Recondo Technology to Demonstrate How Machine Learning and Web Bots Are Automating Complex and Costly Areas of Revenue Cycle at HFMA Annual Conference
Summary
These factors include access to large, high quality data sets, expertise in machine and deep learning, and extensive subject matter and workflow knowledge. This is where companies with less experience than Recondo find themselves naively applying machine learning tools to build models that result in sporadic or overall minimal performance improvement. Weve incorporated machine learning standards from the educational programs at Stanford and MIT, and require advanced degrees and knowledge in computer science and related studies from all of our software engineers," said Eldon Richards, Recondo Technology CTO. "With health system margins now below three percent nationwide, providers are urgently seeking opportunities for digital transformation in the areas of pre-service patient specific price transparency estimates and payments, eligibility and authorization denial reductions, and overall increased automation that delivers employee yield improvements." Healthcare financial leaders at HFMA who are interested in automating their most complex problem areas in revenue cycle will have several opportunities to meet with Recondo at HFMAs Annual Conference.
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