[Recommended] NEED DISCUSSION IN 10 HOURS or LESS
Imagine that you are a member at PLM. This website’s mission is to improve the lives of patients through new knowledge derived from shared real-world experience and outcomes. These group chats offer connections between individuals that may experience the same health issues or challenges. The history behind this platform started when Stephen Heywood was diagnosed with ALS in 1998. His family tried to slow Stephen’s disease progression. The family became citizen scientists, harnessing the power of any and all information they could find. Nowadays, social media is the modern-day equivalent of the game of telephone; therefore, its impact on community health can’t be underestimated.
Elaborate how data is important to public health.
include the following aspects in the discussion:
1) What are some of the potential problems that could arise from using “Patients Like Me” and how can you mitigate these problems?
2) Visit the PLM website and review the various diseases. Then, discuss what functionality you would suggest be added to the site to improve greater traffic moving among subscribing users and newcomers.
3) Research how dedicated healthcare-focused platforms are being used in public health. Give specific illustrative examples.
REPLY TO MY CLASSMATE’S DISCUSSION TO THE ABOVE QUESTION AND EXPLAIN WHY YOU AGREE. (MINIMUM OF 150 WORDS)
Data has always played a vital role in the development of health care services and technologies. Throughout the ages, health care providers have relied on data gathered from patients and their caregivers to make decisions. To meet the needs of the health market, data that serves as a bridge between illness and medical interventions; it must be accurate, up-to-date, and detailed. For this reason, there are a variety of online platforms that provide real-time data and information, as well as innovations. When it comes to internet platforms, Patient Like Me (PLM) stands out as one of the most established, founded by patients’ families to disseminate information about their illnesses to the public. According to Wicks (2009), PLM was created by two Motor-Neurone Disease-affected siblings and a family friend. He also stated this platform enables patients (and their careers) to input data on their illness progression. PLM has proven to be incredibly beneficial for disseminating knowledge and experience on wide range of diseases and medical conditions. Despite its advantages, there are some drawbacks to PLM.
Although the PLM platform’s main purpose is to improve health outcomes by sharing sensitive health data, they put patients’ medical histories at risk by turning most medical notes inside out. Among the users of PLM are patients 68%, careers 17%, visitors 10%, researchers 4%, and physicians 1%, as per Smith and Wicks (2008). As a result, a large number of words, supplied by PLM, did not fit the Unified Medical Language System (UMLS) Methesaurus, and no nursing terminologies were included. There seem to be 5% misspellings, 1.4% slang with seventy symptoms which were unclassifiable. Although the information offered seems to make sense to ordinary people, it makes no sense to health professionals. To avoid these mistakes and to increase the accuracy of the data, a medical practitioner must review all the information before it is uploaded. Medical professionals are experts in their field, so they can help better understand what treatment is appropriate and how that can improve overall health (Lai el at., 2021). To further safeguard patient privacy while simultaneously offering current and useful information about illnesses and ailments, medical specialists from health institutions may add medical data. Because of the tremendous load of the online user, being able to access from anywhere at any time may cause the system to crash. Due to a large volume of online users, a system crash could occur if access is always available. Reduce the number of users by delivering the same information in the facilities via counseling sessions, books, and brochures, to avoid this kind of crash from occurring.
When using PLM systems, it offers the impression of a more conventional approach while still including a touch of modernism. In recent years, internet platform has undergone a transformation from texts to graphics. A stronger visual framework allowing health professionals, patients, and others’ input is required. PLM is a solid source of information about a wide range of medical illnesses and diseases. There seems to be an advantage to including a variety of personal perspectives. PLM is constantly upgrading its services, taking care of these challenges, and attempting to remain on top of the latest software and information. PLM should focus on a dedicated platform to dominate the field of health care online platforms.
The digital revolution in healthcare and education is real and needs health informatics systems. Dedicated platform helps for formal training and ongoing professional development in healthcare and being used in cross institutional, professional, and national boundaries. Gray (2016) claims that purpose-built tele-health systems have grown and complexity. She mentions dedicated platforms support multimedia education across biomedical disciplines, for direct provision over distance, and support multi-institutional, multi-stakeholder clinical and biological research.
Gray K. (2016). Public Health Platforms: An Emerging Informatics Approach to Health Professional Learning and Development. Journal of public health research, 5(1), 665. https://doi.org/10.4081/jphr.2016.665
Lai, A. G., Chang, W. H., Parisinos, C. A., Katsoulis, M., Blackburn, R. M., Shah, A. D., Nguyen, V., Denaxas, S., Davey Smith, G., Gaunt, T. R., Nirantharakumar, K., Cox, M. P., Forde, D., Asselbergs, F. W., Harris, S., Richardson, S., Sofat, R., Dobson, R. J. B., Hingorani, A., & Patel, R. (2021). An informatics consult approach for generating clinical evidence for treatment decisions. BMC Medical Informatics & Decision Making, 21(1), 1–14. https://doi.org/10.1186/s12911-021-01638-z
Smith, C. A., & Wicks, P. J. (2008). Patients Like Me: Consumer health vocabulary as a folksonomy. AMIA … Annual Symposium proceedings. AMIA Symposium, 2008, 682–686. Retrieved from: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2656083/
Wicks P. (2009). Sharing information with patients like me. British Journal of Neuroscience Nursing, 5(3), 132–133. https://doi.org/10.12968/bjnn.2009.5.3.40616