Health Analytics and Artificial Intelligence Insights
Learn how artificial intelligence and analytics are reshaping healthcare
Artificial intelligence (AI) technologies, as they’re developed and adapted for an ever-growing variety of specialized uses, hold the promise to help reshape all sectors of society, including healthcare and life science.
The changes that AI will usher into healthcare are already underway. According to an article in the Yale Journal of Health Policy, Law, and Ethics, AI’s in-progress transformation of healthcare delivery can be categorized into at least four major areas:
Pushing frontiers of medical knowledge
AI is being used to predict patient outcomes at high rates of accuracy, enabling clinicians to be more proactive in treating patients and mitigating further risk of disease progression. For example, AI may be used to better predict factors such as suicide risk, the likelihood of re-hospitalization, or the adverse effects of medication on a particular population.
Replicating and democratizing medical expertise
AI can be used to supplement provider expertise. For example, some AI programs are using images of the human eye to provide information that otherwise would require an ophthalmologist. Using AI image analysis, a general practitioner or other non-specialist can diagnose after interpreting the results.
Automating drudgery within the medical system
Providers spend much of their time documenting results in electronic medical records, reading screens, and recording real-time information during patient visits. Using AI to automate these tasks can greatly reduce their administrative burden.
Allocating scarce medical resources
AI can be used to manage resources. For example, AI can predict which hospital departments may need additional staffing, suggest which patients might benefit the most from additional medical resources, or identify ways to maximize hospitals’ operational revenues.
Booz Allen is fully committed to helping our healthcare and life science clients realize AI’s potential to transform medicine while avoiding all-to-common pitfalls such as algorithmic bias or online privacy breaches. Our clinicians, scientists, and bioinformaticians work hand in hand with our analytics and AI experts across health and other industries to share best practices and inspire specialized innovation.
We know you’re wondering how healthcare and life science can better take advantage of all that AI has to offer. The insights below will shed some light on how we can tackle the future, together.
Artificial Intelligence
Artificial Intelligence Bias in Healthcare
In the first post of a three-part blog series on algorithmic bias in healthcare AI, Wendy Watson and Christina Marsh discuss the benefits and risks of using AI in healthcare and the impacts of human bias on AI data and algorithms.
Identifying Bias in Hospital Length of Stay Algorithm
In this second installment of a 3-part blog series on algorithm bias in healthcare AI, our experts present a case study of how to prevent algorithmic bias at the University of Chicago Medicine.
How to Mitigate Bias in Healthcare Algorithms
In the third installment of a 3-part blog series on algorithm bias in healthcare AI, our experts discuss how AI and machine learning will increasingly play a role in patient care.
Connected Health in the Digital Age
This blog provides an overview of Dr. Kevin Vigilante and Dr. Mohsin Khan's article, "Connected Access: Titrating the Right Dose of Access in the Digital Age," in the October 2019 edition of Journal of Ambulatory Care Management. Subscribers can access the full article through the Journal's website.
Artificial Intelligence in Healthcare - Lessons from the Intelligence Community
Healthcare organizations and the intelligence community face similar challenges when it comes to drawing actionable plans from raw data. Watch Dr. Kevin Vigilante, Catherine Ordun, and Joachim Roski discuss how the use of AI can be applied to solve some of their common issues.
Big Data and the Intelligence Community - Lessons for Healthcare
As discussed in the May 2019 New England Journal of Medicine “Big Data and the Intelligence Community – Lessons for Healthcare," Dr. Kevin Vigilante, Steve Escaravage, and Mike McConnell describe what the intelligence community can teach the healthcare industry about big data and AI. Subscribers can access the full article through the New England Journal of Medicine website.
Data Science
Harnessing Big Data for Precision Medicine - Part 1
As the first in a five-part series, Dr. Kevin Vigilante discusses how Booz Allen can help make it possible to integrate a virtually unlimited amount of precision medicine data—and put it directly into the hands of researchers and other users.
Harnessing Big Data for Precision Medicine - Part 2
This is the second installment of a five-part series on using big data for precision medicine. Dr. Kevin Vigilante proposes applying lessons from the intelligence community to precision medicine.
Harnessing Big Data for Precision Medicine - Part 3
In part three of a five-part series, Dr. Kevin Vigilante discusses the paradigm shift of a data lake. As data is no longer locked in siloed databases but rather consolidated into data lakes, cloud computing is now required to effectively use data.
Harnessing Big Data for Precision Medicine - Part 4
In part four of a five-part series, Dr. Kevin Vigilante reminds readers to let data speak for itself. Advanced analytics and tagging allow data to self-identify hidden patterns and connections in medicine.
Harnessing Big Data for Precision Medicine - Part 5
In the final installment of a five-part series, we explain how Booz Allen's approach to big data and analytics visualizations allow people who are not computer experts to explore and analyze data, without an intermediary.
In the News
AI Success in Federal Health Agencies Starts with Effective Data Management
Published in Federal Computer Week, Dr. Joachim Roski and Catherine Ordun explain how important effective AI use is in the midst of COVID-19 and how federal health agencies can learn AI data management lessons from the defense and intelligence sectors.
For Federal Healthcare Agencies, a Case for Better AI Outcomes
Published in Government Executive, Catherine Ordun warns officials that as they increasingly turn to algorithms for assistance, they should be wary of tools that make harnessing artificial intelligence look easy.
Artificial Intelligence in Healthcare: the Hope, the Hype, the Promise, the Peril
In a special publication from the National Academy of Medicine, Dr. Joachim Roski led a team of colleagues to author Chapter 3, where they share insights regarding AI solutions and their role in healthcare.
Four Lessons in the Adoption of Machine Learning in Healthcare
Published in Health Affairs, our Booz Allen experts Joachim Roski, Steve Escaravage, and Ernest Sohn share four key lessons about how to generate value from electronic health records and machine learning applications.
Blockchain as a Foundation for Sharing Healthcare Data
Published in Blockchain in Healthcare Today, Marek Cyan presents how blockchain technology has the potential to transform healthcare delivery through the facilitation of data sharing among providers and electronic health records.
Implementing and Scaling Artificial Intelligence Solutions: Considerations for Policy Makers and Decision Makers
Published in Health Affairs, Dr. Joachim Roski and Ernest Sohn discuss how healthcare organizations can quickly scale up responsible implementation of AI solutions to improve health and reduce inefficiencies.
