Next Generation Healthcare

Most current systems reward innovation that prolongs life, not necessarily the quality of life.

Quality of life can be defined as an individual’s perception of their position in life in the context of the culture, values and spirituality in which they live and in relation to their expectations, concerns and it cannot be separated by their own individuality.

To reach a stage where healthcare will be personal, a medical treatment must consider individual variability. For such purpose, it is necessary to combine EMR records with data about the patient’s societal environment, lifestyle, and their genomic data, on which medical staff can leverage. On the prevention side, would also allow identification of genetic variants that increase a patient’s chances of developing diseases.

With this type of engagement, patients are likely to be more cooperative, and comply with procedures and treatment plans.

The last year and most probably this one was shaped by the COVID-19 pandemic. If the introduction of new ways of providing medical treatment, like tele-healthcare and robotic triage, these drivers are still relevant such as: changing care models; cost efficiency; data silos & value-based-care model adoption.

In the interactions I had with healthcare providers globally it surfaced the wish to accelerate the following next generation scenarios:

Across the Value Chain

Disease control – using the sensor networks to detect pathogenic agents, classify infection diseases and raise alerts to relevant stakeholders (citizens, government, providers) to act. This scenario can be integrated in the context of municipality management that I alluded before in the writings of Smart City OS.
Cultural analytics – how to turn cultural processes that reflect the societal context into exploring cultural datasets (non-healthcare data sources) on different unstructured data formats: text, image, video. This allow to understand population profiling and its contribution to most common diseases and support healthcare public policy design.

Patients and citizens centricity

Connected devices with dedicated medical features – infused with interpretive AI that can predict and advise based on indicators and conditions prior to medical events.
Healthcare passport – managed by the citizen it can: curate, record, monitor and share various aspects of your medical history. It can be integrated with a digital identity and be enhanced in pandemic/epidemic response.
Data access and permission management – the patient is able to define the ability to accept, reject or modify relationships with healthcare providers payors such as: hospitals, insurers and clinics (“I control my data I decide with whom I share my ”data”).

Empowering medical staff

Emergency department management – enabling to handle sudden unscheduled walk-in visits, effective triage and monitoring of different patients’ vital signs and conditions, like skeleton motion, emotional state, in real-time. This scenario will loom with the implementation of 5G networks.
Medical digital twin – augmented human-machine interface and immersive collaboration environments in the context of: anatomy education; functional diagnostics – allow analysis of the patient-specific status quo and predict the surgical outcome; validate the change in functionality that can be expected after a surgical intervention and surgical procedure training.
Patient reported outcomes – recognizing the patient’s affective state, the whole area of human emotional intelligence especially dealing with people’s emotions and incorporating such emotional intelligence into patient interaction.

The last year and most probably this one was shaped by the COVID-19 pandemic. If the introduction of new ways of providing medical treatment, like tele-healthcare and robotic triage, these drivers are still relevant such as: changing care models; cost efficiency; data silos & value-based-care model adoption and they will shape the introduction of innovation in healthcare.

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