2024 FedHealth Thought Leadership Compendium

THOUGHT LEADERSHIP COMPENDIUM

REDESIGNING THE FUTURE OF WORK

Our workplace experts guide you through trends and best practices shaping the workforce of the future.

The Future of Work

How can business leaders stay ahead of workplace trends?

Aerobodies identifies core areas of performance to co-create wellness programs that are strategically integrated into operational workflow from a sustainable human-centric approach. The solution is simple: when your employee culture is healthy and motivating, your business thrives.

KEY TAKEAWAYS

>> Transparency about what a successful wellness culture looks like, how it will be measured, and what milestones will be achieved will clarify the significance of your initiatives.

>> Start with getting employees to participate in your current wellness programming, and ask for honest feedback on what their frequent stressors are and how to best support them.

>> Evolve your organization's language, actions, and behaviors at the leadership level to elevate conversation around personal topics and reduce stigmatization.

>> The future maturity of Health & Wellness programming requires a shift from vertical HR benefits to embedding wellness into business practices, resulting in greater synergy across the organization

>> Focusing on individualizing Health & Wellness at the employee level enables workers to personalize programs based on their unique needs and goals, yielding more significant and enduring outcomes of participation and success

Trend Analytics on Retention & Engagement

According to The Hartford's 2022 Future of Benefits Report

59% of U.S. workers believe it would be easy to find a new job

According to The Hartford's 2022 Future of Benefits Report

79%

of U.S. workers who left or plan to leave their job for reasons related to culture, flexibility, and poor leadership

Virtual Globalization

Our ability to accelerate business communications and attract top talent on a global scale is as easy as connecting to WiFi. Globalization leads to greater levels of workplace diversity, a larger range of business partners, and access to more resources. Professionals are beginning to prioritize flexibility even ahead of salary, which drives competition for wellbeing innovation within organizational cultures. Aerobodies leverages a global perspective on wellness with digitally integrated and customizable solutions that demonstrate flexibility adaptable for growth.

When leading a successful hybrid or remote workforce, there are several considerations that enhance collaboration and autonomy: Whitepaper by www.Aerobodies.com

>> Showing interest in your employees' lives outside of meetings brings a genuine humanitarian perspective on their overall wellbeing.

>> Eliminating the head of the table perspective for virtual meetings by having all participants shown at an equal screen size empowers people to speak and be heard.

>> Clarifying project scope and deadlines allows autonomy over an individual's work product, and gives a sense of direction for task and time management regardless of their office location.

>> Strategic ergonomic design of work environments maximize collaboration and productivity among colleagues by providing appropriate mental and physical stimulation.

Remote & Hybrid Work Trends

66% of U.S. employees work remotely at least part time

50% of remote workers feel isolated and crave more team collaboration

50%

turnover reduction when employees have access to a remote work option

22% increase in performance when given the ability to work remote

AI Drives Collaboration and A Sustainable Work Culture

Utilize technological advancements to stay ahead of workplace trends and prioritize employee wellbeing for sustainable growth.

The power of collaborative technologies and automation is increasingly valuable for companies conducting business without geographic boundaries.

The ability to organize and share ideas, coordinate tasks, and manage projects digitally helps teams solve business problems and accomplish specific goals in a shorter amount of time.

When 47% of a worker's time per week is dedicated to administrative tasks such as managing emails and gathering information, investing in collaborative automation tools will save you time and resources while improving communications and productivity. Utilizing automations for predictable workflow patterns increases efficiency by releasing the requirement of manual intervention. The ability to shift workplace priorities and expand human skillsets leads to transformative structural changes within your organization.

Balancing the challenges of constant training, initial costs, open APIs for flexibility, and cybersecurity brings to light a shift in focus for prioritization. Aerobodies utilizes this shift regarding health and wellbeing to drive accessible, cost effective and sustainable solutions that are well received by employees across your organizational portfolio.

Automation Trends in the Workplace

of companies have increased their revenue by deploying AI technology of business leaders believe that automating tasks in the organization increase productivity of all stakeholders

Attracting the Workforce of the Future

Knowing these workplace trends, how can business leaders attract and retain top talent?

Invest in the wellbeing and workplace culture initiatives that empower employees increasing productivity and engagement.

Talent acquisition has become increasingly more competitive with employees seeking priority for health, wellness, and flexibility within their ideal work culture. To stay ahead of the race for top talent, hiring managers can push the envelope of candidate expectations and apply proactive recruitment strategies to attract the workforce of the future

>> A thoughtfully crafted representation of an organization's vision, mission, ethos and culture gives a holistic perspective into the company and showcases the benefits of being part of the business. Leveraging positive employee experiences through testimonials is another highly effective and transparent way to attract potential employees and clarify day to day business objectives.

>> Creating clear job descriptions, keeping communication lines open, and giving honest feedback in a timely manner provide a more positive candidate experience and helps employers fill roles more effectively.

>> Hiring managers carefully constructing purposeful interview questions that focus on wellbeing priorities of the candidate gives the opportunity to clarify cultural expectations. Asking what fulfills them in a job or how they would like to make a bigger contribution to the company helps make the interview feel warm and personal

Whitepaper by www.Aerobodies.com

The Future of Reporting on Workplace Wellbeing Metrics

55% of employees and 77% of C-suite executives believe companies should be required to publicly report workforce wellbeing metrics, just as they do with ESG metrics, thus developing trust and a more desirable workplace.

To develop a nuanced, actionable understanding of wellbeing across the organization, self-reported data alongside measured observable proxies assess wellbeing in an empirical way.

Aerobodies strategizes measurements on the percentage of workers who use their entire PTO, amount of overtime worked, volume of work-related emails sent on the weekends, and the WELL Building Standard framework, among other deliverables, to gauge an organization's wellbeing culture.

REFERENCES

Allison, E (2022, May 9) Council Post: Three Proactive Ways To Attract The Workforce Of The Future Forbes https://www forbes com/sites/forbesbusinesscouncil/2022/05/09/ three-proactive-ways-to-attract-the-workforce-of-the-future/?sh=83f657d742d3

Alton, L. (2018, February 1). Workplace Changes Are Accelerating: Why And What Millennials Should Do About It. Forbes. https://www.forbes.com/sites/larryalton/2018/02/01/workplace-changes-areaccelerating-why-and-what-millennials-should-do-about-it/?sh=298026062def

Glossop, A (2021, November 29) 5 benefits of online collaboration tools with examples | Ideagen Www ideagen com https://www ideagen com/thought-leadership/blog/5benefits-of-online-collaboration-tools

Granholm, C. (2020, August 28). Models & Dimensions of Wellbeing. NIRSA. https://nirsa.net/nirsa/portfolio-items/health-and-wellbeing-models-and-dimensions/ Hagerman, L. C. S. (2017, April 5). Workplace Health and Wellness as a Strategic Talent Management Lever WISP Blog https://www wispapp com/blog/2017/04/05/workplace-health-and-wellness-as-astrategic-talent-management-lever-3/

Learn more at www aerobodies com/case-studies Fran Dean-Bishop - 703-820-0217

FranB@Aerobodies.com

Protecting patient privacy in public health research

How can public health researchers leverage patient data without compromising privacy?

When it comes to patient data privacy, public health leaders may feel like they are caught between a rock and a hard place. On one hand, they require highquality and comprehensive data to fuel their research and develop effective interventions. But they must also protect privacy, as patient health data is frequently targeted in data breach schemes. In fact, between 2015 and 2022, 32% of all recorded data breaches were in the healthcare sector—almost double the number recorded in the financial and manufacturing sectors.

Complicating matters is the need to connect and combine patient data sets to derive insights. For example, if a patient’s name and social security number are the link between their HIV test results and their medical risk factors, a data breach could publicize the patient’s HIV status, name, social security number, and more. Likewise, for smaller test groups like historically underrepresented communities and rare disease patients, it can be difficult to make progress on research because the ability to identify sensitive data becomes greater as the sample size reduces.

“Despite the challenges, data sharing is essential. The public and health care sectors need to share data to prevent and control infectious disease outbreaks, chronic diseases, and other risks to the public. We saw the importance of such sharing during the COVID-19 pandemic when policymakers and the public wanted the most accurate assessment of risk. But such sharing must be done with the utmost caution and privacy protections, or other serious problems will result— including loss of trust in the health system,” says John Auerbach, ICF’s senior vice president of federal health and former CDC official.

How can agencies protect highly sensitive, personally identifiable information (PII) and protected health information (PHI) without restricting it so much that it can’t be used when needed to protect either the individual or the larger community?

Promising health data privacy solutions

Here are three techniques we’ve been exploring and researching for our federal health clients:

Homomorphic encryption is a specific cryptographic technique that allows analysts to perform analytics and data processing with patient-level data—without needing to decrypt it first. Because the data is fully encrypted and never exposed, it remains unreadable even by those doing the computations, protecting patient privacy while offering the full research value of the data to agencies.

Using homomorphic encryption, our data scientists have successfully carried out analytics and trained classification models on data while it was fully encrypted—in other words, the data was not only encrypted both at rest and in motion/transport, but also while in use. We conducted analytics as both single-party and multi-party computations for a leading U.S. public health agency, helping them assess the limitations and opportunities homomorphic encryption presents for public health research.

Homomorphic encryption is best suited for simple computations on small to moderately sized quantitative datasets. However, advancements in techniques and hardware acceleration are gradually improving its performance and may make it available for more complex computations and larger datasets.

Confidential computing is an infrastructure technology that protects data as it’s being used by analyzing it in a secure area of a main processor, which prevents unauthorized access or data manipulation. Confidential computing works by establishing a security boundary, or secure enclave called a trusted execution environment (TEE), to isolate the computation from the rest of the system. Data is decrypted only within the TEE—once the computation is complete, the data is reencrypted and returned to its original state.

Our data scientists have developed a proof-of-concept that demonstrates singleand multi-party computational analytics in a TEE in the cloud. While there are many intricacies to the confidential computing architecture, this technique is suitable for complex workloads and large datasets, and often requires collaboration with a cloud provider or an enterprise partner.

Privacy-preserved datasets use a hybrid of masking privacy techniques to create variance data sets, so they can be shared and protected at different levels for different purposes and population sizes, with varying levels of granularity. This bypasses the typical limitations seen in sophisticated analysis by mixing synthetic data in with the real data, or by masking certain fields, without losing the significance of the data set. The original data can then be multi-purposed in a variety of ways. We are exploring public health uses cases with Anonos and their patented implementation of privacy-preserved datasets, Variant Twins.

These three techniques—homomorphic encryption, confidential computing, and privacy-preserved datasets—make it easier for risk-averse data owners to share their data, and the promise of privacy-preserving technologies is likely to play a prominent role in shaping the legal and regulatory landscape surrounding public health data management and sharing.

Making a choice

These are just three of many data privacy technologies now available. Some can be combined at scale, but since none are the single-best solution across the board of public health data privacy challenges, it can be hard to know what to look for, especially with new techniques frequently coming online.

Our initial R&D work has helped our public health agency clients understand the fundamental differences in the use cases these techniques apply to—when it’s prudent to use one versus another—and will help them make informed decisions moving forward.

A trusted partner with experience not only in data privacy research and development, but in the public health sector as well, is vital to applying the right technology to your unique challenge.

From data to insights

ICF has played a central role in advancing public health around the world for nearly 50 years. We support federal agencies such as the National Institutes of Health (NIH) and the Centers for Disease Control and Prevention (CDC) in the development and delivery of mission-critical public health programs. While the techniques outlined above show great promise, the orchestration of secure data solutions can involve a range of technologies and approaches.

For example, ICF developed a research data management solution for the National Cancer Institute (NCI). The NCI receives large volumes of mass spectrometry data from research groups in the Clinical Proteomic Tumor Analysis Consortium (CPTAC). The agency needed a way to store this data in one central location to make the information accessible to all cancer researchers interested in the tumor proteome—and maintain the results for future research after the conclusion of each CPTAC cancer program. In addition, the proteomic data needed to be moved securely, with no loss of content. But the proteomic data storage site previously used by the research community had challenges with slow data transfer times and some file loss.

Our team created a secure data portal for researchers by combining a web server, database, file storage system, and an IBM-Aspera high-speed data transfer server. The portal allows as many researchers as necessary to access the important proteogenomic data. We built quality control and security into data receipt by encrypting data in transit and then verifying it with a checksum file. Due to this focus on data integrity, researchers can trust that files correctly map back to the right sample and accurately capture the information associated with tumor acquisition.

We also developed daily transfer logs to track and troubleshoot errors, and our team employs harmonization to ensure clinical data from many different sources are usable and may be compared across cancer programs.

The CPTAC Data Coordinating Center and Proteomic Data Commons are providing information about the cancer proteome to researchers around the world so they can use these data in their work. The portal regularly manages 29 terabytes, with 785 terabytes of data downloaded in 140 countries. The impact of the CPTAC has been showcased in 18 scholarly publications, which highlights the breadth of researchers using this technology and data resource to advance our understanding of proteogenomics across many cancers, including ovarian, breast, colon, lung, pediatric and adult brain cancer, and others while prioritizing data privacy protections.

Earning patient trust

Taking steps to protect patient data privacy is an important way for public health agencies to earn the trust of those they serve. While the systems and solutions we develop for research have thorough privacy protections built in, those protective measures need to be communicated to the public in a way they can understand. When patients trust that their data are protected, they may be far more willing to participate in trials and programs that can have life-saving impacts.

ICF is a global consulting services company, but we are not your typical consultants. We help clients navigate change and better prepare for the future.

We’ve played a central role in advancing public health around the world for nearly 50 years. As close collaborators and seasoned experts, we bring both leading-edge skills and a powerful drive to improve public health outcomes for all populations. We provide advisory services and project implementation to government agencies and top science organizations. From conducting surveys and managing sensitive data to motivating behavior change and assessing program performance, we combine our domain expertise with cutting edge technology solutions to maximize the impact of our clients’ programs.

Learn more at icf.com/health.

Ar�ficial Intelligence and the Impact on Global Dispari�es

Arlyne Beeche, MSc, PhD, The MayaTech Corpora�on

Ar�ficial intelligence (AI) has infiltrated discussions at all strata of global society, from households to government. Many consider AI to be a transforma�ve technology with the poten�al for significant impacts on the world at large. Advocates and cri�cs alike claim that AI will revolu�onize nearly every area of human endeavors – a realis�c presump�on that requires acknowledging the poten�al for both posi�ve and nega�ve societal outcomes. This is par�cularly relevant when considering the impact of AI on lowand middle-income countries (LMICs), who already face dispropor�onate dispari�es, insecurity, and exploita�on, when compared to their high income country (HICs) counterparts. Whether AI will have a societal impact is not in ques�on, as it most certainly will.

The question is whether that impact will result in increased disparities and the propagation of poverty and insecurity, or increased security and economic opportunities, particularly for the impoverished and most vulnerable.

AI Technology and Limita�ons

AI is defined as technology that enables computers and machines to simulate human intelligence and problem-solving capabili�es by using complex algorithms, extremely large data sets, and massive computa�onal power 1 However, AI technology via dataset restric�ons and algorithm design, has significant limita�ons that can lead to inaccurate predic�ons. Large dataset quality is ques�onable, as available datasets are o�en erroneous, incomplete, noisy, and rapidly outdated. Furthermore, datasets may not be representa�ve of different communi�es, and have been shown to contain biases and stereotypes present in socie�es. 2 Algorithms, human-writen and automated, are fallible, and through purposeful or inadvertent design, can lead to flawed decision-making that exacerbates social inequali�es, reinforces stereotypes, or contributes to social unrest (Figure 1). To mi�gate these risks, it is essen�al to be proac�ve in considering ethical principles, community values and contextual representa�on in the design of algorithms and sourcing of large datasets in AI technology.

Figure 1. Cascading effects of health inequality and discrimina�on manifest in the design and use of ar�ficial intelligence (AI) systems. Source: Leslie D, et al. BMJ. 2021; 372;n304. 3

AI and Global Development

It has been suggested that AI advances could double economic growth rates and increase labor produc�vity in the U.S. by 40% by 2035. 4 However, economic growth rates are not experienced equally across and between socie�es, and some advances may serve to increase socioeconomic gaps (e.g., impact on the unskilled labor workforce). 5 While it has been forecasted that AI has the poten�al to drive economic growth and development in LMICs, it is ques�onable how such development will ameliorate significant exis�ng gaps in infrastructure, accessibility to clean water and food security. AI proponents suggest that a focus on AI skills development is the answer; however, as 244 million children and youth worldwide are s�ll out of school for social, economic, and cultural reasons, the forecasted benefits of local AI training might be experienced only by future genera�ons.

The jus�fica�on of investment in AI ecosystems (the interconnected network of stakeholders, resources, technologies, and ins�tu�ons involved in the development, deployment, and u�liza�on of AI technologies) in LMICs requires accountability to support claims of egalitarian and posi�ve development outcomes, as LMIC popula�ons have significant limita�ons to equitable opportuni�es that have direct impacts on human development. Figure 2 highlights the 2021 Inequality-adjusted Human Development Index, which is the “actual” level of human development, as it accounts for inequality. 6

Figure 2. Inequality-adjusted Human Development Index vs. GDP per capita, 2021 Source: UNDP, Human Development Report (2024); Leandro Prados de la Escosura (2021). htps://ourworldindata.org/grapher/hdivs-augmented-hdi6

AI is progressing at an incredible speed and the differen�al impact on human outcomes merits significant aten�on and investment. Many interna�onal agencies whose mandate is to improve development outcomes in LMICs 7 have already embraced AI in the implementa�on of their work. The World Bank Group is suppor�ng Ini�a�ves that u�lize AI to “inform country level and global governance challenges” and the United States Agency for Interna�onal Development is applying AI with hopes to reshape healthcare, agriculture, and democracy in the developing world. 8, 9 The o�en limited agency of LMICs to unilaterally accept/reject development projects should not be underes�mated."

There is o�en an unequal balance between LMIC governments and wealthy philanthropies or external government development agencies for desired projects. 10 Some�mes there is congruency (e.g., common goals and research priori�es); at other �mes, there are donor-driven development programs and projects accepted by LMIC governments due to external pressures or agreed upon exchanges. Although some programs may result in successful efforts towards sustainable development goals, others may not benefit local researchers or may not directly benefit research par�cipants. 11

Power imbalance structures in AI project expansion must be addressed, especially when considering the implementa�on of new technologies that can have vast societal impacts. AI tools can be used to infringe on basic human rights by enabling surveillance, censorship, or more effec�ve targe�ng of individuals for malign or exploita�ve purposes. AI applica�ons lie at the center of emerging na�onal security concerns and have the poten�al to promote instability and conflict. 12 In developed countries, AI tools have on occasion automated racial profiling, fostered surveillance, and perpetuated racial stereotypes; 13 however, they can manifest in any se�ng, especially in places with histories of ethnic conflict or inequality. As the development community adopts tools enabled by AI, we need a clear understanding of how to ensure their applica�on is effec�ve and with equitable benefits.

Maintaining and expanding ethical governance standards should be priori�zed as the applica�on of new AI technologies con�nues to grow in LMICs, especially as many are at the behest of interna�onal donors. 14 The increased flow of foreign funding in AI systems should raise ques�ons on the true beneficiaries of AI investment and dedica�on to basic development needs in LMICs. The pursuit of maintaining and expanding ethical governance standards, 15 as well as collabora�ve efforts involving governments, businesses, academia, and civil society, must be priori�zed as the applica�on of new AI technologies con�nues to grow in LMICs, to ensure that the benefits of AI are equitable and sustainable 16 In addi�on, there must be a focus on strengthening the civil society structures holding AI systems and actors accountable, and shaping policy environments that in turn encourage open, inclusive, and secure digital ecosystems. 17

AI impacts can be catered to localized se�ngs for more relevant outcomes and equitable opportuni�es for development and representa�on. 18 Inten�onal investment in preparing future genera�ons to tackle the con�nued evolu�on of AI can serve to avoid the widening of dispari�es within groups, socie�es, and na�ons. Enhancing AI focused educa�on and training can increase opportuni�es for AI skills training and ecosystem investment and development, and diminish the impact of unchecked AI technologies that may result in LMIC dominance, manipula�on, abuse, and the perpetua�on of poverty through the broadening of dispari�es 19

Conclusion

AI’s capacity to leverage large, complex datasets to create predic�ons and corresponding ac�ons is unprecedented, and the impact on humankind will be significant. AI advocates forecast societal benefits through the increased applica�on of the rapidly growing technology; however, in moving

forward we cannot be blindsided to the dangers of unguided and ungoverned AI applica�ons. Ethical and responsible ac�ons are required to limit foreseeable and unforeseen risks associated with the unrestricted implementa�on of AI technologies across the globe, par�cularly amongst the most impoverished and vulnerable popula�ons, without redress or recourse.

As AI has the poten�al to impact the masses, there must be ethical considera�ons and oversight to address likely increases in development, health, and security dispari�es. 20 AI products have already been shown to incorporate societal biases, which risks increased discrimina�on based on gender, socioeconomic status, and race. These nega�ve impacts will manifest more severely in LMICs, where dispropor�onately limited access to educa�on, healthcare, safety, and food security already exists. Those socie�es, par�cularly the younger genera�ons therein, should not be le� behind in the progression of alternate development opportuni�es, including AI training, design, and implementa�on.

If LMICs are le� behind, global dispari�es and corresponding outcomes will certainly worsen, resul�ng in increased global insecurity for us all.

References

1. IBM.com, What is AI

2. Srinivasan R & Chander A, 2021, Associa�on for Compu�ng Machinery, Biases in AI Systems. A survey for prac��oners

3. Leslie D, et al, March 16, 2021, Does “AI” stand for augmen�ng inequality in the era of covid-19 healthcare? BMJ, BMJ 2021; 372;n304.

4. Accenture (www.accenture.com), June 21, 2017, Accenture Report: Ar�ficial Intelligence Has Poten�al to Increase Corporate Profitability in 16 Industries by an Average of 38 Percent by 2035

5. Ellingrud K, et al, McKinsey Global Ins�tute, July 26, 2023, Genera�ve AI and the future of work in America

6. UNDP, Human Development Report (2024); World Bank (2023), OurWorldInData.org/human-development-index | CC BY.

7. DAC List of ODA Recipients | Effec�ve for repor�ng on 2024 and 2025 flows. 8. USAID from the American people, 2023, Inventory of Ar�ficial Intelligence (AI) Use Cases

9. USAID from the American People, 2022, Reflec�ng the Past, Shaping the Future: Making AI Work for Interna�onal Development.

10. Charani E, et al, June 3, 2022, Funders: The missing link in equitable global health research? PLOS Glob Public Health. doi: 10.1371.

11. Schroeder, D., et al, 2019, Exploita�on Risks in Collabora�ve Interna�onal Research. In: Equitable Research Partnerships. SpringerBriefs in Research and Innova�on Governance. Springer, Cham. doi:10.1007/978-3-030-15745-6_5.

12. Horowitz MC & Scharre P, Technology and Na�onal Security, January 2021, AI and Interna�onal Stability Risks and Confidence-Building Measures

13. Howard, A. & Borenstein, J, 2018, The Ugly Truth About Ourselves and Our Robot Crea�ons: The Problem of Bias and Social Inequity. Sci Eng Ethics 24, 1521–1536.

14. Dafoe A, August 27, 2018, AI Governance: A Research Agenda, Centre for the Governance of AI Future of Humanity Ins�tute University of Oxford.

15. Gibaja AF, November 1, 2022, Democracy in the Republic of the Internet is backsliding. Is it too late to act?, Interna�onal IDEA, Suppor�ng Democracy Worldwide.

16. Araz Taeihagh, Governance of ar�ficial intelligence, Policy and Society, 2021;40(2): 137–157.

17. Helen M, Rethinking AI for Good Governance, Daedalus 2022; 151 (2): 360–371.

18. Roche C, et al, 2021, Ar�ficial Intelligence Ethics: An Inclusive Global Discourse?, Proceedings of the 1st Virtual Conference on Implica�ons of Informa�on and Digital Technologies for Development.

19. Van Cappelle F, Global Lead, Digital Educa�on, UNICEF, October 17, 2023, Can AI transform learning for the world's most marginalized children?, World Economic Forum.

20. The Honorable Clay Jr WL, et al, 2023, The Impact of Ar�ficial Intelligence on Vulnerable Popula�ons in the Workforce, Pillsbury.

As a long-standing stakeholder in helping to advance U.S. public health outcomes, The MayaTech Corporation is deeply committed to our nation’s health – with a keen eye on addressing social determinants of health and reducing systemic barriers that result in health disparities and inequities. We provide a portfolio of research, training, evaluation, capacity-building, and other strategic support services - all aimed at reaching and impacting the most vulnerable populations, amplifying best practices, and innovating the practice of public health.

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