Description: This session will examine bias from a social science perspective. It will discuss the three types of systemic biases using the National Institute of Standards and Technology (NIST) model. The NIST model details the three types as historical bias, societal bias, and institutionalbias. The session will also provide several examples of each type to provide a framework for identifying the social structure of bias.

Description: "Examine the exciting possibilities for artificial intelligence (AI) in health care and its potential to transform the patient journey. You will learn about the various touchpoints where AI is being applied along the patient/care journey, including provider search tools, claims analysis, and fraud detection. By attending the session, you will be able to: Have a comprehensive understanding of the opportunities and challenges presented by AI in health care Evaluate the potential impact of AI on their own organizations Be equipped with strategies for effectively implementing AI solutions and maximizing their benefits for patients, providers, and payers"

Description: This presentation will explore innovative approaches to high performance networks (HPN). The session will compare the more traditional narrow network solutions offered by national carriers vs. different models established by newer vendors that focus on a different value proposition and/or does not involve narrowing the network at all.

Description: This session will cover the current and potential use of artificial intelligence (AI) in the health care space. Participate in this interactive session and learn how AI is being used today and discuss its potential to reshape and revolutionize health care. You will get an opportunity to learn how AI can influence patient experience in every phase of healthcare delivery and talk about the challenges and limitations that arise with the use of this technology.

Description: This study would assess the impact of recent patient care innovation(s) on health care and the health insurance industry.

Description: Gather with members and non-members in the China actuarial community to discuss recent topics and related issues in areas such as macroeconomic sharing, pension, investment, product strategy, and more.

Description: Get up to date on the current and potential use of artificial intelligence (AI) in the health care space. In this interactive session, you will learn how AI is being used today and discover its potential to reshape and revolutionize health care. Take advantage of the opportunity to find out how AI can influence patient experience in every phase of health care delivery, and join the conversation about the challenges and limitations that arise with the use of this technology.

Description: Learn more about interpretable machine learning techniques for health insurance fraud detection.

Description: ReMark's Global Consumer Study delivers 10 key insights to empower customers. Insurers can design products that meet customers' needs and enhance client experiences and add significant value to their business. At the same time with new products being launched seemingly continuously, it is important to take a step back and assess risk throughout the product management cycle.

Description: The supplemental health market is changing. Carriers are looking to simplify claims processes, proactively identify missed claim opportunities, and reduce barriers to claim payment. As a result, more and more companies are looking at ways to use data from medical diagnostic and treatment codes. Take an introductory look at the most used medical codes—ICD (9 and 10), CPT, and HCPCS. Discuss the history and purpose of each code system and decipher the structure. Dive into how medical codes can be used in the supplemental health market (automatic claims adjudication, fraud identification, pricing), as well as common pitfalls encountered when using medical coding. By attending this session, you will have a basic understanding of the different types of medical codes, their actuarial applications, and common pitfalls.