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