• Examining key features of inclusive future healthcare pathways

  • Sharing how future trends and an inclusive healthcare scenario may evolve chronic and acute care in a decade (two patient stories)

  • How an inclusive approach to healthcare may unlock value within healthcare systems

The true impact of ‘inclusive’ healthcare transformation through which technology, communities and workforces are leveraged together only becomes apparent when future trends and their applications to healthcare and aspects are considered together. How would the combined effects of transformation in technology, communities and the health workforce change the experiences of patients today?

Four features of inclusive future care pathways

Future care pathways in inclusive healthcare scenarios are predicted to embody the following four attributes:


Predictive analytics are used to identify those at risk for infections and chronic diseases, forecast worsened conditions, and to analyze patient data and outcomes to assist clinicians in developing treatment plans. Further in the future, genotyping and phenotyping will help to prevent many diseases and conditions from happening.


Care and treatment plans are developed that cater to individual’s circumstances, preferences and eventually due to genome mapping, approaches based on genetic traits and predispositions will evolve personalized treatments to personalized prevention plans.


Patients are empowered to manage their own health, such as equipping them with information to participate in decision-making or by providing them with the tools and technology to manage and monitor their own health. Communities are empowered to take on delivery of health promotion, prevention and care services for their populations.


Modifiable risk factors for chronic diseases are addressed through smoking cessation and healthy living programs. Genetic testing and screening programs support disease prevention or early detection.

The content that follows predicts how two typical patient pathways for chronic and acute care might be different in 10 years’ time if health systems act now to turn insights about the future trends and their industry implications into care experience opportunities.

Patricia is an older woman who lives alone in subsidized housing in a major urban center. Her only child, a daughter, lives hours away in another city.

Patricia’s care today

Population health management:

Patricia has frequent exacerbations of chronic obstructive pulmonary disorder (COPD), which she manages with inhalers and home oxygen while her congestive heart failure (CHF) is medically managed. During a primary care center visit to update her prescriptions she is assessed using a mini-mental state exam and found at 75 to be experiencing early cognitive decline – this is flagged by center staff as something to monitor in the future. Patricia has some social support from her housing community and a personal care assistant who visits her weekly to help her with light housekeeping and to arrange her medications. She has mentioned that she is lonely and fears for her safety.

During a visit to Patricia’s home, the care assistant notices that Patricia appears confused and short of breath. The worker calls her manager who recommends that an ambulance is called. Patricia is taken to an emergency room where the attending physician finds that her oxygenation is poor, and her congestive heart failure is exacerbated. Consultations are booked with cardiology, respiratory and geriatrics, and an electrocardiogram and bloodwork (including arterial blood gas) are arranged. Patricia remains confused and is unsure of where she is or what is happening.

Care delivery and coordination:
Patricia is admitted to a geriatric assessment unit where she receives additional tests and consultations: a medication review, geriatric psychiatry assessment, social work consult and respiratory therapy assessment. She is diagnosed with dementia and, after a review with her homecare service to assess placement options for Patricia and an in-person meeting with her daughter (who has flown in from out of town), it is decided that she is best discharged to a long-term care facility. Patricia is not happy about this but understands that there are few alternatives available to her. The hospital discharge coordinator cancels her home care services.

Discharge and community management:
Patricia is discharged from the hospital to a step-down care facility where she spends four months before a place (and funding) are found at a care home 20 minutes away. She now has revised COPD and heart failure medications and is supported by 24/7 care assistants and nursing when needed. She is pleased to have more company but misses her old neighborhood and independence, and as her dementia progresses finds it harder to remember where she is or why she is there.

Patricia’s care in 10 years

Population health management:
Patricia’s health and overall wellbeing are monitored through a health app that feeds data back to a local ‘health data center.’ Patricia is 70 when the center sends an alert to her phone that it might be a good idea to go for dementia screening – the device has detected minor changes in her touchscreen interactions, response times and eye-movement that can be a sign of early cognitive decline. Her care team identify genetic markers for early onset dementia, and she is prescribed a subscription to a library of validated apps on her phone, TV and VR headset that use games and online communities to improve brain health. Patricia enjoys the games but is also motivated to keep up at them because they earn her rewards in the real world such as trips to the cinema. She is registered with the national Dementia Society through which she gets access to a clinical trial and permissions her data through a decentralized autonomous organization (DAO).

At 75, Patricia has developed COPD and CHF. These are monitored passively using implantable devices that automatically feedback and adjust her medications and treatment regime to keep it effective and easy to follow.

At 80, the data from Patricia’s health apps detect further decline in her cognition and an alert is issued for a virtual appointment with her primary healthcare provider. Patricia is skeptical as she feels well, but her daughter who has pre-emptively undertaken micro-credentialed dementia caregiver training convinces her it is a good idea. Patricia logs on to her care record and requests a consultation by explaining her concerns to a primary care digital (non-human) worker.

Care delivery:
Soon an algorithm at the health data center makes a prediction of worsening health for Patricia and an in-depth multidisciplinary wellbeing and care planning meeting is organized at her home. Using a digital twin (computer simulation) approach, the care team visualizes for Patricia and her daughter different scenarios for her mental and physical health and how that could change with different courses of action. A care plan including a detailed description of Patricia’s wishes is agreed upon and uploaded to a funded AI health coach, which is connected to the health data center. The AI coach is able to monitor Patricia’s health and respond accordingly. When her activity and mood levels drop, the AI coach suggests activities based on her interests (e.g., mapping a walking route that will intersect with a friend’s house). Seeing the positive impact the coaching has had on her life, Patricia decides to get training as a dementia peer support volunteer to help other people locally and online.

Community management:
At 85, Patricia’s local health data center is alerted by her AI coach that Patricia’s cognition is beginning to decline further. As her local area has become a dementia-friendly community, a variety of trained local people are asked to look out for Patricia and help with things she might need.

She also receives homecare help from a care assistant with micro-credentials in dementia management and COPD. This care is gradually increased over the coming months until home monitoring detects that declines in her gait are putting her at risk of a fall. Though she is offered various adaptations, after discussion with her daughter, friends and caregivers Patricia decides her current house is no longer the best place for her to live.

Having made this decision, a room is added to a nearby, small-scale, modular smart care home, in which small numbers of residents live with round-the-clock care workers and support from care robots. Patricia continues to receive good continuity of care from her local community members, daughter and AI coach. She feels well supported and though eventually she no longer acts as a dementia peer support volunteer, by passively sharing her data with research institutions she still feels she is making a contribution by participating in dozens of clinical trials that she hopes will contribute to an eventual cure for the disease.

Sebastian is a three-year old boy who lives with his parents in a rural area. Both of his parents work full time

Sebastian’s care today

Population health management:
One Friday afternoon Sebastian has an accident in the playground and suffers a closed leg fracture. His childcare provider calls an ambulance and his parents.

Sebastian is brought to a hospital emergency room by ambulance and is assessed by the pediatric emergency team of a physician and nurse. He is transported to diagnostic imaging for an x-ray, where the fracture is confirmed by a radiologist. The pediatric orthopedic surgery team decides that he is in need of an open reduction and gets consent for surgery from his parents. During the admission process, it is discovered that the family does not have a primary care provider and Sebastian’s childhood vaccinations are not up-to-date.

Care delivery and coordination:
The trauma surgeon completes the surgery the next day, in two hours, and Sebastian stays in an inpatient unit where he is monitored closely by the nurses for infection, motor function and pain, and also receives a course of IV antibiotics and inpatient physiotherapy sessions. He recovers well and after five days is assessed as ready to go home. During the discharge assessment, the care team detects a possible speech delay, and an outpatient appointment for a speech and language assessment is booked at the hospital the following week, as well as an appointment at their nearest clinic to get Sebastian’s vaccinations up to date.

Discharge and community management:
Sebastian is discharged with pain medication and anti-inflammatories as well as outpatient wound care appointments. He also receives limited outpatient physiotherapy appointments as children of his age tend to be active once their pain is controlled. Sebastian is thrilled to be home again, but his parents are struggling to understand how they will be able to coordinate and attend all of the different appointments he is now booked in for. On his second night at home Sebastian’s pain is worse and he is unable to sleep, so his father drives him to the emergency room where they adjust his pain medication.

In the months following discharge Sebastian’s parents manage to make all of his wound care, physio and occupational therapy appointments, orthopedic follow-up, and speech and language therapy sessions, though this causes considerable disruption to their work schedules. They continue to worry about his speech and are unsure what impact this may have as he prepares to start school.

Sebastian’s care in 10 years

Population health management:
Sebastian’s health and wellbeing are monitored by the local health data center. He receives regular care from his virtual provider, which organizes his vaccinations to be delivered through a partnering pharmacy chain nearby. When he was two years old, the health data center sent an automated at-home developmental test which discovered a speech delay and Sebastian was prescribed a virtual reality game to improve this, which automatically evolves as his speech progresses and feeds back milestone data to his parents and primary care provider.

One Friday afternoon he has an accident in the playground and suffers a closed leg fracture. His childcare provider calls an ambulance and his parents.

When the ambulance arrives, Sebastian is assessed on the scene by paramedics. A speech-to-text algorithm populates his case notes and predicts that an open reduction is likely and so pre-emptively books an operating room slot at the hospital designated as the specialist pediatric trauma center and routes the ambulance there. The system also triggers an emergency care coordinator to call Sebastian’s parents to brief them on his condition, need for surgery and obtain their consent virtually. Upon arrival at the trauma center, Sebastian’s injuries are confirmed via x-ray, and by the time his parents arrive he has already been assessed and prepared for surgery.

Care delivery and coordination:
The surgery is performed as minimally invasive as possible, using a surgical robot and in-theater imaging which has automatically mapped out the optimum points to make incisions and refix the bone. The procedure is completed in around 1.5 hours. Later that day, to prepare herself for Sebastian’s discharge, his mother takes an interactive mini course on caring for someone recovering from surgery. The following morning, Sebastian is prepared for discharge and is assigned to a virtual ward. An autonomous vehicle delivers a range of adapted hospital equipment to his home, including a smart bed and other non-invasive monitors. Once the equipment is set up, a member of the virtual ward team checks in to see if he is comfortable.

Discharge and community management:
Most of the equipment is automated but his parents are shown how to upload photos and other details that will help algorithms and the virtual ward team to monitor his progress. Physical therapy is gamified through a VR headset, and a camera tracks Sebastian’s progress as he regains movement. He does not need to return to hospital as his pain medications automatically adjust when the smart bed detects increased pain. It also monitors other vital signs. His parents are helped to care for him through on-demand support through the virtual ward, and an allowance that is debited into a care services marketplace app so that they can arrange for someone to come and help with meals and other housework. When his recovery is complete, Sebastian’s hospital equipment is picked up by an autonomous vehicle and sterilized for reuse. All consumables are reused through the hospital’s circular supply chain.

Unlocking value

While inclusive future care pathways can improve customer experiences by being predictive, personalized, proactive and preventative, they can also help to unlock value within healthcare systems. The chart below uses a quadruple aim lens of improving patient experiences and outcomes, workforce experiences and reducing costs to illustrate potential opportunities.

Patient experiences

  • Care services delivered closer to, and at home
  • Highly personalized care based on prevention and early bespoke intervention
  • Increased involvement, self-management, and governance on patients’ life and health situations
  • Increased fulfillment by the ability to take up roles to help others in need of care
  • Less disruption of daily life routines

Clinical outcomes

  • Reduced complications due to prevention and early intervention
  • Increased ‘in-time’ interventions based on continuous monitoring of a range of functions
  • Outcomes focused on both health and wellbeing

Workforce experiences

  • Staff able to perform at the top of their game by use of more diverse and community-based skills
  • Administrative tasks and routine care tasks taken over by AI and digital tooling
  • Increased quality of professional decision-making based on actual and relevant data
  • Multidisciplinary approaches towards patients’ issues
  • Higher flexibility in staff deployment due to transformation from organizational employment to system employment
  • Taps into a wider array of workforce potential through the skilling of informal workers and micro-credentialing
  • Improved staff satisfaction due to ability to spend more focused high-quality time with patients (leading to higher retention levels)


  • Reduced emergency department consults
  • Reduced in-hospital diagnostics
  • Reduced inpatient care
  • Lower waste levels due to increased personalized care
  • Use of high-cost infrastructure (hospital care) replaced by use of lower cost infrastructure (primary and community care)
  • Less use of expensive highly specialized staff and more use of community-based workers



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