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TB Notes Newsletter

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No. 3, 2013

Hot Off the Press! Quality Assurance for Tuberculosis Surveillance Data: A Guide and Toolkit – 2013

Quality Assurance for Tuberculosis Surveillance Data: A Guide and Toolkit, 2013

Background

Quality assurance (QA) is a critical part of any successful surveillance system. QA is a continuous cycle of monitoring, evaluating, and improving data quality.

The National Tuberculosis Surveillance System (NTSS), located in the Division of Tuberculosis Elimination (DTBE), CDC, is the national repository of tuberculosis (TB) disease surveillance data in the United States. CDC receives data on TB cases from reporting jurisdictions through a standardized data collection form, the Report of Verified Case of Tuberculosis (RVCT).

The RVCT is revised periodically as the epidemiology of TB in the United States changes. The most recent revision was implemented in 2009. As part of that revision, data collection and reporting transitioned into web-based systems. An interdisciplinary DTBE team collaborated with key national partners, state public health officials, and other local healthcare professionals to develop and launch a national training program on the new RVCT. As a logical follow-up to the RVCT trainings, the DTBE staff began working individually with state public health partners to develop the QA guide and toolkit.

DTBE wants to ensure that data are collected as uniformly as possible across all jurisdictions, whether large or small. The RVCT QA training team, in collaboration with key partners, developed the QA guide and toolkit to provide standardized methodologies, skill development, and tools to enhance the capacity for QA. The team used the systematic health education approach to develop training materials: this included needs assessment, development, pilot testing, implementation, and outcome evaluation.

How to Access the Materials

A limited number of copies of the QA Guide and Toolkit have been printed. Each reporting jurisdiction will receive at least one hard copy with a CD that includes the toolkit.

To view or download the "Quality Assurance for Tuberculosis Surveillance Data: A Guide and Toolkit," please visit the CDC website or the RVCT ftp site listed below.


Quality Assurance Components

The QA process is based on the 2014 CDC Tuberculosis Elimination and Laboratory cooperative agreement and the results of a QA needs assessment conducted with 11 of the 60 reporting jurisdictions. The process includes five components as shown in the figure below.

Five Quality Assurance Components for TB Surveillance Data

Graphic depicting five quality assurance components for TB surveillance data

 

QA Components

QA Components Definition
Case Detection Detection of one instance of a specific disease or exposure, e.g., TB. A front-line surveillance activity, it is typically accomplished as a by-product of routine medical or veterinary care, or laboratory work, or via an astute observer such as a health care worker.
Data Accuracy The data submitted match patient records maintained at the point of care. The recorded data in the surveillance system are consistent with what activities happened in a clinical encounter, whether or not they were clinically appropriate.
Data Completeness A measure that indicates whether the information submitted contains the complete set of data items.
Data Timeliness Prompt reporting of surveillance data to health authorities.
Data Security and Confidentiality Data security is the protection of public health data and information systems to prevent unauthorized release of identifying information and accidental loss of data or damage to the systems.

Data confidentiality is the protection of personal information collected by public health organizations. The right to such protection is based on the principle that personal information should not be released without the consent of the person involved except as necessary to protect public health.

 

Goal

The goal for the QA manual is to help improve the quality of TB surveillance data by providing TB surveillance reporting jurisdictions with

  • A standardized process for QA, and
  • Tools that can be used and adapted for QA.

Objectives

After using this guide and toolkit, the user should be able to

  • Describe the five components of the QA process,
  • Access various QA tools for TB surveillance data, and
  • Describe what to include in a written QA protocol as required by the cooperative agreement.

About the Guide

  • The guide includes a set of nine chapters and four appendices. A description of the chapters and appendices is shown in the table below.

 

Description of Chapters and Appendices

Chapter Title Description
1 Introduction to the Guide and Toolkit Background, goals and objectives, target audience, and how to use the guide and toolkit
2 National Tuberculosis Surveillance System Data Flow Data flow structure from the jurisdictions to CDC
3 Overview of the Quality Assurance (QA) Process Definition of QA, factors influencing data quality, cooperative agreement, QA component definitions, and tools
The five QA components that provide the main content of the manual
4 Case Detection Purpose, definitions, process, and tools
5 Data Accuracy Purpose, definitions, process, NTSS data validation, laboratory data accuracy, data validation pilot project, and tools
6 Data Completeness Purpose, definitions, process, missing and unknown, data completeness, accuracy study, and tools
7 Data Timeliness Purpose, definitions, process, case count process, and tools
8 Data Security and Confidentiality Purpose, definitions, process, data security and confidentiality guidelines, and tools
9 Quality Assurance Cross-cutting Systems and Process: NTIP, TB GIMS, and Cohort Review Examples of systems and a process that can be used for improving at least three of the five QA components (e.g., accuracy, completeness, and timeliness). These include the National TB Indicators Project, the TB Genotyping Information Management System, and cohort review.
10 Toolkit for Quality Assurance Examples of the tools that can be easily adapted for local use. Tools are grouped by chapter and content topic (e.g., Chapter 3: Overview of the Quality Assurance Process).
Appendix Title Description
A References List of all references used in the development of this guide
B Glossary Compilation of all the definitions provided in this guide
C Quality Assurance Process Slides Set of slides that describe the QA process
Chapter Title Description
D Report of Verified Case of Tuberculosis (RVCT) Questions and Clarifications Compilation of questions and clarifications since the 2009 publication of the RVCT instructions. This document is updated periodically and is available at http://www.cdc.gov/tb/programs/rvct/default.htm.
E Answers to the Exercises Discussions of answers to exercises included in this guide

 

Two women filling out forms

About the Toolkit

Staff from CDC and various jurisdictions developed approximately 50 QA tools that include tables, charts, graphs, processes, and templates. The tools are available in commonly used software so that they can be easily used or adapted to a jurisdiction’s setting.

Additional Information

For additional information about QA for Tuberculosis Surveillance Data, please contact the RVCT/QA Training Team at rvctqualityassurance@cdc.gov.

 

—Reported by DTBE's RVCT QA Training Team:
Lilia Manangan (lmanangan@cdc.gov),
Elvin Magee (emagee@cdc.gov),
and Cheryl Tryon (ctryon@cdc.gov)
Division of TB Elimination

 

References

  1. CDC. DTBE’s Comprehensive and Innovative Training Program on the Revised RVCT. TB Notes Newsletter, No. 3, 2009.
  2. CDC. DTBE Training Course on Quality Assurance for Tuberculosis Surveillance Data. TB Notes Newsletter, No. 4, 2011.
  3. Magee E, Tryon C, Forbes A, Heath B, Manangan L. The National Tuberculosis Surveillance System Training Program to Ensure Accuracy of Tuberculosis Surveillance Data. J Public Health Management Practice 2011; 17(5): 427–430.
  4. Manangan LP, Tryon C, Magee E, Miramontes R. Innovative Quality-Assurance Strategies for Tuberculosis Surveillance in the United States. Tuberculosis Research and Treatment 2012. Article ID 481230; doi:10.1155/2012/481230: http://www.hindawi.com/journals/trt/2012/481230.


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