AI Software Turns Uncompensated Care into Revenue.

How disability benefits “fall through the cracks.”

Medicaid applications are fairly simple and straight-forward. If the individual fits into a recognized Medicaid Group, the application is submitted through the local social services agency, and almost always awarded. Disability is different. SSI and SSDI applications are administered through the Social Security Administration, and the applicant must make a case that he or she is disabled, and therefore prohibited from “substantial, gainful employment” and the situation is expected to last at least a year or result in death. In order to make a case for disability, you must have documented evidence of “onset” from the individual’s health record. Then prove that the disability keeps the individual from work. Often, physicians and employers must make statements for the record, substantiating the claim. Then there are numerous “checks & balances” to the SSA disability awards process – primarily to screen-out fraud.

It typically takes three to five times longer to work a disability case, than a Medicaid case.

Eligibility teams, like all other business groups, are staffed to the point where workers will be utilized at 100% of capacity. So, when a worker can process three or four or five Medicaid cases in the time it takes to work one disability case, the more resource intensive disability cases tend NOT to get worked. There are exceptions of course. For example, some disabilities are easy to diagnose, and awards are expedited by the SSA (i.e. terminal cases). So, performance reports will often show a handful of disability cases. But unless the hospital tracks Medicaid applications vs. SSI/SSDI filings, there’s no way of knowing if disability is under-represented, and if potential revenue is being left on the table.

Lift someone up today.

Besides reducing Charity Care and increasing Medicare/Medicaid billings. Besides adding to DSH and 340B thresholds and reducing readmissions, hospitals that employ a specialized disability service like UC Disability Solutions, provide a valuable community service. That’s because when you help a low-income disabled individual qualify for SSI/SSDI, you have contributed to a life-changing experience. Not only will the individual receive health insurance, but also a monthly government stipend that can mean the difference between paying rent or being evicted. Or providing child-care services, or any of a number of things that change the life trajectory of your patients…your community.

UC DISABILITY SOLUTIONS is funded 100% by QRS.

The uninsured patient pays nothing for UC DISABILITY SOLUTIONS. And all up-front program costs are funded by QRS. CRM software tracks all patients in the approval pipeline, including all hospital visits in the interim. Once the disability candidate is awarded SSI benefits, the hospital may bill Medicaid for all services going back to the date of application. And in some states going back to three months prior to filing.

Medicare benefits begin sometime after "date of onset" QRS Provides billing instructions with back-up for the hospital, and once Medicaid/Medicare payments have been received by the hospital, QRS will invoice a percentage of this (incremental) revenue. So, all hospital fees are contigent upon "found" revenue that otherwise would have never been realized.

What is AI?

The general consensus among computer scientists today, is that “…AI…refer(s) to machines that respond to stimulation consistent with traditional responses from humans, given the human capacity for contemplation, judgement and intention.”(1) In other words, AI systems can think, and make decisions which normally require a level of human expertise.

The hype around AI often confuses Machine Learning with Artificial Intelligence. Machine Learning describes a system’s ability to automatically learn and improve from experience, without being explicitly programmed. Machine Learning is a component of AI. What separates AI from Machine Learning, is the ability to take the product of Machine Learning (self-improving data analysis) and make decisions in a human-like fashion.

QRS AI

Disability eligibility is very resource intensive. It is therefore imperative, that self pay patients be prioritized in terms of probability for disability award, so that hospital resources may be applied against those patients most likely to be awarded disability and thus Medicaid/Medicare. Initially, QRS software used algorithms that scanned ICD10 codes (diagnosis and billing) for disability indicators. Then gave each patient a rank score that physicians and analysts used to decide which patients to pursue for disability eligibility.

Today, QRS uses an AI platform built on “R” to host a multi-dimensional predictive model for identifying disability candidates. Instead of relying solely on algorithms to rank patients, the predictive model receives thousands of data points each day profiling demographic and medical data in addition to ICD10 codes. A denied/awarded key is eventually given for each patient. And thus, the AI model learns and becomes more and more accurate. The software has advanced to the point where it is far more accurate at predicting disability success than the humans who used to analyze the old algorithm reports.

(1) Brookings Institute, Darrell M. West, October 4, 2018

How does your hospital compare nationwide, in Charity Care write-offs?

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Charity Care to Patient Revenue Ratios for US hospitals

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QRS has developed a predictive model for estimating revenue that a hospital can expect to receive as a UC DISABILITY SOLUTIONS client.

QRS management uses this predictive model to determine:if the program will benefit a given hospital; and if so, what kind of disability program would best serve the hospital.

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