Data quality assessment instrument for electronic health record systems in Saudi Arabia

Almutiry, Omar Saud (2017) Data quality assessment instrument for electronic health record systems in Saudi Arabia. University of Southampton, Doctoral Thesis, 240pp.

Record type: Thesis (Doctoral)

Abstract

The provision of high quality data is of considerable importance to both business and government; poor data may lead to poor decisions, so quality plays a crucial role. With the proliferation of electronic data collection by businesses and governments, there has arisen a pressing need to assure this quality. This has been recognized by both the private and public sectors, and many initiatives such as the Data Quality Initiative Framework by the Welsh government, passed in 2004, and the Data Quality Act by the United States government, passed in 2002, have been launched to improve it in those countries.

At the same time, healthcare is a domain in which the timely provision of accurate, current and complete patient data is one of the most important objectives. Instigation of a so-called Electronic Health Record (EHR), defined as a repository of patient data in digital form that is stored and exchanged securely and is accessible by different levels of authorized users, has been attracting the attention of both research and industry. EHRs allow information regarding a patient’s health to be distributed among heterogeneous information systems. This evolution has added a layer of complexity in data quality, making data quality assurance a challenging issue, as the key barriers to optimal use of EHR data are the increasing quantity of data and their poor quality.

Many data quality frameworks have been developed to measure the quality of data in information systems. However, there is no consensus on a rigorously defined set of data quality dimensions. Existing dimensions are usually based on literature reviews, industrial experiences or intuitive understanding and do not take into consideration the nature of e-healthcare systems. Moreover, definitions of these dimensions vary from one data quality framework to another.
The aim of this research is to develop a data quality framework consisting of health-relevant dimensions, and data quality measures that help health organisations to enhance the quality of their data. The study provides both subjective and objective measures for assessing the quality of data.

An 11-dimensional data quality framework has been developed and confirmed by EHR stakeholders and a group of experts and data consumers. With each dimension, several associated measures have been developed to help an organisation to measure the quality of the data populating their EHR systems. Some issues linked with the measures associated with security-related dimensions have arisen during the confirmation stage. Therefore, these issues were further discussed and reviewed with security experts in order to revise the proposed framework and its measures.

Subsequently, a case study was conducted in a large hospital to examine the practicality of the proposed instrument. The instrument was used to help hospitals to assess their data. After that, the usefulness and practicality of the instrument were examined through an evaluation questionnaire distributed to quality assessment team members. Follow-up interviews with senior managers were carried out to discuss the output of the assessment and its practicality.

The contribution of this research is the development of a proper data quality framework for EHRs in the context of Saudi Arabia which resulted in 11 health-relevant data quality dimensions. An instrument was also introduced to represent all developed and confirmed measures that assess data population in EHRs.