Interest and investment in healthcare AI/ML tools is booming with approximately $4B in capital funding pouring into this healthcare sector in 2019. Such investment is spurring a vast array of AI/ML tools for providers, patients, and payers accelerating the possibilities for new solutions to improve diagnostic accuracy, improve feedback mechanisms, and reduce clinical and administrative errors, according to Chilmark Research’s last report.
The Promise of AI & ML in Healthcare Report Background
The report, The Promise of AI & ML in Healthcare, is the most comprehensive report published on this rapidly evolving market with nearly 120 vendors profiled. The report explores opportunities, trends, and the rapidly evolving landscape for vendors, tracing the evolution from early AI/ML use in medical imaging to today’s rich array of vendor solutions in medical imaging, business operations, clinical decision support, research and drug development, patient-facing applications, and more. The report also reviews types and applications of AI/ML, explores the substantial challenges of health data collection and use, and considers issues of bias in algorithms, ethical and governance considerations, cybersecurity, and broader implications for business.
Health IT vendors, new start-up ventures, providers, payers, and pharma firms now offer (or are developing) a wide range of solutions for an equally wide range of industry challenges. Our extensive research for this report found that nearly 120 companies now offer AI-based healthcare solutions in four main categories: hospital operations, clinical support, research and drug development, and patient/consumer engagement.
Report Key Themes
This report features an overview of these major areas of AI/ML use in healthcare. Solutions for hospital operations include tools for revenue cycle management, applications to detect fraud detection and ensure payment integrity, administrative and supply chain applications to improve hospital operations, and algorithms to boost patient safety. Population health management is an area ripe in AI/ML innovation, with predictive analytics solutions devoted to risk stratification, care management, and patient engagement.
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A significant development is underway in AI/ML solutions for clinical decision support, including NLP- and voice-enabled clinical documentation applications, sophisticated AI-based medical imaging and pathology tools, and electronic health records management tools to mitigate provider burnout. AI/ML-enabled tools are optimizing research and drug development by improving clinical trials and patient monitoring, modeling drug simulations, and enabling precision medicine advancement. A wealth of consumer-facing AI/ML applications, such as chatbots, wearables, and symptom checkers, are available and in development.
Provider organizations will find this report offers deep insight into current and forthcoming solutions that can help support business operations, population health management, and clinical decision support. Current and prospective vendors of AI/ML solutions and their investors will find this report’s overview of the current market valuable in mapping their own product strategy. Researchers and drug developers will benefit from the discussion of current AI/ML applications and future possibilities in precision medicine, clinical trials, drug discovery, and basic research. Providers and patient advocates will gain valuable insight into patient-facing tools currently available and in development.
All stakeholders in healthcare technology—providers, payers, pharmaceutical stakeholders, consultants, investors, patient advocates, and government representatives—will benefit from a thorough overview of current offerings as well as thoughtful discussions of bias in data collection and underlying algorithms, cyber-security, governance, and ethical concerns.
Source: HIT Consultant
