Health system data incompletely capture the social risk factors for drug overdose. This study aimed to improve the accuracy of a machine-learning algorithm to predict opioid overdose risk by integrating human services and criminal justice data with health claims data to capture the social determinants of overdose risk in Allegheny County, Pennsylvania, an area heavily affected by the opioid crisis.
Recent Abstracts
Model Kentucky Ordinance Establishing a County Opioid Abatement Advisory Council
The invisible pain: Gaps in Brazil’s public health system data on Menstrual and…
Exploring the Interface Between Birth Registration and Citizenship Determination: A Scoping Study in…
A dor invisível: lacunas nos dados do SUS sobre dor menstrual e pélvica
Catalyzing Support for CRVS Improvement – Examples from the Data for Health Initiative
A Guide to Designing Contextualized Civil Registration and Vital Statistics E-Learning Courses
Guide to Developing Standard Operating Procedures (SOPs) for Civil Registration Using a Case-Based…
Building Safe and Healthy Communities
Uncovering the Hidden Risks of PM 2.5 Exposure Among School-Aged Children in Jakarta
Strengthening Health Systems to Address Air Pollution in Ethiopia