Becton Dickinson is a medical technology company with a broad portfolio spanning medical devices, drug delivery, pharmacy automation and interventional products. Its Connected Care segment develops pharmacy robotics, dispensing cabinets, infusion pumps, patient monitors and AI-powered cloud software that turns health care data into actionable insights across care delivery. How does BD define connected care in a practical hospital setting?
Health systems are faced with constant financial pressure, staffing shortages, increasing patient acuity and aging populations and are looking to drive efficiencies. Hospitals generate vast amounts of data that are not yet leveraged to bring value back. For technology and transformation officers, connected care means digitalizing the ecosystem and extracting value by bringing high-value data streams into a cohesive framework.
At BD, our portfolio already spans much of this infrastructure. By connecting automated pharmacy robotics, BD Pyxis™ medication dispensing solutions and BD Alaris™ Infusion Systems and advanced patient monitoring systems, we touch the key components driving the care continuum. Historically, connectivity meant pushing data into an electronic medical record (EMR).
But because EMRs are inherently episodic and slow in data capture, that lag time cannot unlock predictive capabilities. We are helping hospitals bridge that gap and transition to real-time, predictive care. How does moving to a real-time model fundamentally change things at the bedside?
Reliable, continuous data is the missing link required to unlock true predictability. If a clinician checks on a patient intermittently every quarter-hour, predicting what will happen next is guessing at best because the data is too sparse. Conversely, when a care team can continuously watch live trends and waveforms, they can determine if a patient is stabilizing or deteriorating and recommend immediate action.
When you apply AI to this environment, that same real-time synthesis happens at a much higher magnitude. By capturing continuous physiological data rather than intermittent snapshots, intelligent systems can analyze complex waveforms. This allows the care team to see a negative clinical trajectory before traditional symptoms manifest, fundamentally changing how clinicians interact with patient data.
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