On June 19, 2026, researchers, clinicians, and policy advocates gathered for a pivotal learning session titled “Data Scraping for Health Research: How to Use Online Data in Your Study”. The virtual event explored data scraping as an emerging and practical methodological approach toward innovative, data-informed health research and policy development.
The session was organized by Women in Global Health (WGH) Philippines, the Alliance for Improving Health Outcomes (AIHO), Damiana Social Ventures, and 101 Health Research, with support from FutureWORKS Asia, LIRNEasia, and IDRC CRDI Canada. Dr. Katherine Ann V. Reyes, Principal Investigator and Component Lead for Capacity Building & Policy Analysis, opened the session by anchoring the discussion on the broader FutureWORKS Asia Grants Program, which examines how digitalization, automation, climate change, and demographic shifts are reshaping labor markets in Asia.
Transforming the Web into Evidence
Leading the technical discussion was Aian L. Rosales, MSDS, COO and Data Scientist of 101 Health Research. Rosales introduced data scraping as the automated process of collecting large amounts of data efficiently from websites and online platforms, bypassing the need for manual copying. He emphasized that health research traditionally relies on surveys and clinical records, which can be time-consuming, whereas scraping allows researchers to access real-time insights from social media, public health websites, and job portals.
To demonstrate the power of this methodology, Rosales presented findings from a comprehensive case study analyzing the impacts of climate change and digitalization on the nursing industry. The 101 Health Research team scraped job-searching sites using Python libraries like BeautifulSoup, Selenium, and Regex, followed by data pre-processing using Large Language Models (LLMs).
Key Findings from the Nursing Labor Market
The exploratory data analysis generated profound empirical insights into the nursing profession’s current landscape:
- The Rise of Travel Nursing: Demand for travel nurses is relatively high, dominating the top job titles and filling up most of the list in the extracted data.
- The Wage Divide: The mean monthly salary for jobs based in the Philippines is around PHP 20,000, whereas U.S.-based postings show a mean monthly salary of around USD 10,000, noting stark regional wage disparities.
- Digital Competencies are Mandatory: Proficiency in Microsoft Excel, electronic health records, and other data-handling tools is now expected alongside classic clinical competencies, reflecting a major shift toward digital workflows.
- A “Soft-Skills Core”: Adaptability, communication, and technical competence form a universal core, emerging as the single most prevalent skill community in two-thirds of the analyzed nursing sectors.
- Educational Geography: Demand for lower- and mid-level qualifications is broadly dispersed across the Philippines, but higher-degree requirements (like Master’s degrees) cluster tightly around Metro Manila.
- Benefit Discrepancies: While U.S. listings layer on travel and education perks, domestic Philippine roles emphasize overtime pay and wellness programs. Interestingly, Geriatrics and Home Health postings now feature the highest benefit coverage at over 75%.
- A Blind Spot for Climate Stress: Almost no job postings mention disaster readiness or flexible deployment during heat waves, leaving nurses underprepared for extreme environmental events.
Policy Implications and the DOH Perspective
The presentation drew significant insights from policymakers. Sir Pio, Chief Program Officer of the Health Research Division of the Health Policy Development and Planning Bureau at the Department of Health (DOH), noted that data scraping presents a compelling response to the constant need for faster, better evidence. He highlighted that data scraping can serve as a low-cost, real-time early warning system to detect emerging trends and public concerns ahead of formal reporting systems.
Sir Pio also underscored the implications of the findings, stating that the demand for travel nurses and massive wage differentials highlight a deeper health systems vulnerability tied to workforce retention. He echoed the urgency of aligning the national curriculum and training with emerging digital skills and disaster risk reduction, noting that the absence of climate resilience language in job postings points to a misalignment with established policy priorities.
Ethical Scraping and Next Steps
Rosales reminded attendees that methodological agility must come with ethical responsibility. When dealing with potentially sensitive data, he emphasized the importance of pseudonymization and utilizing localized, open-source LLMs rather than public commercial AI tools to ensure data privacy.
Closing the session, Kim Sales, Co-convenor of WGH Philippines, affirmed that generating evidence on equity and gender means finding the data where it lives—often described within the online portals that data scraping can capture.