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Envisioning the future of clinical analytics: a modified Delphi process in New South Wales, Australia.

ABSTRACT: BACKGROUND:Clinical analytics is a rapidly developing area of informatics and knowledge mobilisation which has huge potential to improve healthcare in the future. It is widely acknowledged to be a powerful mediator of clinical decision making, patient-centred care and organisational learning. As a result, healthcare systems require a strategic foundation for clinical analytics that is sufficiently directional to support meaningful change while flexible enough to allow for iteration and responsiveness to context as change occurs. METHODS:In New South Wales, the most populous state in Australia, the Clinical Analytics Working Group was charged with developing a five-year vision for the public health system. A modified Delphi process was undertaken to elicit expert views and to reach a consensus. The process included a combination of face-to-face workshops, traditional Delphi voting via email, and innovative, real-time iteration between text re-formulation and voting until consensus was reached. The six stage process engaged 35 experts - practising clinicians, patients and consumers, managers, policymakers, data scientists and academics. RESULTS:The process resulted in the production of 135 ideas that were subsequently synthesised into 23 agreed statements and encapsulated in a single page (456 word) narrative. CONCLUSION:The visioning process highlighted three key perspectives (clinicians, patients and managers) and the need for synchronous (during the clinical encounter) and asynchronous (outside the clinical encounter) clinical decision support and reflective practice tools; the use of new and multiple data sources and communication formats; and the role of research and education.

SUBMITTER: Sutherland K

PROVIDER: S-EPMC7650225 | biostudies-literature | 2020 Sep

REPOSITORIES: biostudies-literature

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Envisioning the future of clinical analytics: a modified Delphi process in New South Wales, Australia.

Sutherland Kim K Yeung Wilson W Mak Yoke Y Levesque Jean-Frederic JF

BMC medical informatics and decision making 20200904 1

<h4>Background</h4>Clinical analytics is a rapidly developing area of informatics and knowledge mobilisation which has huge potential to improve healthcare in the future. It is widely acknowledged to be a powerful mediator of clinical decision making, patient-centred care and organisational learning. As a result, healthcare systems require a strategic foundation for clinical analytics that is sufficiently directional to support meaningful change while flexible enough to allow for iteration and r ...[more]

PMID: 32887609

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Project description:BackgroundIn 2017, the New South Wales Cancer Registry (NSWCR) participated in a project, supported by Cancer Australia, aiming to provide national stage data for melanoma, prostate, colorectal, breast, and lung cancers diagnosed in 2011. Simplified business rules based on the American Joint Committee for Cancer (AJCC) Tumour-Node-Metastasis (TNM) stage were applied to obtain Registry-Derived (RD) stage, defined as the best estimate of TNM stage at diagnosis using routine notifications available within cancer registries. RD-stage was compared with Degree of Spread (DoS), which has been recorded for all applicable cancers in NSWCR at a population-based level since 1972, and a summary AJCC-TNM stage group, which has been collected variably since 2006. For each of the five high incidence cancers, we compared the level of improvements RD-staging provided in terms of completeness and accuracy (alignment to more clinically relevant AJCC-TNM) over DoS.MethodsFor each of the five cancers, stage data were extracted from NSWCR pre- and post- RD-staging to compare data completeness across all three staging systems. The alignment between DoS/RD-stage and AJCC-TNM was compared, as were the expected and observed cross-tabulated frequency distributions using a subset of NSWCR data. To determine differences between use of DoS, RD-stage, and AJCC-TNM in an epidemiological analysis, we compared survival models developed from each of the three stage variables.ResultsWe found RD-staging provided greatest stage data completeness and alignment to AJCC-TNM for prostate cancers, followed by breast, then melanoma and lung cancers. For colorectal cancer, summary stage from DoS was confirmed as an equivalent surrogate staging system to both AJCC-TNM and RD-stage.ConclusionsThis analysis provides an evidence-based approach that can be used to inform decision-making for resource planning and potential implementation of a new stage data field in population-based cancer registries.

Project description:The koala (Phascolarctos cinereus) is currently listed by both the IUCN and the Australian Governments' Threatened Species Scientific Committee as vulnerable to extinction with an overall decreasing population trend. It is unknown exactly how many koalas remain in the wild, but it is known that habitat fragmentation and bushfires have ultimately contributed to the decline of the koala all over Australia. This novel study is a retrospective analysis of data over a 29-year period (1989-2018) using records for 12,543 sightings and clinical care admissions for wild koalas from the major koala hot-spots (Port Stephens, port Macquarie and Lismore) in New South Wales, Australia. This study aims to understand the long-term patterns and trends of key stressors that are contributing to the decline of koalas in New South Wales, and the synergic interactions of factors such as rescue location, sex and age of the koala, and if their decline is influenced progressively by year. The main findings of this retrospective analysis indicated that between all 3 rescue sites, the most common prognosis was disease, the most common disease was signs of chlamydia, and the most common outcome was release. The location where the highest number of koalas were found prior to being reported as sighted or admitted into clinical care was within the regional area of Lismore. Furthermore, sex was not a discriminating factor when it came to prognosis or outcome, but age was significant. Finally, incidents of disease were found to increase over long-term, whereas release decreased over time and euthanasia increased. The wealth of data available to us and the retrospective analysis enabled us in a way to 'zoom out' and reveal how the key environmental stressors have fluctuated spatially and temporally. In conclusion, our data provides strong evidence of added pressures of increased human population growth in metropolitan zones, which increases risks of acute environmental trauma and proximate stressors such as vehicle collisions and dog-attacks as well as increased sightings of virtually healthy koalas found in exposed environments. Thus our 'zoom out' approach provides support that there is an urgent need to strengthen on-ground management, bushfire control regimes, environmental planning and governmental policy actions that should hopefully reduce the proximate environmental stressors in a step wise approach. This will ensure that in the next decade (beyond 2020), NSW koalas will hopefully start to show reversed trends and patterns in exposure to environmental trauma and disease, and population numbers will return towards recovery and stability.

Dataset Information

Envisioning the future of clinical analytics: a modified Delphi process in New South Wales, Australia.

Publications

Envisioning the future of clinical analytics: a modified Delphi process in New South Wales, Australia.

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