Improving Patient Outcomes with Machine Learning
Artificial intelligence and machine learning (AI ML) are exciting innovations for healthcare marketers, enabling them to analyze data faster, and communicate with patients and their providers in a more personalized way.
But simply communicating with health audiences is skimming the surface of what is possible and what will inevitably come.
As the capabilities of AI and ML increase and access to health data becomes more democratized, the potential for impact grows exponentially. More data than ever before is being produced and stored. Each year, the U.S. healthcare system creates 1 zettabyte of data, which is projected to double every year moving forward. To put that massive number into context, 1 zettabyte is equivalent to the storage capacity of 230 billion iPhones.
Collecting and effectively analyzing data in a HIPAA-compliant way is imperative for healthcare marketers to better understand their audiences and drive personalization that makes their message relevant. Organized, meaningful information, such as diagnosis and pharmacy data, helps create a clearer, more complete picture, allowing marketers to make informed decisions about the information needs of their patient population. Marketers’ efforts to reach target audiences in a timely fashion with personalized information is amplified by ML.
This is important, as improved personalized marketing has the potential to change patients’ lives by providing valuable information about medicine and treatment options that are actually relevant.
With that information, patients can investigate conditions and treatment options, setting the stage for more open, bidirectional conversations with their healthcare providers. What’s more, patients are more likely to take treatment advice about something they recognize and recall from advertising. Once this is considered, healthcare marketing should be viewed as a public health tool that can create a meaningful impact in improving patient outcomes.
With advanced analytics and the right solutions, healthcare marketers can utilize AI and ML to go beyond better personalization and optimize campaigns in-flight in a more efficient, cost-effective way across all channels. Rather than rely on measurement reports months after a campaign ends, marketers can now leverage platforms that embed privacy-safe ML algorithms which adapt messaging and channel delivery to the changing needs and preferences of audiences. These platforms drive significantly better engagement which is reflected in the metrics that matter, such as audience quality and script performance. Timely script metrics drive more actionable insights, which helps marketers learn even more about their audiences, enabling them to be more proactive with marketing investments and set them up for success for future campaigns.
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AI and ML can also positively affect patients once they have taken the steps to seek medical care and are in the process of treatment. Using solutions fueled by AI and ML, patients and providers can access a plethora of information such as patient records and past treatment and medication histories in a better-structured way, in order to organize treatment plans more efficiently. Patients can also be reminded to adhere to their treatments through the combination of data and personalized marketing.
Artificial intelligence and machine learning are revolutionizing the healthcare industry by unlocking new ways to support and enable more relevant conversations between patients and their providers. As a result, we believe a more informed and personalized experience at the point of care greatly reduces the burden of disease and ultimately drives better patient outcomes.
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