The healthcare industry must start adopting emerging technologies, such as robotic process automation, to handle the increasing demand for care.
Healthcare providers currently write off millions of dollars worth of costs per year, per medical facility. These costs arise in part from inefficient and error-prone processes for making claims and handling denied claims. Equally, healthcare payers spend a fortune on manually checking and denying claims that don't meet their payout requirements.
If providers and payers don’t embrace new technologies to streamline their workflows and inefficient revenue cycles, millions of dollars more will be wasted per facility as treatment volumes continue to increase.
Healthcare providers and payers traditionally process claims manually or using generic, unoptimized software. Compiling and reviewing claims is a complex and time-intensive process for both sides. Providers make errors that result in them not claiming for some of the costs that they incurred. Meanwhile, payers invest a lot into labor to spot claims that don’t meet payout requirements.
Almost one-third of US healthcare providers handle claim denials manually. These providers search for mistakes in existing claims by manually referencing multiple disparate sources of information to appeal the rejection. This disconnect of systems and miscommunication between departments is, in part, what causes claims to be denied in the first place.
A bottleneck in the revenue cycle is when a healthcare payer enrolls a provider in its system. Enrollment involves credentialization, which can take months. Providers must prove their clinicians’ credibility by submitting proof of skills, qualifications, training, and licenses. The longer the enrollment process takes, the longer providers go without revenue for care that they already provided.
Providers commonly duplicate patient data across multiple systems, creating lots of manual work when data needs to be updated. Human errors lead to inconsistent patient data across systems. Clinicians use this incorrect information to inform treatments and when submitting claims which will inevitably be denied.
Healthcare providers routinely compile evidence of the care that they claim to have provided. Healthcare payers require this evidence to approve claims. Providers also need this evidence for themselves for internal audits to ensure that all staff are behaving properly. Furthermore, regulators need this evidence to check that providers are complying with regulatory requirements.
Robotic process automation can automate the compilation of evidence, saving labor costs while also decreasing the time taken for the information to become available. In providing the evidence to healthcare payers, collating this evidence faster decreases claim processing time.
Both healthcare providers and payers work with sensitive information. Staff working for providers typically have access to expensive facilities and equipment. When staff move on to another job or retire, payers and providers have long exit checklists that must be followed to prevent security vulnerabilities. Access to data and facilities needs to be revoked; equipment must be returned; work must be reassigned; payroll must be updated; and so on.
When done by humans, some of these tasks can be pushed back and forgotten about. Robots can automate these menial tasks and ensure that everything on the checklists gets done promptly.
Patients can worry when waiting to hear back about whether the care they received has been authorized by their payer. Robotic process automation can connect patients with their payers’ systems and with Medicare to see their claims’ status in real-time.
Providers can also benefit from instant access to claim statuses. They can act on denied claims as soon as the decision is made by the payer, further streamlining the revenue cycle.
Medical images, like X-rays, MRIs, and CTs, are typically manually reviewed by medical professionals to identify anomalies that warrant further investigation. Robotic process automation combined with computer vision and machine learning is now capable of accurately identifying anomalies more reliably than humans specialists can, given the same short timeframe.
Senior VP Revenue Operations, U.S. Based Health System
Let robots handle the mundane, repetitive healthcare tasks that are prone to human error to help free up clinicians’ valuable time and optimize the revenue cycle.
Robots can read patient records from multiple provider systems in different departments. Bots can then add the codes for the medical procedures that patients received to claims forms. They can also set up banking connections for automatic payments for when claims are approved.
RPA can automate the evaluation of whether a specific treatment will meet a particular patient’s / payer’s requirements before any care is provided. Knowing that a treatment won’t be authorized before administering it saves a provider from subsequently having to write off the cost. For claims that do come back delined, bots can flag incorrect medical procedure codes and missing authorizations.
Robotic process automation can improve the revenue cycle by automating credentialization. This process traditionally takes months. Automating it results in faster payouts from payers for treatments. Robots can perform background checks against clinicians, flagging inconsistencies in their work and education histories, the invalidity of professional licenses, and any malpractice complaints to be investigated by a human.
Robots can automate the duplication of patient data across multiple systems with 100% accuracy, effectively creating a single system. Providers can see huge cost savings from accurate, consolidated patient records thanks to no manual data duplication, fewer claim denials to manage, and fewer cost write-offs. Providers also make fewer treatment mistakes when working with consistent patient records.
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