The consumers' social media use in choosing physicians and hospitals: the case study of the province of Izmir : Choosing Physicians and Hospitals

To investigate patients' and health professionals' (a) motives and use of social media for health-related reasons, and (b) barriers and expectations for health-related social media use. We conducted a descriptive online survey among 139 patients and 153 health care professionals in obstetrics and gynecology. In this survey, we asked the respondents about their motives and use of social network sites (SNS: Facebook and Hyves), Twitter, LinkedIn, and YouTube. Results showed that patients primarily used Twitter (59.9%), especially for increasing knowledge and exchanging advice and Facebook (52.3%), particularly for social support and exchanging advice. Professionals primarily used LinkedIn (70.7%) and Twitter (51.2%), for communication with their colleagues and marketing reasons. Patients' main barriers for social media use were privacy concerns and unreliability of the information. Professionals' main barriers were inefficiency and lack of skills. Both patients and professionals expected future social media use, provided that they can choose their time of social media usage. The results indicate disconcordance in patients' and professionals' motives and use of social media in health care. Future studies on social media use in health care should not disregard participants' underlying motives, barriers and expectations regarding the (non)use of social media. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

Recent years have seen increasing interest in patient-centred care and calls to focus on improving the patient experience. At the same time, a growing number of patients are using the internet to describe their experiences of healthcare. We believe the increasing availability of patients' accounts of their care on blogs, social networks, Twitter and hospital review sites presents an intriguing opportunity to advance the patient-centred care agenda and provide novel quality of care data. We describe this concept as a 'cloud of patient experience'. In this commentary, we outline the ways in which the collection and aggregation of patients' descriptions of their experiences on the internet could be used to detect poor clinical care. Over time, such an approach could also identify excellence and allow it to be built on. We suggest using the techniques of natural language processing and sentiment analysis to transform unstructured descriptions of patient experience on the internet into usable measures of healthcare performance. We consider the various sources of information that could be used, the limitations of the approach and discuss whether these new techniques could detect poor performance before conventional measures of healthcare quality.