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.

Realizing Human Potential in the COVID-19 Context

Amid the COVID-19 pandemic, the incomes of self-employed people have been affected and companies are starting to retrench workers, on the other hand, it is necessary to support workers especially on net new core competencies, is what makes somebody adaptable in the face of changes, as work from home created new job opportunities and at the same time, a considerable threat to existing ones. In some circumstances companies may not see the need to physically locate themselves in the region anymore with remote working becoming more prevalent, and amid rising protectionism. In Brazil and USA there is already a movement on decreasing office space capacity and in Southeast Asia, “near-shore” operations are quickly becoming a reality. The Japanese government is supporting to help its companies shift their production out of China and back to Japan. Supply chains are also going to be redesigned.

From the graduate starting out on a career, mid-career worker looking for new job opportunities or trying to stay employed in a new role, there is a new mandate to ensure that people gain accurate and up-to-date information about their options based on available labor market data, individuals’ goals, aptitude, career program and, government and employers.

This requires public sector, educators and the private sector to collaborate on developing and strengthening an educational framework to enable ongoing learning and training opportunities for workers at all stages of their careers.

  • Every individual should gain accurate guidance about their options on personal development, based on data. A promising model is for example, Singapore’s SkillsFuture initiative.
  • The extent to which the existing and future working population acquires the right skills within the workplace, is one of the most critical variables to engage with new opportunities in a constantly shifting labor market.
  • A smart learning environment that is designed towards learning at all stages of life and at the dame time to ensure employability – “get a job”; enables adaptive access to reskilling, upskilling; put individuals at center-stage to take ownership of their own learning paths and accelerate job opportunities with personalized mentorship, will contribute to employability and self-realization.

For educators, priorities for change and business model evolution, should include the following scenarios, coming from a training provider to future of jobs for every individual.

Adaptive Learning

Leveraging on forecasts of future skills requirements for existing workforce, social protection schemes and skills reconversion, integrated with about the degree of fit of candidate, cultural affinity, new operational models, technological evolution, career and performance management, adaptive learning can predict next wave of required training or to update a learning path at the individual level.

Mentoring and Employability

Automated career aspiration path, matching with job market status, person skills and existing learning path. Mentoring support in career progression activities. Accelerate employment by matching candidate profile with personalized recruiter outreach, integrated with employment government agencies.

Digital Credentials

Enables education providers and learners to control and share the credentials that can be trusted and verified. One has the appropriate knowledge, and experience that are necessary and sufficient for being a professional in a certain field or practice, a pre-requisite to perform a role and to be able to practice one’s profession.

Virtual Nomadic Campus

Cross reality environment designed for learning, visualization, social collaboration, knowledge capture, with real-time interaction in physically simulated virtual environment, using immersive technologies.

Smart Cities Operating System

One important element of implementing a smart city is the city become the platform and the platform is able to learn and have an embodied cognitive replica. A platform that apart from:
  • The connectivity provided by the ICT infraestruture;
  • The applications that can be used to request, use or monitor services;
  • The underlying data in the city data lake – enabling understanding about the interactions produced, the patterns and the behaviors, how to optimize traffic flow or waste management.

Have the ability o manage with formal and non-formal forms of human and machines interaction – operational technology and the pervasive communication infrastructure – nevertheless, still requires a number of considerable advancements, in particular, in the domain of understanding human behavior [1] as an important data source of the city planning and service evolution.


city os

City OS framework

Cognitive cities may be constituted with [2] many richly interacting adaptive components that include human beings and other entities with sufficient awareness – sensors – reconfigurability, learning, autonomy and cooperation capabilities at materialized in a City operating system. However, the value of the City OS is if it scales across multiple cities in an ecosystem. In this sense, the objective is to create a Smart City operating system, an “universal-platform” for cities. While they acknowledge the competitive nature and that each city has its own character, identity, tax system or unique capabilities (healthcare or education) there are more commonalities than there are differences. Apart of common services like energy or waste management, the approach is how the ecosystem City OS, connected to other cities can evolve, for example in areas like traffic management, mobility as a service, safety, once the algorithms will be trained in larger data sets or sharing a common capability like person digital identity or resilience (cyber-attacks, geopolitical conflicts, diseases, resources shortages).


[1] Cognition Digital Twins for Personalized Information Systems of Smart Cities: Proof of Concept – Jing Du, Qi Zhu2, Yangming Shi, Qi Wang, Yingzi Lin and Daniel Zhao

[2] Cognitive cities and intelligent urban governance – Ali Mostashari, Friedrich Arnold, Mo Mansouri, and Matthias Finger

Smart Mobility

Governments are increasingly committed to shrinking the environmental footprint of the urban transport sector. The European Union has set a 2050 target of zero carbon emissions from transport in cities. Lisbon is planning an extensive area at downtown with zero emissions, others like Copenhagen and Stockholm, becoming more aggressive in terms of banning combustion engines circulation. Singapore, aims in 2040 that the majority of vehicles, public and private will be electric. This will also contribute to improve the livability of the communities, that become also safer with reduced accident indexes, walkable, were people can cycle, promoting a healthier way of life, as well as, democratize access to a destinations via multiple modes of transport that matches the individual preferences.

Smart mobility can be perceived only as a perfect advanced combination of infrastructure & intermodal transport, taking individuals between two points as fast as possible. Smart mobility is much beyond that.

Smart mobility is what about by better communities. Better communities are safe, walkable, healthy places that promote sustainable and access to destinations by multiple modes and keep together human interaction and connections in a community. Promoting a healthier lifestyle, can be also achieved under the principle of government agencies cooperate under the principle of ecosystems. I’ve been working with some healthcare providers that are promoting a wellness education program. Mobility that invite walking and cycling that can help reverse the trend toward sedentary urban living. Connections are vital to the inner of a community, of a family. People need convenient access to schools, offices, and shopping, leisure areas, to go about their lives. Environmentally progressive cities with world-class public transport and cycling infrastructure, leading the change in decrease carbon footprint, which the majority of the households (75%) to be close to a carbon free public transport in 10 minutes.

Smart mobility can become a reality via the combination of the scenarious as follows, based on a spectrum of government agencies I am working with. At the heart of the concept of smart mobility is data. Data that is going to allow the citizens, a better commute and be on the forefront in terms of influencing the next stage of smart mobility in terms of public policy design.


Scenarios that enable smart mobility

Mobility as a service

The concept of mobility as a service (MaaS) is not about using an application to show travel options and itineraries. Carrying 10 different mobile applications one for each transport mode is not for certain the objetive. 
The concept of MaaS is simple: bundling different transport modes, public and private to end-customer. This breaks traditional paradigms of owning a car, that is one of the biggest outcomes that a transport authority wants to influence. Hence, the development of MaaS is fostered by a new way of thinking that does not considers traffic flow as an isolated function but linked to society. And society is about people. And people have preferences. Hence MaaS is about incorporating a digital assistant that recognizes our preferences as an individual. Who we are.
That matchmaking process ensures the captures and learns all preferences of the traveler and his travel conditions in a mobility profile. A digital assistant demonstrates that the options combined his preferences concerning comfort, available budget, and time made available to meet business partners and share lunch or dinner, travel with the family to the park or go the airport. It will learn if and individual have more time to travel and want to be environmental friendly.
Traffic Accident Prevention / Traffic Flow Management
Proactive traffic enforcement and intervention should be based on an analysis on the collision data available to identify leading causes of accidents, the most prone locations, as well as, to predict the conditions for collision occurrence, data such as weather, geospatial information and social events data that can be obtained via a combination of datasets with existing sensor technology. Traffic collision should also be integrated into traffic flow management in order to ensure smooth travels and road safety.
Using a machine learning model is possible to aggregate historical data sets about regarding collisions, traffic intersection volumes, social events – national day, sports events – geospatial road segments, weather conditions. This way, it is possible to estimate collision probability map per road segment. The model is updated in real time and regenerates itself with real live data.
This information can be proactively shared with drivers, law enforcement authorities to redirect them in order to escape to points where there is a higher probability of accident and at the same time support decisions in terms of changes in traffic flow direction of infraestruture configuration. In the future with the introduction of autonomous vehicles (buses, automobiles) managed like a device with with traffic management systems, the value realization is much higher.
Asset Integrity
Asset integrity is one of the areas that evolved very much in the last 2 years. Despite the fact anomaly prediction models are well know, the key factor that enable the change is a combination of new hardware: drones with cameras, mixed reality devices like HoloLens, sensors and be able to run applications on real time using edge or fog technologies, that makes possible to localize issues, predict failure and integrate end to end the maintenance supply chain, spare parts, automatic routing based on issue taxonomy, crew availability based on estimarted risk.



Ecosystems and Personal Healthcare

To reach a stage where healthcare will be personal, there is a fundamental step: designing a medical treatment considering individual variability. For such purpose it is necessary to combine and curate to existing EMR records with data about the patient’s societal environment, lifestyle, and their genomic data. This can assist the doctors in identifying which approaches, treatments, and preventions will be effective for the patients, what also can be called personalized healthcare, on the prevention side, would also allow identification of genetic variants that increase a patient’s chances of developing diseases. Treatment could begin earlier, helping reduce risk through behavior modification (healthier diet or increased exercise) or leading to placement of patients on drug therapies.

Such an outcome relies of connecting and sharing data within a particular ecosystem. The ecosystem of me (ties back to the earlier concept of the internet of me). On one hand phone, wearables, health sensors, connected clothing—and combining that with clinical tests, scans, and check-ups—will allow much-improved analysis and monitoring and focus on health optimization. On the other hand, sharing such data in medical doctor community, academia, healthcare think tanks will improve healthcare foresight and shape healthcare public policy design, but most importantly will support via the existence of such dataset to create models of detecting effectively symptoms, understating treatment impact, find new ways of treatment and assist medical doctors with assisted reasoning.


Personalized healthcare is about shifting from volume to value. Revealing the unknown and creating a healthcare ecosystem continuum. The purpose of the transformation journey is to shift from normalized healthcare to personalized healthcare.



Personal Healthcare Ecosystem


With this type of engagement, patients are likely to be more cooperative, and comply with procedures and treatment plans. There are of course other kind of benefits, like ease to schedule an appointment and track medication time, decrease healthcare costs, however, the biggest benefit and value of such an approach allows patients and citizens to look after themselves better and have better quality of life, because healthcare become, personal, anchored on a personal health record, which data sharing consent is managed by the individual.

Technology and healthcare always had an uneasy relationship, and the latest announcements that Apple and Google did entering into healthcare may bring the argument of massive surveillance, however, countries like Singapore, are aggressively progressing towards the creation of a shared nationwide healthcare data lake, by law. It should give us some thoughts about how healthcare is fast becoming personal.