Data Completeness in Healthcare: A Literature Survey

Abstract

As the adoption of eHealth has made it easier to access and aggregate healthcare data, there has been growing application for clinical decisions, health services planning, and public health monitoring with daily collected data in clinical care. Reliable data quality is a precursor of the aforementioned tasks. There is a body of research on data quality in healthcare, however, a clear picture of data completeness in this field is missing. This research aims to identify and classify current research themes related to data completeness in healthcare. In addition, the paper presents problems with data completeness in the reviewed literature and identifies methods that have been adopted to address those problems. This study has reviewed 24 papers (January 2011-April 2016) published in information and computing sciences, biomedical engineering, and medicine and health sciences journals. The paper uncovers three main research themes, including design and development, evaluation, and determinants. In conclusion, this paper improves our understanding of the current state of the art of data completeness in healthcare records and indicates future research directions.

Machine Learning Analysis for Data Incompleteness (MADI): Analyzing the Data Completeness of Patient Records Using a Random Variable Approach to Predict the Incompleteness of Electronic Health Records

“…With regards to other previous works, the researchers sought to explore novel and computational methods to apply data incompleteness to an applied health dataset. Some of the studies done in the past relied heavily on supervised machine learning methods [24] [25], or used differing statistical methodologies [26] [27] [28] [29]. Our focus in this study wanted to provide two clear goals: 1) Provide a practical utilization of machine learning analysis with regards to electronic health record data incompleteness.…”

Medical Dialogue Summarization for Automated Reporting in Healthcare

“…In addition, to the best of our knowledge, medical professionals in the Netherlands do not receive any formal training on how to write such formatted reports. Therefore, in order to determine the quality of the generated reports, we will rely on consultation reports, written by a GP in the SOEP format, which we use as a golden standard [16].…”

Knowledge Profile in PAJAIS: A Review of Literature and Future Research Directions

“…They attempted to find out how papers in EC journals could differ from those in IS journals. Liu (2017) reviewed 24 papers published in information and computing sciences, biomedical engineering, and medicine and health sciences, in order to identify current research themes in the area of data completeness in healthcare. Deng and Ji (2017) presented a comprehensive review of existing Design Science Research (DSR).…”

“…These attributes would determine how the nursing staff viewed both the need and the urgency associated with the calls. Liu (2017) reviewed 24 papers published in information and computing sciences, biomedical engineering, and medicine and health sciences journals to identify and classify current research themes related to data completeness in healthcare.…”