As the COVID pandemic unfolded, pharmaceutical companies were suddenly thrust into the limelight with the virus becoming a household topic. Fast forward three and a half years, these very same companies are now rolling out their updated mRNA Covid-19 vaccines to combat the prevalent circulating variants [1].
In March 2020, numerous states implemented stay-at-home orders, causing millions to turn to the internet for communication. This situation led to a staggering 5-fold surge in online conversations about vaccines compared to pre-pandemic times. Now, nearly 4 years after the pandemic began, is the patient still talking about COVID?Talking Medicines is revolutionizing healthcare by unlocking intelligence within Conversational Data.
A sample of Conversational Data from over 8,000 unique sources (sourced from Talking Medicines’ Data Aggregator) was curated. The examination focused on aggregated trends and patterns within the evolving discourse surrounding Covid-19 vaccine brands, since the onset of the pandemic. The data was classified using Talking Medicines’ proprietary patient voice classifier and encompassed both conventional medical platforms and other open sites where authors share their health experiences.
Conversation about Pharmaceutical Manufacturers
The US has administered over 676 million doses of Covid-19 vaccinations, an average of two doses for every citizen, with more than 99% of these coming from three major pharmaceutical companies [2]. The conversation surrounding these pharmaceutical manufacturers remains heavily focused on their work in Covid-19 vaccinations. The intelligence points to 70% of online patient discussions being centered around these companies’ contributions to Covid-19 vaccinations, as opposed to their other products, such as inhalers, tablets and alternative vaccines, highlighting the substantial notoriety this generates the manufacturers.
Spread of Voice
Examining a sample of the patient and HCP voice discussing Covid-19 enables the identification of aggregated trends and topics. Vast amounts of Conversational Data can be analyzed, covering a wide range of topics, including symptoms, vaccines, and potential comorbidities. Real-time global events can be compared with the topics being discussed, as well as the fluctuations in the frequency of these conversations.
While the peak of Covid-19 discussions has passed, there is still evidence that there is rich intelligence within Conversational Data. It contains vast amounts of insights, featuring diverse discourse on the pandemic, post-pandemic world, and various perspectives on the vaccines’ pros and cons.
Using the power of the Talking Medicines Advanced Topic and Multi-Sentiment Models, the results show the shift in keywords since the start of the pandemic (left, below) and specifically for the post pandemic world (right, below). A shift can be seen in the topics, the discussions have moved away from talking about lockdowns towards discussion about their symptoms and current concerns over Covid-19.
What else are patients speaking about?
As a result of the pandemic, patients are participating in many new online health forums as they have enjoyed using virtual/online communities resulting from the COVID lockdown experience and digital upskilling. They are now participating in groups discussing their experiences across for example cardiovascular, dermatological, and neurological conditions, as well as many more. For example, online patient conversations around psoriasis saw a 225% increase in 2022 compared to 2019, highlighting the growing reliance on digital platforms for health discussions in the post-pandemic era.
Unlocking Value
Talking Medicines Advanced Data Science and Artificial Intelligence models possess the capability to perform multi-level sentiment and topic analysis in near real-time. Results are delivered through the PatientMetRx® platform; this empowers Customers to gain the strategic advantage in analysis, measurement, and enhanced brand equity, through structuring Conversational Data.
By Ronan Cons, Data Analyst, Talking Medicines
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