The utilization of healthcare services serves as a barometer for current and future health outcomes. Even in countries with modern healthcare IT infrastructure, however, fragmentation and interoperability issues hinder the (short-term) monitoring of utilization, forcing policymakers to rely on secondary data sources, such as surveys. This deficiency may be particularly problematic during public health crises, when ensuring proper and timely access to healthcare acquires special importance. We show that, in specific contexts, online pharmacies' digital footprint data may contain a strong signal of healthcare utilization. As such, online pharmacy data may enable utilization surveillance, i.e., the monitoring of short-term changes in utilization levels in the population. Our analysis takes advantage of the scenario created by the first wave of the Covid-19 pandemic in Mainland China, where the virus' spread lead to pervasive and deep reductions of healthcare service utilization. Relying on a large sample of online pharmacy transactions with full national coverage, we first detect variation that is strongly consistent with utilization reductions across geographies and over time. We then validate our claims by contrasting online pharmacy variation against credit-card transactions for medical services. Using machine learning methods, we show that incorporating online pharmacy data into the models significantly improves the accuracy of utilization surveillance estimates.
Keywords: Digital footprint; Healthcare; Healthcare utilization; Online pharmacies.
© 2023. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.