A review of data quality assessment methods for public health information systems.

Ping Yu,Hong Chen,David Hailey,Ning Wang

doi:10.3390/ijerph110505170

Abstract

High quality data and effective data quality assessment are required for accurately evaluating the impact of public health interventions and measuring public health outcomes. Data, data use, and data collection process, as the three dimensions of data quality, all need to be assessed for overall data quality assessment. We reviewed current data quality assessment methods. The relevant study was identified in major databases and well-known institutional websites. We found the dimension of data was most frequently assessed. Completeness, accuracy, and timeliness were the three most-used attributes among a total of 49 attributes of data quality. The major quantitative assessment methods were descriptive surveys and data audits, whereas the common qualitative assessment methods were interview and documentation review. The limitations of the reviewed studies included inattentiveness to data use and data collection process, inconsistency in the definition of attributes of data quality, failure to address data users’ concerns and a lack of systematic procedures in data quality assessment. This review study is limited by the coverage of the databases and the breadth of public health information systems. Further research could develop consistent data quality definitions and attributes. More research efforts should be given to assess the quality of data use and the quality of data collection process.

Highlights

Public health is “the science and art of preventing disease, prolonging life, and promoting physical health and efficiency through organized community efforts” [1]
As the three dimensions of data quality are embedded in the lifecycle of public health practice, we propose a conceptual framework for data quality assessment in PHIS (Figure 1)
Data quality has always been an important topic in public health, we have identified a lack of systematic review of data quality assessment methods for PHIS

Summary

Introduction

Public health is “the science and art of preventing disease, prolonging life, and promoting physical health and efficiency through organized community efforts” [1]. Information and knowledge underpin these three functions, public health is inherently a data-intensive domain [3,4]. High quality data are the prerequisite for better information, better decision-making and better population health [5]. Public health data represent and reflect the health and wellbeing of the population, the determinants of health, public health interventions and system resources [6]. The levels and distribution of the determinants of health are measured in terms of biomedical, behavioral, socioeconomic and environmental risk factors. Data on public health interventions include prevention and health promotion activities, while those on system resources encompass material, funding, workforce, and other information [6]

Methods

Results

Discussion

Conclusion