reliance on physical spot checks of patients, and the lack of rules-based analytics to assess a patient’s current condition in real-time or identify signs of deterioration puts that achievement out of reach for many hospitals and health systems.

Facilitating and Operationalizing Continuous Surveillance

Patient safety in the era of value-based care is increasingly defined as preventing adverse events before emergency interventions or costly escalations are required. However, most common monitoring practices are reactive, not proactive; meaning, interventions are often applied only after a patient has deteriorated.

Defining Clinical Surveillance

Clinical decision support (CDS) and clinical surveillance are often used by clinicians as an interchangeable, catch-all category of human- and technology-based capabilities that allow for the observation of patients for the purposes of ensuring safety and optimal outcomes.1

A Little Chit-Chat About Continuous Clinical Surveillance

On June 26th I will be joining Tim Gee at Medical Connectivity Consulting on a webinar to discuss continuous clinical surveillance. Since coming to Bernoulli about 18 months ago, I have developed a whole new perspective on how the landscape of various vendor solutions fit together.

Is technology endangering the ‘art of nursing’?

Digital technology has fundamentally transformed healthcare. Use cases abound of improved patient outcomes, lowered costs and the elimination of critical gaps in the care continuum. Advancements in tools that enable better collaboration, management and support have become essential for frontline clinical staff to deliver superior care.

Unleashing the EHR with Real-Time Data

Continuous clinical surveillance solutions that analyze real-time patient data can identify clinically relevant trends, sustained conditions, reoccurrences and combinatorial indications which tells a more complete story, especially when evaluated with EHR-stored data. In short, the analytics with the most data inputs are often the best analytics.