Health Informatics

Artificial intelligence (AI) tools, particularly those that use natural language processing (NLP), are becoming increasingly prominent in healthcare delivery. For these systems to operate safely and reliably in clinical settings, they require high-quality training datasets drawn from multiple sources, including electronic health record (EHR) data, that closely reflect real-world conditions.

The United States (U.S.) faces urgent health challenges, including poor maternal and childhood health outcomes, childhood obesity, opioid use disorder, cancer, and chronic conditions, which require personalized care tailored to each patient’s unique circumstances.

Patients, clinicians, decision makers, and other stakeholders depend on robust, evidence-based information to make informed health care decisions. Linking Medicaid data to other sources enables a deeper understanding of how Medicaid services and interventions influence health outcomes.

In Fiscal Year 2025, OS-PCORTF projects and other OS-PCORTF initiatives collectively enhanced the data infrastructure available for patient-centered and comparative clinical effectiveness research (CER) across national and HHS health objectives.

This Issue Brief explores opportunities that technology-enabled care (TEC) offers to help meet patient and provider needs for high-valued coordinated care to improve health outcomes. It explores literature surrounding existing available TEC options, as well as economic and payment issues that influence whether this is taken up.

ASPE recently published a narrative review in PLOS Digital Health exploring how synthetic data are being used. Researchers searched published literature and known, publicly available synthetic datasets.

OVERVIEW HHS has proposed a $20 million initiative in the President's FY 2001 budget dealing with Health Informatics: Improving Information for Decision Making. The ultimate goal of this initiative is to improve patient care and health outcomes through the efficient and effective use of data.

This paper compares CHIP and QHP out-of-pocket spending for premiums and cost sharing, taking into account premium subsidies and cost-sharing reductions for Marketplace plans. We also review analyses done by others comparing the benefit packages in separate CHIP plans and QHPs.

Identifying Opportunities To Maximize the Utility of Genomics Research Data Through Electronic Health Information Exchange Meeting Summary Andrew Dorfmann and Jessica Nadler 10/15/2009