Drug and Substance Abuse Point of Interest (POI) conflation and spatial attribute enrichment framework
Year: 2026
Type: article
Abstract: Point of Interest (POI) data is essential for accurate spatial analysis of pressing healthcare issues such as Drug and Substance Abuse (DSA). However, retrieving accurate healthcare POI information remains complicated. POI conflation integrates data from multiple sources to enhance spatial attribute quality and coverage. This study proposes a multi-step framework for healthcare POI conflation, including POI data collection from Location-Based Services (LBS), geographic and spatial attributes collection, calculating similarity across datasets, POI matching, spatial attributes enrichment, manual labeling, quality control, and deployment. We tested this framework on a DSA use case in California, USA. Our automated approach was able to detect 11,936 unique POIs related to this healthcare tag. Of the locations used for use case validation, 33% were common with the commercial benchmark POI dataset used by Safegraph. Out of the 11,936 total POIs, we were only able to find 4,535 (38%) that were not in the commercial benchmark dataset and relevant to the use case. Moreover, our results indicate that spatial attributes fill rates are 32% at the geometry building level and 98% at the Census block group (CBG) level. We conclude that using LBS can provide POIs with relevance and spatial attributes similar to commercial datasets.
Institutions: Cairo University, University of California System
Language: English
Topic: Data Quality and Management
Field: Decision Sciences
Domain: Social Sciences
Open Access status: green
Awards: Digital Device ID Targeting for Increasing Medications for Opioid Use Disorder: A Feasibility and Acceptability Study, Influence of Social Media, Social Networks, and Misinformation on Vaccine Acceptance Among Black and Latinx Individuals, Big Data Digital Outreach and Epidemiology Methods for HIV Care among Communities of Color
OpenAlex ID: W7138222501