Provider organizations have taken big strides towards personalization. According to the Redpoint Global Survey, 75% of consumers in the United States wish their healthcare experiences were more personalized. The main reason people are gravitating towards personalized healthcare is because it improves patient engagement, experience, and leads to better outcomes.

Pharmaceutical companies can learn from provider organizations, particularly in the clinical trial setting. The clinical trial setting is an excellent opportunity to better understand and engage patients much like a provider organization. From the patient’s perspective, the experience in a clinical trial is akin to that of a doctor’s visit so pharmaceutical businesses that are able to personalize this experience will reap the same benefits.

Patient Needs and Frustrations

The first step to personalizing the clinical setting is to better understand who the patient is and to listen to what they may need and want.

Patients have reported many needs that have not been met and frustrations that arise from the current experience in healthcare. As a whole, patient satisfaction in healthcare is low. In fact, over half of consumers said they would rather endure a typically frustrating experience, like jury duty or waiting at the DMV, than deal with a health insurance issue.

A majority – 71% – of patients still report facing major frustrations throughout the experience. These frustrations include long wait times, impersonal visits, a confusing process, and trouble when scheduling an appointment. To combat these frustrations, companies should turn towards more personalized models. 61% of patients said they would visit their healthcare provider more often if the communication experienced felt more personalized.

Lessons Learned from Healthcare on Improving Patient Experience

To mitigate these needs and frustrations, healthcare providers have implemented many new methods to personalize healthcare. Below, we list three examples of what healthcare providers have done and what pharmaceuticals can learn from their actions:

1. Orlando Health used patient data to create personalized email communication for new mothers. Mothers could choose one or multiple tracks on which to focus based on their needs. These tracks included caring for a newborn, caring for mom or caring for family. They would receive regular, personalized emails that could address any questions related to the focus selected. Given the stress and fatigue that comes with caring for a new baby, Orlando Health helped avoid frantic Google searches and deliver quick answers to mothers’ inboxes.

Lesson Learned: Collecting data is the first major step towards a personalized experience for patients. To provide individualized insights, you first need to know the individual. As with any data collection endeavor, it’s imperative to be open and transparent with your patient as to the nature of the data you’re collecting and how you intend to use it.

2. Novo Nordisk and Glooko provide an excellent example of how strong insights can support a patient’s experience. The diabetes drug company and digital health company worked together to create a personalized tool for diabetes monitoring. The tool uses each patient’s individual data to make accurate recommendations for better treatment. The Cornerstone4Care app and website makes it easy for patients to track blood sugar and meals. The app then uses current research to make personalized recommendations for how the patient should diet and exercise to better manage their diabetes.

Lesson Learned: Proper analysis and communication of the data is the next step in providing accurate and actionable insights for your patient. Patients will benefit from better understanding their personal health journey, and learning exactly what they need to do, so they can continue to progress.

3. An interactive virtual assistant app called Healthily uses AI algorithms to search medical literature that covers over 1,000 conditions. Patients can use the chatbot to talk about their symptoms or ask questions to get personalized and accurate responses. Once the bot identifies a potential condition, the bot connects the patient to top doctors within their area. Overall, it’s goal is to use personalized, data-driven care that ensures all users can get the help they need.

Lesson Learned: Using AI technology and machine learning can be really helpful in creating your patients’ insights. There is huge promise in big data and machine learning research. Scientists are increasingly turning towards technology to help digest large amounts of data and pick out key insights that would best help their patients.

Pharmaceutical companies can leverage these lessons learned in order to create better engagement for their patients with regards to clinical trials. Patients who receive compassionate care can reduce the likelihood of trial opt-outs and increase the likelihood that patients will be strong proponents of trial participation in the future. From enrollment to completion, it is critical to provide accurate and insightful information and care directly to the patient throughout the clinical trial. Leveraging big data and technology is just the start to increase the holistic patient experience, which can boost clinical trial success.

Coauthor and contributions by Maggie Wong