Design Thinking
The project will utilise a design thinking approach involving all its collaborators (PHNs, general practices, consumer groups, researchers, and digital health developers, pathology professionals) to enhance the development of meaningful and translational project outcomes. Design thinking seeks to incorporate user needs and feedback throughout the development of the research process. The approach involves rounds of ideation, prototyping, and testing[1] to enhance understanding of underlying problems or unpredictable situations[20].
The project builds upon an established collaboration between Macquarie University, the Royal College of Pathologists Quality Assurance Programs, Outcome Health and Gippsland, Eastern and South Eastern PHNs, which evaluated the appropriateness and quality use of pathology in general practice[21] using pooled electronic general practice data[22]. This project provided an overview of pathology testing within Australian general practice, along with reporting on variation across key indicators including vitamin D testing, glycated haemoglobin (HbA1c) and kidney function tests for monitoring type 2 diabetes, ferritin testing for iron deficiency and prostate-specific antigen (PSA) testing[23].
Observational studies
A series of observational studies will be carried out over 1.5 years (July 2020 – December 2021) utilising near real-time electronic general practice data to promote effective care and best-practice policy. The studies will be centred on 350 general practices within three Victorian PHNs, Gippsland PHN, Eastern Melbourne PHN and South Eastern Melbourne PHN. These PHNs cover metropolitan and rural regions across a combined area totalling 48,903 km, delivering healthcare to 3,132,382 Australians[23]. Data will be supplemented by participation of two PHNs from New South Wales, Central and Eastern Sydney PHN and South Western Sydney PHN. Central and Eastern Sydney PHN encompasses 2,053 general practices and covers 1,637,740 people living in this region[24], while South Western Sydney PHN encompasses 1,045 general practices with 966,450 people living in the region[25].
Data source
Outcome Health, as a data custodian, uses its Population Level Analysis & Reporting (POLAR) Data Space to provide a secure and comprehensive digital health platform which collects data from consenting general practices across participating PHNs[19, 21, 22, 26, 27]. Data variables include de-identified demographic information about patients and general practices, as well as visit records (diagnosis, past history, medications, immunisation, radiology) and pathology test records (test name and result).
Until recently, there was little evidence about the landscape of pathology testing and diagnostics in Australian general practice, due to a lack of reliable data and expertise in data management, information systems and quality improvement infrastructures[28]. The research partners in this project have been amongst the first in Australia to successfully use and analyse electronic patient data from general practice and evaluate patient outcomes in both cross sectional and longitudinal studies[21, 23].
Sample size considerations
Current estimates suggest that the study will be centred on data from over 350 general practices. This will provide sufficient scope to detect significant variation in practices across patient and general practice demographic domains.
Analyses
Data examination and analysis will be performed using Stata/MP 16 (StataCorp),[29] R v4.0.2 (R Core Team)[30], SAS 9.4 (SAS Institute) statistical software[31] and ArcGIS (Environmental Systems Research Institute)[32] for geo-spatial reporting. Statistical methods will include descriptive and inferential statistics (e.g., exploratory analyses using descriptive statistics, t-test for group comparisions) depending on the components of the project. Where spatial or temporal evaluations are required, stochastic (e.g., mixed models) and deterministic models (e.g., Bayesian structural time series) will be developed as per the study aims, and if applicable, incorporated into machine learning for building prediction models. The methods outlined in this research protocol will be structured according to the reporting of studies conducted using observational routinely collected health data (RECORD)[33]. The RECORD checklist deals specifically with real world research and evaluation using routinely collected data from electronic health records such as that provided by electronic general practice sources[33]. It represents the current best practice standard to ensure the robust reporting on non-interventional research using routinely collected health data[33].
The study will involve four components:
1) The building of a meaningful near real-time COVID-19 geo-spatial reporting framework and dashboard for decision-makers at community, state and nation-wide levels, to identify and monitor emerging trends and the impact of interventions/policy decisions. This will include:
- Monitoring of the rates of COVID-19 testing in general practice.
- Examination of related general practice activities in the wake of COVID-19, particularly in relation to diagnostic (pathology and medical imaging) requests and medications.
- Key issues related to the identification of COVID-19 cases.
- Monitoring the impact of key risk factors (e.g., age, co-morbidities, smoking etc.)
- Identification of the impact of telehealth usage on the flexibility and responsiveness of general practice.
2) The generation of timely and critical evidence about the impact of the COVID-19 pandemic across the following care level dimensions:
- Clinical: Patient-level impacts based on:
- Diagnostics (Most common COVID-19 symptoms; alarm flags for COVID-19, e.g., white blood cells, lymphocytes, platelet counts; risk factors, e.g., smoking, respiratory failure etc.);
- Medications (The dangers of prescribing antiviral drugs e.g., drug-drug, drug-disease interactions; risks associated with chloroquine/hydroxychloroquine, ACE Inhibitors, aggravation of symptoms etc.); and,
- Patient care (Special considerations for treatment in pregnancy, care of infants, use of nebulisers, recommendations for paediatric patients etc.).
- Population: What populations are being impacted, not only from a direct COVID-19 perspective, but from a regular care perspective (e.g., impact on chronic disease, preventative care and mental health).
- Business: What impact has the COVID-19 pandemic had on general practice (e.g., number and types of services, tests, medications etc.) from a business and financial perspective? Types of interaction with patients, telehealth vs face-to-face, how has this worked, what are the immediate and future implications? How has this impacted patient care on a clinical level and population level?
3) Develop a predictive geo-spatial analytics dashboard for timely, evidence-based decision-making at community, state and nation-wide levels and include:
- Visual representations of patient status and clinical environments that change dynamically in near real-time.
- Risk prediction tools based on statistical modelling incorporating demographics, co-morbidities, patient symptoms and risk factors.
- Incorporation of displays and decision support features, tailored to the needs and preferences of key recipients including GPs, PHNs and government health agencies.
4) Establish an evidence-based suite of general practice outcome measures required to monitor the quality and effectiveness of care related to incidence, prevalence, recovery and mortality.
Patient and public involvement in research
Each of the project partners have strong track records of collaborative research which includes engagement with patients and the public. The Macquarie University research team has an established Consumer Reference Group made up of consumer representatives who have contributed to the design, development and promulgation of research aims[34, 35]. The Consumer Reference Group was initiated following a national stakeholder forum (which brought together representatives from 14 stakeholder groups including patient organisations, clinicians and healthcare professionals) that outlined key patient safety challenges related to the utilisation of digital health and the diagnostic process[35]. The project will draw on established PHN stakeholder (patient and public) involvement using design thinking approaches to inform research questions, the design and conduct of studies and choice of outcome measures.