Towards a Common Data Model: An Evaluation of Standardized Healthcare Reporting Data Models Restricted; Files Only

Nair, Shailesh (Spring 2018)

Permanent URL: https://etd.library.emory.edu/concern/etds/9z902z90g?locale=es
Published

Abstract

Abstract

Over the past two decades, we have witnessed the widespread adoption of Electronic Health Records (EHR) systems by hospitals and clinics to streamline, improve and enhance patient-centered care. Consequently, there is a heightened emphasis on coupling patient care with the reuse and synthesis of clinical and administrative data.

Data processing frameworks whether at information ingestion stage or during reporting and analytics are built on a data storage substrate. Data standardization is central to collaborative research data-sharing, health registry reporting, and the adoption of crowd-sourced solutions. These trends are disrupting the healthcare analytics landscape and spurring institutions to explore standardized data models.

This thesis evaluated two popular common data models (CDM) - Observational Medical Outcomes Partnership (OMOP) and the Patient-Centered Outcomes Network (PCORnet). The evaluation process consisted of identifying candidate standard data models, generating requirements criteria based on past trove of data requests received by Emory Library and Information Technology Services department, longitudinal health registry reporting and departmental data marts. These specifications informed the evaluation criteria formulated by the synthesis of established data model assessment frameworks in published literature - namely Moody and Shanks, which was further adapted by Kahn et al. and operationalized by Garza and colleagues.

The evaluation criteria of domain coverage, flexibility, use of controlled vocabularies, ease of querying, understandability, stability, adoption and community support found the OMOP CDM to be the data model of choice. The OMOP CDM supports the highest number of data domains, attributes and offers comprehensive coverage of standard terminologies.

Table of Contents

Introduction 5

What is a Data Model? 7

Rationale 11

Need for a Common Data Model (CDM) 13

Decision Support System (DSS) 15

Method 17

Evaluation Process 17

Candidate Common Data Models 21

OMOP CDM   22

Background 22

Introduction 22

OMOP Table Names and Description 25

PCORNet CDM   33

Background 33

Introduction 33

PCORnet Table Names and Description 35

Evaluation Criteria 40

Moody-Shanks Evaluation Model 42

Completeness 43

Simplicity 44

Flexibility 44

Understandability 45

Integration 46

Implementability 46

Results 48

Completeness - Domain and attribute coverage. 49

Integration 52

Flexibility 53

Simplicity - Ease/Complexity of Querying 54

Implementation - Field Experience, Stability, Adoption. 54

Discussion 58

Limitations 62

Conclusion 64

References: 65

About this Master's Thesis

Rights statement
  • Permission granted by the author to include this thesis or dissertation in this repository. All rights reserved by the author. Please contact the author for information regarding the reproduction and use of this thesis or dissertation.
School
Department
Subfield / Discipline
Degree
Submission
Language
  • English
Research field
Palabra Clave
Committee Chair / Thesis Advisor
Committee Members
Última modificación No preview

Primary PDF

Supplemental Files