Date of Award

January 2015

Document Type

Open Access Thesis

Degree Name

Doctor of Nursing Practice (DNP)

Department

Yale University School of Nursing

First Advisor

Allison Shorten

Second Advisor

Jessica Coviello

Abstract

The goal of evidence based population health aligned with financial outcomes is to effectively and efficiently manage a defined population to promote wellness, prevent disease progression and manage chronic conditions and acute events. A prerequisite to this model, which is in its early stages of evolution, is an electronic trace of patient information across continuum of care (COC) providers spanning hospitals, physician offices, home health programs, skilled nursing facilities, retailers, payers and new entrants. The information captured along the information trace can be mined from a data repository to analyze cohort specific evidence based care models. A newly formed, large academic employee Accountable Care Organization (ACO) designed and implemented a chronic care program, beginning with a diabetes cohort pilot. An innovative Electronic Medical Record (EMR) prioritization tool was designed according to Design for Six Sigma principles to scope data element additions to the EMR related to weighted outcome measures such as readmission, complications, ED visit reductions and presenteeism at work. Sixteen diabetes care area data categories were prioritized to include compliance, symptoms, diabetes specific risk factors and relationship to biometric indicators. The original prioritization tool and process was further validated via a survey of national experts and a literature evaluation conducted by an expert diabetes physician. Ten of the top eleven prioritized diabetes care areas were consistent between the baseline and survey group. The literature evaluation provided additional research, further substantiating the EMR prioritization data categories

The prioritization tool and validation process can be replicated by experienced clinicians and applied to additional chronic conditions. This may be valuable for the prioritization of additional EMR metrics that are relevant to care, business and clinical attributes. Most importantly its application to real time EMR based evidence based population health will benefit populations of patients.

Comments

This is an Open Access Thesis.

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