Health and Human Services disposition analytics Bookmark has been added
Health and Human Services disposition analytics
Take three minutes to learn how analytics can help
While electronic interactions have changed and simplified processing efforts for the better, it’s not always perfect. Take three minutes to give yourself a mini-crash course on how disposition analytics can provide structured guidance for Health and Human Services (HHS) agencies and help prevent errors.
Nudging the way through predictive modeling and behavioral analytics
Health and Human Services organizations have tried many tactics to combat incorrect payments. But mistakes still occur, and it’s next to impossible to retrieve overpayments. Now there’s a better way.
How can analytics help state agencies combat the issue of incorrect payments?
Lessons from Health and Human Services leaders
Influence accuracy and timeliness
During application or recertification of benefits and services, clients and providers may not know what information to provide and when to provide it. A reminder can help improve accuracy and timeliness.
Aid in decision-making
Agency staff rarely have time to research historical case data to pick up on patterns or inconsistencies. Analytics can help staff members make smarter decisions by highlighting past behaviors.
Guide with prompts
Communication prompts with information about individual clients and providers can help reduce errors during authorization of benefits.
Mitigate potential errors before they happen
State agencies want to deter errors, but they also want to make sure eligible people receive benefits. It’s challenging to keep up with the latest regulations whether you are a client or a worker. This could easily lead to the wrong conclusion or incorrect interpretation.
Disposition analytics in action
The New Mexico Department of Workforce Solutions (DWS), like so many others, had historically combated improper payments with policy changes, training initiatives, and the latest tools and modules. Despite some technological gains and reductions in errors, overpayments continued to be a challenge.
By leveraging predictive modeling and behavioral analytics, the New Mexico DWS was able to substantially influence claimants’ behavior and reduce high instances of “small” errors with smart, subtle changes in how the agency communicates. Strategically placed nudges to do the right thing went a long way.
Learn more about disposition analytics
We’re just getting started. To learn more about the role of disposition analytics in health and human services, check out more of our thought leadership.
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