C427: Technology Applications in Healthcare

[Audio] Hello! Welcome to Topic 1 of Technology Applications in Healthcare. This section will discuss the different roles and functions of information technology (IT) in the healthcare setting. We will address the following three questions: What is the history of Healthcare Information Technology (HIT)? What components comprise the foundation of Healthcare IT? Who is accessing health information?.

[Audio] To answer these questions, we must first understand a digital health ecosystem. A digital health ecosystem refers to the interconnected set of tools, solutions, stakeholders, and processes that leverage digital technologies to improve healthcare. This ecosystem encompasses a range of components that can interact with one another, which, combined, can transform patient care, healthcare delivery, monitoring, and overall public health. Some key elements of a digital health ecosystem are technologies, stakeholders, data, regulations and standards, and integration and interoperability. The digital health ecosystem constantly evolves with technological advancements and healthcare needs. The goal is to harness these elements to deliver better healthcare outcomes, reduce costs, increase accessibility, and offer personalized care to individuals. CMS Meaningful Use is a set of criteria introduced by the U.S. Centers for Medicare & Medicaid Services (CMS) to incentivize healthcare providers to adopt and effectively utilize electronic health record (EHR) systems. The initiative was a part of the Health Information Technology for Economic and Clinical Health (HITECH) Act, passed in 2009. CMS's Meaningful Use was a foundational program that catalyzed the adoption of digital health tools, especially EHR systems and laid the groundwork for a more connected and interoperable digital health ecosystem. One of the core aspects of Meaningful Use was ensuring that health data could be easily shared and accessed across different healthcare settings, a foundational piece in a robust digital health ecosystem. In 2018, the Meaningful Use program was effectively renamed and incorporated into the CMS's Promotion of Interoperability program. This new focus was to advance the interoperability of health information and emphasize patient access to health data. Promoting a vision of a healthy, interoperable, and learning health Information System/Information Technology (IS/IT) ecosystem is grounded in the ambition to transform healthcare delivery, outcomes, and patient experiences. Some of the primary goals are to enhance patient care, improve health outcomes, efficiency and cost savings, safety and reduction of human error, and support population healthcare. A healthy, interoperable, and learning health IS/IT ecosystem aims to create a future where healthcare is more personalized, efficient, and effective. It envisions an environment where every stakeholder, from patients to providers, benefits from seamless data exchange, continuous learning, and technology-driven insights. The five major components of a health IS/IT system are the content and data component, the infrastructure component, the data analytics components, the network compatibility and communications component, and the platform/interface component. These components are used to promote interoperability within the digital healthcare ecosystem. A Healthcare Management Information System (HMIS) culture within an organization is vital to ensuring successful and effective health IS/IT leadership. Four of the main cultural orientations are an information-functional culture, an information-sharing culture, an information-inquiring culture, and an information-discovery culture. Understanding the different characteristics of each culture is essential to guide managers, administrators, and systems analysts in generating appropriate health IS/IT solutions for the organization..

[Audio] Precision Medicine (PM) is an approach to health care largely dependent on digitizing health data and bioinformatics, a field of study intersecting key areas of computer science and biology. Precision Medicine attempts to improve health outcomes by refining diagnosis, treatment, and disease prevention through understanding many factors that can contribute to the intrinsic biology of disease. The four principles of PM are predictive, preventing, personalized, and participatory. This is known as P4 medicine. P4 medicine combines system-based biology, patient-provider data generation, and advanced technology through digital tools. While it holds significant promise, adopting P4 medicine faces several challenges. Precision medicine relies heavily on analyzing vast amounts of data, including genomics, proteomics, metabolomics, and other 'omics' data. This data's sheer volume and complexity can be overwhelming and require advanced analytics and storage solutions. For precision medicine to be effective, seamless integration of data from different sources (e.g., EHRs, genetic testing labs, wearables) is essential. Current systems often operate in silos, making data integration a challenge. Genomic and other personal data are sensitive. Ensuring data privacy while promoting data sharing for research purposes poses regulatory and ethical challenges. PM is fundamentally altering the practice of traditional medicine by tailoring treatment to patients based on their genetic make-up, improving diagnosis by analyzing patient's genetic and molecular profile, targeting cancer therapies by recommending treatment that is based on the genetic mutation of tumors, and reducing the risk of adverse drug reactions. PM is weaving a new paradigm in healthcare, moving away from a reactive, one-size-fits-all approach to a proactive, individualized one..

[Audio] Digital health solutions promise to redefine healthcare by dramatically enhancing the care experience, improving clinical outcomes, and reducing costs. Like many large and complex institutions, health systems might resist digital innovations for several reasons: financial concerns, change management, patient care quality concerns, data security and privacy, technical challenges, and regulatory and compliance issues. Reducing communication barriers between health systems and digital health innovators is crucial to successfully implementing and adopting new technologies. Involving end-users early, such as clinicians, nurses, and administrators, is a meaningful way to bridge the communication gap. Other ways to close the communication gap include education and training workshops, encouraging project collaboration, and implementing structured feedback mechanisms. Some innovations to expect in today's digital health ecosystem include telemedicine and telehealth, Artificial Intelligence (AI), and Machine Learning (ML) interoperable EHRs, healthcare analytics platforms, 3D printing, and voice-activated systems..

[Audio] Thank you for joining us for our discussion of Topic 1! Please reach out to your Course Instructor if you have any questions on any of the material covered during our session..