Digital health experts’ views on building One Health Surveillance using Telehealth

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Digital health experts’ views on building One Health Surveillance using Telehealth

https://doi.org/10.21203/rs.3.rs-3420054/v1

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One health (“OH”) refers to integration of human, animal, and ecosystem health. An OH-based disease surveillance will enable early detection of zoonoses and ecosystem changes, instrumental for pre-empting future pandemics. Telehealth is used for preventive and curative remote care; telehealth can be instrumental for developing OH-surveillance but the barriers and levers in building such systems are unknown. We address this by conducting an innovation sprint with digital health experts at an international conference. We asked the participants how we might build a telehealth-driven OH surveillance system. They identified barriers, opportunities, and needs, and constructed empathy maps. Analyses of their responses revealed that they identified lack of a centralised system as a barrier. Networks, and centralised data systems would facilitate building telehealth-based OH surveillance. These findings are also consistent with existing approaches of OH surveillance without telehealth. This suggests implementing telehealth in OH surveillance will have similar issues to existing approaches.

Health sciences/Health care/Health policy

Health sciences/Health care/Public health/Epidemiology

The One Health High Level Expert Panel has defined One Health as an integrated and unified approach to sustainably balance and optimise health of humans, animals, and ecosystem as interdependent entities¹. OH has ushered a new paradigm in organising health services in a horizontal, trans-disciplinary integration of zoonoses, antimicrobial resistance, and health effects from ecosystem changes such as global warming, and biodiversity loss². Given the interconnected and interdependent nature of OH, if disease surveillance systems were designed incorporating OH with remote monitoring, they would be instrumental in pre-empting future pandemics³.

Global population needs have made humans vulnerable to old and new pathogens despite advances in disease surveillance, as evidenced by 13 public health emergencies of international concern being declared between 2005–2023⁴. Experience from COVID-19 pandemic suggests that infectious diseases initiate in animals, start slow and then rapidly evolve in uncertain ways resulting in pandemics. At the same time, COVID-19 pandemic also highlighted the role of telehealth (“TH”) in ensuring smooth operation of health services in the face of mounting uncertainties when face to face delivery of care is deemed infeasible^5–8. Post-pandemic, as TH continues to evolve, it is pertinent to ask how might TH be integrated with OH^9–11. It is increasingly important to pre-empt pandemics by integrating TH and OH..

The effectiveness of TH for disease surveillance is well established. Mansberger (2013) reported an RCT found that compared with traditional surveillance, non-mydriatic camera-based surveillance using telehealth was more effective for screening and triaging patients for diabetic retinopathy¹². A retrospective time-series analysis of the National Ambulatory Care Reporting System (NACRS) ED discharges and Telehealth Ontario data for GI illness found when TH were integrated into a real-time syndromic surveillance system for detection of unexpected events¹³. Bhunia et al (2012) conducted a systematic review of the effectiveness of TH for reducing the number of emergency visits to the hospitals for patients with kala azar and found TH to be a transformational force¹⁴. Caruso et.al (2022) found that TH was effective for renal cell carcinoma surveillance during COVID-19¹⁵. Delgado-Noguera et al (2022) have conducted a community-based citizen-science initiative to address Chagas Disease in Venezuela with tele-parasitology and have reported that incorporating TH into surveillance affords building persistent educational resources¹⁶. Regardless, all these projects are either for specific human diseases, so how might an OH and TH based disease surveillance work?

Bordier et al (2019) have identified that a key characteristic of One Health surveillance is multisectoral collaboration across institutions and disciplines to plan, coordinate, and implement surveillance¹⁷. They have proposed a four step “socio-technical framework” that includes a participatory and iterative process implemented during a consensus-building workshop: these include defining the problem, and co-construction of the current and the desired surveillance system, and identification of changes and actions required to progress from the current situation to the desired state¹⁸. This framework of a OH surveillance system suggests that TH can be used for collaboration, given the distributed nature of the professionals who work in animal health (veterinarians and animal health experts), ecosystem (farming community and environmentalists), and human (medical practitioners, epidemiologists, and public/population health specialists). We have extended this iterative participatory process by conducting a design innovation sprint to ask health and informatics professionals how we might design a OH disease surveillance system and what issues we might face.

Innovation Sprint. -- Design innovation sprints refer to bursts of activities used to brainstorm new prototypes or innovations and there are emerging instances of using design innovation sprints in health care¹⁹. Vechakul et.al. (2015) have reported conducting a 12-week design sprint in California in 2015 for creating a “best baby zone” aimed at reducing inequities in infant mortality rates and at the end of that exercise, they have found that design sprint helps in creating innovative programmes in solving complex challenges²⁰. Kruger et.al (2023) have reported results of an innovation sprint with pharmacy and public health students that sprints foster interprofessional collaboration and problem-solving skills; further, faculty observed a high rate of interprofessional behaviors within student teams²¹.

As described here, we conducted an innovation sprint with digital health professionals about developing telehealth and OH based surveillance systems at an international conference of digital health, medical and healthcare informatics professionals titled Medinfo. Medinfo is a biennial conference of digital health experts and the 2023 Medinfo conference was hosted in July 2023 in Sydney²². The goal of the sprint for the participants to ideate how telehealth might be used in OH surveillance systems and identify the needs and barriers.

Notification of the sprint was sent to conference participants a week before the sprint. After obtaining the verbal consents from all participants to participate and record their written notes, we briefed the participants about the purpose and organisation of the sprint for the first 10 minutes. We did not collect any personal data from any participant. Following the introduction, participants ideated the next ten minutes on the barriers of implementation of a TH based OH surveillance system, wrote their ideas on individual “sticky notes”, and pasted the notes on the walls around the room. The participants moved around the room to identify common points based on the ideation exercise. This was followed for the next 30 minutes where the participants filled in an empathy map (Fig. 1)

Empathy Map. -- The empathy map had four quadrants: in the “Say” quadrant, the participants indicated what they would say about opportunities, barriers, and building of TH based One Health surveillance systems. These were captured in coloured sticky notes that were kept for this purpose. In the “Think” quadrant, likewise, the participants posted what they thought about it. In the “Do” quadrants, the participants posted action points and in the “Feel” quadrants, the participants posted their emotional contents about OH and TH based disease surveillance. The “sprint” was wrapped up around 50 minutes.

Data collection and analysis. -- After this workshop, individual pieces of text written on sticky notes and the empathy map sheets were collected and the statements and phrases on the slips and the empathy map worksheet were transferred to a number of electronic text files (the number of text files corresponded to the number of sticky notes and empathy map sheets). The texts were then read and analysed using Taguette²³ and used a computational text processing pipeline to identify individual emergent codes. This process was repeated several times till all categorisation of codes were exhausted. The codes and associated text documents were then textually analysed, tabulated, and word clouds were generated.

Ethics. -- This research was exempted from Human Ethics Review as no personal data and a Human Ethics Approval was not applicable as per Helsinki Declaration as in this case as we worked with opinion data from individuals who were not identifiable in any way²⁴. All authors reviewed the themes and commented on them.

This sprint resulted in 71 individual documents and seven themes - Challenges, Needs, Actions, Opportunities, Feelings, Concerns and Questions, and Barriers. Challenges were statements expressing difficulties and problems associated with TH based OH surveillance. Needs were what would be necessary for building TH based OH surveillance. Actions were what needed to be done; opportunities were future positive gains expected from such implementations. Besides these themes, the participants also noted doubts and questions, their feelings about the project, and identified barriers of implementations. We analysed the barriers and challenges together.

Majority of the sentiments were challenges (28%, N = 20 documents), needs (25%, N = 18), actions (21%, N = 15) and opportunities (11%, N = 8) (Table 1). The dominant themes within challenges included “non-centrality”, i.e., lack of a central, unifying construct and geographical dispersion of countries but also dispersion across disciplinary domains (ecosystem, animal, and human health) that needed reconciliation. Lack of a unified definition of health was identified as a barrier. In terms of barriers, participants identified that OH was global in its scope but issues around regulatory and infrastructure for each country or jurisdiction were barriers in implementing a global telehealth based solution for OH surveillance. Scale of the problem was noted as a barrier. Participants identified worldwide variation in quality of healthcare delivery and monitoring as challenges. They also identified implementation of a unified process of data sharing across boundaries as a challenge.

Needs for interoperability and integration of the data structures and processes, consumer involvement, buy-in by the health consumers and education were identified needs. In particular, the participants felt the need for interoperable systems to build telehealth based OH disease surveillance solutions. Interoperability meant users of TH based OH would be able to use it in health systems in the world equally, and that, TH based OH surveillance would be operable across ecosystems, animal, and human health. As with the challenges, regulations, government and politics were also identified as necessities to build TH based OH surveillance systems.

The participants identified six actions and several opportunities. These included (1) network of data acquisitions, (2) developing structured universally accessible data portals, (3) automated analyses supplementing real-time disease surveillance, (4) centralised data lakes integrating animal, human, and ecosystems, (5) integrating extant health surveillance systems, and (6) making it easy for everyone. Integration and interoperability were identified as needs and action points to build a TH based OH surveillance. Developing a TH based OH surveillance system would be “big 4 EMRs” (“big for EMRs”), indicating that significant implication for electronic medical records, and that clinical decision support systems couls be integrated into the EMR. Other themes were the roles of “human factors” in influencing uptake and role of tools such as wearables to continuously feed information to such a system, indicating the role of built-in temperature and air pressure sensors in smartwatches and wearables can be connected to this system to integrate not only human factors but also associated ecological variables. Word-cloud based on bigrams identified consumer involvement, controlling politics, and surveillance systems.

Main themes

Table 1

Main categories of themes identified by the participants in the sprint
Category	N (%)
Challenges	20 (28.2)
Needs	18 (25.3)
Actions	15 (21.1)
Opportunities	8 (11.3)
Feelings	5 (7.1)
Concerns and Questions	3 (4.23)
Barriers	2 (2.82)

Table 2

Themes from the innovation sprint. The “Text Codes” are actual text words written on the “sticky notes” or on the empathy map sheets used for the purpose of this innovation sprint activity
Theme	Text Codes
Needs	Human Buy-in Needs design Consumer involvement Education Regulatory International collaborations are essential Consumer Involvement Touch of Interoperability Making data sharing more available Shared compiled vocabulary Reference terminology Integration of Teleconsultation int EMR (Interoperability) Enabling Environment for Interoperability Regulations Workforce Strategy UX Design has to control Politics has to control Politics Government The People Surveillance systems are already in place and need integration
Challenges and Barriers	Conspiracy theorists No Centralised System Hundreds on non-centralised systems Government structure Boundary Issues Sharing of data among different parties How to develop generalized model for how the different components of OH lead to concerning events & outcomes Consumer Involvement Centralisation Information How to find How to collect How to connect Regulatory/Legislations ICT/IOT infrastructure Shared compiled vocabulary Defining the boundaries of the problem The scale of the problem Settling on a unifying definition for health in this context Anything not used is useless – so multitask Globally so dispersed (Government, WHO) has to control Politics Government The People “Telehealth” = misleading term
Actions	Create the network of human data acquirers Provide them with a structured & understandable data portal Incorporate onehealth acquired data could be analysed automatically to develop signals for outbreaks, areas of concern If area of concern identified a telehealth Connection could be initiated from experts to the concern site Build a network of data acquisition both human and electronic (eg temperature, weather) that communicate & enter data into a repository Use devices (ios android etc) Collect telehealth data to understand human interactions/impact on animals & environmental – eg food consumed Incorporate data collected by those who look after the environment/seek data input Interoperability In establishing a centralized data lake, include all categories of human, zoological, and ecological elements, and crosslink by e.g. fungal {human, animal, plant} Monitoring eg reporting of COVID data – match with monitoring data on coronavirus in animals etc Make it easy for the end user Standardised data/processes Education Make it easy Surveillance systems are already in place and need integration
Opportunities	Big 4 EMR acquired data could be analysed automatically to develop signals for outbreaks, areas of concern Human Factors influence uptake Globally -> WHO Common systems will ensure oneness Human Factors and ability for patients to use/wear technology “Telehealth” connected health Surveillance systems are already in place and need integration

Word cloud or tag clouds

We have approached this exercise with the goal of generating ideas. To that extent, sprint participants have identified that the distributed nature of disciplines, geographical variations, differences in jurisdictions, and differences between health systems presented challenges to implementation of a TH based OH surveillance. The participants also articulated the need for a unified, centralised system in developing a TH based OH surveillance system. They emphasised consumer and stakeholder involvement in designing such systems, the role of developing a network of data acquisition, and creating centralised data lakes to integrate the diverse systems. At the sae time, they have observed that diverse disciplines that have different standards and operations of data acquisitions, and management, and overcoming these can present a challenge to the implementation. From the perspective of digital health, these themes warrant further exploration as building effective OH based surveillance systems is necessary to integrate animal, human, and ecosystem health and in the process prevention or early detection of outbreaks.

The challenges identified by the digital health experts for a TH based implementation of OH surveillance are similar to those reported in the literature for developing OH surveillance systems in general. Johnson et.al. (2017) in their qualitative analysis of ten participants have found that the absence of a definition of One health and siloed approaches by different sectors restrict the ability for professionals to work collaboratively across disciplines as a barrier, and stressed the need for political will as an essential requirement for the integration of surveillance systems. They have therefore suggested establishment of a formal governance body with representatives from each sector could assist in overcoming long-standing barriers of privacy and distrust and developing interdisciplinary training in One Health concepts for medical, environmental and veterinary students may encourage cross-disciplinary collaboration, much in line with what we have reported here²⁵. In a systematic review of the existing One Health surveillance system, Bordier et al (2020) also have noted the pre-eminent role of collaboration among professional sectors at different decision-making scales for coordination and implementation of OH surveillance systems. In their accompanying model, the role of horizontal (across-sectors at the same level) and vertical (policy, institutions, and operations) levels are articulated as well²⁶.

In terms of building global TH based OH based disease surveillance, the health sector’s collective experience with COVID-19 pandemic and TH driven response can serve as a guide as to how we might transcend the geographical and disciplinary barriers that we identified. Analysing the responses of the digital health community, Gunasekeran et.al (2021) have noted the rise of digital communications platforms (DC) in response to a global pandemic, but will this enable us to bridge the gaps we have identified when it comes to bridging the divide across disciplines and silos of concepts and jurisdictions?²⁷. Harnessing the power of digital communications platform may enable creation of centralised data lakes, facilitate a network of data scientists and digital health specialists across the disciplines of medicine and public health, veterinary science and ecology to enable the hyper-connected global surveillance systems, as well as integrating with the stakeholders and members of the public to inform and raise awareness about One Health. This will in turn facilitate the development of a “citizen science” modality of surveillance. Carney et.al. (2022) and Delgado-Noguera et.al. (2022) have shown the effectiveness of integrating global citizen science networks for mosquito borne diseases and tele-parasitology surveillance networks, with projects such as theirs this provide an opportunity to build a framework of citizen science network and that would mean integrating or building a centralised database and “make things easy” as we observed in our sprint^{28, 16}.

A design sprint such as this is one of the first steps towards building a TH based OH surveillance but this has at least three limitations that are worth noting. First, this sprint selectively presents the viewpoints of digital health professionals, not necessarily those of ecologists, zoonoses experts or epidemiologists who are typically at the forefront in the operationalisation of the surveillance systems. The real world “boots on the ground” experience is necessary to evaluate these ideations with what needs to be built. Second, a rapid, directed, small scale exercise to ideate a few issues and possible solutions is at best indicative and needs further validation as to what other issues may arise, as Bordier et.al. (2021) noted in developing their framework that a collective process is necessary. Third, we did not consider the technological limitations as to what is achievable in terms of setting up global scale OH surveillance systems in our sprint¹⁸. Zoonotic diseases are spreading through a variety of sources, including direct and indirect animal contact, food and waterborne contamination, and vector- borne illness and is measured by the global health security index for countries.

Despite these limitations, the findings from our sprint indicate that integration of telehealth and One Health surveillance holds promise and collateral benefits. Incorporation of OH surveillance will lead to a development of an automated centralized data repository incorporating diverse data sources that in turn can bolster the effectiveness of disease surveillance overall and help in pre-empting future outbreaks. Reconciliation of jurisdictional boundaries globally concerning data requirements and quality standards has the potential of not only benefitting the One Health system but also enhancing the practice of telehealth and standardise delivery health services globally. As we confront the challenges of a changing climate, warming oceans, and the ongoing threat of zoonotic epidemics, telehealth remains a critical tool in disease prevention and healthcare delivery.

Going forward, we’d like to conclude with a call to action. We hope to build a coalition of telehealth and digital health experts, epidemiologists, ecologists, and veterinarians and animal health experts who will bring to the table diverse expertise and wisdom to develop a worldwide intelligence system that will enable humanity to pre-empt future pandemics. This will require interoperability across jurisdictions and at the same time, build decentralised, federated solutions. More sprints, deliberations, and projects with real world applications will help build that reality.

Acknowledgements

The authors acknowledge all participants in the Medinfo2023 innovation sprint for their input to the process

Author Contributions

Arindam Basu (AB) contributed to planning the innovation sprint, data collection, analysis, authoring the manuscript, and submission to the journal and handle correspondence

Sheila John, Anandhi Ramachandran, and Najeeb Al-Shorbaji participated in the innovation sprint as facilitators, read the manuscript, and edited the manuscript.

Charles Umeh read and edited the manuscript.

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There is NO Competing Interest.

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