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Why does my medical claim take a long time to process?

Why does claims processing move slowly? Understanding the root cause of the backlog goes a long way towards helping players in the claims space clear the way for a speedier future. Here are some of the biggest reasons the system is experiencing so much delay.

Published on:
October 13, 2022

It’s no secret that the healthcare industry is under serious strain. Whether it’s crowded emergency rooms, backlogged disability files, or long processing times for insurance applications, companies in the healthcare space are struggling to keep up. This has consequences for patient care, quality of life, and staff burnout — which are all major indications that something needs to change. 

Why does claims processing move slowly? Understanding the root cause of the backlog goes a long way towards helping players in the claims space clear the way for a speedier future that can lead to improve patient care and access. Here are some of the biggest reasons the system is experiencing so much delay:

Claims Processing Moves Slowly because of Manual Work

While some claim tasks are meant to be done by hand, many insurance carriers and those within the ecosystem benefit from the aid of technology. Automating time-intensive processes not only gets claims paid out faster, it also reduces costly turnover and employee stress. Case management for short term and long term disability, medical leave, or insurance claims is a labor intensive process with high stakes consequences for people’s lives, and compiling and assessing medical data is a delicate task. 

Whether you’re the healthcare employee creating the report of an injury, an IME processing records for a case, or the lawyer or insurance company handling the claim, there’s a good chance you’re processing these documents by hand. Hospital, insurance, and claims systems still rely primarily on manual processes, which means a higher risk of error and more time spent summarizing, organizing, and analyzing data. 

According to consulting firm McKinsey, the increasing use of AI in the claims industry can reengineer business processes at their core — creating systems where there is a ‘human in the loop,’ but not necessarily one processing each document by hand. This is likely to increase productivity, turnaround time, and accuracy: all factors that keep the claims industry bogged down. 

Claims Processing Move Slowly because There are Virtual Teams — yet Physical Paperwork

The rapid increase in the remote workforce combined with a paperwork-heavy industry is a major problem in the claims space. How can healthcare and claims providers remain compliant, protect the privacy and accuracy of their data, and scale their business models when so many of these documents are physical copies processed by hand?

Not only does a manual process cause inefficiencies, it also raises problems with accessibility. Printing, scanning, organizing, and shredding medical paperwork is no longer an option for a workforce operating from home. Employees need to be able to retrieve documents remotely, and they need to be able to find them with ease. 

One of the benefits of automated document processing is speed. On average, US employees spend about 6 days per year searching for paperwork they’ve misplaced. Without a cloud based system to provide easy access for remote staff, hospital, insurance, and claims providers will continue to face major delays. 

Claims Processing Moves Slowly because there are Increasingly Complex Claims

New types of employment (like gig workers and small business owners), more complicated claims (like mental health), and an aging population all contribute to a healthcare industry under more pressure than ever before. Whether it’s worker’s compensation or disability insurance, today’s claims professional has a lot on their plate. 

While businesses in the industry have room to scale, the existing processes for case management are often too labor intensive to allow them to do so. Many insurance providers outsource their medical record management, but third party providers add additional cost and risk. Some tasks can be automated, but complex claims require a human touch. 

Technology like AI can be leveraged to take out much of the time-intensive work involved in processing medical files, without sacrificing the flexibility and judgment needed for an accurate claim. With insurers already overwhelmed by their workload — 40% of insurers are actively searching for efficient tech —- a new volume of time intensive, labor intensive claims means keeping up with demand can no longer be done alone. 

Claims Processing Moves Slowly because of The Great Resignation

With inflation pushing up salaries and workers leaving their jobs in droves, it’s never been more important to have a great working environment. Turnover in the claims space is high, and it’s hard to keep processing times down with a workforce already stretched thin. 

Even though the industry is projected to grow, low staff attrition rates mean claims providers can start to fall behind. Whether it’s affecting employee satisfaction, limiting the bottom line, or leading to lengthy wait times, reducing manual tasks and increasing productivity is crucial for keeping staff around. 

Technology for the Claims Ecosystem

Like many parts of the global economy, the hospital, insurance, and claims systems are at a crossroads. With surging demand, more complex cases, and an outdated system of reviewing documents leading to long wait times for processing claims, the industry will need to adapt in order to grow. Knowing what causes the backlogs is crucial — but it’s how the industry responds that will really lead to changes on the path ahead.

Kristen Campbell
Content Writer

Kristen is the co-founder and Director of Content at Skeleton Krew, a B2B marketing agency focused on growth in tech, software, and statups. She has written for a wide variety of companies in the fields of healthcare, banking, and technology. In her spare time, she enjoys writing stories, reading stories, and going on long walks (to think about her stories).

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