Abstract
Clinical quality indicators providing valuable information about outcomes and care variance are manually collated in resource-intensive clinical registries. In principle, automated collation of routinely collected data housed in eMRs could enable audit and feedback on all patients in near-to-real time. The aims of this pilot study were to examine 1) feasibility of using eMR data to measure Australian Commission on Safety and Quality in Healthcare (ACSQHC) ACS Indicators, and; 2) to examine the usefulness of benchmarking reports with clinicians and health service managers. The sample comprised suspected ACS presentations to emergency departments of two NSW local health districts (LHD) between April-June, 2017 (n=40009). eMR data for patients with ICD10 code for STEMI (LHD 1: n=102, 26 females, 67±15y; LHD 2: n=50, 15 females, 70±15y) were extracted, processing and bespoke software developed to address the heterogenous nature of eMR data including free-text clinical documentation and scanned ECGs. Results were reviewed by a multidisciplinary clinical and informatics team every 2-4 weeks and a benchmark report compiled for local ED and Cardiology clinicians for review. Feasibility analyses demonstrated reliable eMR data addressed ACSQHC ACS indicators for early assessment (time-to-ECG), timely reperfusion (door-to-balloon time) and individualised care plan (discharge medications). Clinician feedback demonstrated results were trustworthy and similar to manually-obtained data. The next steps are to extend analyses to a longer duration and to NSTEACS populations. This is the groundwork for near-to-real time feedback of eMR data whereby frontline clinicians can act upon these insights to improve care disparities and variance.
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