Payers and members make up two-thirds of the healthcare ecosystem and bear the brunt of the care delivered. Undesired care outcomes mean growing inconvenience for the member who has to go back to the provider. For the payer, this means more prior authorization requests, more claims, and ultimately more time and cost spent on one member.
Payers must aim to reduce the resources they spend on each member while ensuring the member is healthy. To do so, payers must be proactive in their approach to members’ healthcare.
What does Proactive Care Have to Offer?
Proactiveness from payers ensures that their members are recommended care programs and preventive care measures to keep any future illness at bay. This way members do not get sick often, which reduces hospital visits, re-admissions, and such, resulting in a decline in the number of claims. The reduction in the number of claims yields better results in terms of cost reduction and revenue growth
Let’s Reduce Claims
In this blog, as mentioned earlier, we shall look into health plan member engagement strategies that will push for a better member experience through improved care.
Member Data Collection
In order to ensure accurate proactive care, payers need access to data. Data that will help payers formulate and curate care program recommendations. Collecting data is no longer a tedious task, however, identifying the right data that would be helpful for proactive care is tricky. Once the necessary data points are agreed upon, payers must work on collecting them.
A fool-proof method to collect data is to enable easy third-party integration within the payer’s website or applications. The digital solution must be crafted with reusable third-party APIs that allow members to integrate external applications with their payer application to get a holistic view of their health. Applications that monitor sleep, heartbeat, calories loss, steps walked, etc. could be helpful for payers when trying to come up with proactive care programs.
Introduce AI/ML
AI/ML is the talk of the town. Within the healthcare ecosystem, AI/ML has many applications and use cases, but here we will elaborate on one such use case. Preventive care for high-risk diseases.
Preventive care is a subset within proactive care that requires artificial intelligence to recommend care measures based on member lifestyle patterns. The lifestyle patterns can be tracked using the third-party API integration mentioned in the previous section. These include member behavior, medication adherence, care outcomes, food intake, and so on. These data points run through an AI algorithm will produce care recommendations that members should adhere to avoid high-risk diseases. This way, members will stay healthier for longer, aiding payers in reducing the number of claims to be processed.
Incentives for Improvement
In the above sections, we went through preventive care measures, and proactive care programs that could help members get on the right health track, thereby reducing claims. However, payers need to have a plan to ensure their members are following through on their recommendations.
This is where incentives come in. Introduce incentives within care programs, to motivate members to complete them. These incentives could be in the form of coupons, discounts, gym memberships, and whatnot. As the member progresses through the care programs and improves, they are becoming healthier which, as we know it, reduces claims.
Partner with us for More Member Engagement Strategies
Member engagement is often overlooked. Payers have CMS breathing down their necks to ensure interoperability via FHIR APIs. It is difficult to navigate through the deadlines and still have time to come up with member engagement strategies.
The healthcare IT team at Nalashaa is well versed with the workings of the eco-systems, be it regulations, FHIR APIs, EDI integration, and so on. Partner with us for health plan member engagement solutions and you can sit back and relax.
Shireen Noushad