Technology Mediated Collaborations in Healthcare and Wellness Management
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ItemDetailed Perceptions by Health Service Providers Around EHRs: A Case Study of Australia’s e-Health Solution( 2018-01-03)The Australian government has invested heavily in the national e-health solution; namely, initially, the PCEHR, now MyHealth Record. A critical success factor is concerned with the perception and expectations of health service providers regarding the MyHealth Record. Further, it is important to understand the effect of the MyHealth Record on the patient-provider relationship, quality of care, and service providers’ views toward data security and confidentiality. The primary goal of this pilot study is to understand the health service providers’ perceptions and expectations; and thereby, predict the likely sustainability of the MyHealth Record. This has important implications in general as all OECD countries’ transition to large-scale e-health solutions.
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ItemWhat are the Gaps in Mobile Patient Portal? Mining Users Feedback Using Topic Modeling( 2018-01-03)Patient portals are positioned as a central component of patient engagement through the potential to change the physician-patient relationship and enable chronic disease self-management. In this article, we extend the existing literature by discovering design gaps for patient portals from a systematic analysis of negative users’ feedback from the actual use of patient portals. Specifically, we adopt topic modeling approach, LDA algorithm, to discover design gaps from online low rating user reviews of a common mobile patient portal, EPIC’s mychart. To validate the extracted gaps, we compared the results of LDA analysis with that of human analysis. Overall, the results revealed opportunities to improve collaboration and to enhance the design of portals intended for patient-centered care.
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ItemA Scorecard Method for Detecting Depression in Social Media Users( 2018-01-03)A Scorecard Method for Detecting Depression in Social Media Users Netsanet Tefera Lina Zhou University of Maryland, Baltimore County {netsa2, zhoul}@umbc.edu Abstract Depression is one of the most prevalent mental health disorders today. Depression has become the leading causes of disability and premature mortality partly due to a lack of effective methods for early detection. This research explores how social media can be used as a tool to detect the level of depression in its users by proposing a scorecard method based on their user profiles. In the proposed method, depression is measured by a selected set of key dimensions along with their specific indicators, which are weighted based on their importance for signaling depression in the literature. To evaluate the scorecard method, we compared three types of social media users: users who committed suicide due to depression, users who were likely suffering from depression, and users who were unlikely suffering from depression. The empirical results demonstrate the effectiveness of the scorecard method in detecting depression.
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