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

BACKGROUND

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.

OBJECTIVE

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.

METHODS

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.

RESULTS

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).

CONCLUSIONS

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.

CLINICALTRIAL

N/A.

Incidence of adverse incidents in residential aged care

ObjectiveAdverse incident research within residential aged care facilities (RACFs) is increasing and there is growing awareness of safety and quality issues. However, large-scale evidence identifying specific areas of need and at-risk residents is lacking. This study used routinely collected incident management system data to quantify the types and rates of adverse incidents experienced by residents of RACFs.MethodsA concurrent mixed-methods design was used to examine 3 years of incident management report data from 72 RACFs in New South Wales and the Australian Capital Territory. Qualitative thematic analysis of free-text incident descriptions was undertaken to group adverse incidents into categories. The rates and types of adverse incidents based on these categories were calculated and then compared using incidence rate ratios (IRRs).ResultsDeidentified records of 11 987 permanent residents (aged ≥65 years; mean (±s.d.) age 84 ± 8 years) from the facilities were included. Of the 60 268 adverse incidents, falls were the most common event (36%), followed by behaviour-related events (33%), other impacts and injuries (22%) and medication errors (9%). The number of adverse incidents per resident ranged from 0 (42%) to 171, with a median of 2. Women (IRR 0.804; P < 0.001) and residents with low care needs (IRR 0.652; P < 0.001) were significantly less likely to adverse incidents compared with men and residents with high care needs respectively.ConclusionThis study demonstrates that data already collected within electronic management systems can provide crucial baseline information about the risk levels that adverse incidents pose to older Australians living in RACFs.What is known about the topic?To date, research into aged care adverse incidents has typically focused on single incident types in small studies involving mitigation strategies. Little has been published quantifying the multiple adverse incidents experienced by residents of aged care facilities or reporting organisation-wide rates of adverse incidents.What does this paper add?This paper adds to the growing breadth of Australian aged care research by providing baseline information on the rates and types of adverse incidents in RACFs across a large and representative provider.What are the implications for practitioners?This research demonstrates that the wealth of data captured by aged care facilities' incident management information systems can be used to provide insight into areas of commonly occurring adverse incidents. Better use of this information could greatly enhance strategic planning of quality improvement activities and the care provided to residents.

Transforming routinely collected residential aged care provider data into timely information: Current and future directions

Electronic information systems are becoming increasingly common in residential aged care in Australia. These systems contain valuable data generated during day-to-day care delivery for older adults. These data (termed 'routinely collected residential aged care provider data') are currently underutilised, however have potential significant benefits for both care delivery and research purposes. Routinely collected residential aged care provider data are more readily accessible, contain up-to-date information and can be linked to existing national or state-based administrative data sets, while providing more granular details about care delivered at the coalface. The aim of this paper is to provide clinicians, researchers, policymakers and providers with an understanding of the strengths of these types of data, as well as identifying areas that require future development to maximise their potential to drive improvements in resident care and outcomes. These considerations include data quality, data standardisation and models for data governance, consent and consumer involvement.