POLAR Diversion: Using General Practice Data to Calculate Risk of Emergency Department Presentation at the Time of Consultation

Preconception health risk factors documented in general practice electronic medical records

BACKGROUND

Documenting medical and lifestyle preconception health risk factors in electronic medical records (EMRs) could assist general practitioners (GPs) to identify those reproductive-aged women who could most benefit from preconception care (PCC). However, it is unclear to what extent PCC risk factors are identifiable in general practice records. This study aimed to determine the extent to which medical and lifestyle preconception health risk factors are documented in general practice EMRs.

METHODS

We conducted an audit of the documentation of medical and lifestyle preconception risk factors in 10 general practice EMRs in Melbourne, Australia. We retrospectively analysed the EMRs of 100 consecutive women aged 18-44 years who visited each practice between January and September 2022. Using a template informed by PCC guidelines, we extracted data from structured fields in the EMR and conducted a descriptive analysis.

RESULTS

Among the data extracted, the more commonly documented medical and lifestyle preconception health risk factors in the EMRs included smoking (79%), blood pressure (74%), alcohol consumption (63%) and body mass index (57%). Among the women audited, 14% were smokers, 24% were obese, 7% had high blood pressure, 5% had diabetes, 28% had a mental health condition, 13% had asthma, 6% had thyroid disease and 17% had been prescribed and could be using a potentially teratogenic medication.

CONCLUSIONS

Better documentation of medical and lifestyle preconception health risk factors in structured fields in EMRs may potentially assist primary care providers including GPs in identifying and providing PCC to women who could most benefit from it.

Value‐based primary care in Australia: how far have we travelled?

In this article, we discuss how the value‐based health care concept has matured across recent years, and consider how it can be achieved in the primary health care sector.

We provide illustrations of related initiatives across the four domains of value‐based health care, highlight the need for cultural transformation and reorientation of the system, and call for a national framework and agreed plan of action.

Responding to COVID-19 with real-time general practice data in Australia

INTRODUCTION

As SARS-CoV-2 spread around the world, Australia was no exception. Part of the Australian response was a robust primary care approach, involving changes to care models (including telehealth) and the widespread use of data to inform the changes. This paper outlines how a large primary care database responded to provide real-time data to inform policy and practice. Simply extracting the data is not sufficient. Understanding the data is. The POpulation Level Analysis and Reporting (POLAR) program is designed to use GP data for multiple objectives and is built on a pre-existing engagement framework established over a fifteen-year period. Initially developed to provide QA activities for general practices and population level data for General Practice support organisations, the POLAR platform has demonstrated the critical ability to design and deploy real-time data analytics solutions during the COVID-19 pandemic for a variety of stakeholders including state and federal government agencies.

METHODS

The system extracts and processes data from over 1,300 general practices daily. Data is de-identified at the point of collection and encrypted before transfer. Data cleaning for analysis uses a variety of techniques, including Natural Language Processing and coding of free text information. The curated dataset is then distilled into several analytic solutions designed to address specific areas of investigation of interest to various stakeholders. One such analytic solution was a model we created that used multiple data inputs to rank patient geographic areas by the likelihood of a COVID-19 outbreak. The model utilised pathology ordering, COVID-19 related diagnoses, indication of COVID-19 related concern (via progress notes) and also incorporated state based actual confirmed case figures.

RESULTS

Using the methods described, we were able to deliver real-time data feeds to practices, Primary Health Networks (PHN) and other agencies. In addition, we developed a COVID-19 geographic risk stratification based on local government areas (LGAs) to pro-actively inform the primary care response. Providing PHNs with a list of geographic priority hotspots allowed for better targeting and response of Personal Protective Equipment allocation and pop-up clinic placement.

CONCLUSIONS

The program summarised here demonstrates the ability of a well-designed system underpinned by accurate and reliable data, to respond in real-time to a rapidly evolving public health emergency in a way which supports and enhances the health system response.

Lumos: a statewide linkage programme in Australia integrating general practice data to guide system redesign

Objective

With ageing of the Australian population, more people are living longer and experiencing chronic or complex health conditions. The challenge is to have information that supports the integration of services across the continuum of settings and providers, to deliver person-centred, seamless, efficient and effective healthcare. However, in Australia, data are typically siloed within health settings, precluding a comprehensive view of patient journeys. Here, we describe the establishment of the Lumos programme—the first statewide linked data asset across primary care and other settings in Australia and evaluate its representativeness to the census population.

Methods and analysis

Records extracted from general practices throughout New South Wales (NSW), Australia’s most populous state, were linked to patient records from acute and other settings. Innovative privacy and security technologies were employed to facilitate ongoing and regular updates. The marginal demographic distributions of the Lumos cohort were compared with the NSW census population by calculating multiple measures of representation to evaluate its generalisability.

Results

The first Lumos programme data extraction linked 1.3 million patients’ general practice records to other NSW health system data. This represented 16% of the NSW population. The demographic distribution of patients in Lumos was >95% aligned to that of the NSW population in the calculated measures of representativeness.

Conclusion

The Lumos programme delivers an enduring, regularly updated data resource, providing unique insights about statewide, cross-setting healthcare utilisation. General practice patients represented in the Lumos data asset are representative of the NSW population overall. Lumos data can reliably be used to identify at-risk regions and groups, to guide the planning and design of health services and to monitor their impact throughout NSW.

Predictors of ED attendance in older patients with chronic disease: a data linkage study

Objective Older people represent a large proportion of emergency department (ED) presentations, with multiple comorbidities a strong predictor of frequent attendance. This study examined associations between the general practice management received by older patients with chronic disease and ED attendance. Methods This retrospective study examined linked data from general practice and ED for patients aged ≥65 years who presented to a general practitioner (GP) between 2010 and 2014. Data from the computerised medical records of patients attending 50 general practice clinics in the inner east Melbourne region ere linked with ED attendance data from the same region. Patients with chronic disease were identified and characteristics of ED versus non-ED attendees were compared. Poisson regression was used to explore factors associated with ED usage. Results During the study period, 67474 patients aged ≥65 years visited a GP, with 63.3% identified as having at least one chronic condition and 21.4% of these having at least one ED presentation. Over 70% of the ED presentations in this group resulted in hospital admissions. The most common diagnoses for ED presentation were cardiovascular disorders, pain and injuries. ED attendance was associated with being aged ≥85 years (incidence rate ratio (IRR) 2.09; 95% confidence interval (CI) 1.96-2.11), higher socioeconomic status (IRR 1.49; 95% CI 1.45-1.53), having a GP management plan (IRR 1.47; 95% CI 1.43-1.52), multimorbidity (IRR 1.53; 95% CI 1.46-1.60), more frequent GP visits (IRR 1.10; 95% CI 1.05-1.15) and having a higher numbers of prescriptions (IRR 1.51; 95% CI 1.44-1.57). Conclusion This study suggests that ED presentation is associated with greater frailty and multimorbidity in patients. Further research is necessary to determine why higher rates of chronic disease management through GP management plans and more frequent visits did not mediate higher rates of presentation and the reasons behind the socioeconomic differences in ED presentation for patients in this age group. What is known about the topic? Increases in the volume and rate of ED presentations by older people will markedly affect emergency and acute hospital care and patient flow as the proportion of older Australians increases. What does this paper add? We used a novel and highly transferable data linkage between data collected from the clinical records of general practice patients and their associated data from ED and hospital settings and examined the relationship between GP management received by older patients with chronic disease and ED attendance. What are the implications for practitioners? Increasing utilisation of GP services may not have an effect on reducing ED attendance, particularly for older patients who may experience poorer overall health.