CC BY-NC-ND 4.0 · Yearb Med Inform 2022; 31(01): 047-059
DOI: 10.1055/s-0042-1742502
Special Section: Inclusive Digital Health
Working Group Contributions

Towards Equitable and Resilient Digital Primary Care Systems: An International Comparison and Insight for Moving Forward

IMIA Primary Care Informatics Working Group
Craig Kuziemsky
1   Office of Research Services and the School of Business, MacEwan University, Edmonton, Alberta, Canada
,
Siaw-Teng Liaw
2   WHO Collaborating Centre on eHealth, School of Population Health, UNSW Sydney, Kensington, NSW, Australia
,
Meredith Leston
3   Clinical Informatics and Health Outcomes Research Group, Nuffield Department of Primary Care Health Sciences, University of Oxford, Eagle House, Oxford, UK
,
Christopher Pearce
5   Outcome Health, Blackburn, Victoria, Australia
6   Monash University, Clayton, Victoria, Australia
,
Jitendra Jonnagaddala
2   WHO Collaborating Centre on eHealth, School of Population Health, UNSW Sydney, Kensington, NSW, Australia
,
Simon de Lusignan
3   Clinical Informatics and Health Outcomes Research Group, Nuffield Department of Primary Care Health Sciences, University of Oxford, Eagle House, Oxford, UK
4   Royal College of General Practitioners Research and Surveillance Centre, London, UK
› Author Affiliations
 

Summary

Objective: While the COVID-19 pandemic provided a global stimulus for digital health capacity, its development has often been inequitable, short-term in planning, and lacking in health system coherence. Inclusive digital health and the development of resilient health systems are broad outcomes that require a systematic approach to achieving them. This paper from the IMIA Primary Care Informatics Working Group (WG) provides necessary first steps for the design of a digital primary care system that can support system equity and resilience.

Methods: We report on digital capability and growth in maturity in four key areas: (1) Vaccination/Prevention, (2) Disease management, (3) Surveillance, and (4) Pandemic preparedness for Australia, Canada, and the United Kingdom (data from England). Our comparison looks at seasonal influenza management prior to COVID-19 (2019-20) compared to COVID-19 (winter 2020 onwards).

Results: All three countries showed growth in digital maturity from the 2019-20 management of influenza to the 2020-21 year and the management of the COVID-19 pandemic. However, the degree of progress was sporadic and uneven and has led to issues of system inequity across populations.

Conclusion: The opportunity to use the lessons learned from COVID-19 should not be wasted. A digital health infrastructure is not enough on its own to drive health system transformation and to achieve desired outcomes such as system equity and resilience. We must define specific measures to track the growth of digital maturity, including standardized and fit-for-context data that is shared accurately across the health and socioeconomic sectors.


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1 Introduction

Much has been written about how the COVID-19 was the push needed for digital health expansion at a global level [[1], [2]]. Digital health models emerged that offer promise for more robust health delivery systems going forward. However, we also know that health systems are learning health systems and our goal must be to develop a health system that is sustainable in the long term and not to simply to develop tools or approaches to manage COVID-19. To that end, we know that the digital response to COVID-19 has also generated unintended consequences, including equity issues and uneven access to healthcare services [[3] [4] [5]]. To develop health delivery systems that are equitable for everyone we need to focus on the entire spectrum of system components and not just the technology aspect.

Digital health maturity refers to the structured way that behaviors, structures, and processes are aligned to reliably achieve desired outcomes from the use of digital health [[6]]. Digital health maturity models enable us to monitor and track the progress of digital health solutions over time so that we can create positive health outcomes while mitigating any unintended consequences. The COVID-19 pandemic and its resultant public health measures and social restrictions (including periods of local and national lockdown) led to a global acceleration in the uptake of digital care delivery models. Virtual care tools such as telehealth enabled core micro level tasks like home monitoring, virtual health assessments, medication review, education and support for patients and families and coordination between family doctors [[7] [8]]. At a macro level, digital health tools and methods effectively supported essential tasks like disease surveillance and contact tracing [[9]].

While digital health solutions were essential in supporting regional, national and global responses to COVID-19, the benefit from these solutions were not shared equally across all populations. Negative unintended consequences (UICs) including inequity issues and uneven transition of some tasks to digital format were commonplace [[10] [11] [12]]. UICs often occur during and post health information technology (HIT) implementation [[13], [14]]. However, we cannot focus on technology as a direct cause of UICs and instead need to assess the respective contributions and of social, policy and organisational factors and their myriad interactions [[15] [16] [17]]. Designing health systems that are resilient and equitable for all citizens is not a one-time task but rather an ongoing one that requires a learning health system approach [[18]]. A digital health maturity lens enables systems design that considers how digital health capabilities and competencies are developed over time as a precursor to building a resilient and equitable health system.

Relevant to primary care was that the pandemic-mediated move to virtual care did not benefit all citizens equally but rather certain communities such as those with socioeconomic risk factors were underserved by comparison and suffered more adverse outcomes overall [[19] [20]]. Similarly, uneven development of digital tools and capacity created adverse outcomes because of partial or underdeveloped virtual care models [[21]]. Our global desire to develop a digital primary care system cannot only focus on technology but rather must provide a systematic approach for the design of a resilient and equitable primary care system [[22]]. Digital health interventions can worsen existing health system inequities [[23]]. This trend was observed during COVID-19 where digital inequities led to poor health outcomes [[24]]. Other system factors including social, political, and human resource factors must be co-designed with the technology used to support healthcare transformation [[15]]. While the configuration and design of resilient and equitable health systems is a universal goal, we need to make sustained incremental progress to get to this goal. Gathering evidence on how digital health tools are adopted and implemented into primary care delivery over time is an essential first step to achieving our overall goal [[25]].

This paper from the IMIA Primary Care Informatics Working Group (WG) provides necessary first steps for the design of a digital primary care system that can support system equity and resilience. We use the concept of digital maturity to study the growth of primary care informatics during the COVID-19 pandemic. We look at digital health capacity in primary care in three countries (Australia, Canada, England) before and during the COVID-19 pandemic to understand how digital healthcare has evolved and how we can continue to build resilient and equitable primary care systems. We then use our analysis to offer a set of recommendations for developing digital primary care capacity to support resilient and equitable primary care delivery.


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2 Methods

We based our study on a digital health maturity conceptual framework, comparing maturity in the influenza and COVID-19 domains. The WG consensus was to report digital capability and growth in digital maturity in four key areas: (1) Vaccination/Prevention, (2) Disease management, (3) Surveillance, and (4) Pandemic preparedness. We review each of those categories across four foundational aspects of digital health maturity: essential IT infrastructure, essential digital tools, readiness of information sharing and readiness of health system/enabling environment, drawing upon a digital health maturity framework [[6]]. Our data sources for the work came from a variety of publications, reports, government documents and websites in the three countries.

Our first level of analysis looks at each of the four digital maturity categories for seasonal influenza management prior to COVID-19 (2019-20). We then carry out the same analysis for the digital health capacity that emerged during COVID-19 (winter 2020 onwards), with an emphasis on the differences between influenza and COVID-19. We provide a synopsis of each country followed by a discussion that provides global comparison across the three countries.


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3 Results

Our results are first presented at a country level with data tables for Australia, Canada, and the United Kingdom (data from England). We then provide a synopsis for each country followed by an integrated discussion.

3.1 Australia

[Table 1] describes Digital Health Maturity Foundations by Prevention/Vaccination, Disease Mx, Surveillance & Pandemic preparedness for Australia with a comparison between influenza in 2019-20 and the COVID-19 pandemic (winter 2020 and beyond).

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Table 1 Digital Health Maturity Foundations by Prevention/Vaccination, Disease Mx, Surveillance & Pandemic preparedness for Seasonal Influenza and COVID-19 in Australia.
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Table 1 continued Digital Health Maturity Foundations by Prevention/Vaccination, Disease Mx, Surveillance & Pandemic preparedness for Seasonal Influenza and COVID-19 in Australia.

Australia Synopsis

Australia has a national digital health strategy, released in 2017, that is focused on development of digital health capability and integration within the health system, to support the availability, exchange and quality of health information, and its subsequent use to support innovative models of care. (https://conversation.digitalhealth.gov.au/australias-national-digital-health-strategy). A key element is a national online, personally-controlled, shared health summary, called My Health Record (mHR) [[26]]. Australian GP data repositories include POLAR [[27]] and MedicineInsight [[28]]. The Australian Sentinel Practices Research Network (ASPREN) is a network of sentinel general practitioners and nurse practitioners who report de-identified information on Influenza like illness and other conditions seen in general practice (https://aspren.dmac.adelaide.edu.au/).

The Australian National Framework for Communicable Disease Control (https://www1.health.gov.au/internet/main/publishing.nsf/Content/ohp-nat-frame-communic-disease-control.htm) is a foundation of the Australian Health Sector Emergency Response Plan for Novel Coronavirus (the COVID-19 Plan), which guides the Australian health sector response. (https://www.health.gov.au/resources/publications/australian-health-sector-emergency-response-plan-for-novel-coronavirus-covid-19). The Australian Technical Advisory Group on Immunisation (ATAGI) advises the Minister for Health on the National Immunisation Program (NIP) and other immunisation issues (https://www.health.gov.au/committees-and-groups/australian-technical-advisory-group-on-immunisation-atagi#members).

There was limited flu in Australia during 2020, which dropped away rapidly in March 2020 with virtually no flu about in 2021. POLAR showed an increase in influenza testing, as part of opportunistic testing for multiple viruses, with little positive identification of influenza. Eventually, GPs were advised to cease test requests for influenza as there just wasn't any. Little swabs were done in general practice because of financial losses from shutdown of practices for two weeks if a positive case was detected in the practice. POLAR data showed that over half the participating general practices in NSW and Victoria assessed symptomatic patients by telephone, variations on the car park consultation or through dedicated GP respiratory clinics established as part of the COVID-19 response. PPEs were provided to general practices via Primary Health Networks (PHN). However, the success varied according to variable quality of PHNs and supply chain. COVID vaccination was initially undertaken in Federal and state vaccination hubs and workplace. When general practice started in May 2021, they could only provide Vaxzevia (AstraZeneca). The AstraZeneca-Pfizer competition and an overly cautious ATAGI led to a lack of public confidence in Vaxzevia and people waited for emergency purchases of the Pfizer vaccine to come about. GP vaccination rapidly became, with the state hubs, the main sources of vaccination. Interpretation of GP vaccination data requires an understanding of these developments.

The essential DH foundations are at various levels of maturity. The Internet Communication and Technology (ICT) and Internet of things (IoT) infrastructure are robust and reliable, but the issue of access and inequity is an issue especially from the rural and other disadvantaged patient and citizen perspectives. Similarly, primary care and general practice varied in their investments and maturity in their digital infrastructure. Government initiatives and funding for “telehealth” helped to a certain extent but reinforced existing strengths with the telephone rather than encouraged more video consultations.

A range of digital tools were available for use by patients and providers especially for telehealth and home telemonitoring in NCD contexts [[29]]. The AusVaxxSafety (https://ausvaxsafety.org.au/) program is an example of Pre-COVID vaccine safety monitoring. Many tools, including home telemonitoring apps were repurposed for use as standalones or as part of a COVID-19 response system to support community-based management of NCDs with or without COVID infections. Many funded COVID-specific initiatives failed amid controversial governance and funding arrangements by governments. The major question here is whether COVID-prompted development of new digital tools is fit for purpose and sustainable, highlighting the need for systematic evidence-based evaluation [[30]].

The National Interoperable Notifiable Diseases Surveillance System (NINDSS) is an example of health information sharing, but only in one direction (state to national). The transmission of data may be synchronous in some way in terms of acknowledging successful receipt and upload. The NSW Notifiable Conditions Information Management System (NCIMS) was significantly altered to accommodate the extra information collected for the surveillance of COVID-19, including every reportable COVID test. Surveillance information collected is largely guided by the national guideline (https://www1.health.gov.au/internet/main/publishing.nsf/Content/cdna-song-novel-coronavirus.htm). However, while the NCIMS captured every reportable COVID test, only aggregate counts were shared with the national department, not notifications. Also, daily reporting on notifiable diseases is usually a state responsibility, so the NINDSS would have required significant investment to achieve that for national COVID-19 daily reporting. Daily reporting was available to some PHNs, but not all. Weekly national surveillance meetings are held to discuss data field definitions and alignment across jurisdictions. The mandated use of the Australian Immunisation Registry (AIR) for COVID vaccinations also helped the ongoing national response.

Post-pandemic, the mHR can potentially enhance information sharing in the management of “long COVID” and monitoring of vaccination and vaccine safety. This requires good documentation culture and good health information sharing across the continuum of care and health services. The enabling environment evolved quickly, including appropriate regulations and policies as well as capacity building programs in R&D and training of health professionals and citizens. However, the quality improvement environment is less well defined despite a few Centres for Research Excellence funded for COVID-related topics.


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3.2 Canada

[Table 2] describes Digital Health Maturity Foundations by Prevention/Vaccination, Disease Mx, Surveillance & Pandemic preparedness for Canada with a comparison between influenza in 2019-20 and the COVID-19 pandemic (winter 2020 and beyond).

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Table 2 Digital Health Maturity Foundations by Prevention/Vaccination, Disease Mx, Surveillance & Pandemic preparedness for Canada
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Table 2 continued Digital Health Maturity Foundations by Prevention/Vaccination, Disease Mx, Surveillance & Pandemic preparedness for Canada

Canada Synopsis

Canada showed an acceleration of digital tools in response to the COVID-19 pandemic. A study from the Canadian Institute of Health Information (CIHI) showed marked increase in the delivery of virtual care by physicians between February and November 2020 (https://www.cihi.ca/en/health-workforce-in-canada-highlights-of-the-impact-of-covid-19/increase-in-virtual-care-services) in a study of five provinces. Micro level digital tools for ePrescribing, COVID-19 exposure and contract tracing, uploading of vaccination records, and remote monitoring apps were developed. Macro level digital tools that provided general information on symptoms of COVID-19 and public health guidelines were also common. However, Canada also had some challenges in its response to the pandemic. Many of the digital tools were pilot projects that have not been formally evaluated to assess the value and impact of their sustained use. The rapid jump to virtual care delivery also lacked the necessary training to effectively transition patients and providers to virtual care [[10], [31]].

A system level challenge in Canada was that while many jurisdictions had been developing virtual care tools such as telehealth systems prior to the pandemic, they had not anticipated the rapid uptake of virtual care due to the pandemic [[10]]. This resulted in short term issues such as a lack of consensus on privacy and other regulatory issues, as well as more substantial system issues such as a lack of access to timely data and inequitable access to broadband internet [[32]]. Essential IT infrastructure did not change between influenza management in 2019-20 and the onset of COVID-19 in winter 2020. While widespread broadband internet access is available in urban areas, rural areas may lack needed technical infrastructure for a digitally driven pandemic response. With respect to availability of broadband internet, equity issues related to affordability, insufficient digital literacy, and socioeconomic issues persisted in the response to COVID-19. Further, inequity issues related to digital health became worse, or at least had greater impact during the COVID-19 pandemic due to the closure or reduction of face-to-face care delivery during public health measures such as lockdowns.

The Canadian health system response to the COVID-19 pandemic also exacerbated existing system issues. One example is the digital divide. Racial and ethnic minorities and those impacted by social determinants of health issues had worse health and social outcomes than other population groups [[19]]. This issue was not caused by the pandemic per se but rather was an example of how digital health can manifest inequity and other system issues. The solution moving forward to is address system issues such as health and digital literacy and equity prior to a pandemic.

Canada certainly had some health system successes in managing the COVID-19 pandemic. The increased development and dissemination of digital health capacity such as virtual care delivery is one example. However, we have also had some failures related to digital health deployment and scale of digital health tools. We must ensure that we use the pandemic as a learning experience to continue to push the needle on digital health maturity.

The overarching challenge that Canada must overcome is a lack of system level pandemic planning that would drive core tasks such as data access and sharing, design and scale up of digital tools, consumer engagement and training, and monitoring of desired system outcomes such as equitable access to services. We also need to recognize that structural elements such as IT infrastructure will not on their own bring about desired system change. System structures must be complemented with the system behaviors that are needed to achieve meaningful progress towards a resilient and equitable Canadian health system.


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3.3 United Kingdom (Data from England)

[Table 3] describes Digital Health Maturity Foundations by Prevention/Vaccination, Disease Mx, Surveillance & Pandemic preparedness for England with a comparison between influenza in 2019-20 and the COVID-19 pandemic (winter 2020 and beyond).

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Table 3 Digital Health Maturity Foundations by Prevention/Vaccination, Disease Mx, Surveillance & Pandemic preparedness for England.
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Table 3 continued Digital Health Maturity Foundations by Prevention/Vaccination, Disease Mx, Surveillance & Pandemic preparedness for England.
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Table 3 continued Digital Health Maturity Foundations by Prevention/Vaccination, Disease Mx, Surveillance & Pandemic preparedness for England.

UK (England) Synopsis

The NHS Long Term Plan [[33]] plainly states its intention to develop the digital maturity of the nation's healthcare ecosystem to achieve its ambitions for a coherent, paperless, and futureproofed NHS. Its flagship policies of disease prevention and care that is joined-up, personalised and increasingly community-based will only be accomplished through a robust digital infrastructure.

The UK government has a strong digital track-record to leverage, however, most notably regarding disease surveillance and response. The government has invested significant resource into sentinel networks, for example, and these have been tested and refined through several public health emergencies over the decades – most notably over the course of the COVID-19 pandemic and the concurrent circulation of seasonal illness. The unique centrality and consistency of the English healthcare system also lends itself well to executing these digital goals: here researchers, healthcare workers and civil servants alike can benefit from features including the NHS Number, NHS Staff ID and standardised SNOMED disease codification that collectively ensure data is rich, linkable, interoperable, and universally understandable. Furthermore, though sometimes accused of being labyrinthine, the centralised structure of the NHS means that the systems and standards that underpin healthcare provision are universal; they do not vary across localities as much as nations that bestow jurisdiction over both at the state-level.

In terms of digital maturity, England began the COVID-19 pandemic in a relatively strong position. However, several underlying factors have undermined the full digital-enablement of the NHS and its pandemic preparedness and response. Firstly, health data in general is tremendously complex and, even when presented via digital record and reinforced by robust disease surveillance, the signal it generates is still affected by the noise created by data incompleteness and inconsistency. Secondly, even though data linkage via unique patient or carer identifiers is easier than it might have been made otherwise, it has been unrealistic to expect clinicians to take on the bureaucratic burden of digitising their notes at the point of care and data is often lost to paper record as a result. Thirdly, a patient's vaccination history is often incomplete – especially for those performed annually, such as inoculation against seasonal influenza.

The extent to which the national government fully and effectively utilised whatever digital advantage they possessed during the COVID-19 pandemic has been debatable. There are several digitally enabled milestones and achievements to celebrate here, however, most notably the unprecedented coverage of testing and tracing mechanisms and the speed of vaccine discovery and roll-out. That said, there are still some criticisms that warrant discussion.

While the UK government's commitment to taking a digitally-enabled response to the pandemic was commendable, doing so through a mesh of public-private partnerships and emergency commissioning led to runaway expenditure; the full costs of which will not be known for some time and will likely hang heavy on the budget going forward. This over-reliance of private firms and consultants to meet the demands of the pandemic also often undermined previous due diligence measures, transparency standards, privacy regulations and even led to security breaches. The lack of coherence between the offerings that did emerge also often only served to exacerbate pressures on the NHS. Expensive mistakes were made – NHS Test & Trace will likely struggle to justify its current £37 billion price tag [[34]] – and the new systems and products that were instituted during the pandemic often forced many healthcare workers to return to paper-based working styles when they encountered digital teething problems. Furthermore, the unfortunate timing between the pandemic and the exit of the UK from the European Union demonstrated how vulnerable the functioning of the NHS was – both online and offline – to under-staffing and supply chain disruptions. All this has amounted to a major erosion of public trust, exemplified by the growing calls for an independent inquiry into COVID-19 related expenditure.

Finally, it remains to be seen whether the UK government will effectively repurpose the digital infrastructure, products and services that have emerged from the pandemic. There is a real opportunity for these to be absorbed into disease surveillance and pandemic preparedness efforts going forwards. Parallels could be made here to global cities' efforts to effectively re-engineer Olympic stadiums after the games have come to an end; considerable thought must be put in to ensure these developments do not become ‘white elephants’ – underused or obsolete constructions that only become cost burdens for the cities they call home. The digital infrastructure and maturity gains seen over the course of the pandemic – as arguably hit and miss as they have been – are just as liable to becoming white elephants unless considerable thought and care is put into their preservation and repurposing. For example, plans are currently underway to decommission the impressive Test and Trace network of case identification and contact tracing; it will be vital to think through how to pivot at least some of what has been created into early warning systems rather than dismantling this investment in its entirety.

A potential candidate for absorbing this pandemic infrastructure includes England's influenza surveillance and vaccine effectiveness sentinel network, the Oxford-Royal College of General Practitioners (RCGP) Research and Surveillance Centre (RSC) [[35]]. This nationally representative network of 1,900 general practices – a subset of which conduct virology and serological surveillance – could greatly benefit from the increased capabilities and capacity that infrastructure stood up for COVID-19 surveillance could provide. Here, virology and vaccine recording is still individually entered via different computerised record or test request systems; the more advanced IT systems created to combat COVID-19 would rapidly enhance the digital maturity of this network.


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4 Discussion

The preliminary analysis showed significant growth across micro, meso and macro levels with respect to information analysis and dissemination, coordination across care delivery centres and agents, and tracking and monitoring of group level interventions such as vaccinations. Common across all three countries (Australia, Canada, and England) was significant growth in micro level tools that could push information such as COVID-19 test results or reduce the risk of exposure directly to people. That was changed from 2019-20 influenza level monitoring that put the onus on individuals to monitor outbreaks and manage possible exposures.

All three countries showed growth in digital maturity from the 2019-20 year and management of influenza to the 2020-21 year and the management of the COVID-19 pandemic. However, while progress in digital maturity was seen, the degree of progress was sporadic and uneven. A plethora of digital tools were developed to support COVID-19 tasks related to care delivery/monitoring and surveillance, but these offerings were hindered by their incoherence with one another and the ways in which they often only duplicated pre-existing efforts and added unnecessary levels of complexity to monitoring and treating patients. Work that was done to advance the digital health maturity of nations during the pandemic often appeared ad hoc, lacking systems thinking, and without robust monitoring and evaluation mechanisms to ensure responsible spending and outcomes that would best serve both the general public and specific populations in need. This was not helped by the presence of non-competitive tendering processes during the pandemic. Some countries with strong track-records for disease surveillance and supporting digital infrastructure did not use their natural advantage to the best of their ability during the COVID-19 pandemic and instead opted for ‘from scratch’ investments. England is a notable example here; its government has been accused of fiscal irresponsibility enough to warrant a public enquiry. It remains to be seen how many other countries will also have to justify their pandemic-related expenditures to their tax-paying public in this way. The digital health maturity comparison we provided is important as it is not enough to simply have a digital health infrastructure but rather, we need to have specific measures to track the growth of digital maturity, including fit-for-purpose data shared accurately across the health and socioeconomic sectors.

Contract tracing was also a digital phenomenon that evolved greatly from influenza to COVID-19. Influenza tracking pre-COVID-19 was often based on population level maps where individuals would have to track outbreaks and monitor their own exposure. While all three countries saw a marked uptake in digital capacity, concerns were raised about the ad-hoc nature of how digital capacity developed. Common across all three countries was a previously described phenomenon that the development of new technologies and innovations occurred faster than the policy that is needed to guide their evolution [[36]]. Privacy and security issues as well as uncertainty and challenges about data access and sharing were common and impacted effective pandemic response.

Going forward, determining which digital tools provide value and should be kept and which tools need to be redesigned or eliminated is an essential task. This requires a re-invigorated evidence-based approach to integrated primary care informatics and its evaluation to gain public confidence and trust in digital health across primary and other health sectors. We cannot assume that equity and positive health and social outcomes for all will automatically be enabled by health IT. Instead, we need to design for purpose to achieve desired system outcomes.

The opportunity to use the investment in and lessons learned from COVID-19 should not be wasted. Future pandemic planning should focus on enhancing the surveillance systems for influenza and other notifiable infectious diseases that currently exist with an explicit focus to improve digital health maturity and the quality of surveillance enabled by existing systems. As the sociotechnical maturity and associated traits such as dependability, resilience, and agility of digital health systems improves, so will the ability to deal not only with an epidemic/pandemic but also the monitoring and management of long-term sequelae such as “long covid” and other chronic diseases. Perhaps a transparent approach emphasising mutual trust and reciprocity will then facilitate international digital health diplomacy [[37]] to achieve a treaty to underpin a truly global and equitable response to future pandemics that “leaves no one behind” [[38]].


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5 Conclusion

While the COVID-19 pandemic provided a global stimulus for digital health capacity, its development has often been inequitable, short-term in planning, and lacking in overall health system coherence. Inclusive digital health and the development of resilient health systems are broad outcomes that require a systems approach to achieve them. This paper from the IMIA Primary Care Informatics Working Group provided an international comparison of digital maturity from influenza in 2019-20 to COVID-19 in 2020 and beyond. Our analysis and discussion provide direction for the design of digital primary care systems as part of enabling system equity and resilience.


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No conflict of interest has been declared by the author(s).

Acknowledgments

Prof Nigel Stocks, Director ASPREN, for contribution to early stage of paper.

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  • 27 Pearce C, McLeod A, Supple J, Gardner K, Proposch A, Ferrigi J. Responding to COVID-19 with real-time general practice data in Australia. Int J Med Inform 2022 Jan;157:104624.
  • 28 Busingye D, Gianacas C, Pollack A, Chidwick K, Merrifield A, Norman S, et al. Data Resource Profile: MedicineInsight, an Australian national primary health care database. Int J Epidemiol 2019 Dec 1;48(6):1741-1741h.
  • 29 Jonnagaddala J, Godinho MA, Liaw ST. From telehealth to virtual primary care in Australia? A Rapid scoping review. Int J Med Inform 2021 Jul;151:104470.
  • 30 Wong ZS, Rigby M. Identifying and addressing digital health risks associated with emergency pandemic response: Problem identification, scoping review, and directions toward evidence-based evaluation. Int J Med Inform 2022 Jan;157:104639.
  • 31 Alami H, Lehoux P, Attieh R, Fortin J-P, Fleet R, Niang M, et al. A “Not So Quiet” Revolution: Systemic Benefits and Challenges of Telehealth in the Context of COVID-19 in Quebec (Canada). Frontiers in Digital Health 2021;3:133.
  • 32 Koch, K. The digital divide and the lack of broadband access during COVID-19. [cited 2022 March 24] Available from: https://www.policyschool.ca/wp-content/uploads/2020/06/Infrastructure-Trends-Digital-Divide.pdf
  • 33 NHS England (2019). The NHS long term plan. London. [cited 2022 March 24] Available from: https://www.longtermplan.nhs.uk/
  • 34 Mahase E. Covid-19: NHS Test and Trace failed despite “eye watering” budget, MPs conclude. BMJ 2021 Oct 27;375:n2606.
  • 35 de Lusignan S, Jones N, Dorward J, Byford R, Liyanage H, Briggs J, et al. The Oxford Royal College of General Practitioners Clinical Informatics Digital Hub: Protocol to Develop Extended COVID-19 Surveillance and Trial Platforms. JMIR Public Health Surveill 2020 Jul 2;6(3):e19773
  • 36 Rheuban K, Shanahan C, Willson K. Telemedicine: Innovation Has Outpaced Policy. Virtual Mentor 2014 Dec 1;16(12):1002-9.
  • 37 Godinho MA, Martins H, Al-Shorbaji N, Quintana Y, Liaw ST. “Digital Health Diplomacy” in Global Digital Health? A call for critique and discourse. J Am Med Inform Assoc 2021;:ocab282.
  • 38 Godlee F. Covid 19: Why we need a global pandemic treaty. BMJ 2021;375:n2963.

Correspondence to:

Craig Kuziemsky

Publication History

Article published online:
02 June 2022

© 2022. IMIA and Thieme. This is an open access article published by Thieme under the terms of the Creative Commons Attribution-NonDerivative-NonCommercial License, permitting copying and reproduction so long as the original work is given appropriate credit. Contents may not be used for commercial purposes, or adapted, remixed, transformed or built upon. (https://creativecommons.org/licenses/by-nc-nd/4.0/)

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  • 26 Kariotis T, Prictor M, Chang S, Gray K. Evaluating the Contextual Integrity of Australia's My Health Record. Stud Health Technol Inform 2019 Aug 9;265:213-8.
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  • 29 Jonnagaddala J, Godinho MA, Liaw ST. From telehealth to virtual primary care in Australia? A Rapid scoping review. Int J Med Inform 2021 Jul;151:104470.
  • 30 Wong ZS, Rigby M. Identifying and addressing digital health risks associated with emergency pandemic response: Problem identification, scoping review, and directions toward evidence-based evaluation. Int J Med Inform 2022 Jan;157:104639.
  • 31 Alami H, Lehoux P, Attieh R, Fortin J-P, Fleet R, Niang M, et al. A “Not So Quiet” Revolution: Systemic Benefits and Challenges of Telehealth in the Context of COVID-19 in Quebec (Canada). Frontiers in Digital Health 2021;3:133.
  • 32 Koch, K. The digital divide and the lack of broadband access during COVID-19. [cited 2022 March 24] Available from: https://www.policyschool.ca/wp-content/uploads/2020/06/Infrastructure-Trends-Digital-Divide.pdf
  • 33 NHS England (2019). The NHS long term plan. London. [cited 2022 March 24] Available from: https://www.longtermplan.nhs.uk/
  • 34 Mahase E. Covid-19: NHS Test and Trace failed despite “eye watering” budget, MPs conclude. BMJ 2021 Oct 27;375:n2606.
  • 35 de Lusignan S, Jones N, Dorward J, Byford R, Liyanage H, Briggs J, et al. The Oxford Royal College of General Practitioners Clinical Informatics Digital Hub: Protocol to Develop Extended COVID-19 Surveillance and Trial Platforms. JMIR Public Health Surveill 2020 Jul 2;6(3):e19773
  • 36 Rheuban K, Shanahan C, Willson K. Telemedicine: Innovation Has Outpaced Policy. Virtual Mentor 2014 Dec 1;16(12):1002-9.
  • 37 Godinho MA, Martins H, Al-Shorbaji N, Quintana Y, Liaw ST. “Digital Health Diplomacy” in Global Digital Health? A call for critique and discourse. J Am Med Inform Assoc 2021;:ocab282.
  • 38 Godlee F. Covid 19: Why we need a global pandemic treaty. BMJ 2021;375:n2963.

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Table 1 Digital Health Maturity Foundations by Prevention/Vaccination, Disease Mx, Surveillance & Pandemic preparedness for Seasonal Influenza and COVID-19 in Australia.
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Table 1 continued Digital Health Maturity Foundations by Prevention/Vaccination, Disease Mx, Surveillance & Pandemic preparedness for Seasonal Influenza and COVID-19 in Australia.
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Table 2 Digital Health Maturity Foundations by Prevention/Vaccination, Disease Mx, Surveillance & Pandemic preparedness for Canada
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Table 2 continued Digital Health Maturity Foundations by Prevention/Vaccination, Disease Mx, Surveillance & Pandemic preparedness for Canada
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Table 3 Digital Health Maturity Foundations by Prevention/Vaccination, Disease Mx, Surveillance & Pandemic preparedness for England.
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Table 3 continued Digital Health Maturity Foundations by Prevention/Vaccination, Disease Mx, Surveillance & Pandemic preparedness for England.
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Table 3 continued Digital Health Maturity Foundations by Prevention/Vaccination, Disease Mx, Surveillance & Pandemic preparedness for England.