Harnessing Digital Health Technologies to Combat Climate Change‐Related Health Impacts

Yuhang Li; Ge Wu; Puxi Gong; Chang Liu; Lizhong Liang; Mengchun Gong; Zhirong Zeng

doi:10.1002/hcs2.70032

. 2025 Aug 17;4(4):235–242. doi: 10.1002/hcs2.70032

Harnessing Digital Health Technologies to Combat Climate Change‐Related Health Impacts

Yuhang Li ¹, Ge Wu ^2,³, Puxi Gong ², Chang Liu ^4,⁵, Lizhong Liang ^6,⁷, Mengchun Gong ^2,^3,^✉, Zhirong Zeng ^8,^9,^✉

PMCID: PMC12371720 PMID: 40861518

ABSTRACT

Climate change poses a significant threat to global health. It exacerbates existing health challenges and generates new ones. Therefore, innovative solutions to mitigate and adapt to its adverse effects are urgently required. This article explores the potential of digital health technologies to address the challenge posed by climate change‐related health issues. It discusses their dual functionality of diminishing the carbon footprint of healthcare services and increasing understanding and governance of climate‐sensitive diseases. Notably, with advanced technologies such as Generative medical AI (GMAI) presenting environmental concerns like substantial energy consumption during data processing and the generation of electronic waste, it is essential to underscore the significance of their responsible development and implementation of these technologies. This will ensure that the benefits of digital health technologies can be maximized while minimizing their ecological drawbacks. This study, therefore propose, a framework for leveraging digital health technologies to support climate change adaptation, including disease surveillance, telemedicine, patient support systems, and public awareness campaigns.

Keywords: climate change, digital health technologies, health impact, healthcare innovation, sustainable development

We proposed a framework for leveraging Digital Health Technologies (DHTs) to mitigate and adapt to climate change‐related health impacts. It highlights DHTs' dual role in enhancing healthcare efficiency (such as real‐time monitoring) while reducing its environmental footprint through decarbonization (e.g., lower travel emissions, reduced paper use). The framework emphasizes sustainable DHT development (energy‐efficient AI, e‐waste management) and climate‐health adaptation strategies (disease surveillance, telemedicine access), addressing key challenges like data privacy and infrastructure needs.

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Abbreviation

DHTs: digital health technologies

1. Introduction

Climate change is no longer a distant threat, its impact on human health is already evident. Rising temperatures contribute to heat‐related illnesses, extreme weather events cause injuries and displacement, and changing environmental conditions facilitate the spread of infectious diseases. Air pollution, often exacerbated by climate change, leads to respiratory and cardiovascular problems [1]. The healthcare sector itself is now also a notable contributor to climate change, responsible for almost 5% of global carbon emissions [2]. Addressing these multifaceted effects on health requires a comprehensive approach, and digital health technologies (DHTs) offer a promising shortcut for mitigating and adapting to climate change.

A wide range of tools are considered to be digital health technologies, from electronic health records (EHRs) and telemedicine platforms to wearable sensors and artificial intelligence (AI) applications. These technologies have the potential to revolutionize healthcare delivery, improve efficiency, and enhance patient outcomes. In the context of climate change, DHTs can play a crucial role in reducing the environmental impact of healthcare operations and empowering individuals and communities to better manage climate‐sensitive health risks.

This article aims to explore the potential of DHTs to address climate change‐related health impacts. We will examine how DHTs can contribute to decarbonizing healthcare, facilitate research on climate–health linkages, and support adaptation strategies. We will also discuss the challenges and ethical considerations associated with the development and deployment of these technologies.

2. Digitalization for Decarbonizing Healthcare

DHTs actively promote efficiency in use of resources, reducing waste and lowering the environmental impact of the healthcare sector. One way is by reducing paper use. This is mainly driven by the use of EHRs, electronic prescriptions, and online appointment systems. These technologies reduce dependence on paper‐based methods of operation. The reduced use of paper decreases deforestation and energy costs associated with paper production and transport [3].

DHTs have also enabled relatively easy sharing of information with little need for travel or transport of documentation. These technologies include telemedicine, remote monitoring, and online consultations, all of which enable patients to be treated without traveling to healthcare facilities, therefore reducing transport‐related carbon emissions. One study found that the use of DHTs can both reduce carbon emissions from patient transportation and provide better overall services for patients [4].

Data‐driven DHTs could also improve efficiency of resource use in the health sector. By data‐analyzing use of inventory, patient flow, and energy consumption, hospitals can identify possible improvements to reduce waste. For example, AI‐based systems can predict patient needs, and this information can be used to support staff scheduling, saving energy and increasing operational performance. Telemedicines significantly promotes healthcare decarbonization. One report suggests that the use of telecardiology services has saved the equivalent of 2,000 flights and lowered carbon dioxide emissions by more than 16,000 tons [5].

DHTs may also help to redefine healthcare decarbonization. The implementation of these technologies has the potential to improve healthcare quality, for example, by personalization of treatment regimens and use of AI‐based prediction models to identify patients most at risk. This implementation should help to deliver better patient outcomes and more efficient use of medical resources.

3. Establishing Causality: The Role of Digitalization

Understanding the causal link between climate change and health outcomes is central to designing effective interventions. DHTs provide powerful tools for collecting and analyzing data to establish these links. During the COVID‐19 pandemic period, they were used to contribute towards the public health response to COVID‐19 globally, through tasks like population surveillance, case identification, contact tracing, and behavior assessments based on mobility data and public communication [6]. As DHTs continue to improve, they are beginning to use more sources of data to deliver real‐time monitoring of health threats, offering the potential to predict the effect of climate change on human health.

Wearable sensors, environmental monitoring devices, and EHRs can capture a wealth of information on individual health, environmental exposure, and disease patterns. These data can be integrated and analyzed using advanced techniques like machine learning to identify correlations and predict risks. For example, researchers can analyze data from wearable sensors and air quality monitors to assess the impact of air pollution on respiratory health in different populations. The integration of data from different sources is vital in dealing with the potential health risks induced by climate change. For vector‐borne diseases which are particularly sensitive to changes in weather and climate, DHTs have enabled the incorporation of climatic data into surveillance systems, enhancing the capacity to predict trends in outbreak prevalence and location. The timely warning supplied by accurate monitoring systems helps to detect and control outbreaks of infectious diseases, promote effective management of limited resources, and facilitate knowledge generation, response planning, and long‐term resource prioritization, reducing the potential for future outbreaks [7].

Another potential application of DHTs is empowering individuals to manage their own health in response to environmental changes. There are many apps that can provide personalized health management plans based on users' personal health data and environmental information. These may include diet suggestions, exercise plans, and sleep management. These apps can provide relevant information in a timely manner to remind users to make adjustments, for example to manage conditions such as high temperature, severe air pollution or high incidence of influenza.

There are considerable benefits to shared large‐scale data exchange and collaborations on climate impacts among researchers and healthcare providers. This approach would potentially provide rigorous studies on climate–health connections. DHTs create data‐sharing platforms and networks for cooperative research that increase the pace of discovery to inform public health interventions. The life cycle assessments of a digital service being operated at a few older people's living schemes demonstrated that it reduced the environmental impact by 8.1% by increasing the lifespan of the equipment by 20% [8]. Digitization has the potential to improve patient care while decreasing expenditure, but it is imperative to consider the environmental impact and provide mitigation measures that will ensure sustainable development of the industry.

4. Navigating the Environmental Impact of Advanced DHTs

The application of digital health technology in different fields of medicine is increasing. Advanced technologies like GMAI require substantial computing power. Clinical practices also have an impact on energy consumption, for example, through the data processing and storage requirements associated with the use of image data in diagnosis and video transmission in telemedicine [9].

These technologies also have an environmental impact through the production, use and disposal of digital health devices such as wearable monitors and telemedicine systems. The raw materials for the manufacture of these devices include rare metals that must be mined. They also use plastics, which also require the extraction of natural resources and could contaminate soil and water. If not properly treated, plastics may also find their way into e‐waste landfill. E‐waste contains hazardous substances like lead, mercury, and brominated flame retardants. Informal processing (e.g., open‐air burning, acid baths, landfilling) releases these toxins, contaminating the environment and posing significant health risks, particularly to neurological development in children and pregnant individuals, and causing respiratory diseases, birth defects, and cancer in exposed workers. Improper e‐waste management causes global economic losses of $37 billion annually, primarily from environmental and health damages [10].

The design and implementation of these technologies must therefore be energy efficient. This includes developing energy‐efficient algorithms and hardware, improving data storage and transfer protocols, and increasing the drive towards responsible uses of data. Data centers are major consumers of energy to run their servers, cooling systems, and networking appliances. They may be powered by sources that emit high amounts of greenhouse gases. One estimate suggests that data centers account for approximately 1% of the world's electricity use, but this is expected to rise with the demand for AI and digital services [11]. Medical AI's growing computational demands could increase global carbon emissions by 8%–12% annually if data centers rely predominantly on fossil fuels. These facilities also impose severe water strain, consuming 12.98 billion liters yearly—over 62% (nearly 8 billion liters) lost to evaporation—with Google using 8.6 billion liters at only 26.6% recycling rates. Beyond energy, AI hardware drives intensive extraction of critical minerals: Lithium and cobalt demand may surge 300% by 2030, exacerbating ecological damage [12]. Current rare earth shortages are amplified by China's 85% global production share (with high‐carbon impacts) and Western supply chain instability [13].

Consequently, the creation and deployment of AI systems impact ecosystems through three key pathways: (1) extraction of rare earth elements and raw materials for hardware; (2) transportation and logistics across AI supply chains; and (3) GPU and energy consumption during model training [14]. It is therefore imperative to implement comprehensive environmental impact assessments and strategic energy‐efficiency policies to ensure sustainable development of digital health technologies [15].

The ethical aspects around data privacy, security and bias in the equitable and sustainable deployment of DHTs must also be considered. Personal and health information must remain private. Protections must be established to ensure that data are secure during transmission, processing, and storage. Health institutions and technological enterprises must scrupulously comply with laws and regulations on data use, and define the scope and purpose of data use established when seeking informed consent from patients. Greater supervision is needed to avoid any violations, and penalties against violations should be strengthened. For instance, algorithmic innovations exemplified by DeepSeek demonstrate significant reductions in computational resource requirements compared to conventional models like ChatGPT [16]. This optimization substantially lowers energy consumption and carbon emissions during large‐scale AI training, illustrating how energy‐efficient architectures can concurrently mitigate environmental burdens and maintain technological performance.

5. Digital Solutions for Climate Change Adaptation

DHTs offer a range of solutions to support adaptations to the health impacts of climate change.

5.1. Surveillance Systems

Real‐time data from wearable sensors, environmental monitors, and EHRs can be combined to develop early warning systems for climate‐sensitive infectious diseases. AI‐based platforms can be used to forecast outbreaks and guide public health responses. For example, by tracing the spread of vector‐borne diseases like dengue fever, local health authorities can target interventions to protect vulnerable populations. A recent study suggests that query data on the internet and climate variables could predict epidemics of climate‐sensitive infectious disease [17]. The integration of climate and weather variables into models using Google search data could allow health authorities several additional weeks' warning of new outbreaks of influenza‐like illnesses and respiratory diseases compared to traditional methods [17]. Surveillance systems should therefore combine climate and clinical data to develop predictive models or management strategies that improve the ability to accurately predict climate‐sensitive disease outbreaks and also reduce the response time of public health departments. These applications highlight the potential usefulness of digital technologies in public health management.

5.2. Telemedicine

Telemedicine can help to increase access to healthcare in remote areas that may also be among those most affected by climate change. Telemedicine technologies include video consultations, remote monitoring, electronic transmission of medical reports, and tele‐robotic surgery. It will also soon be possible to incorporate real‐time tele‐mentoring into telemedicine systems. This will mean that expert clinical staff will be able to provide expert guidance and support to local teams even from a considerable geographical distance [18]. Telemedicine has already shown its value in increasing accessibility to healthcare in rural and remote areas of low‐to middle‐income countries like India. It concurrently reduces healthcare expenditures and transportation‐related emissions, while also protecting vulnerable groups—particularly children and older adults—from exposure to hazardous weather conditions during travel [19].

By enabling remote consultations, diagnosis, and monitoring, telemedicine therefore reduces the need to travel, lowers the carbon footprint of healthcare, and improves access to healthcare for vulnerable communities. However, significant disparities persist between developed and developing nations: High‐income countries widely deploy tele‐rehabilitation technologies (e.g., remote monitoring systems), whereas resource‐constrained regions remain dependent on traditional care models. This divergence presents distinct challenges‐developed economies must optimize technology energy consumption, while developing regions like Africa require infrastructure development alongside healthcare access expansion.

Notably, breakthroughs in climate‐responsive telemedicine are emerging in the Global South. Indonesia's $4 billion healthcare reform now covers 273 million people via telemedicine and low‐carbon devices, reducing medical emissions. Sierra Leone's solar‐powered facilities serve one‐third of its population, curtailing patient travel and associated emissions. These innovations demonstrate how policy‐supported technological adaptation can synergize healthcare access with climate action in developing contexts [20].

5.3. Patient Support and Early Warning Systems

New digital systems could provide individual users with personalized information and alerts for environmental risks to support the prevention and self‐management of health and safety issues. For example, a system might notify vulnerable individuals of an impending heat wave and suggest that they should increase their water intake, avoid going outdoors, and use indoor cooling methods. On days when air quality is poor, people with respiratory conditions might get messages recommending that they stay indoors, turn on air purifiers, and modify their respiratory treatment plans. Patients with pollen allergies might also get personalized guidance, including ideas for improving nasal hygiene or dosage alterations and recommendations of when to avoid going outdoors.

Mobile apps and wearable devices can provide real‐time feedback and guidance, promoting self‐management and reducing the burden on healthcare systems. Health apps on smartphones are now used by billions of consumers, and record highly detailed data about users, offering the possibility of greater self‐knowledge, self‐help, connection, and community [21]. The security of personal health records is a key issue for the promotion of these digital health tools [22]. However, they can enhance patients' ability to self‐management chronic conditions, and reduce the risks to health caused by environmental factors, further improving the quality and efficiency of public health services.

5.4. Social Awareness and Education

Digital platforms, including social media networks, websites, and mobile apps, can be used to raise public awareness about climate change and its health impacts. These platforms can disseminate information on climate‐related health risks, promote sustainable lifestyle choices, and encourage community engagement in climate action. The “ActNow” chatbot on Facebook Messenger disseminates actionable guidance for daily energy conservation and emission reduction, such as shortening the duration of showers and minimizing private vehicle use, which has significantly enhanced public engagement in climate action. Facebook also hosts numerous groups and professional pages dedicated to climate change, offering a space for users interested in climate change to engage in communication and learning. Reports about climate change may cause some people to feel “climate change anxiety”. However, involving young people in conversations and education about climate change has been identified as a protective factors for mental health and enablers of motivation [23]. Digital platforms are therefore emerging as important tools to drive awareness and action on climate change, spreading knowledge, and energizing communities.

6. Challenges and Future Directions

DHTs therefore have significant potential to address climate change‐related health issues, but several challenges must be addressed to ensure their effective and equitable implementation.

6.1. Data Privacy and Security

In modern healthcare and digital systems, protecting sensitive health data is vital. Robust security measures and guidelines are required to ensure information remains private and is not misused. In developed countries, strict policies and application measures have been put in place by governments and enterprises to protect sensitive health data. The USA demands data privacy on the basis of the Health Insurance Portability and Accountability Act (HIPAA), which imposes standards and requires all entities holding personal health information to undertake proper security checks. In Europe, data protection has reached an entirely new level under the General Data Protection Regulation (GDPR), which goes beyond health data to all personal data. For example, it provides data subjects with amendable rights to delete personal information. These laws have propelled a substantial improvement in data protection for digital health platforms. To secure stored and transmitted data, advances in encryption technology should be applied to digital health platforms at the application level [24] Techniques like federated learning ensure data safety, and policies for dealing with data use and privacy protection cover the entire data lifecycle: data generation, transmission, storage, use, sharing, destruction, and management. User rights management will further empower users to control their health data. These initiatives will together lead to a robust ecosystem of data applications.

6.2. Infrastructure Limitations

Access to reliable internet connectivity and digital devices is essential for DHTs to be usable. In many remote or economically underdeveloped areas, insufficient Internet coverage, unstable power supply and lack of digital equipment are major obstacles to the popularization of DHTs [25]. This limits the access of residents to health information in these areas, and may affect the implementation of telemedicine services, exacerbating the uneven distribution of medical resources. Bridging the digital divide and ensuring equitable access to technology, particularly in underserved communities, is crucial. One study found that digital tools can improve health outcomes for individuals in rural areas [26], but this requires the collaboration and efforts of different parts of society.

Governments should increase investment in infrastructure construction, especially network construction in remote areas to improve the speed and stability of the network. Enterprises should be encouraged to develop digital devices suitable for low‐income groups through policy guidance and financial support. Infrastructure construction needs to consider both hardware (e.g., network facilities, medical equipment, wearable devices and information security hardware) and software (e.g., surveillance systems, AI‐based prediction applications, and mobile apps).

6.3. Digital Literacy and Health Equity

Promoting digital literacy and ensuring that DHTs are designed to be accessible and user‐friendly for diverse populations is essential to avoid exacerbating existing health disparities. Digital tools can facilitate patient education, self‐management and empowerment. DHTs also have the potential to improve clinical decision‐making, treatment options and communication among healthcare providers [27]. It is important that the design of healthcare technology takes into account the diversity of users, including age, educational background, physical conditions, and geographical differences. Interfaces should be intuitive and easy to use, so that diverse groups can all benefit from digital health services. Strengthening digital literacy education and improving everyone's ability to identify health information is also essential for building a fair digital health environment. The World Health Organization has emphasized the importance of digital literacy education and inclusive design in digital health technologies to ensure that everyone, regardless of their abilities or backgrounds, can benefit from these technologies [28]. To ensure equal access cooperation between policy makers and technology developers is necessary to embed health equity principles into every aspect of technology design. Developers of DHTs can draw on user surveys and feedback to ensure that these technologies are continuously optimized for accessibility and applicability. In these ways, the uneven distribution of health resources caused by technical barriers can be avoided.

6.4. Directions for Future Research

The development of DHTs to address climate change‐related health issues should adhere to two fundamental principles of health informatics: connectedness and sustainability. Connectedness involves linking and integrating health data from multiple sources and sustainability aims to enhance the overall efficiency and effectiveness of healthcare [29]. We propose three directions for future research:

a.
Developing more energy‐efficient AI models and sustainable data management practices. This includes the design and optimization of AI‐based computational methods that minimize energy consumption. This can be achieved through the implementation of lightweight network architectures and efficient algorithms that reduce computational demands. The promotion of sustainable data management practices is also crucial. For example, distributed storage systems and cloud computing technology can optimize resource use and decrease energy consumption. Data centers should prioritize renewable energy adoption while implementing intelligent data archiving and cleansing systems to minimize redundant storage burden.
b.
Evaluation of the effectiveness of DHT interventions in moderating and adapting to climate change‐related health issues. This includes supplying mobile health app‐based climate‐sensitive disease warning information; using telemedicine or online consultations for residents of areas affected by climate change; and big data analysis to clearly demarcate the potential impacts of climate change on specific population health risks, and develop targeted intervention strategies. This use of technologies will decrease the health burden of climate change and also improve the resilience and response value of public health services.
c.
Connect climate data and health information systems to improve risk assessment and prediction. An interoperable framework should be created to facilitate the integration of climate monitoring data (temperature, rainfall, and air quality index) into public health databases (e.g., disease incidence rates and medical resource distribution). This combined approach would enable advanced predictive modeling to characterize the effects of climate change on disease transmission patterns, water resource security, food supply stability, and other related factors. This approach could therefore help to establish proactive response strategies. This fusion of data could also allow dynamic adjustments in public health policies, to ensure the optimum allocation of resources and enhance the resilience of the public health system.

6.5. Policy Tools and Governance Framework

To optimize the role of DHTs in addressing the health impacts of climate change, it is essential to establish robust policy formulation and governance frameworks. Current policies in many countries remain nascent, necessitating urgent development of systematic solutions. Policy formulation should prioritize establishing mandatory energy efficiency standards and green certification systems for medical AI models and data centers, supported by fiscal incentives—including tax reductions, subsidies, and dedicated R&D funding—for enterprises developing energy‐efficient algorithms (e.g., DeepSeek optimization models) or adopting renewable energy infrastructure. Furthermore, cross‐sectoral data integration mandates should legislatively compel health departments to share data with meteorological and environmental agencies, establishing unified climate‐health databases such as the US CDC's Climate and Health Program, with privacy‐enhancing technologies embedded in data‐sharing protocols and independent regulatory oversight for compliance auditing.

Government‐led investment strategies are critical for underdeveloped regions, requiring strengthened green infrastructure investments to incrementally establish regional green medical data centers, alongside digital inclusion programs modeled after initiatives like India's “Digital India” that provide subsidized health terminals to low‐income populations. Such integrated approaches can simultaneously advance digital healthcare adoption and carbon reduction objectives.

Global climate action demands enhanced multilateral cooperation, including finalization of technical protocols, harmonization of international agreements aligning digital health with climate goals, and establishment of open technology‐sharing platforms. Particular emphasis should be placed on facilitating South‐South technology transfer to enable developing nations' access to energy‐efficient algorithms and climate‐health monitoring tools. Through these multidimensional collaboration networks, global climate‐health governance capacities can be cohesively strengthened.

7. Conclusion

DHTs are powerful levers that can help to counter the health‐related impacts of climate change. As technological solutions, they can be used to decarbonize the operations of healthcare facilities, enable more research on the links between climate and health, and facilitate adaptation strategies to deliver a healthier, more sustainable future. Responsible innovations, inter‐disciplinary cooperation, and an active effort to engage with ethical considerations are required to ensure equitable access to technology. Integration of DHTs into climate change and health policies is vital to build resilience in all healthcare systems, and empower individuals and communities to manage climate change. Figure 1 shows our proposed framework for managing the health impact of climate change.

DHTs: A framework for managing the health impact of climate change. DHT, digital health technologies.

While DHTs offer promising solutions to climate‐related health threats, their sustainable deployment is challenged by interconnected barriers: the rapid hardware iteration cycle (e.g., wearables, telemedicine terminals) intensifying e‐waste demands circular economy integration; significant carbon footprints from energy‐intensive operations like AI training necessitate coupling green computing with renewable energy systems; inadequate governance of data privacy/security in global frameworks requires balanced openness‐protection mechanisms; and infrastructural inequity risks exacerbating the digital divide, mandating targeted policies for vulnerable populations. Addressing these multidimensional challenges demands interdisciplinary collaboration, adaptive policy making, and synergistic alignment of technological innovation with ecological conservation to ensure DHTs' authentic sustainability in climate adaptation.

Author Contributions

Yuhang Li: visualization (equal), writing – original draft (equal), writing – review and editing (equal). Ge Wu: conceptualization (equal), writing – original draft (equal), writing – review and editing (equal). Puxi Gong: conceptualization (equal), writing – original draft (equal). Chang Liu: supervision (equal), writing – review and editing (supporting). Lizhong Liang: supervision (equal). Mengchun Gong: conceptualization (equal), project administration (equal), supervision (equal). Zhirong Zeng: funding acquisition (equal), project administration (equal), supervision (equal).