the impact of artificial intelligence on the revenue cycle management
Thesis: Artificial intelligence (AI) is a rising approach to an already widely established revenue management cycle, with the hope that it will help curve the healthcare cost trends; AI can provide better insight to billing approaches with automated processes which will redirect staff efforts, stop claim denials, base the billing process on patient demographics, and overall predict when payments will be made to reimburse the claims.
A countless number of errors can severely affect the revenue cycle management of an organization by prolonging the process or even breaking it completely.
Using a staff team to run the billing system wastes time, money, and staff. By using artificial intelligence, we can cut costs in multiple different aspects, allowing for the organization’s revenue to increase. The cycle needs to be as short as possible and with AI, we know that coding and billing is being done in a timely manner. Predicting and preventing claim denials saves the time and effort of staff, as well as prevents complete denial of reimbursement due to an organizational error. Billing codes are generally the same nation-wide but are used differently. Each patient is unique, meaning codes will be used in different ways; AI can help us analyze patient demographic data, which will help predict the correct billing approach. AI can also predict payer-specific payment behavior through CPT codes, meaning the organization will know how long it should take for the claim to be paid. With AI, an organization will benefit in many different aspects, but over-all the revenue cycle management will be shortened, meaning the organization will receive reimbursements faster.
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