Health information technology to advance care in accountable care organizations: Implications for Medicare patients.

Background: Prior research has explored the link between health information technology (HIT) and performance of accountable care organizations (ACOs). However, the challenges of HIT use in ACOs for the management of chronic diseases among Medicare beneficiaries remain less examined.

Purpose: Given the high costs of implementing HIT and the occurrence of multiple chronic conditions (MCC) among elderly individuals, it is important to understand the extent to which HIT capabilities enable chronic disease management among the Medicare population.

The interaction between high-level electronic medical record adoption and hospitalist staffing levels: A focus on value-based purchasing.

Objective: This study sought to understand the relationship of hospital performance with high-level electronic medical record (EMR) adoption, hospitalists staffing levels, and their potential interaction.

Materials And Methods: We evaluated 2,699 non-federal, general acute hospitals using 2016 data merged from four data sources. We performed ordinal logistic regression of hospitals' total performance score (TPS) on their EMR capability and hospitalists staffing level while controlling for other market- and individual-level characteristics.

On the unsupervised analysis of domain-specific Chinese texts.

With the growing availability of digitized text data both publicly and privately, there is a great need for effective computational tools to automatically extract information from texts. Because the Chinese language differs most significantly from alphabet-based languages in not specifying word boundaries, most existing Chinese text-mining methods require a prespecified vocabulary and/or a large relevant training corpus, which may not be available in some applications. We introduce an unsupervised method, top-down word discovery and segmentation (TopWORDS), for simultaneously discovering and segmenting words and phrases from large volumes of unstructured Chinese texts, and propose ways to order discovered words and conduct higher-level context analyses.