HPM 250 Midterm

trends in digital health evolution

significant growth and investment in DH driven by advances in healthcare informatics, data science, AI and digital technologies

who is funding digital health evolution?

governments, healthcare organizations, private investors

what will DH improve?

healthcare access, quality, efficiency

trends driving DH growth

government investment, addressing health disparities, private sector growth, market expansion

challenges in adopting digital technologies

complex healthcare ecosystems, interoperability issues, data security concerns, organizational and regulatory barriers

evolution of digital health from health 1.0 to health 4.0

evolution of DH reflects transformation from traditional face-to-face healthcare delivery to an intelligent, interconnected healthcare ecosystem powered by data, AI, connected tech

health care 1.0

traditional care (in-person, hospitals, paper based records)

health care 2.0

digitalization of healthcare (biotech, medical devices, information systems; advanced diagnostic equipment, portable monitoring devices, EMRs, HIT, internet accessed health info)

health care 3.0

connected and virtual care (EHRs, digital workflows, computerized provider order entry, digital imaging systems, electronic prescribing, telehealth/medicine, remote patient monitoring, patient portals → communication)

health care 4.0

intelligent and personalized healthcare (internet of things, wearables, cloud computing, dig data analytics, AI, clinical decision support, robotics and smart medical devices)

what will health care 4.0 lead to?

• highly interconnected across providers, patients, homes, communities

• data driven and predictive

• personalized

• proactive prevention/early intervention

• supporting precision medicine/intelligent care delivery

data, information, informatics in digital heath

data serves as teh foundation for scientific advancement, healthcare innovation, emerging technology (AI)

big data healthcare (big 3)

volume (amounts), variety (types), velocity (generation/processing)

what do healthcare organizations use big data for?

• identify medical trends

• predict health outcomes

• support population health management

• enable predictive analytics and clinical decision-making

informatics and digital medicine

application of data, info, tech, to improve healthcare delivery and patient outcomes - combines data collection, analysis, and technological tools to create effective medical interventions and healthcare systems

predictive analytics and clinical decision support

key outcome of healthcare informatics and:

• analyze patient data trends

• predict disease risk and progression

• support diagnosis and treatment decisions

• forecast patient responses to therapies

• improve disease prognosis and prevention strategies

technological infrastructure in DH

foundation that enables DH technologies to be safely/effectively integrated into healthcare. as new innovations are implements, frameworks are necessary to ensure safety, reliability, and minimal disruption

security

protects healthcare systems and patient data from unauthorized access, manipulation, threats; use firewalls. passwords, biometric authentication, access controls

privacy

gives patient control over who has access to health info & how it is used; patients should have ability to grant, monitor, revoke access to data; organization responsible for ensuring privacy rights are protected

interoperability

ability of new technologies to integrate and communicate with existing healthcare systems; technologies must be compatible/capable of sharing data across platforms for efficiency, support, adoptions

poor interoperability

inefficiencies, increase costs, hinder patient care

technical standards and regulatory requirements

devices, software, data systems, must meet gov approved standards, functions, function reliably, be regularly evaluated, as tech evolves

patient-centric care in DH

tech and healthcare processes should be designed to improve patient outcomes while ensuring patients are protected from harm and unnecessary risk

ethical use of health data

patient info should only be used to benefit patient

usability and accessibility of digital health technologies

digital tools and medical devices should be:

• user freindly/intuitive

• accessible to diverse populations

• culturally appropriate

• easy to navigate regardless of technical skill level

emerging technologies in DH

shaping the future of DH by expanding healthcare capabilities

• internet of things

• nanorobotics

• 3D printing

internet of things (IoT) and wearable technologies

support:

• remote patient monitoring

• smart home healthcare integration

• in-hospital monitoring

• rehab and self-management

• elderly and pediatric care

nanorobotics

involves microscopic devices capable of operating within human body. potential:

• targeted drug delivery

• biological data collection

• minimally invasive treatments

nanorobotics challenges

• safe design

• potential inflammatory responses

• regulatory and ethical considerations

• high development and maintenance costs

3D printing

• create customized medical devices and biomedical components

• improve manufacturing efficiency

• produce detained anatomical models for physician training and surgical planning

regulatory issues in DH

speed of innovation often exceeds regulatory frameworks; rapid development requires more flexible clinical evidence; different countries require approval from different oversight

healthcare informatics

integration of tech, data, and health sciences to collect, manage, analyze, use health info to improve patient care, clinical decision making, and healthcare outcomes; proffesionals must develop expertise in info systems and data management to enhance efficiency, reduce errors, improve workflow, support better patient safety

key components of healthcare informatics

EHRs, biomedical informatics, pathology informatics, imaging informatics, public health informatics, community health informatics, nursing informatics, home health informatics, consumer health informatics - help identify critical needs and establish systematic approaches to delivering high-quality value-based care