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Financial Assistance and Collection Practices at a Critical Access Hospital

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Financial Assistance and Collection Practices at a Critical Access Hospital

Prairie Ridge Health is a 25-bed critical access hospital that is a nonprofit hospital organization under IRC 501(r). Its financial assistance policy provides a full discount for households at or below 200% of the federal poverty guidelines and a 50% sliding discount from 201% to 400%. In the most recent fiscal year only 0.9% of patients were approved for assistance, while 14% of county residents are uninsured. Registration staff ask only whether the patient has insurance; they do not screen for Medicaid or financial assistance, and no presumptive eligibility process exists. Self-pay balances over $1,000 are referred to a collection agency on day 90 after discharge, and the agency reports accounts to credit bureaus on day 120. Last year 212 accounts were referred, and a retrospective review found that 68 of them had household income below 200% of the federal poverty guidelines. Separately, a Medicare patient receiving outpatient physical therapy was handed an advance beneficiary notice after the sixth visit had already been delivered, and was later billed $310 for that visit.

1. Identify each compliance exposure in this scenario, naming the requirement it implicates and the evidence that supports the concern.

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Extraordinary collection actions before the 240-day threshold. Section 501(r)(6) prohibits initiating an extraordinary collection action, including reporting to credit bureaus, before 240 days after the first post-discharge bill. The policy refers at day 90 and reports at day 120, so every referral is premature on its face. The 212 referrals are the evidence.

No reasonable efforts to determine financial assistance eligibility before collections. Before initiating an extraordinary collection action, the hospital must make reasonable efforts to determine whether the individual is eligible for assistance, including notifying them about the policy and processing any application received. Referring 68 patients whose incomes were under 200% of the federal poverty guidelines, and doing so without an application process at the front end, is direct evidence that reasonable efforts were not made.

Failure to widely publicize the policy and to screen. Section 501(r)(4) requires the policy and a plain-language summary to be widely publicized and available. A 0.9% approval rate against a 14% uninsured county rate suggests patients never learn the policy exists; the absence of Medicaid or presumptive screening at registration supports that inference.

Improper advance beneficiary notice timing. An ABN must be delivered and signed before the service is furnished, when the supplier believes Medicare will likely deny the item as not reasonable and necessary. An ABN handed over after six completed visits cannot support billing the patient, and a beneficiary who was not given the option before service may not be charged. The $310 bill is at risk of being a write-off.

2. Design a corrective action plan with concrete owners and timeframes, including how presumptive eligibility would work.

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Immediate, within 30 days. Suspend all credit bureau reporting and all collection agency referrals until a 240-day rule is built into the system. General counsel and the revenue cycle director own this, and the change should be a hard system hold, not a policy memo. Reverse the $310 patient bill and re-educate the therapy staff on ABN timing.

Within 60 days. Add a presumptive eligibility screen in registration. Use available data rather than asking patients to prove poverty: Medicaid eligibility files, prior-year assistance approval, enrollment in SNAP or other means-tested programs, homelessness indicators, and the EHR's existing financial class. The patient access manager owns the build; the eligibility vendor or state portal provides the data source. Build an application pathway that is one page and available at every point of service, with a documented decision within 30 days.

Within 90 days. Rewrite the collection policy so the sequence is: bill, plain-language summary with the first bill, 120-day notice, 240-day referral only after documented screening. Add an annual ABN competency for all therapy and outpatient staff. Widely publicize the policy: signage, website, discharge packet, and a line on every statement.

Ongoing governance. The compliance officer reports monthly to the board on referrals, days to referral, screening volume, and approvals, so the board has evidence rather than assurance. Retroactively review the 212 referred accounts and refund or adjust the 68 identified cases.

3. Which metrics would you put in front of the board to show the plan is working, and what would each tell them?

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Financial assistance approval rate as a percentage of self-pay patients. Baseline 0.9%, with a directional target in the range of 5% to 8% given a 14% uninsured county. The point is not the exact number but the gap between eligible population and approved applications, which currently suggests the program is invisible.

Median days from first post-discharge bill to any collection referral. Baseline 90, target 240 or more with zero referrals below the threshold. This is the single cleanest test of whether the 501(r)(6) control is real, because a system hold is either working or it is not.

Percentage of self-pay accounts screened for presumptive eligibility before referral. Baseline effectively zero, target 100%. Without this, the 240-day rule simply delays the same mistake.

Medicaid screening conversions and application outcomes. Number of patients screened, applications submitted, approvals, and denials with reason. This tells the board whether front-end staff are actually asking, which the current interview script does not.

Dollar value of assistance granted versus bad debt written off. A shift from bad debt to charity care indicates patients are being classified correctly rather than defaulted.

Present these four to five measures as a single page with a trend line, not a data dump; boards act on direction and exceptions, and every metric above is chosen because it changes a decision if it moves the wrong way.