How to Validate Data Quality in a Trauma Registry? The Helsinki Trauma Registry Internal Audit

Abstract

Background and Aims: Trauma registry data are used for analyzing and improving patient care, comparison of different units, and for research and administrative purposes. Data should therefore be reliable. The aim of this study was to audit the quality of the Helsinki Trauma Registry internally. We describe how to conduct a validation of a regional or national trauma registry and how to report the results in a readily comprehensible form. Materials and Methods: Trauma registry database of Helsinki Trauma Registry from year 2013 was re-evaluated. We assessed data quality in three different parts of the data input process: the process of including patients in the trauma registry (case completeness); the process of calculating Abbreviated Injury Scale (AIS) codes; and entering the patient variables in the trauma registry (data completeness, accuracy, and correctness). We calculated the case completeness results using raw agreement percentage and Cohen’s κ value. Percentage and descriptive methods were used for the remaining calculations. Results: In total, 862 patients were evaluated; 853 were rated the same in the audit process resulting in a raw agreement percentage of 99%. Nine cases were missing from the registry, yielding a case completeness of 97.1% for the Helsinki Trauma Registry. For AIS code data, we analyzed 107 patients with severe thorax injury with 941 AIS codes. Completeness of codes was 99.0% (932/941), accuracy was 90.0% (841/932), and correctness was 97.5% (909/932). The data completeness of patient variables was 93.4% (3899/4174). Data completeness was 100% for 16 of 32 categories. Data accuracy was 94.6% (3690/3899) and data correctness was 97.2% (3789/3899). Conclusion: The case completeness, data completeness, data accuracy, and data correctness of the Helsinki Trauma Registry are excellent. We recommend that these should be the variables included in a trauma registry validation process, and that the quality of trauma registry data should be systematically and regularly reviewed and reported.

The reliability of the ICD-AIS map in identifying serious road traffic injuries from the Helsinki Trauma Registry

“…The collected data includes parameters for predictive models (patient and injury severity variables including AIS and ICD-10), process mapping (variables describing care provided), and resource utilization (variables describing the hospital resources needed). The validity of the data (completeness of cases and data and data accuracy) has been found to be excellent [11,12].…”

“…Head and neck S02.0 (7) S06.0, S06.2 (4), S06.3 (11) S06.4 (3), S06.6 (8) S12.0, S12.1 (2), S12.2 (3) S13.0, S14.3 S15.0 (3), S15.1 (2) S01.7 (5) S02.01, S02.71 (2), S02.7 (3), S06.7 S12.7 (5), S15.7 (2) S16.0 S06.8 (12), S06.9 S07.9 S19.8 T00.9 (12), T01.9…”

Providing a Population Based Registry Model of Drug Poisoning in Iran

“…Gathering and focusing on data integrity are among the goals emphasized by many registries. Attention to the accurate collection of data is a pillar of data management, and emphasizing it as a major goal of registries facilitates other registry steps and processes (53). In the model proposed for Iran, electronic and manual case report forms were agreed upon for data collection and summarization.…”

Major blunt trauma causes increased mortality up to 12 years: Long-term survival in 3 557 patients compared to 35 502 control persons

“…Due to differences in health policies and health care systems and their possible effect on outcomes, we do not know whether our results can be generalized. As we linked the data of multiple different databases, we did not encounter problems related to failure to follow-up as all the mortality data were available from Finnish health authorities and the validated trauma registry [17,18] was used to identify the patient cohort.…”