Abstract

An evolution in healthcare is taking place throughout our country. Healthcare providers are required to achieve an ever-growing number of regulatory and metric-driven standards. This transformation aims to improve both the quality and cost of healthcare in the United States. Diabetes mellitus (DM) is one of the most costly chronic diseases in the United States. Since DM has high mortality, high morbidity, and low quality of life rates, it is no wonder that DM is one of the focuses of the National Committee for Quality Assurance performance improvement tools known as the Healthcare Effectiveness Data and Information Set (HEDIS). In addition, the HEDIS set of metrics is increasingly being used to judge the quality of healthcare providers and health systems, as well as link this performance to reimbursement. For healthcare providers to remain financially viable, they need to score well on these metrics. The aim of this study was to identify which common quantitative laboratory data elements in the Cerner Health Facts database correlate to poorly controlled glycosylated hemoglobin (HbA1c) levels in adult patients with DM that could be used in the future to create a mathematical model to predict which patients may have poorly controlled HbA1c levels.

Project Sponsors

Dr. Angelia Delucas

Language

English

Document Type

Scholarly Project

Degree Name

Doctor of Nursing Practice (DNP)

Level of Degree

Doctoral

First Advisor

Dr. Angelia Delucas

Second Advisor

Dr. Melissa Cole

First Committee Member

Dr. Angelia Delucas

Second Committee Member

Dr. Melissa Cole

Keywords

A1c, predict, diabetes, EMR, lab values, administrative data

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