Automation of medical imaging business reporting workflows in Ontario for quantitative and qualitative process improvement.

INTRODUCTION/BACKGROUND: Medical imaging facilities in Ontario often rely on cyclical reporting workflows to submit system data for provincial funding and performance monitoring. These workflows often involve repetitive and manual steps to collect, process, model and circulate data. Workflow automation was applied at the business level to minimize the time and effort required to process key system metrics such as wait time cases and scanner fleet activity for regulatory reporting of utilization and financial workstreams. The time saved from workflow automation can be shifted to focus on higher-value innovation-based or patient-centred work to improve healthcare delivery within Ontario medical imaging and diagnostic systems. Efficiency and user experience improvements gained from workflow automation are realized directly by the report analyst. Subsequent improvements to report data quality are translated downstream to the clinical, clerical and operational stakeholders who use these reports to inform operational decision making. Workflow automation goals can be identified by the stakeholders who interact with workflows and workflow outputs. The workflow automations and evaluations outlined in this paper were completed by the report author and reflect the author's individual experience.

METHODS

A 2-phased approach was applied to optimize in-scope workflows to consider time saved and improvements to the user experience through automation. Efficiency and user experience improvements were quantified by segmenting workflow processes into sub processes. Output accuracy, time savings and user experience improvements were measured at various checkpoints. A framework consisting of technical and documentation-based deliverables was developed to define automation design and solution impact across each workflow to 1) educate multidisciplinary stakeholders on process changes and automation design 2) validate solution accuracy and 3) support ongoing process change management.

RESULTS

Automations were developed across 4 optimized workstreams to facilitate data cleaning, verification, consolidation and modelling. Across all workstreams a total of about 2 working days of time was saved in parallel with design improvements such as reductions in data entry errors, visual inspection, repetition and screen crowding. These automations optimized key medical imaging workstreams such as managing diagnostic imaging wait time cases, reporting scanner operating hours and fleet utilization.

DISCUSSION/CONCLUSION: It was critical to ensure automated outputs remained familiar and accessible to all stakeholders to support effective engagement within medical imaging settings. This strategy was applied by considering the need to preserve legacy process strengths to support various clinical, operational and clerical stakeholders in engaging with workflow outputs in a familiar and accessible way. Challenges with workflow automation emphasized that automations within healthcare environments must be implemented with caution to ensure solution outputs are interpretable and meaningful to multidisciplinary stakeholders. This paper encourages workflow subject matter experts to asses repetition present in medical imaging business reporting workflows and explore digital solutions that minimize time spent away from innovation-based work to improve system performance.