An increasing number of healthcare organizations are employing artificial intelligence to gain clinical and operational efficiencies, which puts AI on a path to transform how healthcare organizations operate. That sort of transformation in healthcare management can help AI reach its potential of making a positive impact on healthcare’s quintuple aim—enhancing the patient care experience, improving population health, improving the satisfaction and well-being of the healthcare team, advancing health equity and reducing healthcare costs—while improving overall productivity.
In some ways, that movement is already underway. AI is assisting hospitals and health systems predict and diagnose diseases and while providing insights for multidisciplinary and interdisciplinary care teams across organizations and research institutions. The next step is for organizations to develop an AI-based healthcare ecosystem, which would connect and communicate with patients, hospitals, healthcare professionals, family practices, payers, pharmaceutical companies and research organizations, among others. Such an ecosystem – has the potential to optimize how a healthcare system is organized and administered using AI guidance.
How would an AI-based ecosystem work in hospitals and other care facilities? AI would be used to, for example, integrate guidance and decision support systems for evidence-based practices, advise on tailored clinical research trial enrollments and provide real-time diagnoses to assist healthcare professionals provide personalized care. With an ability to analyze billions of data points in near to real time to support daily operations, AI can convert that data in ways that build efficiencies in such areas as patient flow and scheduling, supply chain management, managing healthcare facilities, augmenting staffing solutions through just-in-time information based on patient equity data, allocating equipment, streamlining procedures and automating operations. Traditional healthcare and technology-generated data could then be federated and made available to an AI system to streamline and generate near real-time predictions.
This can help establish a common data language that would be used across the healthcare ecosystem. The growing need, demand and potential for AI in healthcare management could be the dawn of a new era once such an ecosystem is effectively used globally. Legal, regulatory, privacy and ethical challenges also could be governed through the ecosystem. AI can feed machine-generated intelligence, insights and solutions along with raw as well as processed data to operational and decision support systems.
Social data also can be assimilated into the ecosystem, with the underlying benefits in converging the two separate sets of data and information. AI in healthcare uses “fuzzy logic” to achieve many objectives, and methods already explored in this area are gaining momentum. Incorporating AI into healthcare management provides an opportunity for reliable, sustainable, responsible and scalable solutions for large populations while leveraging the latest technology, trends and upcoming advancements.
The use of health data and AI techniques have gained enough traction during the past few years that trust in the technology is increasing, with more organizations realizing the potential benefits and gains. This is advantageous because the more data that flow into AI solutions, the better AI becomes. That, in turn, may accelerate its adoption in healthcare management and ultimately provide timely, cost-effective, high-quality, equitable, safe, efficient, human-centric care that can improve population health outcomes globally.
AI has changed healthcare management in some organizations already by connecting machine learning algorithms and newer devices with sophisticated hardware and software, which produces a connected ecosystem. All the use cases, business processes and enhancements with data funneled into this ecosystem from devices, patient care, hospitals, family care facilities, laboratories, research institutions and pharmaceutical companies can drive drug research and development as well as operational efficiencies. By enabling AI-systems and applications in a data-driven context, AI can take healthcare management into new directions to ultimately make a significantly positive impact on the quintuple aim in healthcare.
Doreen Rosenstrauch, FACHE, MD, PhD, is founder and CEO, DrDoRo® Institute, Global Healthcare Consultancy and Advisory Services.
Utpal Mangla is general manager, Industry EDGE Cloud, IBM Cloud Platform.
Atul Gupta is lead data architect, Merative.
ACHE members: Read more about where artificial intelligence is working in healthcare in the September/October issue of Healthcare Executive.