The future of healthcare is becoming dependent on our ability to integrate Machine Learning and Artificial Intelligence into our organizations. But it is not enough to recognize the opportunities of AI; we as leaders in the healthcare industry have to first determine the best use for these applications ensuring that we focus our investment on solving problems that impact the bottom line.
Throughout these four modules we will examine the use of decision support, journey mapping, predictive analytics, and embedding Machine Learning and Artificial Intelligence into the healthcare industry. By the end of this course you will be able to:
1. Determine the factors involved in decision support that can improve business performance across the provider/payer ecosystem.
2. Identify opportunities for business applications in healthcare by applying journey mapping and pain point analysis in a real world context.
3. Identify differences in methods and techniques in order to appropriately apply to pain points using case studies.
4. Critically assess the opportunities to leverage decision support in adapting to trends in the industry.
Этот курс входит в специализацию ''Специализация Healthcare Trends for Business Professionals'
Business Application of Machine Learning and Artificial Intelligence in Healthcare
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Об этом курсе
Чему вы научитесь
Determine the factors involved in decision support that can improve business performance across the provider/payer ecosystem
Identify opportunities for business applications in healthcare by applying journey mapping and pain point analysis in a real world context
Identify differences in methods and techniques in order to appropriately apply to pain points using case studies
Critically assess the opportunities to leverage decision support in adapting to trends in the industry
Программа курса: что вы изучите
Неделя
1Decision Support and Use Cases
Rapid changes in technology are impacting every facet of modern society, and the healthcare industry is no exception. Navigating these changes is crucial, whether you are currently working in the industry, hoping to step into a new role, or are simply interested in how technology is being used in healthcare. No doubt you have heard the terms, “machine learning” and “artificial intelligence” more frequently in the last few years - but what does this mean for you, or the healthcare industry in general? Keeping up with the changing trends, examining the potential use of decision support, and identifying some of the pain points that can be addressed, are some of the topics we’ll be discussing in this Module.
15 видео ((всего 106 мин.)), 4 материалов для самостоятельного изучения, 6 тестов
15 видео
Course Overview2мин
Introduction to Module 159
Consumerism, Supply Chain and Social & Situational Determinants2мин
Operationalizing Consumerism Using ML and AI1мин
Interview with Caitlyn19мин
Operationalizing a New Supply Chain1мин
Interview with Peter Dunphy15мин
Machine Learning, Artificial Intelligence, and Decision Support6мин
Journey Mapping and Pain Points6мин
Patient Monitoring4мин
Interview with Cait Larson from Dynamicare19мин
Differential Diagnosis6мин
Care Management4мин
Preventive Screening6мин
Avoidable Readmissions6мин
4 материала для самостоятельного изучения
Healthcare Ecosystem Readings10мин
Healthcare Consumer Journey Mapping10мин
TED Talk on an innovation in Remote Patient Monitoring10мин
Innovations and Results in Patient Outreach10мин
6 практического упражнения
Check Your Knowledge3мин
Check Your Knowledge1мин
Check Your Knowledge6мин
Check Your Knowledge3мин
Check Your Knowledge4мин
Module 1 (Graded)30мин
Неделя
2Predictive Modeling Basics
Let’s navigate through what it takes to predict health outcomes and cost. What if we could use machine learning in your organization to reduce the cost of care for both the organization and the members receiving that care? Have you thought about what data you need to collect? How you might need to enrich that data to gain more insight in to what is driving those outcomes and cost? Or what types of machine learning algorithms you might utilize in order to most effectively target patients who are likely to be high cost? We are going to look at not only the tech behind the predictions, but also examine the business and data relationships within the healthcare industry that ultimately impact your ability to deliver an effective solution.
9 видео ((всего 47 мин.)), 2 материалов для самостоятельного изучения, 6 тестов
9 видео
Predictive Modeling6мин
Linear Regression5мин
Disease Burden as a Predictor of Cost5мин
Machine Learning6мин
Data Sourcing5мин
Data Enrichment5мин
Provider Taxonomies and Relationships5мин
Predictive Modeling Process6мин
2 материала для самостоятельного изучения
Linear Regression Explained5мин
Using AI to Diagnose Disease5мин
5 практического упражнения
Check Your Knowledge2мин
Check Your Knowledge2мин
Check Your Knowledge8мин
Check Your Knowledge6мин
Check Your Knowledge6мин
Неделя
3Consumerism and Operationalization
Now that we have discussed various types of predictive models, let’s take a look at which models are appropriate for the business case we are trying to address and how we can evaluate their performance. For example, is using the same performance metric appropriate to use when making predictions about individual vs. population health? In this module we'll discuss how layering appropriate decision support methods on top of predictive analytics and machine learning can lay the groundwork for significant improvements in overall outreach and productivity, as well as decrease costs. Finally, we will discuss the key to blending decision support into the existing ecosystem of your business workflow and technology infrastructure.
9 видео ((всего 53 мин.)), 1 материал для самостоятельного изучения, 6 тестов
9 видео
Analytic Maturity Model5мин
Identifying Historic Addressable Opportunity5мин
Predicting Addressable Opportunity8мин
Measuring Predictive Accuracy9мин
Making Recommendations5мин
Voices from the Industry with George "Russ" Moran7мин
Integration and Orchestration4мин
Operational Engagement Framework6мин
1 материал для самостоятельного изучения
The Future of Predictive Analytics in Healthcare15мин
6 практического упражнения
Check Your Knowledge4мин
Check Your Knowledge4мин
Check Your Knowledge4мин
Check Your Knowledge4мин
Check Your Knowledge4мин
Module 3 (Graded)30мин
Неделя
4Advanced Topics in Operationalization
Now that we know the importance of decision support and predictive modeling, we are going to take that one step further. Not only do we need to predict, but more importantly, we need to prescribe. It is not enough to just implement alerts and reminders - we need to offer guidance and recommendations for healthcare professionals. Let’s take a look at how analytics can improve the patient experience and their overall health status.
9 видео ((всего 65 мин.)), 2 материалов для самостоятельного изучения, 5 тестов
9 видео
Operational Entity Relationship Model7мин
Using Other Administrative Data to Target Avoidable Utilization8мин
Targeting High Value Member Patients Using Consumer Data5мин
Recommending a Program for Care Management7мин
Recommending a Channel for Member Engagement6мин
Interview with Peter Dunphy from Perfect Health15мин
Embedding Decision Support with your Existing Technology Footprint6мин
Deploying Decision Support Beyond the Enterprise to the Consumer6мин
2 материала для самостоятельного изучения
Utilizing Consumer Data10мин
Misconceptions in the Industry10мин
4 практического упражнения
Check Your Knowledge6мин
Check Your Knowledge4мин
Check Your Knowledge6мин
Check Your Knowledge2мин
Преподаватель
Craig Johnson
Part-time Lecturer, Chief Science Officer at Decision Point Health SolutionsCollege of Computer and Information Science
О Northeastern University
Founded in 1898, Northeastern is a global research university with a distinctive, experience-driven approach to education and discovery. The university is a leader in experiential learning, powered by the world’s most far-reaching cooperative education program. The spirit of collaboration guides a use-inspired research enterprise focused on solving global challenges in health, security, and sustainability.
О специализации ''Healthcare Trends for Business Professionals'
This Specialization will provide learners with the knowledge and skills to recognize key shifts in the industry and to have an agile perspective on how these shifts might impact their organizations. Learners will be exposed to the key drivers in the global healthcare industry today so they might apply what they have learned to help their organizations.
Часто задаваемые вопросы
When will I have access to the lectures and assignments?
Once you enroll for a Certificate, you’ll have access to all videos, quizzes, and programming assignments (if applicable). Peer review assignments can only be submitted and reviewed once your session has begun. If you choose to explore the course without purchasing, you may not be able to access certain assignments.
What will I get if I subscribe to this Specialization?
When you enroll in the course, you get access to all of the courses in the Specialization, and you earn a certificate when you complete the work. Your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile. If you only want to read and view the course content, you can audit the course for free.
What is the refund policy?
Is financial aid available?
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