Harnessing Technology and AI to Support Primary Health Services in Post-Disaster Scenarios
10 sept. 2024
by Magen David Adom in Israel
Blog post
The Scenario: A City in Crisis
Imagine a crowded city, 48 hours after a devastating disaster—whether an earthquake, flood, or storm. The aftermath is catastrophic: many casualties, destroyed infrastructure, blocked roads, and limited access to electricity and water. Medical services, severely disrupted by the disaster, are only beginning to recover. As healthcare providers struggle to treat the injured, the primary health system faces unprecedented challenges. Here, innovative technology and Artificial Intelligence (AI) can offer critical solutions.
The Challenges
It is essential to recognize that the healthcare system itself is vulnerable to disasters. Hospitals and clinics are often damaged, and medical personnel may be injured or unable to reach their workplaces. Health facilities might be rendered inoperable, and services will be restricted to safe areas. Medical records, typically stored in clinics or digital systems, could become inaccessible due to physical damage or communication infrastructure failures.
Moreover, the medical needs of the population will likely surge. Chronic patients may lose access to essential medications, living conditions will deteriorate, stress levels will increase, and access to fresh food, drinking water, and hygiene supplies will be compromised. As a result, patients with chronic conditions who were previously stable may now require urgent care, further straining an already overwhelmed hospital system (1).
Technological Solutions
In the face of these challenges, technology and AI can play a crucial role in supporting the primary health system during and after a disaster. Initially, technology can assist in the critical phase of needs assessment. In our data-driven era, vast amounts of information can be rapidly collected from various sources, including reports, satellite and aerial imagery, hospital registries, and even social media. AI can analyze this diverse data to produce actionable insights, helping decision-makers determine the type, extent, and location of the aid required (2).
Bibliography:
-
Del Papa, J., Vittorini, P., D’Aloisio, F., Muselli, M., Giuliani, A. R., Mascitelli, A., & Fabiani, L. (2019). Retrospective analysis of injuries and hospitalizations of patients following the 2009 earthquake of L’aquila city. International journal of environmental research and public health, 16(10), 1675.
-
Abid, S. K., Sulaiman, N., Chan, S. W., Nazir, U., Abid, M., Han, H., ... & Vega-Muñoz, A. (2021). Toward an integrated disaster management approach: how artificial intelligence can boost disaster management. Sustainability, 13(22), 12560.
-
Salehinejad, S., Jannati, N., Ershad Sarabi, R., & Bahaadinbeigy, K. (2021). Use of telemedicine and e-health in disasters: a systematic review. Journal of Emergency Practice and Trauma, 7(1), 56-62.
Khanal, S., Medasetti, U. S., Mashal, M., Savage, B., & Khadka, R. (2022). Virtual and augmented reality in the disaster management technology: a literature review of the past 11 years. Frontiers in Virtual Reality, 3, 843195.