It’s Quitting Time for Manual Scheduling

Developing & implementing optimization algorithms to modernize caregiver allocation

By Naomi Goldapple
Software Solutions

The homecare industry today is racing to meet the demands of an aging population that wants to stay at home to live out their golden years. The United States spent an estimated $122 billion on home health care in 2021, and that number is predicted to surpass $226 billion by 2030, according to the Centers for Medicare & Medicaid Services (CMS). Ten thousand baby boomers in the U.S. turn 65 every day—and it’s projected there will be 88 million retired persons by 2050. Serving this population will require investment, staffing and public-private commitment. One of the main pillars in supporting this growing need is effective scheduling.

Author

  • Naomi Goldapple serves as both senior vice president of data intelligence and general manager of AlayaLabs at AlayaCare. Goldapple leads a team of data scientists and engineers to leverage emerging technologies and build prototypes that will drive present and future value for AlayaCare clients. She is a seasoned data intelligence professional with experience leading innovation teams—specifically in the field of artificial intelligence and machine learning. Having worked in health tech and homecare for the past five years, Goldapple has become recognized as a thought leader on leveraging data for better decision making and creating operational efficiencies with a goal to helping improve health outcomes for those who wish to recover and age in the place they call home. Visit alayacare.com.

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    It’s Quitting Time for Manual Scheduling

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