Practice, Protocols and Innovation of Public Health Decision Support Systems that Advance Automated Disease Reporting Öffentlichkeit

Abrams, Denisha N. (2016)

Permanent URL: https://etd.library.emory.edu/concern/etds/xk81jk49s?locale=de
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Abstract

Public health reporting is the cornerstone of disease surveillance and is a "requisite for managing disease burden in a community". In the United States, selected diseases and conditions must be reported to public health authorities by physicians, hospitals, laboratories and other reporters to control disease and outbreaks. The current process of disease reporting is a manual process, prone to human error and lack of knowledge of what is reportable. Each jurisdiction determines the "who, what, when, where and how" of disease reporting, which is resource-intensive and scattered across documents and websites. The specifications associated with reportable events also vary by condition, which contributes to the complexity and management of changes that occur in reporting guidelines or clinical terminology standards. There is a need for national collaboration that looks towards interoperable standards and system development that can move disease reporting beyond its current state. Standard terminologies such as Logical Observation Identifiers Names and Codes (LOINC®) provide a building block to the data exchange between clinical care and public health. The development of public health decision systems that support automated disease reporting has some notable early adopters. The population of study includes three systems: Massachusetts Department of Health (MDPH) - Electronic Support for Public Health (ESP); Regenstrief Institute - Notifiable Condition Detector (NCD); and the Council of State and Territorial Epidemiologists (CSTE) - Reportable Conditions Knowledge Management System (RCKMS). The purpose of this research is to examine the practice of two locally developed public health decision support systems and compare their development protocols to a national prototype. A content analysis of the existing models will inform national efforts of how these systems work and the innovation behind their development. The reusability of what currently works shows that progress has been made but the associated gaps between local implementations and a national platform to automate disease reporting reveals a journey fraught with barriers to widespread adoption.

Table of Contents

1 INTRODUCTION 5

1.1 INTRODUCTION AND RATIONALE 5

1.2 PROBLEM STATEMENT 6

1.3 PURPOSE STATEMENT 8

1.4 RESEARCH OBJECTIVES 9

1.5 SIGNIFICANCE STATEMENT 9

1.6 DEFINITION OF TERMS 9

2 LITERATURE REVIEW 10

2.1 INTRODUCTION 10

2.1.1 Electronic Health Record/Laboratory Information Systems 14

2.1.2 Data Standards 15

2.1.3 Software Architecture and Message Standards 16

2.2 SUMMARY OF THE CURRENT PROBLEM 17

3 METHODS 18

3.1 INTRODUCTION 18

3.2 POPULATION 18

3.3 RESEARCH DESIGN 19

3.4 PLANS FOR DATA ANALYSIS 20

3.5 LIMITATIONS AND DELIMINATIONS 21

4 RESULTS 21

4.1 INTRODUCTION 21

4.2 FINDINGS 21

4.2.1 Content Comparison 21

4.2.2 Architecture and Technical Framework Comparison 23

4.2.3 Process Flow and Functional Capabilities Comparison 26

4.3 SUMMARY 30

5 DISCUSSION 31

5.1 INTRODUCTION 31

5.2 SUMMARY OF STUDY 31

5.3 CONCLUSION 32

5.4 IMPLICATIONS 33

5.5 RECOMMENDATIONS 33

REFERENCES 34

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