Future of Healthcare Workforce Series: Part 3
This article is the third and final installment in the Future of Healthcare Workforce Series. We explore how technological advances such as artificial intelligence, machine learning, and robotics may impact the healthcare workforce.
The Burden of Administrative Tasks
Healthcare providers spend a substantial amount of time on administrative duties. According to a nationally representative survey of over 4,000 physicians, the average doctor spends 16 percent of their time on administration, with psychiatrists having the highest load to bear, allocating 20 percent of their time. MHC’s Michigan Physician Survey also reaffirms this finding, with respondents mentioning that administrative tasks affect their ability to provide patient care and suggesting decreasing their burdens could yield positive benefits.
The same applies to hospitals and health systems. Administrative (appointment scheduling and customer service responses), financial (billing and collection), and operational duties (inventory and supply chain management) take significant amounts of time, and an effective automation strategy could save resources for the workforce.
Exploring Current Uses of Technology to Support Automation
An American Hospital Association report explores how hospitals and health systems can use AI (Artificial Intelligence) to build and support the healthcare workforce. Lessening some of the burden on the providers and staff creates a win-win situation for everyone involved. In a previous article from this series, we noted that searching for tools and supplies takes substantial time in a nurse’s day, affecting their job satisfaction. In fact, additional research shows that administrative tasks may contribute to job dissatisfaction and burnout after adjusting for gender, race, specialty, and years of experience. Utilizing technology and automating processes enables providers to prioritize and provide optimal patient care.
An example of successfully utilizing technology and automation for administrative tasks comes from the Michigan Department of Education (MDE). MDE deployed an innovative behavioral health software to streamline school mental health service referrals and treatments, which significantly improved operational efficiency. MDE made bhworks software available to all intermediate school districts (ISDs) and so far, it has already been integrated into 41 of the 56. It offers an end-to-end solution where referrals, e-consent forms, assessments, plans of care, progress notes, and billing are in one place. The process of students seeking help and getting referrals that took up to two weeks to complete now takes one day. This time-savings allows students to get the help they need sooner and frees up time and energy for providers and staff. Similar software solutions are used nationwide, but Michigan’s visionary approach gets most of the state’s providers under one roof, uniforming the process and increasing care efficiency tremendously.
Looking Ahead
Research shows that the future of the healthcare workforce could benefit from technology-based automation and AI solutions. These technologies are here to stay, and early adopters may benefit more from having developed innovative solutions for their needs. Additionally, finding ways to shift some or all of the administrative burden from healthcare professionals may provide a much-needed solution for some of the issues our workforce faces when it comes to retention.
Definitions of some AI, machine learning, and robotics terminology ¹:
Robotic Process Automation: Replaces repetitive, rules-based activities to reduce time spent on manual processes
Natural Language Processing: Interprets unstructured and structured data from handwriting or voice into contextually relevant content
Generative AI: A subset of artificial intelligence focused on the ability of machines to create original content across various modalities like text, images, code, audio, voice, and video
Cognitive Analytics: Analyzes complex datasets using AI and machine learning to identify patterns and insights
Intelligent Data Extraction: Intelligent or optical character recognition, paired with machine learning, converts structured and unstructured (e.g., paper) documents into digital data
¹ Shah, Ankur, Amritpal S. Bhohi, Anubhav Rastogi, and Jay Bhatt. “How AI Can Help Hospitals Strengthen Their Financial Performance and Reduce Clinician Burnout.” Deloitte Development, 2024. https://www2.deloitte.com/content/dam/Deloitte/us/Documents/consulting/us-how-ai-can-help-hospitals-strengthen-their-financial-performance-and-reduce-clinician-burnout.pdf.
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