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eClinicalWorks Analytics Dramatically Reduce FQHC No-Shows

Episode 758 of the Healthcare IT Today Interviews podcast, hosted by John Lynn, titled "eClinicalWorks Analytics Dramatically Reduce FQHC No-Shows" was published on December 8, 2025 and runs 10 minutes.

December 8, 2025 ·10m · Healthcare IT Today Interviews

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T.H.E. Clinic, a federally qualified health center serving a low-income communmity in Los Angeles, recently reduced missed patient visits ("no-shows") from 25-28% to 13-14%. To learn more about this exceptional improvement, we sat down with CIO Wilson Santos who describes how the healow AI-Powered No-Show Prediction Model helped their clinic achieve this goal.Many factors create what Santos called an "unacceptable" rate of missed visits. People are tied down taking care of family members, forget visits, get busy, or simply get well before the time of their visit and fail to cancel.T.H.E. Clinic was one of first adopters of healow AI-powered no-show prediction model, and after implementing it saw the great results.  The clinic now identifies the appointments most likely to be missed through predictive analytics on EHR data, and dedicates front desk staff to contacting them.Learn more about T.H.E. Clinic, Inc.: https://www.tohelpeveryone.org/Learn more about eClinicalWorks: https://www.eclinicalworks.com/Healthcare IT Community: https://www.healthcareittoday.com/

T.H.E. Clinic, a federally qualified health center serving a low-income communmity in Los Angeles, recently reduced missed patient visits ("no-shows") from 25-28% to 13-14%. To learn more about this exceptional improvement, we sat down with CIO Wilson Santos who describes how the healow AI-Powered No-Show Prediction Model helped their clinic achieve this goal.

Many factors create what Santos called an "unacceptable" rate of missed visits. People are tied down taking care of family members, forget visits, get busy, or simply get well before the time of their visit and fail to cancel.

T.H.E. Clinic was one of first adopters of healow AI-powered no-show prediction model, and after implementing it saw the great results.  The clinic now identifies the appointments most likely to be missed through predictive analytics on EHR data, and dedicates front desk staff to contacting them.

Learn more about T.H.E. Clinic, Inc.: https://www.tohelpeveryone.org/

Learn more about eClinicalWorks: https://www.eclinicalworks.com/

Healthcare IT Community: https://www.healthcareittoday.com/

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