Doug Golub
Doug Golub, MA, SHRM-CP, serves as President of MediSked focusing his expertise on
delivering innovative technology solutions to the healthcare and human services industry. Prior to joining MediSked, Golub served as Platform Services Manager for Microsoft’s Health Solutions Group. An original member of Microsoft’s healthcare venture, Golub is an expert in health care IT security, implementations, and customer needs assessments. Golub has served on the ANCOR Foundation Board of Directors since 2019 and as Treasurer since 2021. As a Medicaid Transformation policy, data, and technology expert in the human services field, he presents at state and national conferences across the country. Golub holds a Masters of Information Systems from Rochester Institute of Technology and a Bachelor of Science from State University of New York College at Geneseo. Golub has received awards in leadership and innovation, most recently as a Power 50 Technology winner, Tech in Motion Award winner, and Health Care Hero.
Session Topics:
How Natural Language Processing Can Be Applied for Data Analysis to Advocate for the People and
Services that We Support: Artificial intelligence (AI) is no longer just a plot device in the movies – but actually has potential for the work that we do. Natural language processing (NLP) is the use of software to process, analyze, and understand written data – much like the plans and notes we collect on the people we support. This form of AI is the future of what can be harnessed in home and community-based services to extract and quantify written words and study subjective information. MediSked has been engaged in significant work and studies
using data tools and machine learning to analyze patterns in service note documentation such as changes in health, housing, employment, circles of support other data from providers. This will be the trend of the future, but by the end of our session, attendees can expect to:
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Understand the basics of sentiment analysis and natural language processing and how it
can be applied to advocacy in the human services field -
Explore real use cases from real (de-identified) individuals and real provider agencies
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Understand how to improve lives and outcomes through futuristic technologies
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Learn about opportunities to use NLP to address health equity measures
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Looking to the Future: Arkansas Policy Outlook and How Artificial Intelligence Fits In: We seek to improve the quality of life for individuals with a developmental disability and their families through active advocacy, open communications, and an exchange of professional ideas. The goal of the PASSE system is to monitor individuals’ health care needs, keep them healthy, and help them reach goals. The US Department of Health and Human Services (HHS) has identified machine learning as a goal for person-centered outcomes by 2029. Data tools can examine unstructured data like service documentation to analyze patterns and predict when a positive or negative event may occur. This data can help us identify opportunities for interventions and unmet needs much sooner. We can equip individuals and their circles of support with the tools they need to be empowered and in charge of their own lives – and also partner better with the PASSE system. During this session, the presenters
will share real data that includes negative consequences that arise when prior approvals are denied for fear of the bottom line or where the medical model of thinking reigns supreme. For too long individuals have been at the mercy of payers and the provider systems rely on. Machine learning can be used to protect individual autonomy and improve outcomes by predicting and preventing negative consequences before they can occur.
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