Pursuing population health gains through better implementation.

The CUNY Institute for Implementation Science in Population Health (ISPH) was founded on the notion that substantial improvements in population health can be efficiently achieved through better implementation of existing strategies, policies, and interventions across multiple sectors. With that in mind, we study how to translate and scale-up evidence-based interventions and policies within clinical and community settings in order to improve population health and reduce health disparities.

The Institute uses a range of digital communication channels to disseminate news and information among a global network of research colleagues and partners. This website serves as a platform for disseminating our scientific work and tools we have developed, as well as showcasing emergent topics in the field of implementation science.


Staff Spotlight>>

McKaylee Robertson photo

McKaylee Robertson

Investigator Spotlight>>

Heidi Jones photo

Elizabeth Kelvin


Recent ISPH Publications

Development of an opioid-related Overdose Risk Behavior Scale (ORBS). Pouget ER, Bennett AS, Elliott L, Wolfson-Stofko B, Almeñana R, Britton PC, Rosenblum A. Substance Abuse.

Does mHealth voice messaging work for improving knowledge and practice of maternal and newborn healthcare? Chowdhury ME, Shiblee SI, Jones HE. BMC Medical Informatics and Decision Making.

A longitudinal analysis of albendazole treatment effect on neurocysticercosis cyst evolution using multistate models. Montgomery MA, Ramos M, Kelvin EA, Carpio A, Jaramillo A, Hauser WA, Zhang H. Transactions of the Royal Society of Tropical Medicine & Hygiene.

Increasing Depression and Substance Use Among Former Smokers in the United States, 2002-2016. Cheslack-Postava K, Wall MM, Weinberger AH, Goodwin RD. American Journal of Preventive Medicine.

CNVRanger: association analysis of CNVs with gene expression and quantitative phenotypes. da Silva V, Ramos M, Groenen M, Crooijmans R, Johansson A, Regitano L, Coutinho L, Zimmer R, Waldron L, Geistlinger L. Bioinformatics.