For any non-product related queries, please write to info@perfios.com.
For any non-product related queries, please write to info@perfios.com.
Navigating health insurance & healthcare claims analytics can be a daunting task, with complicated products, pricing and distribution turning away potential customers. While it is more expensive than life insurance, it is also poorly understood with non-covered items, pre-existing conditions for healthcare fraud detection, exclusions and riders.
In recent years, insurers have been increasingly reliant on healthcare data analytics to aid and assist claims assessors in deriving valuable insights regarding treatment and pricing patterns. This helps them operate more efficiently and accurately, while providing better customer experience through faster processing and fewer wrong payout denials. This article dives into claims analytics & healthcare data analytics, its advantages and its role in the future of health insurance.
A market study by Grand View Analytics valued the global healthcare market at USD 43 billion in 2023 and is expected to grow at an astounding 21.1% year on year. The healthcare industry labors under to function despite skyrocketing healthcare inflation, falling patient retention and increasing demands on medicare infrastructure due to pandemics and lifestyle diseases. The effects are rippling from hospital to consumer to insurer as policies become increasingly complex in response. Insurance claims analytics is a critical tool to ensure the sustainability of the healthcare ecosystem.
Insurance companies glean valuable insurance claims data insights from hospital bills, doctor’s prescription and claims documents, including patterns and trends in medical treatments and the hospitals that provide them. This information feeds into their product development, policymaking, and business operations.
To pay or not to pay? This is the question that underpins the insurance claims management business. Rejecting a valid claim might mean losing a customer who needed and deserved the money at the time. Approving an ineligible claim means the insurer loses money. Health claims analytics allows an insurer to scrutinize every patient claim carefully to determine what should and shouldn’t be reimbursed.
Healthcare analytics solutions allows an insurer to ascertain whether they’re overpaying or underpaying claims. This helps them keep up their key financial metrics namely claims settlement ratio and claims payout expenses.
As much as it sounds politically incorrect, not every claimant is being truthful with their claims… And this isn’t limited to developing insurance markets! The US loses an estimated $105 billion annually to healthcare fraud according to Forbes’ 2024 Insurance Claims Statistics report. A robust fraud, waste and abuse detection program is key to transparency and trust in the insurance ecosystem.
Insurers are constantly researching and revising their policy products in step with emerging trends and patient needs. Health insurance claims analytics allows them to stay ahead of the shifting patterns in disease including their prevalence, symptoms, demographics, and treatment costs.
Despite widespread acknowledgement of its importance, health insurance claims analytics is still in its nascency. There are several barriers to analytics penetration., Let’s talk about some of them
Healthcare claims processing is a specialized skill set and building an in-house team of experts can be a daunting task for most insurers, especially when it means taking resources away from their busy claims departments.
Reading handwritten notes and prescriptions is difficult and delays healthcare claims processing. The complexity only increases in markets that use and accept multiple languages and medical data standards.
Intelligent healthcare insurance analytics can be expensive to set up and operate, and most insurers balk at the technical expertise needed to maintain and update the infrastructure.
Medical data falls under Personally Identifiable Information, and as such must be handled with care and confidentiality. Sharing this insurance claims data insights with third party solutions providers carries legal and ethical questions that may be difficult to navigate.
Simple automation and OCR for data extraction & healthcare claims processing are simply not intelligent enough to correlate data across 40 pages of medical claims documentation, let alone track and retain patterns across thousands of claims.
So, what happens if health insurers don’t level up their analytics?
While insurance penetration and coverage increase, so do the rates of insurance fraud making healthcare fraud detection for insurance processing pertinent. This forces insurers to pass on these costs to those who can least afford it – their customers. Policies are becoming increasingly complex, with numerous exclusions and rising premiums.
As policies become complex, new users become skeptical of health insurance & claims processing management itself. Fewer people purchasing insurance leads to more people paying out of their own pockets for hospitalization.
As insurance companies increase their scrutiny on network hospitals, they also take more time to process healthcare insurance claims and pay them out. In turn, some network hospitals resort to complicating their billing procedures to couch.
Generative AI, machine learning, natural language processing and other technologies have opened new possibilities to transform traditional manual healthcare claims processing and its management. AI has demonstrated its capabilities to the insurance sector with insurers reporting 3% - 5% reductions in claims payouts through insurance claims digitization and analytics.
With improving technology, healthcare insurance claims analytics will play a pivotal role in helping insurers and hospitals work together to identify cost reduction initiatives and proactive fraud detection triggers and transform customer journeys.
Globally, insurance penetration has become a focus topic for developing economies. India, for example, has announced a vision for inclusive insurance for all its citizens through its Bima Trinity program. Hospitals and insurers now bear the onus of responsibility to ensure that the appropriate technologies are in place to scale up sustainably. At the heart of this endeavor lies insurance claims analytics, serving as the cornerstone for building and scaling these essential capabilities.
