Ernst & Young · Design Strategy & Emerging Technology

Envisioning the Future of Healthcare

EY's Business Growth and Transformation leads asked what healthcare would look like in 2040. I led the research, built four futures to test ideas against, and defined a service EY could start building toward.

Methods

Trend scan Desk research Interview synthesis Persona development Cost modeling Scenario matrix Value exchange Service blueprint Ecosystem map

Timeline

Jan–Apr 2023

Turning home monitoring into earlier care.

Challenge

What could the future of healthcare look like, and how can EY build toward it?

01 · The landscape Trend scan Desk research

Scanning what was already changing in healthcare.

Home health monitoring was increasingly common.

Apple Watches, Fitbits, connected blood pressure cuffs, and other devices collected health information throughout the day.

Healthcare costs were outpacing wages.

In 2022, 46% of working-age adults said they had skipped or delayed care because of cost.

Remote monitoring was becoming reimbursable care.

In 2018, Medicare began paying providers to monitor conditions like high blood pressure using connected devices. Private insurers followed, but adoption stayed low.

02 · Patient lens Interview synthesis Persona development

Grounding the future in real people.

I built Ruth from interview patterns so patient needs stayed visible in every future.

Ruth, 58

Patient

An office manager with high blood pressure who saw her doctor once a year and generally felt fine.

Condition

High blood pressure

Care today

Annual doctor visit

Coverage

Private insurance

Day to day

She felt healthy

03 · Size the stakes Cost modeling

50 years of monitoring costs the same as one year of stroke care.

What Ruth's insurer paid per year

MONITORING HER AT HOME $1,200 CARING FOR HER AFTER A STROKE $60,000

Monitoring: Medicare's published rate, about $100 a month. Stroke care: the US average per patient per year, from a 2021 review of 46 studies.

EY working review 01

Their feedback

Cheaper does not mean people will accept it. Would members let an insurer watch their health?

How it changed the work

I researched usage-based auto insurance, where drivers trade driving data for lower premiums. Uptake holds when the trade is opt-in and the payback is immediate, so I built both into Aeglia.

The problem

Health data was becoming continuous. Care was still organized around appointments.

04 · Possible futures Scenario matrix

Placing Ruth in four versions of 2040.

Two uncertainties stood out from the scan: how quickly health technology would be adopted, and who would pay the bills. Crossing them gave four futures.

Slow Technology adoption Fast
01

Pay to Keep Up

Monitoring devices were cheap and everywhere. Ruth's insurer paid her hospital bills but not prevention, so the device was hers to buy and she skipped it.

Her care started once she felt symptoms.
02

Prevented

Government paid for both Ruth's monitoring and hospital stays. Keeping her well saved the same payer money, so it funded the device.

Her care started before she felt anything.
03

Costly and Stuck

Premiums climbed, treatment never improved, and Ruth canceled checkups. Her insurer still covered the bill when a crisis happened.

Her care started in the emergency room.
04

Backed Up

Government covered everyone, but technology and clinical capacity lagged. Ruth waited longer even though she was covered.

Her care started after a long wait.
← Private insurance Who pays the bills Government →

What the futures showed

Prevention emerged as the strongest direction; funding would determine whether it could scale.

EY working review 02

Their feedback

Members switch insurers every few years. They asked why any insurer would fund prevention when a competitor collects the savings.

How it changed the work

I narrowed the concept to conditions that turn expensive fast. Uncontrolled blood pressure can put someone in hospital inside a single plan year, so the savings land while Ruth is still a member.

05 · Check the trade Value exchange

All three had to come out ahead.

Ruth, her doctor, and her insurer each needed a reason to take part.

Ruth

Worth using

GivesHer daily readings.
GetsA problem caught in week two instead of month six, and a reward for staying with it.
Her doctor

Worth the time

GivesA few minutes reviewing flagged readings.
GetsPaid by the insurer every month to monitor Ruth between visits, which is revenue her practice does not have today.
Her insurer

Worth funding

GivesThe monitoring fee, the visit, and the reward.
GetsFar fewer expensive health emergencies to pay for.
Design criteria

Give Ruth a reason to keep monitoring, pay her doctor for the work, and give her insurer a credible path to lower avoidable cost.

EY working review 03

Their feedback

They flagged the doctor as the fragile point. Another stream of alerts on a full schedule would kill adoption.

How it changed the work

I set Aeglia to flag only sustained trends, never single readings, then blueprinted one episode to show exactly what reached her doctor and what it cost.

The solution · Aeglia

Insurer-funded home monitoring, with the warning signs routed straight to her doctor.

06 · The episode Service blueprint

One rising blood pressure reading, start to finish.

Every step carries what Ruth's insurer spends on it.

01

Baseline

Ruth's cuff sends a reading each morning. Nothing else is asked of her.

$100 a month, cuff and review
02

Signal

Her readings climb for nine days straight. Aeglia flags the climb, not a single bad morning.

$0 nothing has happened yet
03

Check-in

She answers three questions on her phone and books a video visit for Thursday.

$0 included in monitoring
04

Visit

Her doctor opens the call already looking at the nine days and changes Ruth's medication.

$48 paid to the doctor
05

Credit

Ruth gets a grocery credit for filling the prescription and taking her readings.

$25 reward, funded by the insurer

What the episode cost

This episode cost $173. The stroke it prevented would have cost $60,000.

Outcome Build path

Scaling with evidence.

Working reviews built buy-in throughout the project. By the final presentation, EY's questions had been addressed and the rationale behind the recommendation was already clear.

  1. 01

    Build

    Build the service that turns patient health trends into actionable warnings for doctors.

  2. 02

    Validate

    Run the model with one insurer for one year, comparing avoidable hospitalizations against a matched group.

  3. 03

    Scale

    Use validated savings to expand across insurers.

Reflections

What carried forward

Bring the client in while the work is still moving.

Three working reviews meant the final direction was one EY had already shaped. There was nothing left to sell at the end.

Draw the complex parts.

Visuals build shared understanding faster than an explanation, and give people something specific to react to.

Abstract futures need a real person in them.

Feedback got sharper the moment the work stopped being about healthcare and started being about Ruth. Everyone could point to where she would fall through.

Appendix

Selected artifacts