Date of Award

5-18-2023

Document Type

Dissertation

Degree Name

Doctor of Philosophy (PhD)

Department

Information Science

First Advisor

Daniel Berhleant

Abstract

As we progress towards the fourth industrial revolution, where emerging technologies such as artificial intelligence, machine learning, and the Internet of Things (IoT) are becoming more dominant, the quality of data becomes even more crucial. These technologies rely immensely on data to generate insights and make accurate predictions. Poor quality data can lead to incorrect or incomplete insights, resulting in erroneous decision-making that can have significant consequences. It is essential that data quality is addressed early in the development of these technologies to ensure that they operate successfully and provide accurate insights that can lead to positive outcomes. As such, data quality should be a priority for organizations that are looking to leverage these emerging technologies to gain a competitive advantage in their respective industries. Data holds an integral role in healthcare. Doctors and healthcare professionals rely heavily on data to make decisions on patient care thus making data quality imperative. Managed care institutions who administer health plans also rely heavily on data quality to coordinate benefits and care. The disparate sources of data these institutions receive make it difficult to manage quality. In the managed care model, preventative treatment is highly emphasized thus needing data to inform these decisions. As a result, data quality is a major factor in how managed care institutions dictate patient outcomes. However, there are gaps in the understanding on the importance of data quality in managed care within its leadership. Leadership in managed care often have different tasks or priorities which lead to data quality being deprioritized. The lack of internal coordination in managed care often leads to silos. Leadership is not aware of other department’s data platforms or its management. There are also misunderstandings on who owns the data and how it is being used. The information technology department is often mistakenly thought to be the managing and administering the data. Sadly, without its correct owners who understand the background of the data, the information technology department is at a standstill on what to do with its data sources. Leadership who is responsible for setting priorities should lead the direction of proper data management principles. This study was aimed at understanding if leadership in managed care organizations understood the importance of data quality and prioritized it. The study results will guide the formation of an information quality guideline for managed care. Leadership’s input is crucial to developing such a plan. Interviews with leaders will help inform on whether data quality is prioritized and how guidelines can be established. The guidelines will detail how managed care institutions can govern their data sources with the partnership of the business and the information technology department.

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