Structured data quality reports to improve EHR data quality

• SDQR and feedback sessions support improvements in the recording of clinical records.
• Significant improvements were made in the recording of risk factors.
• Improvements not sufficient to meet RACGP data quality standards.
• An ecological approach across the data cycle is needed to improve DQ in EHRs.

ObjectiveTo examine whether a structured data quality report (SDQR) and feedback sessions with practice principals and managers improve the quality of routinely collected data in EHRs.MethodsThe intervention was conducted in four general practices participating in the Fairfield neighborhood electronic Practice Based Research Network (ePBRN). Data were extracted from their clinical information systems and summarised as a SDQR to guide feedback to practice principals and managers at 0, 4, 8 and 12 months. Data quality (DQ) metrics included completeness, correctness, consistency and duplication of patient records. Information on data recording practices, data quality improvement, and utility of SDQRs was collected at the feedback sessions at the practices.The main outcome measure was change in the recording of clinical information and level of meeting Royal Australian College of General Practice (RACGP) targets.ResultsBirth date was 100% and gender 99% complete at baseline and maintained. DQ of all variables measured improved significantly (p < 0.01) over 12 months, but was not sufficient to comply with RACGP standards. Improvement was greatest with allergies. There was no significant change in duplicate records.ConclusionsSDQRs and feedback sessions support general practitioners and practice managers to focus on improving the recording of patient information. However, improved practice DQ, was not sufficient to meet RACGP targets. Randomised controlled studies are required to evaluate strategies to improve data quality and any associated improved safety and quality of care.