Evolution of Digital Health: An Overview
In the rapidly evolving world of healthcare, a consumer-focused approach is gaining traction, with many patients yearning for more choices and easier access to care. This shift is prompting healthcare organizations to adapt, creating roles such as chief digital officers (CDOs) to steer them through the digital landscape and deliver care remotely.
Dr. Denise Basow, Ochsner Health's first CDO, defines digital health as the application of artificial intelligence (AI) for diagnosis and drug development, health apps, wearables, virtual care solutions, and more. However, the role of a CDO extends beyond just technology implementation. They must also focus on clinician wellness, the process around technology adoption, and the evolution of care in a world of fast-moving technology advances.
The digital health landscape is vast and interdisciplinary, combining healthcare, technology, and data to collect, analyse, and interpret health data, facilitate communication between healthcare professionals and patients, streamline services, and support innovative care models. This includes telemedicine, electronic health records (EHRs), mobile health applications, wearables, biomedical informatics, AI, and machine learning, all aimed at promoting personalised, precise, and efficient healthcare.
Health IT leaders are embracing this digital revolution, implementing digital health solutions amidst a rapidly innovating environment. However, integrating multiple point solutions across hospitals and health systems poses challenges. To address this, leaders focus on evaluating and validating AI and digital health tools, implementing innovations in a sustainable and patient-centric manner, and leveraging platforms to streamline deployment of these technologies.
Dr. Shafiq Rab, CDO at Tufts Medicine, underscores the importance of making digital health tools seamless and pleasurable to use, much like popular apps. He believes that precision medicine, catering to each individual's unique needs, will be enabled by rapidly advancing digital health tools.
However, disruption to traditional care models can potentially disrupt continuity of care. CDOs must focus on maintaining it using innovative technologies and processes. The implementation of telehealth, for instance, requires rethinking how appointments are scheduled using this new care delivery model.
Mature data analytics and AI programs are transforming how healthcare organizations receive and act on patient data. When undergoing digital transformation, it's crucial to clearly define the organization's desired outcomes and key performance indicators.
Ochsner Health, for example, created a nursing innovation group to address workflow challenges due to nurse burnout and shortages, focusing on improving nurses' workflows before considering new technologies.
Patient portals have been created to allow patients to access their health information, and digital health technology can monitor patient exercise and deliver data to providers via the cloud. All stakeholders must agree about these goals and the path to achieving them.
In summary, digital health is a comprehensive, technology-enabled ecosystem aimed at improving healthcare precision, personalization, efficiency, and patient outcomes. Health IT leaders are focused on navigating this complex landscape by rigorously validating new technologies and adopting integrated platform approaches to sustainably implement innovation in healthcare delivery.
Dr. Denise Basow's definition of digital health encompasses AI for diagnosis and drug development, health apps, wearables, virtual care solutions, and more, beyond just technology implementation, also focusing on clinician wellness, the process around technology adoption, and the evolution of care in a fast-moving technology world. The digital health landscape, embraced by health IT leaders, is vast and interdisciplinary, combining health-and-wellness, technology, and data to promote personalized, precise, and efficient healthcare, including science-driven innovations like AI, machine learning, and telemedicine.
