December 19 2018 | 0 Comments | 107 reads Average Rating: 3

3 Ways to Make Electronic Communications Engaging, Not Maddening

by Arun Rangamani in Health Analytics

In an “always-on” world, many patients suffer from information overload – a term used to describe the difficulty of understanding an issue and effectively making decisions when one has too much information about said issue.1 The conundrum: Healthcare organizations could still help patients significantly by communicating with them via electronic devices.

The challenge is to provide useful information, without the noise that will inevitably turn consumers off. To that end, here are three ways that your healthcare organization can fine tune its electronic communications:

1. Determine which patients need information most. Sophisticated, next-generation analytics can help you stratify patients/members by risk level. As such, you can understand which ones are in the highest risk categories for hospital admissions, emergency department visits, complex procedures, etc. These patients/members need information expediently as changing their outcomes will have the greatest impact on overall outcomes. Data analytics also can help you identify which patients are trending toward a disease or chronic condition such as pre-diabetics. As such, you can take the steps necessary to prevent or forestall these patients from developing chronic conditions.

2. Make the information easy to digest. A patient/member with chronic obstructive pulmonary disease (COPD) needs information about exercise options, nutrition, oxygen, spirometry readings, inhaler use, lung therapy and so forth. Bombarding patients/members with all this information at once can be disconcerting. Patients/members are much more likely to understand and act upon this information, however, if you break this information up into smaller bites and send regular, short alerts to their mobile devices.

3. Personalize messages to make them actionable. Data can be leveraged to ensure that messages synch with patient’s/member’s needs or interests. Take an overweight patient who has been identified as a “gamer,” either through a conversation, an online survey or as a result of purchase patterns. Rather than sending a generic reminder to get more exercise, the alert could identify various games (such as Pokémon Go), that encourage movement. Of course, to get to this level of personalization you will need a broad swath of data. Supplementing clinical and claims with outside data such as demographic, socioeconomic, and psychographic data can help.

This blog was adapted from “Mobile Alerts Create Personalized Way to Improve Health Outcomes,” an article that was recently published in CIO Insider Magazine.


1. Yang, CC.;, Chen, Hsinchun;; Honga, Kay (2003). "Visualization of Large Category Map for Internet Browsing" (PDF). Decision Support Systems. 35 (1): 89–102. doi:10.1016/S0167-9236(02)00101-X.

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Arun Rangamani
VP, Payment Services Delivery Leader

Arun Rangamani heads the Global Analytics & Technology Centers of Excellence which are based out of SCIO's Chennai office in India. Arun was previously responsible for setting up the SCIO’s global Analytics and Technology portfolios in India prior to moving on to developing the analytics practice from India.

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