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The article presents a study on the hospital-level associations between Web-based patient ratings on the National Health Service (NHS) Choices Web site and the objective measures of quality. The researchers conducted a cross-sectional observational study of NHS acute hospital trusts in England using data from 10,274 patient Web-based ratings. They found that the information provided by the Web sites represents a potentially important development in measuring the quality of health care.

Integrated care aims to organize care around the patient instead of the provider. It is therefore crucial to understand differences across patients and their needs. Segmentation analysis that uses big data can help divide a patient population into distinct groups, which can then be targeted with care models and intervention programs tailored to their needs. In this article we explore the potential applications of patient segmentation in integrated care. We propose a framework for population strategies in integrated care--whole populations, subpopulations, and high-risk populations--and show how patient segmentation can support these strategies. Through international case examples, we illustrate practical considerations such as choosing a segmentation logic, accessing data, and tailoring care models. Important issues for policy makers to consider are trade-offs between simplicity and precision, trade-offs between customized and off-the-shelf solutions, and the availability of linked data sets. We conclude that segmentation can provide many benefits to integrated care, and we encourage policy makers to support its use. [ABSTRACT FROM AUTHOR]