Disability Benefits Yield Medicaid and Medicare Payments.

Using proprietary AI software, UC DISABILITY SOLUTIONS will analyze uninsured patient data for disability indicators, finding patients who would not have otherwise been identified as "disabled". From there, disability experts will cross-reference medical history with work history in order to build a case for the patient, and advocate for the patient throughout the SSA vetting process.

Once awarded, the hospital may bill Medicaid or Medicare for services that once were written-off as uncompensated care. Additionally, this program will reduce re-admissions, bolster DSH and 340B thresholds ... all while providing a valuable community service by arranging health insurance and monthly stipends for the community's most vulnerable.

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. Protected filings are submitted 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.


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.


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

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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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