The COVID-19 pandemic has brought a new set of challenges for the medical community, including how best to share information and engage with patients. To stay informed, more people are looking to their healthcare providers for information and assistance, which is why proactive patient communication around COVID-19 is more important than ever. Not only does improving information flow drive meaningful change, it gives patients the confidence they need to know they are supported by the healthcare community.

COVID-19 has had a major impact on medical practices, causing providers to feel overworked with limited time to spend with patients, inundated by patients’ virtual questions, and struggling to adapt to the limitations of decreased in-person care. The health insurance industry has to make difficult coverage decisions quickly and be transparent to members. A survey conducted by eHealthInsurance in March 2020 indicated that 7 out of 10 members said they don’t understand how their insurance coverage works for coronavirus.

To refine communication and engagement during COVID-19, providers and insurance companies need to share data and regularly discuss their response, coverage and treatment approaches. Predictive analytics tools make it easier to filter and classify patients based on social determinants of health, clinical risk level, and level of patient engagement in order to personalize the outreach strategy for each patient. Having a better understanding of how messaging and information delivery is impacting patients will also help providers and health plans figure out what areas of focus need to be prioritized so they can follow up and improve. Conducting online healthcare surveys is one effective way to collect information that can help medical practices improve patient engagement.

Some places are also turning to artificial intelligence (AI) to improve their ability to identify and communicate with vulnerable patients. Medical Home Network is a Chicago-based formal provider collaborative that is working to provide better care and improve the health of the vulnerable communities they serve. They are working with the ClosedLoop.ai platform to identify and reach out to their patients that have the highest risk for developing severe complications as a result of the coronavirus.

Utilizing previously collected data that assesses various social determinants of health, the AI system is cross-referencing the information against medical vulnerabilities such as age and other health conditions. Then, care managers from Medical Home Network reach out to patients by phone to educate them about the ways that they can lower their risk of contracting the virus, how to detect early symptoms, advise them on what to do should they become sick, and conduct periodic wellness checks. By building these relationships with their patients and care managers, Medical Home Network has been successful at consistent communication and engagement with patients. They also tell their patients to reach out to a care manager or primary care provider instead of rushing to an emergency room if they develop minor symptoms. Healthcare systems can duplicate this approach by collecting information about social determinants of health and using a machine-learning approach to their medical claims data in order to identify priority patients.