Digital Divide Lecture 5

What is digital health about?

=field of knowledge + practice (gadgets, professions, ways of working) associated with the development and use of digital technologies to improve health

How can you divide digital health?

• software-based: mobile health app, telemed platforms, health data systems

• device-based: wearables, surgical robots, imaging equipment, implantable devices

What are the 3 foundations for adoption?

• service delivery infrastructure

• social & demographic readiness

• data infrastructure (standardization & interoperability, governance & trust, security & accessibility)

What is service delivery infrastructure about?

are primary care & local health services able to adopt digital tools? (e.g. telemedicine, overreliance on tertiary hospitals instead of local ones), is it distributed equally?

What is social & demographic readiness about?

(generation differences: trust in apps): without readiness, the adoption is impossible > public trust in culture can make or break adoption

• in many advanced economies, ageing populations are very common: more treatment for older adults with chronic diseases needed > these adults are least likely to accept new digital technologies (high demand but low acceptance)

• digital literacy differs between generations

• cultural acceptance is needed

What is data infrastructure about?

telemedicine works good in Seoul but not in rural areas

• standardization & interoperability

• governance & trust

• security & accessibility

What is standardization & interoperability about (data infrastructure)?

systems need to speak a common language > data exchange + integration:

o   formats and terminology of reports should be the same across providers/institutions

o   international standards should be used

What is governance & trust about (data infrastructure)?

rules of privacy & sharing, trust of government, providers and patients

o   legal and institutional frameworks for safe data sharing

o   health data should be seen as a public good

What is security & accessibility about (data infrastructure)?

access for all groups to close infrastructure gaps (required: broadband internet + device availability), cybersecurity

What is the “Information and knowledge Learning Health System”?

• public health data: births, deaths, demographics

• health care data: hospital/emergency care

• long-term care data: nursing home care

• social care data: support to live at home, transport services

• contextual data: social, economic environment

What are the strengths of Korea’s health infrastructure?

• good administrative + claims data through the national health insurance (includes almost everyone), HIRA: reviewing health insurance + assessment service

• advanced digital initiatives: e.g. chronic disease management systems, “My Healthway”

• High ICT readiness: good broadband penetration + most people have smartphones

• good data availability + governance

What are the limitations of Korea’s health infrastructure?

• overconcentration in metropolitan tertiary hospitals (Seoul), including adoption of technology

• ageing population (chronic disease management), low digital literacy among older adults

• data issue: many hospitals use different electronic medical records, that can’t be interpreted by others> weak interoperability

• regulatory tension: privacy laws are interpreted very strictly > slows innovation

What are some future directions for Korea’s Healthcare System?

• learning health system: national strategy by the health ministry, legal & regulatory reform for data protection, cross-agency cooperation

• equity agenda: digital literacy training for elderly, support for rural/underserved regions, reducing overconcentration

What does “AI in health” mean? What roles can AI take on in health care?

=AI (machine/deep learning, NLP) in medical contexts

two roles: assistive tool and autonomous decision-making

What is assistive/decision support AI?

supporting clinicians by providing analysis/recommendations (final decision > physician! = safer because of required human oversight)

o   e.g. AI interprets X-rays > physician confirms diagnosis

What is autonomous AI? What issues arise?

AI makes diagnostic/treatment decisions without physician involvement

o   problems: accountability (who is liable if issues arise?), ethical + legal debates (patient consent, trust, safety concerns)

→ ADOPTION LIMITED

How can AI be used in health specifically?

• diagnostics: radiology

• personalized treatment

• predictive analysis: disease progression

• operational efficiency: hospital resource management

What are the benefits of AI in health?

• better diagnostic accuracy & speed

• early disease detection

• less administrative burden

• more access in resource-limited settings

What are the risks of AI in health?

·       bias: algorithms trained on non-representative data

·       transparency: black box AI decision-making

·       accountability: who’s responsible if AI makes an error

·       trust & adoption: patients + providers are hesitant

What are some future directions for AI in health?

• robust, diverse datasets (representative)

• transparent AI

• clear governance frameworks

• embed AI into learning health systems with continous evaluation

How can you define “Telemedicine”?

=delivering healthcare services through technology (ICT=information and communication technology)

What are the three forms of telemedicine?

• synchronous: real-time interactions (video/phone consultations)

• asynchronous: store-and-forward (sending images, test results > x-ray)

• remote monitoring: wearable devices that continuously send patient data to healthcare providers

What are some growth drivers for telemedicine?

• advances in ICT infrastructure (broadband, smartphones)

• rising demand for chronic disease management

• need for more efficient health care delivery (less waiting times + travel costs)

• support for remote areas

> COVID-19 increased the need + trend of telemedicine, healthcare while reducing infection risk

What are the benefits of telemedicine?

·       accessibility: reach rural/mobility-limited patients (elderly)

·       convenience: saves time + reduces travel

·       continuity of care: for chronic diseases

·       high patient satisfaction (needs met with less hassle)

·       providers: able to see more patients

What are the risks of telemedicine?

• quality: effectiveness (disease management + follow-up care comparable to in-person visits) + safety (risk of misdiagnosis/medical accidents)

• healthcare access: vulnerable groups have low digital literacy + limited ability to use telemedicine, prescription rules online

• cost-effectiveness: telemedicine is expensive, overuse can raise costs (if telemedicine is so convenient, patients may use it more often)

• healthcare delivery system: patients mainly visit large metropolitan hospitals rather than primary/community care

• accountability: who is responsible for accidents/bad practice

What impact does telemedicine have on health inequality?

higher uptake: younger, urban, higher-educated people

lower uptake: older adults, poorer, rural areas

telemedicine can increase existing inequalities!

How does it look on the korean side of things?

• during COVID-19, Korea allowed telemedicine (phone consultations) temporarily

• in 2023, the authorization ended + MOWH introduced a pilot telemedicine program for follow-up patients and those with limited access

• 2025: telemedicine was legalized in korea (telemedicine is complementary, not substitute > cannot run an online-only hospital)

What are “wearables”?

=devices + softwares that track, monitor, support health (Apple Watch, Samsung Galaxy Watch) > fitness trackers, smartwatches, contact lenses

What are some growth drivers for wearables?

self-care trend, industry/platform ecosystems, ageing population leads to more need for healthcare, demand for 24h monitoring

What are some benefits of wearables?

• patients can self-track and get feedback

• anomalies can be detected early

• improved patient-doctor communication

• supports preventive healthcare

What are some challenges associated with wearables?

• access gap: device affordability, required digital literacy

• data accuracy & reliability: consumer vs. medical-grade

• privacy concerns (sensitive data collected by private companies)

• health disparities: younger, urban users benefit most