JMIR Publications

ABSTRACT

Background:

Online physician rating websites have witnessed a steep rise in prominence over the years and exert considerable influence on high-stake patient decisions. However, the quality of these decisions depends on the quality of data collected by these systems. Hence, there is a need to understand the various data quality issues that exist in such websites.

Objective:

The purpose of this systemic review is to collect the data quality issues discussed in previous studies and classify them based on the data quality framework put forward by Wang et al. This review summarizes the findings and provides an in-depth discussion of various categories of data quality issues and their implications on the users of physician rating websites.

Methods:

We performed a systematic literature search in ACM Digital Library, EBSCO, Springer, PubMed, and Google Scholar. We identified any quantitative, qualitative and mixed-method paper that investigated data quality issues in physician rating websites. Over 192 articles were screened, and 33 were analyzed and summarized for this systematic review.

Results:

We identified 33 studies to collect 19 unique data quality issues that afflict physician rating sites. We classify these issues into 4 categories: Intrinsic, Contextual, Accessible and Representational. 58% (19/33) papers reported the presence of Intrinsic data quality errors, 48% (16/33) highlighted Contextual data quality issues. A small yet considerable number of studies (10/33) discussed issues of Representational & Accessibility data quality. More than half of the papers discuss multiple categories of data quality issues.

Conclusions:

The results of this review demonstrate the presence of a range of data quality issues. While Intrinsic and Contextual factors have been well researched, Accessibility and Representational issues warrant more attention from researchers as well as practitioners. Notably, the Representational factors such as the impact of inline advertisements, positioning of positive reviews, which are usually deliberate and an artifact of the business or revenue model of the PRWs warrant more emphasis.