3 Most Important Challenges to be considered while using social media data for Medical & Healthcare...
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Transcript of 3 Most Important Challenges to be considered while using social media data for Medical & Healthcare...
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3 MOST IMPORTANT CHALLENGES TOBE CONSIDERED WHILE USINGSOCIAL MEDIA DATA FOR MEDICAL& HEALTHCARE RESEARCHTAGS-Tags: Social Media for Exchanging Health Information, Data Analysis, Data Collection, DataAnalyst, Data Collection, Healthcare Social Networking, Predictive Analytics
SERVICES-Research Planning | Data Collection | Semantic Annotation | Business Analytics | Bio Statistics | Econometrics
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In Brief
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Studies indicated that patients primarily used Twitter (59.9%), particularly for increasing knowledge and exchanging advice andFacebook (52.3%), particularly for social support and trading advice.
Professionals mainly used LinkedIn (70.7%) and Twitter (51.2%), for communication with their colleagues and marketing details.
As patients continue to turn to online means for health care information to monitor their decisions, it is becoming graduallysignificant for radiologists to involve with patients online via social media daises.
There are several means that physicians can use social media to deliver patients with valued information and develop thecomplete patient experience.
By elevating discoverability, curating radiology, involving with patient communities, and generating mineable social media content,radiologists can develop as thought leaders in this new form of patient-centered announcement and information discussion.
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IntroductionSocial media channels are being used by patients for switching healthinformation, involvements with their chronic condition, and pursueinformation from other people or establishments, for example
NHS Choices (www.nhs.uk)
Joining the Conversation describes Big White Wall (www.bigwhitewall.com)
Mental health SNS that facilitates peer-professional interactions
National Institute for Health & Care Excellence (NICE)
UK government (https://www.gov.uk/government/publications)
NHS England Publication stores (www.healthline.com)
Contd...
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Given that there is a high usage of social media for exchanging health information, it offersnew opportunities between and amongst healthcare professionals, patients and public.
Data Analysis on Healthcare service information ‘empowers’ patients and the generalpublic to make responsible decisions.
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Today, publicly available real-world social media blogs, microblogs [such as twitter] internet forums, content communities [suchas YouTube, Flickr], social networking sites [such as Facebook and LinkedIn), data can now be analyzed with relative ease,bypassing many logical challenges associated with traditional approaches of Data Collection (e.g. electronic medical records, orconventional randomized clinical trials).
THREE ESSENTIALCHALLENGES OFRESEARCHERS DESPITETHE HIGH FLOW OF DATA
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Which is the Most CommonDisease Category Shared inPublic Posts?
1.
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Social media channels provide efficient, permeating and user-friendly daises that can inspire involvement, engagement andachievement required from both those who collect and deliver care to make health promotion interventions effective.
Participating health methods are progressively drawing consideration among the scientific community and could be used forhealth promotion programs through social media such as reviews, forum discussion, blogs, micro blogs and social networks.
The time restraints of today’s medical practice pooled with the demand for chronic conditions make any additional request ofextra time used by Health Care Experts a challenge.
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What Kind of Information can beExtracted from Social Networking Sites?
2.
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What are Ethical Guidelines to be Adopted forExtracting and Analyzing Health Behaviour?
Study designs using social media-derived data should be transparent and readily available to the public.
Researchers should respect the context in which content is sent.
All data that can be used to recognize tweet authors, including geolocations, should be available.
No information collected from social media should be used to procure more data about tweet authors from other sources.
Study designs that necessitate Data Collection from a few personalities rather than combined analysis entail InstitutionalReview Board (IRB) approval.
Researchers should adhere to a user’s attempt to control his or her data by respecting privacy settings.
3.
Contd.
According to the Fortune Report (March 18, 2019), the parliamentary group called on the social media platforms to giveresearchers all the Data Analyst they need to analyses the problem and the following the polluter pays principle – to pay a0.5% levy on their profit to fund a “Social Media Health Alliance”.
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Contd.
Calculating thepredictability of medical
conditions from socialmedia posts
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Social media applied in a healthcare context represent a temptingopportunity to improve the patients’ well-being, promoting patientcare and education. The major Healthcare Social Networking (HSN) platforms requirethe massive action of a medical professional who replies topatient’s queries, also acting as moderators on specific topicswhen it is needed.
Benefits of Healthcare Social Networks
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Promoting networking and information exchange, enabling self-education among patients about particular diseases.
Sharing patients’ experiences that can be helpful for other ones
Supporting the treatment process
Reducing the patient’s stress when he/she is waiting for a diagnosis or when he/she discovers to be affected by aparticular disease
Promoting information gathering and prevention campaign regarding specific diseases
Optimizing the work of the clinical personnel who interact with patients skilled in their diseases
Promoting knowledge management
Promoting research and monitoring activities
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ConclusionSocial media information has the benefit that it often has a built-incommunication network back to patients.
For example, Facebook now allows users to flag posts within theirsystem that they think may suggest suicidal ideation. Facebook thenanonymously delivers resources for entities at risk. This study hasseveral boundaries.
Constellations of predictive words often do not representcausalmechanisms, and the findings are cor-relational.
However, in enlightening, what people think, feel, and do social mediacapture sensitive, cognitive, behavioural and environmental indicationsthat have substantial Predictive Analytics that to be validates and areotherwise rationally elusive to researchers and clinicians.
Contd.
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People’s character, mental state, and health behaviours are allreflected in their social media and all have a tremendous impacton health.
This blog is to show that language on social media can predictdiagnoses within people’s health record, revealing newprospects to personalize care and understand how patients’ordinary daily lives relate to their health.
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