AI Powered Heartcare. Root-cause cost cutting in an intelligent but not artificial way.

Recently, research findings suggested that a meaningful reduction in variations of care is more effective than traditional cost-cutting. As an American president once said “its all about the economy stupid”. Any meaningful reduction in variations of care is really about focusing on the essential services the hospital needs to deliver in the community it serves, including the primary care community.

Heartcare represents a significant portion of any hospital budget. With heart disease responsible for more death, trauma, and morbidity than all the cancers combined, any meaningful reduction in variations of care must focus on the variations of heart care.

Yet a root-cause analysis of when and how heartcare costs are triggered reveals that they are triggered well before the patient arrives at the hospital, in primary care.

That means that an effective strategy for a meaningful reduction in hospital-related heartcare costs should really start in primary care. Until then patients will continue to be wheeled into the hospital through the ED doors, the most expensive doors to open in healthcare - not a red carpet but a carpet of red. 

But little has changed in primary care. It is still the same basic, archaic, system that “feeds” the hospital with the same basic centuries-old technologies.

A strategic new vision to cost-cutting is needed to address the issues at source. Two innovations can easily, and cost-effectively, enable that vision.

The first innovation should enable more direct collaboration between the hospital and primary care. Hospitals have the expertise that if applied at an earlier stage of disease onset, when it is first discovered in primary care, would lead to more effective and meaningful care, thereby reducing downstream, a.k.a. hospital, costs.

The earlier the onset of heart disease is detected, the more cost-effective the resulting treatment options and the more meaningful the cost savings. And patients remain in Primary Care. 

The bottleneck to this interaction is the technology between the hospital and the primary care clinics – the focus has to be on simpler diagnostic level collaboration.

Too often EHR interoperability is invoked as the panacea for collaboration when in fact it is really a red herring, a minefield of complexity, hidden costs and user problems – a shot-gun wedding is more fun.

This interaction should focus on a simple and effective solution that both fosters and enables “collaborative-triage”, where the hospital’s expertise is made available as part of the Standard of Care to help with patient triage at the primary point of care. The goal, more solid medical-justification as the basis of feeding patients to the hospital.  

This leads us to our second point. To enable effective collaborative-triage requires better Primary Care telemedicine-based diagnostic devices that can provide that provide more robust medical-justification. The right telemedicine diagnostic device is the key, it’s also the hard part.

Currently, ECG is the main “go-to” medical device for diagnosing heart disease in Primary Care (and this only with cardiologists over-read). Yet, despite its iconic status, ECG remains woefully inadequate and ineffective as a widespread screening device for use in Primary Care as the range of diseases it can diagnose is limited to 44% of common heart diseases[1]. This is a serious limitation “gap”, that patients are rarely aware of.

Currently, that gap can only be bridged when and if the patient has access to hospital-level heartcare services, which are not cheap and not readily available - you need a referral based on medical justification. A catch-22?

You need access to higher levels of heart care, to get the medical justification needed to get access to higher levels of heartcare! Yup, Catch-22!

To address this limitations gap requires advanced technological innovations that will both augment and complement ECG with new bio-signal technology powered by Artificial Intelligence (AI). 

Where are the innovators?

Conclusion

For hospitals, effective root-cause cost cutting starts with greater primary care collaboration. Novel innovations in AI-powered bio-signals will help bridge the diagnostic capabilities gap in current technologies enabling more meaningful and effective primary care level screening.

Improvements in Collaborative-triage innovations help bring together primary care and hospital level care that will help hospitals address root cause cost cutting whilst ironically providing more effective and meaningful care.

Cost reductions don’t have to mean care reductions.

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[1] Common heart diseases are defined as all heart diseases that can be identified either by Echocardiography, ECG and are not rare. Rare diseases are defined as having a prevalence of less than 1:10,000+ and do not require specialized tests or specialized equipment to detect it.