scholarly journals 629Influenza-like illness surveillance in Australia: comparison of general practice data with laboratory-confirmed influenza notifications

2021 ◽  
Vol 50 (Supplement_1) ◽  
Author(s):  
Carla Bernardo ◽  
David Gonzalez ◽  
Nigel Stocks

Abstract Background Influenza is a respiratory infection responsible for 645,000 annual deaths worldwide. Surveillance systems provide valuable data for monitoring influenza in order to detect outbreaks and guide public health responses. This study aimed to investigate the epidemiology of influenza-like illness (ILI) using two Australian general practice databases (MedicineInsight and the Australian Sentinel Practice Research Network (ASPREN)) and compare them with laboratory-confirmed influenza from the National Notifiable Diseases Surveillance System (NNDSS). Methods All patients who had a consultation in MedicineInsight general practices or ASPREN and all laboratory-confirmed influenza reported by the NNDSS between 2015-2017 were included. Weekly ILI rates per 1,000 consultations (MedicineInsight/ASPREN) were compared with influenza notifications (NNDSS). Results Data was consistent among sources, with higher cases in 2017, among women and patients aged 20-49 years. The peak rate in MedicineInsight almost doubled in 2017 compared to 2015, while in ASPREN it was less pronounced. MedicineInsight ILI curves more closely resembled NNDSS patterns (shape, the start of the season, peaks) than ASPREN, although both were highly correlated with NNDSS (r = 0.90 to 0.97 and r = 0.88 to 0.98, respectively). Conclusions MedicineInsight and ASPREN provided consistent ILI results, both resembling confirmed influenza epidemic curves, suggesting the potential use of routinely collected electronic medical records (MedicineInsight) in influenza surveillance. MedicineInsight provides comprehensive medical data, such as underlying conditions, medications prescribed and vaccination status, which could be used to improve accuracy on influenza detection. Key messages Electronic medical records could be used to monitor ILI in combination with ASPREN for effective early detection of outbreaks.

2021 ◽  
Vol 50 (Supplement_1) ◽  
Author(s):  
Carla Bernardo ◽  
David Gonzalez-Chica ◽  
Jackie Roseleur ◽  
Luke Grzeskowiak ◽  
Nigel Stocks

Abstract Focus and outcomes for participants Modern technologies offer innovative ways of monitoring health outcomes. Electronic medical records (EMRs) stored in primary care databases provide comprehensive data on infectious and chronic conditions such as diagnosis, medications prescribed, vaccinations, laboratory results, and clinical assessments. Moreover, they allow the possibility of creating a retrospective cohort that can be tracked over time. This rich source of data can be used to generate results that support health policymakers to improve access, reduce health costs, and increase the quality of care. The symposium will discuss the use and future of routinely-collected EMR databases in monitoring health outcomes, using as an example studies based on the MedicineInsight program, a large general practice Australian database including more than 3.5 million patients. This symposium welcomes epidemiologists, researchers and health policymakers who are interested in primary care settings, big data analysis, and artificial intelligence. Rationale for the symposium, including for its inclusion in the Congress EMRs are becoming an important tool for monitoring health outcomes in different high-income countries and settings. However, most countries lack a national primary care database collating EMRs for research purposes. Monitoring of population health conditions is usually performed through surveys, surveillance systems, or census that tend to be expensive or performed over longer time intervals. In contrast, EMR databases are a useful and low-cost method to monitor health outcomes and have shown consistent results compared to other data sources. Although these databases only include individuals attending primary health settings, they tend to resemble the sociodemographic distribution from census data, as in countries such as Australia up to 90% of the population visit these services annually. Results from primary care-based EMRs can be used to inform practices and improve health policies. Analysis from EMRs can be used to identify, for example, those with undiagnosed medical conditions or patients who have not received recommended screenings or immunisations, therefore assessing the impact of government programmes. At a practice-level, healthcare staff can have better access to comprehensive patient histories, improving monitoring of people with certain conditions, such as chronic cardiac, respiratory, metabolic, neurological, or immunological diseases. This information provides feedback to primary care providers about the quality of their care and might help them develop targeted strategies for the most-needed areas or groups. Another benefit of EMRs is the possibility of using statistical modelling and machine learning to improve prediction of health outcomes and medical management, supporting general practitioners with decision making on the best management approach. In Australia, the MedicineInsight program is a large general practice database that since 2011 has been routinely collecting information from over 650 general practices varying in size, billing methods, and type of services offered, and from all Australian states and regions. In the last few years, diverse researchers have used MedicineInsight to investigate infectious and chronic diseases, immunization coverage, prescribed medications, medical management, and temporal trends in primary care. Despite being initially created for monitoring how medicines and medical tests are used, MedicineInsight has overcome some of the legal, ethical, social and resource-related barriers associated with the use of EMRs for research purposes through the involvement of a data governance committee responsible for the ethical, privacy and security aspects of any research using this data, and through applying data quality criteria to their data extraction. This symposium will discuss advances in the use of primary care databases for monitoring health outcomes using as an example the research activities performed based on the Australian MedicineInsight program. These discussions will also cover challenges in the use of this database and possible methodological innovations, such as statistical modelling or machine learning, that could be used to improve monitoring of the epidemiology and management of health conditions. Presentation program The use of large general practice databases for monitoring health outcomes in Australia: infectious and chronic conditions (Professor Nigel Stocks) How routinely collected electronic health records from MedicineInsight can help inform policy, research and health systems to improve health outcomes (Ms Rachel Hayhurst) Influenza-like illness in Australia: how can we improve surveillance systems in Australia using electronic medical records? (Dr Carla Bernardo) Long term use of opioids in Australian general practice (Dr David Gonzalez) Using routinely collected electronic health records to evaluate Quality Use of Medicines for women’s reproductive health (Dr Luke Grzeskowiak) The use of electronic medical records and machine learning to identify hypertensive patients and factors associated with controlled hypertension (Ms Jackie Roseleur) Names of presenters Professor Nigel Stocks, The University of Adelaide Ms Rachel Hayhurst, NPS MedicineWise Dr Carla Bernardo, The University of Adelaide Dr David Gonzalez-Chica, The University of Adelaide Dr Luke Grzeskowiak, The University of Adelaide Ms Jackie Roseleur, The University of Adelaide


Author(s):  
Simon de Lusignan ◽  
Jamie Lopez Bernal ◽  
Maria Zambon ◽  
Oluwafunmi Akinyemi ◽  
Gayatri Amirthalingam ◽  
...  

BACKGROUND The Royal College of General Practitioners (RCGP) Research and Surveillance Centre (RSC) and Public Health England (PHE) have successfully worked together on the surveillance of influenza and other infectious diseases for over 50 years, including three previous pandemics. With the emergence of the international outbreak of the coronavirus infection (COVID-19), a UK national approach to containment has been established to test people suspected of exposure to COVID-19. At the same time and separately, the RCGP RSC’s surveillance has been extended to monitor the temporal and geographical distribution of COVID-19 infection in the community as well as assess the effectiveness of the containment strategy. OBJECTIVE The aim of this study is the surveillance of COVID-19 in both asymptomatic populations and ambulatory cases with respiratory infections to ascertain both the rate and pattern of COVID-19 spread and to assess the effectiveness of the containment policy. METHODS The RCGP RSC, a network of over 500 general practices in England, extract pseudonymized data weekly. This extended surveillance comprises of five components: (1) Recording in medical records of anyone suspected to have or who has been exposed to COVID-19. Computerized medical records suppliers have within a week of request created new codes to support this. (2) Extension of current virological surveillance and testing people with influenza-like illness or lower respiratory tract infections (LRTI)—with the caveat that people suspected to have or who have been exposed to COVID-19 should be referred to the national containment pathway and not seen in primary care. (3) Serology sample collection across all age groups. This will be an extra blood sample taken from people who are attending their general practice for a scheduled blood test. The 100 general practices currently undertaking annual influenza virology surveillance will be involved in the extended virological and serological surveillance. (4) Collecting convalescent serum samples. (5) Data curation. We have the opportunity to escalate the data extraction to twice weekly if needed. Swabs and sera will be analyzed in PHE reference laboratories. RESULTS General practice clinical system providers have introduced an emergency new set of clinical codes to support COVID-19 surveillance. Additionally, practices participating in current virology surveillance are now taking samples for COVID-19 surveillance from low-risk patients presenting with LRTIs. Within the first 2 weeks of setup of this surveillance, we have identified 3 cases: 1 through the new coding system, the other 2 through the extended virology sampling. CONCLUSIONS We have rapidly converted the established national RCGP RSC influenza surveillance system into one that can test the effectiveness of the COVID-19 containment policy. The extended surveillance has already seen the use of new codes with 3 cases reported. Rapid sharing of this protocol should enable scientific critique and shared learning. INTERNATIONAL REGISTERED REPORT DERR1-10.2196/18606


10.2196/18606 ◽  
2020 ◽  
Vol 6 (2) ◽  
pp. e18606 ◽  
Author(s):  
Simon de Lusignan ◽  
Jamie Lopez Bernal ◽  
Maria Zambon ◽  
Oluwafunmi Akinyemi ◽  
Gayatri Amirthalingam ◽  
...  

Background The Royal College of General Practitioners (RCGP) Research and Surveillance Centre (RSC) and Public Health England (PHE) have successfully worked together on the surveillance of influenza and other infectious diseases for over 50 years, including three previous pandemics. With the emergence of the international outbreak of the coronavirus infection (COVID-19), a UK national approach to containment has been established to test people suspected of exposure to COVID-19. At the same time and separately, the RCGP RSC’s surveillance has been extended to monitor the temporal and geographical distribution of COVID-19 infection in the community as well as assess the effectiveness of the containment strategy. Objectives The aims of this study are to surveil COVID-19 in both asymptomatic populations and ambulatory cases with respiratory infections, ascertain both the rate and pattern of COVID-19 spread, and assess the effectiveness of the containment policy. Methods The RCGP RSC, a network of over 500 general practices in England, extract pseudonymized data weekly. This extended surveillance comprises of five components: (1) Recording in medical records of anyone suspected to have or who has been exposed to COVID-19. Computerized medical records suppliers have within a week of request created new codes to support this. (2) Extension of current virological surveillance and testing people with influenza-like illness or lower respiratory tract infections (LRTI)—with the caveat that people suspected to have or who have been exposed to COVID-19 should be referred to the national containment pathway and not seen in primary care. (3) Serology sample collection across all age groups. This will be an extra blood sample taken from people who are attending their general practice for a scheduled blood test. The 100 general practices currently undertaking annual influenza virology surveillance will be involved in the extended virological and serological surveillance. (4) Collecting convalescent serum samples. (5) Data curation. We have the opportunity to escalate the data extraction to twice weekly if needed. Swabs and sera will be analyzed in PHE reference laboratories. Results General practice clinical system providers have introduced an emergency new set of clinical codes to support COVID-19 surveillance. Additionally, practices participating in current virology surveillance are now taking samples for COVID-19 surveillance from low-risk patients presenting with LRTIs. Within the first 2 weeks of setup of this surveillance, we have identified 3 cases: 1 through the new coding system, the other 2 through the extended virology sampling. Conclusions We have rapidly converted the established national RCGP RSC influenza surveillance system into one that can test the effectiveness of the COVID-19 containment policy. The extended surveillance has already seen the use of new codes with 3 cases reported. Rapid sharing of this protocol should enable scientific critique and shared learning. International Registered Report Identifier (IRRID) DERR1-10.2196/18606


2004 ◽  
Vol 13 (11) ◽  
pp. 749-759 ◽  
Author(s):  
Janet R. Hardy ◽  
Theodore R. Holford ◽  
Gillian C. Hall ◽  
Michael B. Bracken

2018 ◽  
Author(s):  
Cheng-Yi Yang ◽  
Ray-Jade Chen ◽  
Wan-Lin Chou ◽  
Yuarn-Jang Lee ◽  
Yu-Sheng Lo

BACKGROUND Influenza is a leading cause of death worldwide and contributes to heavy economic losses to individuals and communities. Therefore, the early prediction of and interventions against influenza epidemics are crucial to reduce mortality and morbidity because of this disease. Similar to other countries, the Taiwan Centers for Disease Control and Prevention (TWCDC) has implemented influenza surveillance and reporting systems, which primarily rely on influenza-like illness (ILI) data reported by health care providers, for the early prediction of influenza epidemics. However, these surveillance and reporting systems show at least a 2-week delay in prediction, indicating the need for improvement. OBJECTIVE We aimed to integrate the TWCDC ILI data with electronic medical records (EMRs) of multiple hospitals in Taiwan. Our ultimate goal was to develop a national influenza trend prediction and reporting tool more accurate and efficient than the current influenza surveillance and reporting systems. METHODS First, the influenza expertise team at Taipei Medical University Health Care System (TMUHcS) identified surveillance variables relevant to the prediction of influenza epidemics. Second, we developed a framework for integrating the EMRs of multiple hospitals with the ILI data from the TWCDC website to proactively provide results of influenza epidemic monitoring to hospital infection control practitioners. Third, using the TWCDC ILI data as the gold standard for influenza reporting, we calculated Pearson correlation coefficients to measure the strength of the linear relationship between TMUHcS EMRs and regional and national TWCDC ILI data for 2 weekly time series datasets. Finally, we used the Moving Epidemic Method analyses to evaluate each surveillance variable for its predictive power for influenza epidemics. RESULTS Using this framework, we collected the EMRs and TWCDC ILI data of the past 3 influenza seasons (October 2014 to September 2017). On the basis of the EMRs of multiple hospitals, 3 surveillance variables, TMUHcS-ILI, TMUHcS-rapid influenza laboratory tests with positive results (RITP), and TMUHcS-influenza medication use (IMU), which reflected patients with ILI, those with positive results from rapid influenza diagnostic tests, and those treated with antiviral drugs, respectively, showed strong correlations with the TWCDC regional and national ILI data (r=.86-.98). The 2 surveillance variables—TMUHcS-RITP and TMUHcS-IMU—showed predictive power for influenza epidemics 3 to 4 weeks before the increase noted in the TWCDC ILI reports. CONCLUSIONS Our framework periodically integrated and compared surveillance data from multiple hospitals and the TWCDC website to maintain a certain prediction quality and proactively provide monitored results. Our results can be extended to other infectious diseases, mitigating the time and effort required for data collection and analysis. Furthermore, this approach may be developed as a cost-effective electronic surveillance tool for the early and accurate prediction of epidemics of influenza and other infectious diseases in densely populated regions and nations.


2013 ◽  
Vol 19 (2) ◽  
pp. 150 ◽  
Author(s):  
Diann S. Eley ◽  
Elizabeth Patterson ◽  
Jacqui Young ◽  
Paul P. Fahey ◽  
Chris B. Del Mar ◽  
...  

The Australian government’s commitment to health service reform has placed general practice at the centre of its agenda to manage chronic disease. Concerns about the capacity of GPs to meet the growing chronic disease burden has stimulated the implementation and testing of new models of care that better utilise practice nurses (PN). This paper reports on a mixed-methods study nested within a larger study that trialled the feasibility and acceptability of a new model of nurse-led chronic disease management in three general practices. Patients over 18 years of age with type 2 diabetes, hypertension or stable ischaemic heart disease were randomised into PN-led or usual GP-led care. Primary outcomes were self-reported quality of life and perceptions of the model’s feasibility and acceptability from the perspective of patients and GPs. Over the 12-month study quality of life decreased but the trend between groups was not statistically different. Qualitative data indicate that the PN-led model was acceptable and feasible to GPs and patients. It is possible to extend the scope of PN care to lead the routine clinical management of patients’ stable chronic diseases. All GPs identified significant advantages to the model and elected to continue with the PN-led care after our study concluded.


Author(s):  
Patricia Deering ◽  
Arthur Tatnall ◽  
Stephen Burgess

ICT has been used in medical General Practice throughout Australia now for some years, but although most General Practices make use of ICT for administrative purposes such as billing, prescribing and medical records, many individual General Practitioners themselves do not make full use of these ICT systems for clinical purposes. The decisions taken in the adoption of ICT in general practice are very complex, and involve many actors, both human and non-human. This means that actor-network theory offers a most suitable framework for its analysis. This article investigates how GPs in a rural Division of General Practice not far from Melbourne considered the adoption and use of ICT. The study reported in the article shows that, rather than characteristics of the technology itself, it is often seemingly unimportant human issues that determine if and how ICT is used in General Practice.


2020 ◽  
Vol 12 (4) ◽  
pp. 373
Author(s):  
Steven Lillis ◽  
Liza Lack

ABSTRACT INTRODUCTIONRepeat prescribing is common in New Zealand general practice. Research also suggests that repeat prescribing is a process prone to error. All New Zealand general practices have to comply with requirements to have a repeat prescribing policy, with the details of the policy to be designed by the practice. AIMTo inform the development of practice policy, research was undertaken with experienced general practitioners to identify and mitigate risk in the process. METHODSAt the 2019 annual conference of the Royal New Zealand College of General Practitioners, a workshop was held with 58 experienced general practitioner participants. The group was divided into six small groups, each with the task of discussing one aspect of the repeat prescribing process. The results were then discussed with the whole group and key discussion points were transcribed and analysed. RESULTSIssues identified included: improving patient education on appropriateness of repeat prescribing; having protected time for medicine reconciliation and the task of repeat prescribing; reducing the number of personnel and steps in the process; and clarity over responsibility for repeat prescribing. DISCUSSIONThis research can inform the local development of a repeat prescribing policy at the practice level or be used to critique existing practice policies. Attention was also drawn to the increasing administrative burden that repeat prescribing contributes to in general practice.


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