How can Data Analytics Boost Member Engagement?

On customer experience, payers rank 19 out of 20 in the Customer experience quality index. A poor score of 57% is the average engagement score that was attributed to payers in Temkins’s Experience ratings. According to Forrester’s US Customer Experience Index, 2018, the topmost health plan ranked 184 out of 318 companies surveyed.

The above statistics lead to one undeniable conclusion. There is a lot of room for improvement in the user experience domain of healthcare. One of the most important levers to improve member experience is working on member engagement.

Organizations face 2 fold problems in member engagement today. Firstly, there is insufficient engagement on the part of the payers and providers i.e. the frequency and volume of communication are greatly lacking. Further on, most healthcare organizations follow a one-size-fits -all strategy. This means they engage with all members in the same fashion, regardless of differences in members’ attitudes, economic conditions, social conditions, etc. This reduces the efficacy of most member outreach activities.

The global customer engagement solutions market size is expected to reach $ 26.4 billion by 2024 and is expected to expand at a CAGR of 11.5% over the forecast period1.

Advancements in Big data processing tools, data organizations, and data mining along with the shift in member attitude demanding retail-like experience in healthcare are prompting healthcare organizations to leverage advanced analytics algorithms to drive member engagement.

The Opportunity for Data-Driven Member Engagement

In healthcare, large amounts of heterogeneous data have become available to various healthcare stakeholders (payers, providers, pharmaceuticals). This data could become the enabling resource for extracting insights to improve care delivery, maximize ROI, boost member engagement, cut down costs and so on.

With the onset of social media, wearables, and member portals, healthcare organizations now have access to much more personal data pertaining to members. This includes their preferences, their likes, and dislikes, their motivations as well as barriers in achieving health goals as well as influencers that they follow. Analyzing this data using the right tools and technologies can help deliver care and experiences that way more effective and relevant for the member.

Proactive Member Participation using Personalization

It is a well-known fact, that only 20% of a member’s health depends on clinical factors or in other words on the treatment delivered by the provider. The rest of the portion is in the hands of the member himself. Thus, it is in the interest of members to start taking care of their own health. For doing the same, members need to be made aware of the best health practices they should follow according to their lifestyle and health conditions.

This makes a strong case for healthcare organizations to try and understand the psychographics and lifestyles of members. Providers and payers alike need to take into account their social determinants of health (including literacy rate, housing, transportation patterns, etc.), economic conditions, motivations as well as obstacles in life, attitudes towards health and so on. Apart from this, family history, their existing fitness regime, their influencers and so on also provide very powerful and relevant information pertaining to the individuals. Only then can we create and deploy effective care strategies that will ensure higher compliance rates among members. E.g. A 30-year old member who works in an office 5 days a week can be sent a notification on an app (assumed he might prefer to ingest information using apps) to go for his annual wellness visit on a Saturday(weekend).

NLP to improve member clinical literacy

Doctor’s prescriptions and clinical notes contain important information that cannot be leveraged easily due to its unstructured format (paper based or digital) which makes it difficult to analyze. Using advanced analytical algorithms, Natural Language Processing can be used to absorb information from all this unstructured data and deliver useful information to members (since payers have access to clinical records in form of CCDA documents) at the right time. 

Incentives to entice members for wellness

Apart from sharing regular and relevant information with members, running a personalized rewards programs can be another way of motivating members to participate in improving their own health. By analyzing each individual’s tastes, likes and dislikes, analytical algorithms like clustering can be used to create personas which are representations of individuals who share similar characteristics. These personas along with claims and EHR data can be combined to recommend member specific health goals and relevant incentives that motivate the members to achieve these goals. Health goals can be anything from physical activity to calorie intake or even closure of existing care gaps. This will lead to healthier members, lower claims and increased profitability.

The ITC Infotech Advantage

Using the Healthy Me solution developed by ITC Infotech, payers and providers can engage with their members effectively while improving member satisfaction, brand image as well as lowering the cost of care delivered to improve profitability. The solution is developed on a big data platform and runs on a core analytics engine.

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