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Northeastern University

Engaging in Improving Patient Experience Through Analytics

Northeastern University via Coursera


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This course is best suited for individuals currently in the healthcare sector, as a provider, payer, or administrator. Individuals pursuing a career change to the healthcare sector may also be interested in this course. This is the second part in a two-part course exploring concepts and topics related to improving the patient experience and reducing pain points in healthcare processes through analytic and decision support frameworks. In this course, you will survey the kind of data that is used to make effective decision support choices, following up with information on how to use the data to predict outcomes. Throughout this course, you will be given the opportunity to apply the course concepts to operational improvements in your own organization.


  • Predicting Outcomes
    • In this module, we'll be looking at experience oriented predictions and some of the different methods and techniques we can bring to bear when building them. We'll examine making predictions for individual patient outcomes, for example: how likely they are to have preventable complications, non-compliance with medication regimens or how likely they are to be satisfied with their provider. We'll take a deeper dive into the CAHPS survey, a common method for evaluating consumer satisfaction with their health plan and provider.
  • Whole Picture Recommendations
    • Now that we have reviewed making predictions in the previous module, we'll explore making recommendations based on these predictions. We'll start by looking at opportunities for outreach and intervention with individual patients. Then we'll examine the prevalent outreach strategies in the industry. Next, we'll examine different ways of allocating campaign resources. We'll then explore the methods and techniques that are needed in order to optimize outreach campaigns.
  • Operational Considerations
    • In this module, we'll focus on operational considerations that are vital if your decision support innovation is to be deployed successfully. We'll start by touching on using data and visualization to support investment in outreach and intervention campaigns. Then we'll examine the considerations you will need to take when embedding a decision support innovation into existing workflows and technology ecosystems. By the end of this module, you will have a solid grasp on issues and challenges you may face when trying to operationalize your experience management decision support.
  • Business Case Considerations
    • In this final module, we'll focus on making the business case for your experience management decision support. We'll explore the impact for three major focus areas: stakeholder impact, cross-cutting areas of impact and financial impact. We'll also delve into changes that may impact the providers such as workflow, compensation, trust and satisfaction. We'll consider potential impact to the organization such as staffing and responsibility changes. By the end of the module, you will have a holistic picture of the areas impact of a decision support when integrated into existing systems.

Taught by

Craig Johnson


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