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The Missing Link for a Successful Open Enrollment 2016: What Insurers Should Know About Data Quality

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With more insurance options available, members want an experience with insurers that is consistent and reliable – and data quality makes that possible

On November 1, open enrollment will begin for 2016 individual health insurance plans on the federal and state-based marketplaces.  These government-sponsored marketplaces initiated by the Affordable Care Act allow individuals and small groups to shop for coverage.  They also allow some individuals to receive subsidies from the government to offset their costs.

Most individuals shop on healthcare.gov or their own state’s marketplace website. For those individuals that know which plan they desire, some health plans allow them to shop directly on the health plan issuer’s website using “Direct Enrollment.” No matter where the member shops, the health plan issuer ultimately receives a submitted enrollment transaction.  Once received, there are multiple points of possible failure for this transaction. For this reason, issuers need to be on guard to ensure a positive first impression with their new member.

Issuers are realizing that they need to engage members so that they renew and issuers increase their market share.  Before issuers can engage members they first have to meet a member’s minimum expectations.  Like Maslow’s Hierarchy of Needs, if issuers fail to meet these most basic needs, they will never reach the nirvana of a fully engaged member who is happy and tells others about their experiences. In short, that means lost revenue.

Members rightfully expect their basic needs to be met, such as:

  • Receiving their invoice in plenty of time to make payment
  • Accurately matched issuer information to what they provided to the marketplace
  • Subsidy amount accurately reflected on their invoice
  • Payment correctly applied to their invoice
  • Smooth pharmacy experience, including correctly applied benefit plan such as the deductible and out of pocket maximum recently applied to their doctor visit accurately considered

If members do not have their basic needs met it is like ordering an item online that was promised in two days and receiving it in two weeks. Instead of trust being built, it is immediately broken.  Any relationship requires a basic element of trust to exist before it can flourish.

For issuers to build this trust with their new members, they must make sure each process occurs as planned.  They can ensure that all of the required actions occur without error and in the expected timeframe by analyzing their data with automated business rules that provide the checks and balances around business processes to validate accuracy and flag exceptions.  As data is analyzed in real-time, data anomalies can be immediately flagged to correct issues before they impact other downstream processes or become externalized to the member.  When alerts are triggered they can immediately be investigated and rectified through a workflow exception management system that provides detailed analysis background information to expeditiously fix the data quality issue.  This prevents the issuer from only finding out about an error when a member calls to report an issue.  In the quest to retain members and keep them happy, monitoring data quality will save time, money and improve the member experience.  Even if they do learn of the issue they will be reassured knowing it had already been identified and is being rectified.

Any step in the process can be analyzed, such as:

  • Validating that the data in the initial enrollment transaction is complete
  • Ensuring that effectuation is sent to the marketplace following the member payment
  • Verifying that the member ID card and welcome packet is sent to the member within a specified timeframe after the payment is received

This type of end-to-end data analysis assures that nothing is lost in the process and if anything does go wrong then someone is immediately alerted.

Going back to the package analogy, proactive communication of an issue, such as a shipping delay, demonstrates that you are constantly analyzing your data to ensure the best customer experience.  You would be reassured that that vendor knows how important your package is to you and in most cases a shipping delay will not be an issue since you are able to adjust your expectations in advance.  For issuers an end-to-end data analysis process can also report issues as they occur to protect the trust and relationship you have with your new members.

As a pre-requisite to member engagement, data quality ensures that members’ data is accurate in order to protect members trust and in return lower your operational costs.  Otherwise members may be dissatisfied before longer engagement can even occur.  If this happens it will be extremely difficult to overcome their initial perception and achieve true member engagement.


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