Capacity and Capability 

In a health emergency event, the responding healthcare system must have the capacity – trained practitioners, availability of hospital beds, adequate supplies of vaccines, among other resources – and the capability – the propensity of the system to effectively utilize these resources to coordinate and manage the response. Digital health tools developed to augment healthcare practices require both familiarity with the tools and the ability of the practitioner to make sense of the data they produce to make informed decisions. However, this presents a challenge in many health departments across the US, which currently lack such personnel. 

Most Master of Public Health degree programs, which is the de facto public health professional credential, do not currently require students to take coding or technology-integrated courses. Though, there are active conversations to remedy this in some circles. This omission in curricula reduces the capability of health departments trained to utilize digital tools when they are needed. 

Modernized Systems and Public Health Infrastructure 

Advanced technologies and digital tools require modern infrastructure to function. The systems built from these technologies and tools enable early detection and warning in the prevention and control of the spread of infectious diseases, allowing for timely decision-making and responses to public health crises. Additionally, establishing these systems facilitates easier implementation of newer tools that may improve access and delivery of healthcare, including telemedicine and mobile health apps, and the quick transfer of data. States like Massachusetts and Rhode Island fall into the list of top 10 states where physicians use telehealth most. Unsurprisingly, they also rank in the top five best states for health outcomes. Telemedicine and telehealth are especially important in remote and underserved areas where healthcare access is limited and, as stated earlier, health outcomes are far worse. Governments should prioritize investments in these services to address these disparities. 

Challenges of Digital Health Surveillance Data 

The collection and analysis of health surveillance data are essential for monitoring public health activities like identifying disease outbreaks and guiding health policies. However, there are associated several challenges including the quality of data collected and data accuracy. Health data can be complex and varied, making it challenging to ensure that all relevant information is appropriately captured. This is especially true of digital tools since the programming the technology relies upon for instructions on how to operate, including what data to collect, is heavily prone to human bias. One challenge of this is completeness – that is, ensuring all segments of the population are included and all relevant characteristics unique to each subgroup are captured. 

Interoperability is also an important factor to consider and remains a major concern. Many of the devices and tools in use today are unable to communicate or integrate with each other, creating barriers to their application and deployment in urgent situations. For example, as COVID continued ravaging countries, proof of vaccination was required to travel across international borders and to enter most establishments. European travelers who had their proof of vaccination stored in their digital wallets still needed to provide physical proof of their vaccine cards in the US, because the digital cards were unreadable by the systems used locally. 

Further, as use of digital tools expands, health data privacy laws and the development of evidence-based standards, governance structures, and ethical frameworks must be put in place to protect users.

Access and Equity 

Many of the technologies developed to improve population health, including telemedicine and health apps, require continuous exchange of data. This can be challenging to the subgroups of the population who are resource constrained and who do not have unlimited mobile data plans. Cities or governments who are interested in implementing these tools may want to consider partnerships with telecom companies who can zero-rate the applications – a procedure by which a data provider removes the cost of data traffic with a particular application. In doing so, the economic cost of access to the technology is significantly reduced or eliminated, creating a more equitable system of use. 

Data sharing does carry risks to members of certain demographics. Sharing sensitive data intended for health may not actually be how governments and federal agencies utilize this data. Targeting is one specific concern. For example, undocumented immigrants may not want to share their data if they believe that Immigration and Customs Enforcement (ICE) may use it to target and track them for deportation. Even immigrants whose legal statuses have not yet been finalized may fear sharing data, if they become ill and the government determines that they are a public charge, for utilizing the healthcare system. The Public Charge Rule which was issued by the U.S. Department of Homeland Security and went into effect in December of 2022, outlines that if “the noncitizen is likely at any time to become primarily dependent on the government for subsistence, as demonstrated by either the receipt of public cash assistance for income maintenance or long-term institutionalization at government expense,” they are a public charge and is grounds for inadmissibility. 

Another concern is that not everyone has a smart phone. Pew Research Center reports that of the 97percent of the U.S. population with a cellphone, 85 percent of them are smartphones. This means that the 15 percent of users who do not have smartphones would likely be unable to participate in any digital surveillance program, because most of the older cellphone models do not have Bluetooth capability. The most resource constrained and likely those who need access to health services most, are typically the ones without smartphones. Not only will they be excluded from these vital services, but the unique characteristics of their demographic will not be included in the datasets used to train the technologies, thereby increasing the risk of bias. 

Knowing When to Implement 

While the implementation of these novel technologies may have significant positive effects, it is important to know when to implement them and under which conditions. An assessment of the current health system’s readiness to adopt and integrate new technologies should be the first step. Factors such as infrastructure resources, workforce capacity, and existing policies should be evaluated to determine the feasibility and sustainability of implementing digital health technologies. 

Amidst a public health emergency, tools may be developed to counter the specific effects of that health event. Implementing novel tools while experiencing and navigating crises is difficult and caution should be taken to ensure the protection of human lives and our privacy. This begins with an assessment to determine that there is a real need for the technology. In our paper “Public Health, Technology, & Human Rights: Lessons from Digital Contact Tracing,” Maria Carnovale and I outlined four principles: necessity, scientific validity, proportionality, and time-boundedness, that when taken together, establishes a threshold beyond which implementation of the technology is justified. This provides a useful framework for policymakers when making decisions about implementing novel tools in a health emergency. 

In considering each of these factors, implementation of digital tools for public health requires extensive resources and special considerations to be effective and reduce harm. Best practices suggest utilizing an interdisciplinary team consisting of technologists, public health practitioners, health policymakers, and in most cases, engagements with the private sector and local leaders of the communities that are included in the technology’s geographical range of operations. Who develops, implements, and manages the technology are important additional questions to answer, which will likely vary across locations and populations. For example, in a U.S. survey to understand the relationship between the public and trust in digital health tools, Julian Zlatev, a professor at Harvard Business School, and I found that about 65 percent of the population generally supported the use of digital health tools. However, they did not trust the federal government to develop or implement them. And while they trusted big tech companies to develop the technologies, they did not trust them to implement or manage the tools. Instead, they preferred their local health departments and universities to manage the operation, a stark departure from the approaches typically taken by governments when implementing novel tools, which are typically top-down. Exploring the structures of public-private-academic partnerships could be a useful line of research. 

In conclusion, the risk of deploying any digital product should never outweigh the potential benefits. As such, the developing and implementing teams must carefully analyze the conditions under which the technology is to be used and ensure that the need for the technology is justified. Questions on the sufficiency of available resources, who will have access and derive benefit, and how will the user be protected should all be answered well before any implementation takes place.