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Updated: Jan 29, 2026

A Novel Digital Platform for a Monitored Home-based Cardiac Rehabilitation Program
Published on: April 19, 2019
Utilising a Data Capture Tool to Populate a Cardiac Rehabilitation Registry: A Feasibility Study
Emma Thomas1, Sherry L Grace2, Douglas Boyle3
1Melbourne School of Population and Global Health, University of Melbourne, Melbourne, Vic, Australia.
Background:
Clinical registries are effective for monitoring clinical practice, yet manual data collection can limit their implementation and sustainability. The objective of this study was to assess the feasibility of using a data capture tool to collect cardiac rehabilitation (CR) minimum variables from electronic hospital administration databases to populate a new CR registry in Australia.
Methods:
Two CR facilities located in Melbourne, Australia participated, providing data on 42 variables including: patient socio-demographics, risk factors and co-morbidities, CR program information (e.g. number of CR sessions), process indicators (e.g. wait time) and patient outcomes (e.g. change in exercise capacity). A pre-programmed, automated data capture tool (GeneRic Health Network Information for the Enterprise [20]: https://www.grhanite.com/) (GRHANITE™) was installed at the sites to extract data available in an electronic format from hospital sites. Additionally, clinicians entered data on CR patients into a purpose-built web-based tool (Research Electronic Data Capture: https://www.project-redcap.org/) (REDCap). Formative evaluation including staff feedback was collected.
Results:
The GRHANITE™ tool was successfully installed at the two CR sites and data from 176 patients (median age = 67 years, 76% male) were securely extracted between September-December 2017. Data pulled electronically from hospital databases was limited to seven of the 42 requested variables. This is due to CR sites only capturing basic patient information (e.g. socio-demographics, CR appointment bookings) in hospital administrative databases. The remaining clinical information required for the CR registry was collected in formats (e.g. paper-based, scanned or Excel spreadsheet) deemed unusable for electronic data capture. Manually entered data into the web-tool enabled data collection on all remaining variables. Compared to historical methods of data collection, CR staff reported that the REDCap tool reduced data entry time.
Conclusions:
The key benefits of a scalable, automated data capture tool like GRHANITE™ cannot be fully realised in settings with under-developed electronic health infrastructure. While this approach remains promising for creating and maintaining a registry that monitors the quality of CR provided to patients, further investment is required in the digital platforms underpinning this approach.
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