Abstract
The increasing digitization of healthcare in LMICs is an ongoing process that occurs at different rates and with variable impacts on the patient populations of different countries. The healthcare data infrastructure has to overcome the local milieu of challenges, and while addressing those, any implementation effectiveness would depend on the different regulatory and legal frameworks extant at each location. The examples used in this chapter come primarily from the Americas (as a representative global snapshot), and highlight the relative lack of regulations specific to digital healthcare applications, as well as use of healthcare data. A major challenge includes the acute need for digital education of the professional and wider population. Despite the above, the COVID-19 pandemic has sharpened the national focus on healthcare digitization, interconnectivity of stakeholders and interoperability of available systems. It is hoped that these aspects, now that they have risen to the top of the agenda, will be addressed in a constructive and effective manner, taking into consideration tailor-made approaches, optimizing the resources deployed to enhance the countries’ digital ecosystems.
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1 Introduction
One of the lasting legacies of the recent COVID-19 pandemic for healthcare is the rapid increase of digitalization that was implemented alongside other major advancements, such as mRNA vaccines development. In terms of economic sustainability, digitization technologies have become more critical post-pandemic (Nandi et al. 2021), with businesses demonstrating high technology adoption and online presence surviving, while for small/medium enterprises with lack of digitization the pandemic increased vulnerability, especially for individuals and family businesses (Bartik et al. 2020). In the field of healthcare, digitalization was brought to the forefront. A dedicated G20 global digital health summit in 2020 produced the Riyadh declaration (Al Knawy et al. 2020), a landmark consensus statement for the future directions on digital health (Al Knawy et al. 2022). Further details on the Riyadh declaration and how this has driven digitalization forward in Saudi Arabia are provided in Chap. “The Emergence and Growth of Digital Health in Saudi Arabia: A Success Story” of this book.
Approximately 30% of the world’s data volume is currently being generated by the healthcare industry. By 2025, the compound annual growth rate of data for healthcare is expected to reach 36%. That’s estimated by some to be 6% higher than industrial manufacturing, 10% higher than financial services (Coughlin et al. 2018). In the USA, as well as Canada, COVID-19 accelerated the healthcare digitisation process, as the pandemic necessitated additional investments in public health infrastructure for diagnosis, tracing and reporting purposes. However, the digitisation process had already started and was on solid foundations. Specifically, the 2009 HITECH Act, allowed the majority of USA hospitals and ambulatory care practices to introduce and incorporate a basic level of electronic healthcare record (HRE) use. Subsequent years focused on interoperability and in enabling electronic access to health data (Adler-Milstein 2021). Taken together, these actions have catalyzed private-sector digital health efforts, which have expanded in scale and scope (Rock Health 2023), complementing the public health sector investment in healthcare research (Baumgart 2020).
However, healthcare digitalization has not been equally attempted and available globally. Chapter “Biobank Digitization in Low-Middle Income Countries (LMICs): Current and Future Technological Developments” of this book provides a scoping review on the digital divide based on technological development and availability, and how infrastructural requirements are an important limiting factor to such digitalization attempts. The term “techquity” is frequently used to describe this overall digital divide. Techquity is defined as the strategic development and deployment of technology in healthcare and health to achieve health equity (Shelton 2021), having four core components: (i) education, (ii) data trust, (iii) measurability and (iv) explainability (Rhee et al. 2021). In this chapter, we will focus on the aspects of techquity that relate to the data trust, and how this is interlinked with the existing data infrastructures. Many of the examples will relate to low- and middle-income countries (LMICs) in Latin America, highlighting the diversity of context, approaches, challenges and opportunities.
2 Healthcare Data Infrastructure
In general, healthcare data infrastructure follows a similar pattern in most locations (Ozaydin et al. 2020). Healthcare data is collected continuously in four distinct areas: (i) administrative, (ii) clinical data (including imaging and -omics data), (iii) decision-support systems that provide interoperability with (i) and (ii), and (iv) research data and data analytics platforms, that rely on interoperability primarily with (ii) and (iii) and less so with (i). While the impact of the pandemic has touched all four areas of healthcare data infrastructure; the relative impact on each aspect was highly dependent on the local context. Thus, digitalization in healthcare, as well as the impact of the pandemic on healthcare data infrastructure are highly variable globally.
For example, in Brazil, the main healthcare databases are generated by the Brazilian unified national health system [Sistema Único de Saúde (SUS)] (de Mello Jorge et al. 2010), classified into: (1) epidemiological, used for surveillance and research; (2) administrative, used for accounting; and (3) clinical, used to store the patient data (Souza et al. 2016). In addition, data relevant to healthcare is also generated and managed by other departments, such as the Ministry of social development, for provision of social services, and others, summarized by Ali et al. (2019). In Mexico, the Coordination of the National Digital Strategy (CNDS), as part of the Office of the President of Mexico, is responsible for designing, establishing and maintaining the national digital infrastructure for the objective of securing the country’s innovation and development (Arpi n.d.), in coordination with the National Commission for Bioethics (de Chavez et al. 2017). The latter provides qualified directions and guidelines in the manner in which healthcare data is used and can be used, for example, providing advice on the regulation and governance of artificial intelligence (AI) in healthcare. Mexico and Brazil offer the two most advanced such examples in the Americas, beyond the USA and Canada (Tentori et al. 2020). For the remaining countries in the Americas, the healthcare data infrastructure is more fragmented, i.e., with fewer integrated systems within a unified healthcare system, and in some cases such infrastructure may be entirely absent (Curioso 2019). Thus, this part of the world offers a representative image of the global picture.
3 Healthcare Data Policy and Governance
In 2019 the World Health Organization (WHO) published the “Global strategy on digital health 2020–2025”, endorsed by the 73rd World Health Assembly [decision WHA73 (Monraz-Pérez et al. 2021)] (World Health Organization (WHO) 2021), and echoed in the “Plan of Action for Strengthening Information Systems for Health 2019–2023” published in the same year by the Pan American Health Organization (PAHO) (Pan American Health Organization (PAHO) 2019). In this global view, digital health is positioned as the game changer for effective healthcare delivery, in particular within developing economies, where mobile connectivity is transforming local markets and capacities rapidly (however, there has not been an estimate as yet, on the level of completion/adoption of this global strategy). Four guiding principles were outlined to orient the global strategy towards the appropriate and sustainable adoption of digital health technologies within the contexts of national health sector and strategies (Table 1).
However, as part of the implementation of the digital health strategies, the consensus is that legal and ethical frameworks will be created, supporting and regulating the emerging sets of healthcare activities, as well as the novel fields of the healthcare market (World Health Organization (WHO) 2021; Thomason 2021). For example, to harness existing datasets, abundant medical data would need to be made readily accessible to researchers and the private sector, under defined conditions of access, sharing and use. Additionally, the emergence and persistence of healthcare data marketplaces will be an inevitable outcome to making healthcare data accessible and interoperable. Thus, important questions remain, such as the monetization of healthcare data, secondary use of healthcare data, and return of incidental findings. These all require, if not a legal framework, a set of national guidelines linking to the wider healthcare provision. As an example of monetization, the value of healthcare data has been calculated in real-terms by Roche’s acquisition of Flatiron, the latter combining extensive sets of patient data, an electronic healthcare record (EHR) as well as an oncology platform. Based on the published records, a value of USD 950 per patient record was estimated as part of the agreement (Thomason 2021; Wayman and Hunerlach 2019). However, such an investment formulates the exception of healthcare data monetization currently rather than the rule, perhaps limiting further such transactions by the lack of relevant legal frameworks.
4 Observed Regulatory Challenges
In the Americas, in particular Latin America, healthcare systems are highly fragmented between public and private institutions, with the quality of healthcare systems generally considered superior in private institutions. The overall investment in Latin America’s public healthcare systems is estimated to be low, as compared to other global regions, resulting to an even greater inequity in care (including digital healthcare) across public and private institutions (Kanavos et al. 2019; Atun et al. 2015; Organisation for Economic Co-operation and Development (OECD) 2020). This was further accentuated during the COVID-19 pandemic, where Latin America recorded over 27% of the cumulative global death toll (Ezequiel et al. 2021; Camacho-Leon et al. 2022). Therefore, the creation of a regulatory framework as a support tool for the digitalization of healthcare and the development of techquity, based on local capacities and addressing local needs, is critical. Having said that, a number of challenges remain.
Most Latin American countries (notable exceptions are Bolivia and Honduras) have some form of regulation regarding healthcare data, telemedicine, and patient data protection (Camacho-Leon et al. 2022). These laws tend to be expanded in their implementation to encompass digital healthcare applications; however, they are not specifically designed to address those emerging challenges and opportunities, and can lead to regional interoperability restrictions. For example, Mexico does not have specific regulations for telemedicine, even though over 5.5 m telemedicine consultations were reported in 2020 alone (Monraz-Pérez et al. 2021), and has been included in public policies since 2015 with accompanying published guidelines and recommendations by the national Ministry of Health. In June 2020, a document titled “Contact unit for remote interconsultation (UCID) Mexico: attention to chronic diseases” was published, which consolidates guidelines on teleconsultation and promotes the use of telemedicine in the treatment of chronic diseases (Aizenberg 2023). However, this still falls short of consolidating the expertise of a decade of digital health implementation and provision within a legal framework. Camacho-Leon et al. provide an excellent narrative review of the current status, where it becomes evident that the example from Mexico is a typical one for the region (Camacho-Leon et al. 2022). Importantly, the lack of a dedicated and/or updated legal framework impedes the sharing of healthcare data across jurisdictions. In the short-term this may put patient data confidentiality into question, and in the longer-term may be a critical limiting factor in addressing techquity, as inability to share healthcare data means that these populations would be under-represented in the global databases.
It is important to note that regulation is a challenge linked to a matrix of challenges that would need to be considered/addressed concurrently. For example, for digital healthcare such challenges would be the: unrealistic expectations, biased and non-representative data, inadequate prioritization of equity and inclusion across the population entailing the risk of exacerbating health care disparities, low levels of trust regarding the use of healthcare data, and inadequate evaluation of implemented initiatives. The USA National Academy of Medicine has produced a high-level document describing many of those challenges in detail and how they could be addressed both in isolation as well as part of a wider approach (National Research Council 2009).
5 Local Context
Finally, the pandemic demonstrated the importance of local context in relation to the effectiveness of implemented digital healthcare. Specifically, a number of Latin American countries (Perú, Argentina, Bolivia, Chile, Ecuador, México, Colombia and Brazil) and the Inter-American Development Bank deployed digital applications for the surveillance of viral transmission through testing and tracing. However, they collaborated with private companies and/or universities in each country, resulting in the release of different platforms (Benítez et al. 2020). However, these platforms did not perform as well as originally anticipated due to poor reach and limited effectiveness of mobile technologies, as well as the inability of Latin American healthcare systems to provide follow-up services. Additionally, the massive population surveillance assumed a different dimension than similar efforts in Europe and North America, with heightened concerns regarding the protection of personal data and the balance of public health demands with democratic rights (Waisbord and Segura n.d.; Segura 2022).
6 Opportunities
While many challenges in pursuit of techquity exist, there are also opportunities. Technology, when diffused and utilized equitably, democratizes access to information and can bridge existing knowledge gaps or misinformation. It acts as an effective countermeasure to the digital divide, the latter providing unequal access to, and utilization of, healthcare, predominantly affecting individuals who are hard to reach, or from certain racial and/or from specific socio-economic population groups. Despite the advancement in accessing digital services, the digital divide persists (Vogels 2021). For infrastructure operators, the main challenge to addressing the digital divide remains the economic feasibility of creating and maintaining networks in areas with low population density and/or high geographic fragmentation. However, there are a number of novel wireless technologies, e.g., mmWave Cellular Networks, that can help to address this need, providing a much cheaper alternative and thus, bridging the digital divide (Zhang et al. 2021, 2022). These technological developments can act as an impact multiplier when implemented with supportive regulatory frameworks, however, implementation is still lacking.
The acute need for training and building the digital literacy capacity of healthcare professionals in Latin America (Luna et al. 2014), presents a unique opportunity to design and provide capacity-building activities that could reach very large numbers of professionals. For example, PAHO developed virtual courses (e.g., “eHealth for Managers and Decision Makers”; “Access and Use of Scientific Information on Health”, and others) available through the Virtual Campus of Public Health, and already accessed by thousands (Novillo-Ortiz et al. 2016). The pandemic has highlighted this need for education across many different populations of data producers and data users, and as a result such courses have now been created and multiplied, widening their reach and hopefully their impact (Curioso 2019).
7 Way Forward
The COVID-19 pandemic has revealed the usefulness of digital healthcare to many governments across the world to deliver healthcare utilizing different operating models, e.g., increased remote monitoring of patients and teleconsultations (Jazieh and Kozlakidis 2020), but also as a tool to confront inequities in access to healthcare in their respective countries (Brewer et al. 2020). Digital healthcare services and collected data have been clearly interpreted not just as a set of siloed services, but also as foundational infrastructure for research activities within healthcare. For example, biobanking emerged as a foundational research infrastructure that can be utilized in times of healthcare crises (Henderson and Kozlakidis 2020). Taken together with the experiences of LMICs, in particular in Latin America (Ács et al. 2022), they can offer the following points for the way forward:
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Access to reliable infrastructure remains a key component upon which digitization of healthcare is based. Thus, further investment in digital infrastructure remains a critical need.
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Access to digital applications is not tantamount to utilization; addressing the digital literacy aspects is a pre-requirement for the impactful operation of digital technologies.
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The interconnections between different stakeholders (i.e., clinical professionals, patients, entrepreneurs, individuals, and governments) in the digital economy brings important interoperability challenges to digital platforms.
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Therefore, there is an acute need to provide clear regulatory frameworks for the emerging digitization in healthcare, including provisions for data access, sharing, utilization (including for secondary use) and reporting.
8 Conclusion
The increasing digitization of healthcare in LMICs is an ongoing process that occurs at different rates and with variable impact on patient populations in different countries. On the one hand, the healthcare data infrastructure has certain high-level similarities, but has to overcome the local milieu of challenges (including local and national political challenges, not covered in this chapter). On the other hand, even if the healthcare data infrastructure is fully addressed, digitization implementation effectiveness would depend on the different regulatory and legal frameworks. The examples used in this chapter come primarily from the Americas (as a representative global snapshot), and highlight the relative lack of regulations specific to digital healthcare applications, as well as use of healthcare data. Additionally, challenges include the acute need for digital education of the professional and wider population. Despite the above, the COVID-19 pandemic has sharpened the national focus on healthcare digitization, interconnectivity of stakeholders and interoperability of available systems. It is hoped that these key areas, now that they have risen to the top of the agenda, will be addressed in a constructive and effective manner, taking into consideration tailor-made approaches, addressing the local contexts and optimizing the resources deployed to enhance the countries’ digital ecosystems.
Funding Statement
This work was supported in part by the IARC/WHO, through training by the Biobanking and Population Cohort Network (BCNet; CRDF Global, Award No. 66415).
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Kozlakidis, Z., Kealy, J., Henderson, M.K. (2024). Digitization of Healthcare in LMICs: Challenges and Opportunities in Data Governance and Data Infrastructure. In: Kozlakidis, Z., Muradyan, A., Sargsyan, K. (eds) Digitalization of Medicine in Low- and Middle-Income Countries. Sustainable Development Goals Series. Springer, Cham. https://doi.org/10.1007/978-3-031-62332-5_8
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