- Veröffentlicht: 07. Oktober 2023
As new technologies remake cities around the world, the most impactful and equitable technology-driven urban health interventions will have three core ingredients: data, connectivity, and collaboration.
At the intersection of technology and healthcare, there’s often an uncomfortable question about equity: Even if a new medical innovation can deliver impressive outcomes, what if the intervention remains too expensive to benefit most patients? Recently, that issue has become front and center in the public health vs. precision healthcare debate.
If “smart” healthcare solely meant personalized, AI-designed gene therapies, it might be difficult to reconcile technology-driven precision medicine with public health imperatives. However, viewed through a health equity lens, emerging technologies also present many opportunities to improve healthcare outcomes across the socioeconomic spectrum.
Urban connectivity is accelerating around the world. Smart devices are becoming cheaper, meaning that they can collect more data about more patients. Meanwhile, data analytics capabilities will increasingly enable targeted, hyper-personalized healthcare at scale. These innovations will impact all urban health stakeholders: life sciences companies that develop new therapies and devices, healthcare providers focused on clinical care, and civic entities tasked with improving public health at a population and community level.
Data will be the fuel that drives the smart, healthy cities of the future. But AI and connectivity alone won’t deliver bold healthcare transformations. Integrating this data will require creative, outside-the-box approaches and novel collaborations that prioritize diversity and equity. With the right priorities in place, we will be able to build smart cities with health outcomes that match the sophistication of their technological infrastructures.
Expanding Clinical Trial Access
Half of the FDA’s clinical trials are conducted in just 2% of United States ZIP codes. The subsequent underrepresentation of Blacks, Latinos, Asians, and others has caused uncertainty about the overall efficacy of certain treatments, not to mention doubt about key advancements. In the US, the DEPICT Act now mandates greater representation, but prompt compliance can be challenging due to decades-old clinical trial systems. Life sciences companies now have an enormous opportunity to contribute to smart, healthy cities by diversifying the clinical trials that will ultimately give birth to new health interventions. From a patient perspective, the metaverse and 5G are emerging as technologies that will help connect a more diverse group of patients to more seamless clinical trials. But behind the scenes, AI will also play a critical role in the emerging clinical trial landscape.
By analyzing the digital biomarker data streaming in from connected medical devices and other sources, AI will allow clinical trial sponsors to zero in on diverse, optimized groups of clinical trial candidates across numerous previously-unreachable communities. Advanced connectivity solutions, meanwhile, will enable novel hybrid trial designs and contribute to new clinical trial efficiencies, particularly in the early stages of the clinical trial funnel, and will enable increased diversity in terms of both trial sites and patients. As more people in more cities gain access to the clinical trial ecosystem, patients from previously overlooked communities will begin to feel a stronger connection to life sciences companies and processes, which will destigmatize the healthcare system as a whole.
Connected Clinical Care + Connected Public Health
New data-driven capabilities and accelerating connectivity will enable curated experiences for patients that span the clinical and public health ecosystems.
Increasingly, in a clinical setting, AI will be used to identify emerging health threats, enable early interventions, and communicate rapidly and clearly with patients. For urban populations, many of these innovations will be cost-effective and scalable, meaning that they can and will impact the health outcomes across the socioeconomic spectrum, from free and urgent care clinics to large hospital systems and at-home care.
These same tools will also impact public health. The COVID-19 pandemic revealed both opportunities and barriers when it comes to delivering effective, targeted public health communications at a community level. Increasingly, AI tools will give public health stakeholders the capability to deliver targeted, segmented, cohort-based behavioral nudges and improve the outcomes of those nudges in an iterative, data-driven fashion. Meanwhile, the translation capabilities of GenAI will complement AI-driven analytics, enabling public health officials to break down language barriers and deliver competently translated, culturally appropriate messaging to communities.
In both clinical settings and public health settings, the expansion of 5G will continue to mitigate the digital divide. Access to telemedicine and remote care will become more equitably distributed, and the increased bandwidth and capacity of 5G will support the seamless transfer of large medical datasets, enabling efficient remote monitoring and data exchange. Widespread deployment of IoT-enabled healthcare devices, meanwhile, will open up new opportunities for remote patient monitoring and real-time health data collection. This can lead to early detection and intervention, especially in underserved communities with limited access to healthcare facilities.
In a value-based care model, the cost of health outcomes is a critical metric. As healthcare companies, NGOs, and city governments consider how technology might advance urban health outcomes, cost is perceived as a significant constraint. On this front, data analytics capabilities and 5G connectivity are well positioned to provide solutions that are strongly aligned with value-based frameworks.
Across the clinical and public health ecosystems, one of the key challenges of these new approaches will be simply getting enough data to run effective AI and data analytics models. Here, collaboration will be critical. Public health entities will need to work with private stakeholders (including hospitals, drug companies, and medical device companies) to build and automate data pipelines while maintaining strong governance and privacy frameworks. The COVID pandemic caused many urban health stakeholders to make sudden (if imperfect) technology advances. The AI revolution presents an opportunity to revisit those same technology and data estates to achieve not just crisis readiness, but continuous data-driven health interventions at both a clinical level and a population level.
The Health Imperative for Smart Cities
A thriving city depends on a healthy populace. In this context, we now have the ability to weave new technologies into urban master plans, envisioning not just a next-gen Smart City, but a truly health-centric one. Climate change is already dialing up the health risks to urban populations around the world, making smart interventions all the more urgent. By thoughtfully integrating data and connectivity into the care landscape for all urban populations (including low-income populations), we can pave the way for resilient urban landscapes in which personalized patient care, precision through AI, and connected healthcare foster vibrant urban ecosystems.
Autor(en)/Author(s): Gaurica Chacko
Quelle/Source: wipro, 29.09.2023