HEART FAILURE
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Heart failure (HF) is the leading cause of death and the single largest healthcare cost in the US and EU
The primary reason patients are rushed to hospitals — acute hospital admissions
HF hospital admissions annually: 1.2M–1.6M in the US
High 30-day rehospitalization rate: 23% 6
Cost per HF admission: $13,000–$18,000
Total costs for payers: $16B-29B per year
Prolonged hospital stay: 5–8 days¹ → high bed occupancy & resource use
Penalty risks under Medicare’s HRRP program
Pulmonary artery catheters (PACs) are the standard of care for hemodynamic data to support HF diagnosis and treatment
Patients
Significant risks
Pain & discomfort
No mobility, bed bound
Prolonged hospital stay
Physicians
PAC inaccuracies
Misinterpretation
Mistreatment
Complications
Underutilisation
Payers
Delayed discharge
Rehospitalization
Inefficiencies
Increased costs
Without PAC hemodynamics
Clinicians rely on indirect, less accurate methods resulting in delayed and suboptimal treatment decisions
Existing PACs are bulky, highly invasive catheters that require a complex insertion procedure and deliver hemodynamic data with limited precision, stability and accuracy.
Indirect methods (e.g. physical exams, lung/heart sounds, lab tests, medical imaging) provide delayed data with limited accuracy.
Non-invasive wearable devices are not suitable to guide clinical treatment decisions — they’re suited for general health and fitness tracking.
Misinterpretation of the massive amounts of complex medical data and delayed recognition of deterioration often lead to suboptimal or even harmful treatment decisions.
Conclusion: A safer, more accurate AI-guided PAC would lead to better patient outcomes
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