The Evolution and Typology of Learning Health System Hospitals and other Health Information Interested Hospitals in the US.

This study identifies the type, distribution, and interactions of US hospitals that identify as electronic-data-driven, patient-centric, and learning-focused. Such facilities, termed Health Information Interested (HII) hospitals in this study, meet the defining criteria for one or more of the following designations: learning health systems (LHS), Health Information Technology for Economic and Clinical Health (HITECH) meaningful use stage three compliant (MU3), Patient-Centered Outcomes Research Institute (PCORI) funded, or medical home/safety net (MH/SN) hospital. The American Hospital Association (AHA) IT supplemental survey and other supporting data spanning 2013 to 2018 were used to identify HII hospitals.

Building the foundation for health system transformation: Oregon's Patient-Centered Primary Care Home program.

Objective: Health system reform is largely dependent upon the transformation of primary care in addition to the alignment of incentives that mediate the allocation of resources. The Patient-Centered Medical Home (PCMH) is a model of enhanced primary care that encourages coordination, patient-centered care, integration of public health services, and innovative methods for improving population health-all critical elements of health system reform. Because it changes the way primary care is organized and delivered, the PCMH model has been adopted as a foundational component of Oregon's health system transformation.

Health insurance status, medical debt, and their impact on access to care in Arizona.

Objectives: We examined the impact of health insurance status on medical debt among Arizona residents and the impact of both of these factors on access to care.

Methods: We estimated logistic regression models for medical debt (problems paying and currently paying medical bills) and access to care (medical care and medications delayed or missed because of cost or lack of insurance).

Results: Insured status did not predict medical debt after control for health status, income, age, and household characteristics.