Generative AI and Administrative Automation in Healthcare Evaluating Productivity Cost Savings and Financial Risk
Nathaniel Sackey
ABSTRACT
Generative artificial intelligence is finding its way into healthcare administration to write letters, summarize documents, aid with coding, write prior-authorization documentation, aid follow-up forms on claims, clarify bills, and lessen documentation load. The financial argument is appealing since administrative tasks demand a lot of labor and bring about a slower payment process, payments being denied, re doing work and dissatisfaction among workers. However, the savings in time may not necessarily translate into cash savings, and faulty output or nonconformance can lead to revenue leakage, repayment risk, privacy breaches, operational crashes, and patient harm. This literature review builds up a systematic model to assess productivity, cost reductions, and monetary risk within healthcare organizations in the United States. It differentiates between the completion of technical tasks and the achieved operational value; illustrates the appropriate use cases by volume, and text intensity, rule stability, error detectability, financial impact, and proximity to clinical processes; and proposes a total-cost-of-ownership model that adds up licensing, integration, supervision, rework, security, governance, and added-value-of-residual-loss. A clear picture of analysis of scenarios shows the impact of labor redeployment and adopting and model error and denial avoidance and integration cost on a project resulting into positive net value. The discussion concludes that generative AI can be most justified as an administrative copilot to a supervised AI, rather than and an autonomous financial decision-maker. Hospitals ought to start with low volume, limited scope and reversible, high-volume tasks; claims, coding, coverage and patient facing records must be human verified; there should be subgroup and payer specific error; post deployment benefits and losses have to be monitored. Four analytical figures and four tables put in place a publication-quality structure in the hands of hospital leaders, finance departments, informatics and compliance departments, and researchers.
