For years, healthcare providers have witnessed explosive growth in the number of patients who are self-pay or on high-deductible health plans (HDHP). Even for those who have commercial insurance, the patient share of healthcare financial responsibility is increasing. Since 2012, the average annual deductible for workers who are enrolled in healthcare insurance through their employer has blown up by 61%.i
Self-pay and HDHP patients take longer to pay and pose a higher risk of write-off. This adds to the already significant financial strain on medical practice, emergency medicine, and specialist providers. Therefore, it is in providers’ best interest to search for healthcare insurance coverage as early in the patient encounter as possible to prevent the claim from becoming classified as self-pay in the first place.
One of the most effective solutions for combatting the lack of reliable patient demographic and insurance information is an automated revenue cycle management (RCM) optimization tool suite that can find, correct, and verify patient and payer information. Providers who put AI-enhanced, real-time technology to work can improve their clean claims rate and pull payer dollars in more quickly. Automated RCM optimization tools can be integrated into existing workflows and systems as early as patient scheduling and registration, or later during billing and patient engagement. Essential tools include:
- Demographic verification — can help enhance core data for more than 60% of patient encounters.
- Insurance discovery — solves “coverage not found” errors and can identify active primary, secondary, and tertiary coverage — including retroactive Medicaid.
- Insurance verification — confirms eligibility and benefits, and assesses coverage, co-pays, deductibles, secondary coverage, and codes.
- Deductible monitoring — monitors when the patient deductible has been met and shifts primary financial responsibility to payers.
If it isn’t possible to add all these tools at once, the first investment should be in a robust insurance discovery tool that provides a confidence score. Best-in-class real-time insurance discovery technology delivers a clear return on investment (ROI) by finding more active, billable coverage — including coverage for previously presumed self-pay patients. For example, the ZOLL® AR Boost® Insurance Discovery tool solves providers’ most common challenges, such as:
- Coverage not found
- Patient provides no or outdated insurance information
- Self-pay patients who actually have or are eligible for coverage
- Desire to reduce time-consuming, manual eligibility processes
On average, the ZOLL AR Boost Insurance Discovery tool can find active, billable coverage for 35% or more of accounts. For specialty providers, such as radiology and laboratory, it can find even more. For home health/hospice care providers, the tool has found coverage for upwards of 65% of accounts.
To put the benefits of automated insurance discovery technology into context, with an average commercial claim reimbursement rate of $250, a provider could generate an additional $50,000 in revenue per 1,000 self-pay claims (based on a conservative 20% additional commercial coverage found with a $250 per-claim reimbursement).
A best-in-class, real-time healthcare data solution suite like ZOLL AR Boost harnesses AI-enhanced, automated capabilities to help ensure data quality and reduce denials, increase revenue, and accelerate time to cash. With no end in sight to the growing number of self-pay and HDHP patients, insurance discovery technology with proven, rapid ROI is certainly worth a closer look.
i KFF Employer Health Benefit Survey Finds, https://www.kff.org/private-insurance/press-release/annual-family-premiums-for-employer-coverage-average-22463-this-year/, KFF health Affairs, accessed 2/23/23