Use of data and analytics in health care is growing in popularity, but due to conflicting priorities and some lack of experience in this area, many organizations have not yet been able to implement analytics programs. In this workshop, understand the necessary steps to get started.

• Assess the needs of the organization and determine the business objectives for implementing predictive analytics programs
• Discuss strategies for implementing a predictive analytics program for a health care organization with or without a dedicated analytics team
• Explore the advantages and disadvantages of building a system in-house versus working with outside vendors
• Uncover data governance strategies to manage information within the organization

Most health care organizations have pockets of analytical expertise, while some have made analytics a core part of their strategy and operations. In this discussion, we cover why predictive analytics is important in health care, review examples of predictive analytics applications on the plan and provider side, and discuss how we see predictive analytics evolving over the next few years.

Efforts to collect and analyze data will be useless if the information is not used in everyday decisions around managing patients and members. Encouraging employees to utilize this data in a productive way goes beyond changing processes; the culture of the organization must shift to a culture of data-driven decisions.

• Understand employees’ hesitation to change the workflow and find ways to create enthusiasm around the new method of decision making
• Develop strategies for change management to transition employees to use data as a basis for making decisions

Discussion of data and analytics in health care is often focused around what can be done with the data at hand. However, before discussing how to use data, you need to be clear about what data is available and valuable.

• Understand the need to include multiple data sets to yield the best results
• Explore the possibilities for incorporating data beyond that of hospitals and insurers, including pharmaceutical data and community data
• Discover technologies that successfully integrate structured and unstructured data into one data set
• Explore how health systems and health plans can gain insights from social media postings by natural language processing

By leveraging the “true” power of analytics, companies are able to predict customer complaints before they occur, thereby improving customer satisfaction and reducing service costs.

• Use the power of analytics to run detailed analysis on both qualitative and quantitative data
• Replace call log analysis with call transcript analysis to improve call center performance
• Transition analytics from a reporting tool to a forecasting and business decision support tool
• Reduce call center operational costs by optimizing service channels
• Improve the impact of promotions and marketing efforts