Digital Health vs. Healthcare IT: The Key Differences Driving Innovation and Business Models
AI for healthcare can be classified under both healthcare IT and digital health, depending on the context and specific application.
One of the most common questions and misunderstandings that arises between insiders and others are the stark differences in business model, focus, and go to market for digital health vs. Healthcare IT. In our work, we focus on healthcare IT including for applications of AI.
By Sherri Douville, written by prompts and with ChatGPT
Differences Between Digital Health and Healthcare IT
Digital Health focuses on using technology to improve health outcomes, patient care, and healthcare delivery on a broad scale. It encompasses mobile health (mHealth), telehealth, wearable devices, and personalized medicine. Digital health innovations aim to make healthcare more accessible, personalized, and proactive, often directly involving the patient in their care through tools like apps, remote monitoring, and teleconsultations. This broad focus includes leveraging AI to enhance patient engagement, real-time health monitoring, and personalized treatment plans, ultimately aiming to improve overall health and wellness.
Healthcare IT, on the other hand, is primarily concerned with the infrastructure and systems used within healthcare organizations to manage patient information and improve clinical workflows. This includes electronic health records (EHRs), health information exchanges (HIEs), practice management software, and clinical decision support systems (CDSS). Healthcare IT aims to enhance the efficiency, accuracy, and security of patient data management and streamline administrative and clinical processes. AI in healthcare IT is often utilized for data management, predictive analytics, and supporting clinical decisions within the confines of a healthcare facility.
Implications for Implementation
The implementation of Digital Health technologies requires a focus on user experience, patient engagement, and data integration across various platforms. These technologies must be user-friendly and accessible to patients, requiring robust mobile applications and telehealth platforms. Implementation often involves partnerships with tech companies, ongoing user education, and addressing regulatory concerns related to patient data security and privacy. Digital health solutions must be scalable and adaptable to different patient needs and settings, from remote rural areas to urban healthcare facilities.
Conversely, implementing Healthcare IT systems involves integrating advanced IT infrastructure within healthcare facilities, ensuring interoperability between different systems, and adhering to strict regulatory standards such as HIPAA for data protection. This requires significant investment in hardware, software, and training for healthcare professionals. Healthcare IT implementation focuses on improving internal processes, data accuracy, and clinical decision-making, often requiring collaboration with EHR providers, IT vendors, and regulatory bodies to ensure compliance and optimal functionality.
Business Models
The business models for Digital Health often revolve around direct-to-consumer services, subscription models, and partnerships with healthcare providers and insurance companies. Companies may offer freemium models for mobile health apps or charge for premium features like personalized health insights and telehealth consultations. The success of digital health solutions relies on widespread adoption, patient engagement, and continuous innovation to meet evolving healthcare needs and preferences.
In contrast, Healthcare IT business models are typically B2B, focusing on long-term contracts with healthcare organizations for software licenses, support, and maintenance services. Revenue models include licensing fees, service contracts, and customization fees for tailored solutions. The emphasis is on building robust, scalable systems that integrate seamlessly with existing healthcare infrastructure, ensuring data security and compliance with regulatory requirements.
Healthcare IT
- Definition: Healthcare Information Technology (IT) involves the design, development, creation, use, and maintenance of information systems for the healthcare industry. It primarily focuses on electronic health records (EHRs), health information exchanges (HIEs), practice management software, and clinical decision support systems (CDSS).
AI Applications in Healthcare IT:
- EHR Integration: AI tools that enhance the efficiency and usability of EHRs, such as natural language processing (NLP) for clinical documentation.
- Clinical Decision Support: AI algorithms that assist healthcare providers in making informed clinical decisions based on data analysis.
- Data Management: AI-driven data analytics for managing patient records, detecting anomalies, and ensuring data security.
- Source: Healthcare Information and Management Systems Society (HIMSS) emphasizes the role of AI in improving data management and clinical decision support within healthcare IT .
Digital Health
- Definition: Digital health encompasses a broad range of technologies aimed at improving health and healthcare delivery. It includes mobile health (mHealth), telehealth, wearable devices, health information technology, and personalized medicine.
AI Applications in Digital Health:
- Telehealth: AI-powered virtual assistants and chatbots that provide remote patient consultations and support.
- Wearables and Remote Monitoring: AI algorithms that analyze data from wearable devices to monitor patient health in real-time.
- Personalized Medicine: AI-driven genomics and other technologies that tailor treatments to individual patients based on their unique genetic makeup.
- Source: The World Health Organization (WHO) defines digital health to include advanced computing sciences such as AI, which play a significant role in telemedicine, mHealth, and personalized health .
AI Conclusion
AI in healthcare straddles both healthcare IT and digital health:
- Digital Health: When AI applications extend to telehealth, wearable devices, and personalized medicine, focusing on improving overall health and healthcare delivery through digital innovations.
- Healthcare IT: When AI is used to enhance traditional IT systems like EHRs, HIEs, and clinical decision support systems.
Both classifications highlight AI’s versatile role in transforming healthcare by improving efficiency, personalization, and accessibility.
Takeaway
Digital health, as a category, faces challenges with market timing fit due to low patient literacy — only 12% of adults have proficient health literacy according to the National Assessment of Adult Literacy — and the enormous infrastructure required to go to market successfully. This includes extensive patient education, complex integration with existing healthcare systems, and significant regulatory navigation, which can slow down adoption and implementation. Consequently, the Trustworthy Technology and Innovation Consortium (TTIC) focuses on healthcare IT, where established infrastructure and higher professional literacy among healthcare providers facilitate quicker, more effective integration of new technologies (CompTIA) (UL Solutions).
Sherri Douville BIO
Sherri Douville BIO
Sherri Douville leads at the intersection of mobile, AI, cybersecurity, healthcare and technology. As the CEO and board member of Medigram, the company is advancing secure, real-time mobile communication solutions for healthcare teams.
Beyond Medigram, Sherri co-chairs the IEEE/UL 2933 standards SG for trust in clinical IoT systems, and she founded and chairs the Trustworthy Technology and Innovation Consortium (TTIC), promoting security and trustworthiness in technology. She is also a Taylor & Francis series editor and the author and editor of “Mobile Medicine,” a book on integrating mobile technologies in healthcare and “Advanced Health Technology” about leveraging advanced technologies to reduce risks and foster better patient outcomes, improved patient and clinician experience, and reduce costs.
Sherri’s career includes contributions and awards at Johnson & Johnson and serving on the board of NorCal HIMSS. She is an advisor in corporate board education for SCU.
References
- World Health Organization (WHO) — Digital Health
- Healthcare Information and Management Systems Society (HIMSS) — What is Health IT?
- FDA — What is Digital Health?
- HIMSS — Healthcare Information and Management Systems Society
- National Institute of Standards and Technology (NIST) — NIST Health IT
- WHO — World Health Organization Digital Health
- FDA — Food and Drug Administration Digital Health
