Optimising the quality of clinical data in an Australian aged care and disability service to improve care delivery and clinical outcomes (OPTIMISE): Protocol for an Agile Lean Six Sigma study.

Abstract

In Australia, aged care and disability service providers are legally required to maintain comprehensive and accurate clinical documentation to meet regulatory and funding requirements and to support safe and high quality care provision. However, evidence suggests poor quality clinical data and documentation is widespread across the sector and can significantly affect clinical decision-making and care delivery and increase business costs. The OPTIMISE study uses an Agile Lean Six Sigma framework to: 1) identify opportunities for optimisation of clinical documentation processes and clinical information systems, 2) implement and test optimisation solutions, and 3) evaluate outcomes post-optimisation, in a large post-acute community-based health service providing aged care and disability services in Western Australia. A three-stage prospective optimisation study will be undertaken. Stage 1 (Baseline) will measure existing clinical data quality, identify root causes of data quality issues across services, and generate optimisation solutions. Stage 2 (Optimisation) will implement and test changes to clinical documentation processes and information systems using incremental Agile sprints, and Stage 3 (Evaluation) will evaluate change in primary and secondary outcomes from baseline to 12 months post-optimisation. The primary outcome is data quality measured in terms of Defects Per Unit (DPU), Defects Per Million Opportunities (DPMO) and Sigma level. Secondary outcomes are care delivery (direct care time), clinical incidents, business outcomes (cost of quality, workforce productivity), and user satisfaction. Case studies will be analysed to understand impacts of optimisation on clinical outcomes and business processes. As of 1 June 2022, Stage 1 commenced with baseline data quality audits conducted to measure current data quality. Baseline data quality audits will be followed by user consultations to identify root causes of data quality issues. Optimisation solutions will be developed by January 2023 to inform optimisation (Stage 2) and evaluation (Stage 3). Study findings will be of interest to individuals and organisations in the healthcare sector seeking novel solutions to improve the quality of clinical data and support high quality care delivery and reduce business costs. N/A.