Healthcare Data Quality Survey
2023
Clinical Architecture surveyed various professionals within healthcare enterprises to illustrate the impact of low-quality patient data across several critical factors, from care quality to financial performance.
The Purpose of the Survey
The purpose of Clinical Architecture’s inaugural Healthcare Data Quality Survey is to measure: the perceived quality of the data in healthcare, the impact of data quality on individual and collective objectives, and the factors contributing to poor quality. We do this across different healthcare market segments since each segment creates, collects, uses, and disseminates the data differently.
Do we as an industry realize we have a data quality problem? Do we have confidence that the data we have collected about our patients is reliable?
Do we understand the impact the patient data has on our individual, enterprise, and industry objectives?
Do we know what factors are contributing to the degradation of our patient data so that we can address them?
With the launch of TEFCA and the selection of the first QHINs, how does the industry feel about the quality of patient data from external organizations and whether they are willing to integrate it?
We surveyed professionals from various segments in healthcare.
Care Provider
Academia
Vendor
Public Health
Value Based Care
Payer
Life Sciences
Other
Do we as an industry realize we have a data quality problem?
The survey results indicate that the participants realize there is a problem with patient data quality in healthcare.
%
rated the quality of their enterprise patient data as mixed or poor.
Do we understand the impact the patient data has on our individual, enterprise, and industry objectives?
The survey participants almost unanimously acknowledged that poor data quality had a moderate to high impact on the overall goals of their enterprises.
%
rated poor quality's impact on their enterprises' goals as high.
Do we know what factors are contributing to the degradation of our patient data so that we can address them?
The survey participants were asked to rate several factors (Effort, Standards, Software Design, Interoperability, Unstructured Data, and Data Entry Error) contributing to poor data quality. Their responses did not point to a single factor, but all listed contributed to different extents.
%
believed that the lack of interoperability was a high contributor.
How does the industry feel about the quality of patient data from external organizations, and are they willing to integrate it?
Despite the quality concerns, most indicated that they were currently or would still be likely to integrate external patient data into their enterprise.
%
rated the patient data from external sources as poor or mixed quality.
%