Über diesen Kurs
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Stufe „Mittel“

Ca. 11 Stunden zum Abschließen

Empfohlen: 5 hours/week...

Englisch

Untertitel: Englisch

Was Sie lernen werden

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    Determine the factors involved in decision support that can improve business performance across the provider/payer ecosystem

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    Identify opportunities for business applications in healthcare by applying journey mapping and pain point analysis in a real world context

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    Identify differences in methods and techniques in order to appropriately apply to pain points using case studies

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    Critically assess the opportunities to leverage decision support in adapting to trends in the industry

100 % online

Beginnen Sie sofort und lernen Sie in Ihrem eigenen Tempo.

Flexible Fristen

Setzen Sie Fristen gemäß Ihrem Zeitplan zurück.

Stufe „Mittel“

Ca. 11 Stunden zum Abschließen

Empfohlen: 5 hours/week...

Englisch

Untertitel: Englisch

Lehrplan - Was Sie in diesem Kurs lernen werden

Woche
1
3 Stunden zum Abschließen

Decision 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.

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15 Videos (Gesamt 106 min), 4 Lektüren, 6 Quiz
15 Videos
Introduction to Module 159
Consumerism, Supply Chain and Social & Situational Determinants2m
Operationalizing Consumerism Using ML and AI1m
Interview with Caitlyn19m
Operationalizing a New Supply Chain1m
Interview with Peter Dunphy15m
Machine Learning, Artificial Intelligence, and Decision Support6m
Journey Mapping and Pain Points6m
Patient Monitoring4m
Interview with Cait Larson from Dynamicare19m
Differential Diagnosis6m
Care Management4m
Preventive Screening6m
Avoidable Readmissions6m
4 Lektüren
Healthcare Ecosystem Readings10m
Healthcare Consumer Journey Mapping10m
TED Talk on an innovation in Remote Patient Monitoring10m
Innovations and Results in Patient Outreach10m
6 praktische Übungen
Check Your Knowledge3m
Check Your Knowledge1m
Check Your Knowledge6m
Check Your Knowledge3m
Check Your Knowledge4m
Module 1 (Graded)30m
Woche
2
3 Stunden zum Abschließen

Predictive 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.

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9 Videos (Gesamt 47 min), 2 Lektüren, 6 Quiz
9 Videos
Predictive Modeling6m
Linear Regression5m
Disease Burden as a Predictor of Cost5m
Machine Learning6m
Data Sourcing5m
Data Enrichment5m
Provider Taxonomies and Relationships5m
Predictive Modeling Process6m
2 Lektüren
Linear Regression Explained5m
Using AI to Diagnose Disease5m
5 praktische Übungen
Check Your Knowledge2m
Check Your Knowledge2m
Check Your Knowledge8m
Check Your Knowledge6m
Check Your Knowledge6m
Woche
3
2 Stunden zum Abschließen

Consumerism 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.

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9 Videos (Gesamt 53 min), 1 Lektüre, 6 Quiz
9 Videos
Analytic Maturity Model5m
Identifying Historic Addressable Opportunity5m
Predicting Addressable Opportunity8m
Measuring Predictive Accuracy9m
Making Recommendations5m
Voices from the Industry with George "Russ" Moran7m
Integration and Orchestration4m
Operational Engagement Framework6m
1 Lektüre
The Future of Predictive Analytics in Healthcare15m
6 praktische Übungen
Check Your Knowledge4m
Check Your Knowledge4m
Check Your Knowledge4m
Check Your Knowledge4m
Check Your Knowledge4m
Module 3 (Graded)30m
Woche
4
4 Stunden zum Abschließen

Advanced 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.

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9 Videos (Gesamt 65 min), 2 Lektüren, 5 Quiz
9 Videos
Operational Entity Relationship Model7m
Using Other Administrative Data to Target Avoidable Utilization8m
Targeting High Value Member Patients Using Consumer Data5m
Recommending a Program for Care Management7m
Recommending a Channel for Member Engagement6m
Interview with Peter Dunphy from Perfect Health15m
Embedding Decision Support with your Existing Technology Footprint6m
Deploying Decision Support Beyond the Enterprise to the Consumer6m
2 Lektüren
Utilizing Consumer Data10m
Misconceptions in the Industry10m
4 praktische Übungen
Check Your Knowledge6m
Check Your Knowledge4m
Check Your Knowledge6m
Check Your Knowledge2m

Dozent

Avatar

Craig Johnson

Part-time Lecturer, Chief Science Officer at Decision Point Health Solutions
College of Computer and Information Science

Über 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....

Über die Spezialisierung 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....
Healthcare Trends for Business Professionals

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