Text analytics for health: Exploring the conversations around American healthcare
Healthcare has become a politically charged topic of conversation in the US, with 66.5% of Americans enrolled in private health insurance and 24.8% opting for public coverage.
This complex system of networks, deductibles, co-pays and inflated pricing leaves many Americans confused and in debt. To understand opinions on healthcare in America and common issues relating to the US healthcare system, we used text analytics for health forum conversations.
We compared US healthcare specific forum conversations in comparison to our database of standard English, which represents regular word usage. Our healthcare data analysis reveals the topics, words and phrases that over index in forum discussions compared to how they would be used in general conversation.
This form of text analytics for health will show us the most common and prevalent needs, preferences and opinions on healthcare in America expressed through online forums. Here’s what we found:
Text analytics for health-related opinions in America showed largely negative results, with some to an extreme degree. Forum conversations included words like corrupt, evil, scam and unethical when discussing healthcare providers, pharmaceutical brands and insurance companies. These opinions were often rooted in personal experiences with high pricing and limited care.
Cost was by far the most discussed topic among healthcare forum conversations. Forum users employed the words expensive, bill, afford, pay, price and cost. Many provided specific numbers and prices for treatments or hospital stays to illustrate the need for affordable pricing.
Beyond cost, Americans had regular issues or problems relating to other areas of healthcare. Healthcare data analysis showed that conversations often included words like can’t, couldn’t, won’t, isn’t and doesn’t to talk about their healthcare coverage limitations. They were unable to easily cover out of pocket costs and limited by in-network doctors and coverage restrictions.
These issues were so prevalent that many Americans used generalizations to discuss faults in the healthcare system and opinions on healthcare in America. We saw the words many, most, mostly, totally, basically, absolutely and completely included in conversations. This implies that a majority of healthcare providers are not meeting the needs of their patients.
The complex nature of privatized health care resulted in many forum users utilizing the words think, know and understand to share information and ask questions. Due to the lack of transparency and clarity, Americans are often required to learn on their own, which results in this online exchange of information.
What does this mean?
This data analysis in healthcare tells us that opinions in America are largely negative – with Americans seeking increased price transparency, educational resources and fewer coverage restrictions.
By using text analytics for health to uncover customer insights like these, healthcare providers cater to the needs of their customers and work to change negative perceptions through marketing or customer interactions.
Our software brings measurable metrics to qualitative data sources – in this case by analyzing consumer conversations. If you have healthcare text data which you want to act upon but don’t know where to start, speak to one of our team to learn how Relative Health can help.