56
views
0
recommends
+1 Recommend
1 collections
    0
    shares

      Submit your digital health research with an established publisher
      - celebrating 25 years of open access

      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      Social Media and Rating Sites as Tools to Understanding Quality of Care: A Scoping Review

      review-article

      Read this article at

      ScienceOpenPublisherPMC
      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          Background

          Insight into the quality of health care is important for any stakeholder including patients, professionals, and governments. In light of a patient-centered approach, it is essential to assess the quality of health care from a patient’s perspective, which is commonly done with surveys or focus groups. Unfortunately, these “traditional” methods have significant limitations that include social desirability bias, a time lag between experience and measurement, and difficulty reaching large groups of people. Information on social media could be of value to overcoming these limitations, since these new media are easy to use and are used by the majority of the population. Furthermore, an increasing number of people share health care experiences online or rate the quality of their health care provider on physician rating sites. The question is whether this information is relevant to determining or predicting the quality of health care.

          Objective

          The goal of our research was to systematically analyze the relation between information shared on social media and quality of care.

          Methods

          We performed a scoping review with the following goals: (1) to map the literature on the association between social media and quality of care, (2) to identify different mechanisms of this relationship, and (3) to determine a more detailed agenda for this relatively new research area. A recognized scoping review methodology was used. We developed a search strategy based on four themes: social media, patient experience, quality, and health care. Four online scientific databases were searched, articles were screened, and data extracted. Results related to the research question were described and categorized according to type of social media. Furthermore, national and international stakeholders were consulted throughout the study, to discuss and interpret results.

          Results

          Twenty-nine articles were included, of which 21 were concerned with health care rating sites. Several studies indicate a relationship between information on social media and quality of health care. However, some drawbacks exist, especially regarding the use of rating sites. For example, since rating is anonymous, rating values are not risk adjusted and therefore vulnerable to fraud. Also, ratings are often based on only a few reviews and are predominantly positive. Furthermore, people providing feedback on health care via social media are presumably not always representative for the patient population.

          Conclusions

          Social media and particularly rating sites are an interesting new source of information about quality of care from the patient’s perspective. This new source should be used to complement traditional methods, since measuring quality of care via social media has other, but not less serious, limitations. Future research should explore whether social media are suitable in practice for patients, health insurers, and governments to help them judge the quality performance of professionals and organizations.

          Related collections

          Most cited references41

          • Record: found
          • Abstract: found
          • Article: not found

          Google trends: a web-based tool for real-time surveillance of disease outbreaks.

          Google Flu Trends can detect regional outbreaks of influenza 7-10 days before conventional Centers for Disease Control and Prevention surveillance systems. We describe the Google Trends tool, explain how the data are processed, present examples, and discuss its strengths and limitations. Google Trends shows great promise as a timely, robust, and sensitive surveillance system. It is best used for surveillance of epidemics and diseases with high prevalences and is currently better suited to track disease activity in developed countries, because to be most effective, it requires large populations of Web search users. Spikes in search volume are currently hard to interpret but have the benefit of increasing vigilance. Google should work with public health care practitioners to develop specialized tools, using Google Flu Trends as a blueprint, to track infectious diseases. Suitable Web search query proxies for diseases need to be established for specialized tools or syndromic surveillance. This unique and innovative technology takes us one step closer to true real-time outbreak surveillance.
            Bookmark
            • Record: found
            • Abstract: found
            • Article: not found

            Small area variations in health care delivery.

            Health information about total populations is a prerequisite for sound decision-making and planning in the health care field. Experience with a population-based health data system in Vermont reveals that there are wide variations in resource input, utilization of services, and expenditures among neighboring communities. Results show prima facie inequalities in the input of resources that are associated with income transfer from areas of lower expenditure to areas of higher expenditure. Variations in utilization indicate that there is considerable uncertainty about the effectiveness of different levels of aggregate, as well as specific kinds of, health services. Informed choices in the public regulation of the health care sector require knowledge of the relation between medical care systems and the population groups being served, and they should take into account the effect of regulation on equality and effectiveness. When population-based data on small areas are available, decisions to expand hospitals, currently based on institutional pressures, can take into account a community's regional ranking in regard to bed input and utilization rates. Proposals by hospitals for unit price increases and the regulation of the actuarial rate of insurance programs can be evaluated in terms of per capita expenditures and income transfer between geographically defined populations. The PSRO's can evaluate the wide variations in level of services among residents of different communities. Coordinated exercise of the authority vested in these regulatory programs may lead to explicit strategies to deal directly with inequality and uncertainty concerning the effectiveness of health care delivery. Population-based health information systems, because they can provide information on the performance of health care systems and regulatory agencies, are an important step in the development of rational public policy for health.
              Bookmark
              • Record: found
              • Abstract: found
              • Article: not found

              Harnessing the cloud of patient experience: using social media to detect poor quality healthcare.

              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.
                Bookmark

                Author and article information

                Contributors
                Journal
                J Med Internet Res
                JMIR
                Journal of Medical Internet Research
                JMIR Publications Inc. (Toronto, Canada )
                1439-4456
                1438-8871
                February 2014
                20 February 2014
                : 16
                : 2
                : e56
                Affiliations
                [1] 1IQ healthcare Radboud University Medical Center NijmegenNetherlands
                [2] 2Radboud REshape & Innovation Center Radboud University Medical Center NijmegenNetherlands
                [3] 3Emergency Healthcare Network Radboud University Medical Center NijmegenNetherlands
                [4] 4Faculty of Health Sciences University of Southampton SouthamptonUnited Kingdom
                Author notes
                Corresponding Author: Lise M Verhoef Lise.Verhoef@ 123456radboudumc.nl
                Article
                v16i2e56
                10.2196/jmir.3024
                3961699
                24566844
                9d6542d7-534c-44a0-9708-7ae5ca30c0f5
                ©Lise M Verhoef, Tom H Van de Belt, Lucien JLPG Engelen, Lisette Schoonhoven, Rudolf B Kool. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 20.02.2014.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/2.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in the Journal of Medical Internet Research, is properly cited. The complete bibliographic information, a link to the original publication on http://www.jmir.org/, as well as this copyright and license information must be included.

                History
                : 14 October 2013
                : 07 January 2014
                : 17 January 2014
                : 19 January 2014
                Categories
                Review
                Review

                Medicine
                social media,rating sites,patient experiences,patient satisfaction,quality of health care
                Medicine
                social media, rating sites, patient experiences, patient satisfaction, quality of health care

                Comments

                Comment on this article