Bureaucracy Times

All the news fit to be declassified.

Category: Public Safety & Social Policy

  • CMS Found Possible Errors in Medicaid Financial Data. Then It Didn’t Follow Up.

    The Centers for Medicare & Medicaid Services had a system for checking whether states submitted complete Medicaid managed-care financial reports.

    It also had a system for checking whether some of the numbers in those reports might be wrong.

    What it apparently did not have was a procedure for what to do when the second system found something.

    A new Department of Health and Human Services Office of Inspector General report found limitations in CMS’s process for verifying state-submitted medical loss ratio data, including dozens of reports containing potential inaccuracies that CMS identified but did not pursue with the states involved.

    The findings concern Medicaid managed-care medical loss ratios, or MLRs. An MLR measures the percentage of a plan’s revenue spent on covered health care services and quality-improvement activities. The federal standard is 85 percent, meaning a plan reaching that figure spent 85 percent on those purposes and the remaining 15 percent on administration and profit.

    The numbers aren’t merely informational. States use past MLRs when developing future capitation rates, the fixed monthly amounts paid to managed-care plans for each enrolled beneficiary. States are required to develop those rates so plans can reasonably achieve an MLR of at least 85 percent.

    That makes the accuracy of the underlying data rather important.

    CMS Couldn’t Check More Than Half the Reports

    OIG examined CMS’s oversight of 595 final MLR summary reports submitted by 44 states for the 2019 reporting year.

    CMS used five accuracy checks covering four required MLR data elements. According to OIG, those checks identified 57 reports submitted by 16 states containing at least one potential inaccuracy.

    There was another problem.

    For three of the four required data elements, CMS needed additional information to perform its accuracy checks. But those underlying data elements were optional for states to submit.

    The predictable happened.

    CMS could not conduct each of four accuracy checks on more than half of the 595 reports. Depending on the check, CMS could test only 43 to 46 percent of them.

    Where CMS did have enough information to perform the checks, it found potential problems.

    Among the reports CMS could test, it identified 23 potentially inaccurate MLR numerators, 15 potentially inaccurate denominators using one check, 18 using another denominator check, and one potentially inaccurate adjusted MLR. OIG noted that additional optional data might have allowed CMS to identify additional potential inaccuracies.

    CMS performed another check by comparing reported “member months” against enrollment information. It could perform that comparison for 448 of the 595 reports and identified 25 with potentially inaccurate member-month figures.

    These were potential inaccuracies, not OIG findings that the figures were definitively wrong.

    Determining that would have required another step.

    And Then, Nothing

    CMS itself told OIG that potential inaccuracies require further evaluation and possibly follow-up with states to determine whether the numbers are actually incorrect.

    CMS did not follow up with the 16 states.

    OIG found that the agency therefore missed an opportunity both to obtain corrected information where errors actually existed and to alert states so they could investigate the questionable data themselves.

    Curiously, CMS did have procedures for chasing down missing information.

    For the same 2019 reporting year, CMS followed up with states over missing MLR data and successfully obtained 192 initial or resubmitted reports from 19 states.

    Its written procedures simply did not specify what employees should do about potential inaccuracies detected by CMS’s own accuracy checks.

    Completeness, apparently, had a workflow. Accuracy was still waiting for one.

    The Findings Stayed in Their Lane

    OIG found another disconnect inside CMS.

    As of October 2025, the CMS staff reviewing state-submitted MLR data did not share the results of their accuracy checks with the CMS employees responsible for reviewing states’ future capitation rates.

    Those rates are precisely where historical MLR information can matter.

    CMS reviews the prospective rates and approves managed-care contracts containing the final rates. OIG concluded that by not communicating the accuracy-check results internally, CMS missed an opportunity for those findings to inform its rate reviews.

    OIG recommended that CMS establish procedures for handling potentially inaccurate data, share accuracy-review information with employees reviewing capitation rates, and improve the effectiveness of its MLR oversight, potentially by adding automated accuracy checks to its reporting portal.

    CMS concurred with all three recommendations.

    An Important Date on the Report Card

    There is a significant caveat to the findings.

    Although OIG issued the report in September 2026, the data it analyzed came from the 2019 reporting year.

    CMS emphasized that point in its response, calling 2019 one of the earlier reporting periods for state MLR submissions and saying it has made substantial improvements since then. Those changes include an MLR toolkit, an optional standardized reporting template, a web-based submission portal and public release of plan-specific MLR data.

    The agency also said it has already added automated checks preventing states from submitting reports with blank required fields and will consider expanding the system to perform automated accuracy checks. CMS has encouraged states to submit the optional data needed for additional verification and says it intends to continue doing so.

    That means the OIG report does not establish that the same deficiencies persist today.

    It does establish something narrower, and peculiar enough on its own.

    CMS had financial reports that mattered to Medicaid managed-care oversight. It built checks designed to identify questionable numbers in those reports. Those checks found potential inaccuracies in reports from 16 states.

    And when the warning lights came on, there was no procedure telling the agency what to do next.

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  • The Label Only Needed One Signature. That Was the Problem.

    Every kidney that leaves an organ procurement organization is supposed to travel with two things attached to it: a label confirming which kidney it is, and the signatures of two separate human beings swearing that label is correct. The federal government built that redundancy on purpose, because the alternative to redundancy is a courier showing up at a transplant hospital with the left kidney labeled as the right one. According to a new HHS Office of Inspector General audit, that alternative has already happened. More than once. The report just wasn’t supposed to be the one that found it.

    An Audit About Money That Found a Body Problem

    OIG set out to check whether independent organ procurement organizations, the not-for-profit entities that recover and ship organs for transplant, were reporting their kidney transportation costs correctly on their Medicare cost reports. That is, on its face, an accounting story. Auditors sampled 213 high-dollar kidney transportation costs across 43 of these OPOs and found that 32 of them had reported a combined $428,325 in unallowable expenses, either by dumping the cost of flying a multi-organ recovery team onto the kidney line item, or by billing Medicare for driving a donor’s body to a funeral home, which is not, whatever an OPO’s accounting department may have believed, a step in organ acquisition.

    That’s a real finding, and a real number, though a modest one against the $53.6 million in kidney transportation costs the audit actually covered. It is also, and this matters, not the finding buried five pages later. Four of the 43 OPOs failed to meet Medicare’s separate requirement that two people, one of them an OPO employee, physically verify the label on an organ before it ships. Three of those four submitted verification forms signed by exactly one person. The fourth never sent the required donor documentation to three transplant hospitals at all. OIG did not find a mislabeled organ in its own sample. But it did note, almost in passing, that “some OPOs mentioned incidents in which labeling errors had resulted in the wrong organs being sent for transplant,” including one case in which a label for a left kidney ended up on the container for the right one. That sentence is doing more work than the entire cost-allocation section, and it arrives as a footnote to a footnote.

    “Clerical Error,” Four Times in a Row

    Ask an OPO why it filed for reimbursement of a lung recovery team’s flight as a kidney expense, and the answer, nearly every time, is clerical error or a misunderstanding of Medicare’s rules. Ask an OPO why it billed the transportation of a dead body to a funeral home as an organ acquisition cost, same answer. Ask an OPO why only one person signed a label verification form that federal regulation requires two people to sign, same answer again. Four separate OPOs gave OIG the identical explanation for the identical failure; staff made a mistake, nobody caught it.

    There is a point at which “clerical error” stops describing an incident and starts describing a system. Three OPOs out of four, independently, produced a verification form with one signature where the rule requires two. That is not a typo. That is a control that exists on paper and does not exist in practice, at three different organizations that likely never spoke to each other about it. The audit’s own explanation for why this keeps happening is almost sympathetic (Palmetto GBA, the Medicare administrative contractor responsible for reviewing these cost reports, has never provided direct training to OPOs on how to report transportation costs). It has, per its own account to auditors, discussed the subject “frequently.” Frequent conversation is not instruction, and OIG’s two recommendations to CMS, recover the money and “provide additional education,” read less like accountability and more like a request that someone finally hold the seminar that should have happened years ago.

    The Kidney Gets Reviewed. Everything Else Doesn’t.

    Here is the structural reason 32 of 43 OPOs found it so easy to misfile these costs; Palmetto reviews and caps an OPO’s standard acquisition charge for kidneys, and only kidneys. Nonkidney organs, livers, hearts, lungs, get no such review, and Medicare settles up retroactively with OPOs for kidneys but never for anything else. That asymmetry creates an obvious, if unglamorous, incentive; a cost that gets scrutinized as a kidney expense and a cost that gets waved through as a liver expense are not treated the same way on the back end, and an OPO’s accounting staff does not need to be dishonest to notice which line item is safer to pad.

    CMS has actually acknowledged this is a problem, just not urgently. Its FY 2027 Inpatient Prospective Payment System final rule, issued July 31, 2026, extends MAC review to standard acquisition charges for all organ types, and requires retroactive settlement adjustments for nonkidney organs too. The effective date is October 1, 2028. That is two full budget cycles from now, during which the exact incentive structure that produced $428,325 in documented misallocation over an 18-month audit window remains fully intact, uncorrected, and unreviewed for anything that isn’t a kidney.

    CMS Concurred, Which Is Not the Same as CMS Acting

    CMS’s written response to the draft report is exactly what a government agency’s written response to a draft OIG report usually is; concurrence with both recommendations, a promise to instruct Palmetto to recover the identified reimbursements “consistent with relevant law and the agency’s policies and procedures,” and a commitment to “explore the most effective and efficient way” to get education to OPOs about costs they’ve apparently been miscoding since at least the start of this audit period. Nothing in CMS’s comments, at least in the portion of the letter accompanying the report’s narrative summary, addresses the labeling failures directly, and nothing in either OIG’s recommendations or CMS’s response proposes anything beyond training for the four OPOs that shipped organs without proper verification. Federal rule gives CMS the authority to decertify an OPO that is out of compliance with a process performance measure, making it ineligible for Medicare reimbursement entirely. That authority goes unmentioned. What gets recommended instead, for a failure OIG itself says “may increase risks to patient safety and may lead to compromised transplant outcomes,” is the same fix proposed for OPOs that miscoded a funeral home bill, education.

    The 43 OPOs in this audit are never named. OIG’s own account of the industry describes each one only as “one OPO” or “another OPO,” a convention that protects individual organizations from scrutiny while the aggregate failure gets a press release. Whether that anonymity survives a records request is a question for another piece. Whether a two-year runway before nonkidney costs get reviewed at all survives without another mislabeled kidney reaching a transplant hospital is a question nobody in this report seems in a hurry to answer.

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  • Twenty Two Years, Three Audits, One Excuse.

    The Social Security Administration runs a program that pays benefits to the teenage children of dead, disabled, and retired workers, provided those teenagers are still in high school. The mechanism that decides whether the checks keep coming is a single form, filled out by the student, certified by a school official, and reviewed by an SSA employee who is trusting both of them to be right. It is not a complicated system. It has also failed the same audit three separate times since 2004, for the same three reasons, with SSA agreeing to fix it on all three occasions.

    A Teenager’s Signature Is Still the Control

    Under the Social Security Act, a minor child of an insured worker loses benefits at 18 unless they qualify as a full time student, in which case payments continue until they graduate or turn 19, whichever comes first (42 U.S.C. §§ 402, 423). The instrument that governs this is Form SSA-1372, Advance Notice of Termination of Child’s Benefits. The student states their school, their attendance dates, and their expected graduation date; a school official signs off; SSA takes it from there.

    There is no automated feed from any school system telling SSA when a kid drops out, transfers, or graduates a semester early. There is no real time check against enrollment records. There is a piece of paper, filled out months in advance, describing a future the student is predicting rather than reporting. The Office of the Inspector General’s newest audit (report 022515, released September 2026) exists because that paper, and the employees who process it, keep getting it wrong the same three ways, and this is the third time OIG has documented it happening.

    2004: The Original Diagnosis

    In an August 2004 review titled School Attendance by Student Beneficiaries over Age 18 (A-09-04-14013), OIG sampled 300 students out of a population of 254,121 and found $202,917 in incorrect payments and $56,065 in unsupported payments among them. Projected to the full population, that came to about $70 million in incorrect payments to 32,839 students and $39.5 million in unsupported payments to 10,312 students. The stated causes were that students and schools did not promptly report attendance changes, and that SSA did not retain the documentation needed to prove eligibility either way. SSA’s response was to promise additional employee training and a systems modification to stop paying benefits past the maximum age of entitlement, a related failure mode significant enough that OIG had already given it a separate audit of its own the same year.

    2014: The Same Chart, Bigger Numbers

    A decade later, OIG returned with Payments to Student Beneficiaries (A-09-13-13059, December 2014), sampling 275 students out of 1,539,078 who had received student benefits between 2007 and 2013. The estimate had grown to $225.3 million in overpayments to about 106,000 beneficiaries and $968 million in unsupported payments to roughly 246,000. The trade press covered it as a program in disarray, and the underlying diagnosis had not moved an inch from 2004. Students and schools were still not reporting attendance changes. SSA employees were still failing to retain evidence, and the agency’s own systems still weren’t recording graduation dates on the Master Beneficiary Record where an employee could see them. SSA’s corrective action, according to the background section of this year’s report, was to notify schools and organizations about the importance of timely reporting and remind its own staff to keep the paperwork. In practice, that was a memo.

    2026: Reading the Same Homework Back to Itself

    The current audit sampled 100 of 521,393 beneficiaries entitled to student benefits from January 2022 through December 2024. SSA correctly paid 71 of them. It got 17 wrong and could not document eligibility at all for 12 others, a documentation gap that on its own accounts for more projected dollars than the confirmed errors sitting next to it, an estimated $342 million in unsupported payments to 63,000 beneficiaries against $211 million in confirmed improper payments to 89,000.

    Split the 17 error cases and the causes fall into the same two buckets OIG has now written up three times. Nine cases trace back to students or schools handing SSA outdated or simply wrong attendance information, the kind of error where a beneficiary reports an expected June graduation and then quietly leaves school the previous January, collecting five months of benefits nobody was still entitled to. The other eight trace back to SSA itself. In one, an employee typed a graduation date into the Master Beneficiary Record a full year earlier than what the student had actually reported, cutting off seven months of benefits the student should have received. In another, a beneficiary attending a full year school got their benefits terminated a month early because an employee applied the rules for a quarterly academic calendar instead, a distinction the agency’s own manual spells out clearly enough (SSA, POMS, RS 00205.325, C). In a third, SSA received written notice from a school that a student had graduated a month ahead of schedule and simply never acted on it.

    The report closes with three recommendations. Fix the eight remaining attendance error cases. Fix the six remaining duration miscalculations. Identify why any of this keeps happening at all. SSA’s Chief Risk Officer replied that the agency agrees. That sentence, or one close enough to it, is now sitting in the file from 2004, from 2014, and from 2026.

    What has never been sitting in that file, across three audits and twenty two years, is a system that checks a school’s actual enrollment against what a form predicted six months earlier, or a Master Beneficiary Record built so a graduation date gets flagged rather than typed in by hand and trusted. The dollar figures keep climbing because the beneficiary population keeps climbing, not because anyone at SSA found a new and interesting way to get this wrong. The agency has spent over two decades photographing the same crack in the same wall, filing the photograph, and calling the filing a corrective action plan.

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  • Forty Six Percent of Alaska’s Village Water Systems Have Nobody Watching Them

    Somewhere in Alaska in 2025, tribal members turned on a tap and got water contaminated with E. coli, a bacterium capable of causing gastrointestinal illness serious enough, in vulnerable people, to become life threatening. The cause was not a burst pipe or a natural disaster.

    According to a new Government Accountability Office report on tribal water infrastructure, it happened because the utility did not have enough qualified personnel on staff to make sure its chlorination equipment was actually working (Government Accountability Office, GAO-26-107178).

    This was not an isolated incident. It happened twice in 2025 alone, and it fits inside a much larger, quietly alarming statistic buried in the same report, that nearly half of Alaska Native village drinking water systems had no primary certified operator on staff during that same fiscal year.

    The Job Nobody Explains Until Something Breaks

    Water operators are, in the most literal sense, the reason a water system does what it is supposed to do after the ribbon-cutting ends. GAO’s report spells out exactly what that job entails, running the equipment, controlling the treatment processes, and monitoring the plants that make water safe to drink, while wastewater operators do the equivalent work removing pollutants before water is released back into the environment.

    These are not entry level positions filled on a whim; operators need specialized training and must earn and maintain certifications tied to the specific complexity of the system they run, certifications that exist precisely because getting this work wrong has direct public health consequences.

    A water system without a certified operator is not simply understaffed in the abstract sense that any workplace might be short a hand. It is a facility that treats and delivers drinking water without anyone certified to confirm it is doing so correctly.

    That is the exact condition GAO found across a huge share of Alaska Native villages. Citing State of Alaska data, GAO reports that about 46 percent of Alaska Native village drinking water systems, 73 out of 157, did not have a primary water operator certified to the level required for that system on staff in fiscal year 2025.

    That figure applies specifically to systems that were required to have a certified primary operator in the first place, meaning it is not padded by facilities too small to need one. Nearly half of the systems that were supposed to have a qualified person running them did not.

    Why Nobody Stays

    GAO and the State of Alaska both point to the same root cause, and it is not a mystery requiring further study. Rural utilities in Alaska experience high operator turnover, and IHS senior officials attributed that turnover directly to a lack of tribal funding for water operator salaries.

    This is not a story about a shortage of qualified people willing to do specialized technical work in remote communities; it is a story about tribal water systems that, once built, frequently lack the money to pay the specialized staff needed to keep them running, so operators leave for jobs that pay better, and the system cycles through vacancy after vacancy. One utility, unable to afford the energy costs required to run its wastewater aeration system, simply stopped aerating its wastewater, a direct, documented consequence of an operating budget too thin to cover routine costs.

    This turnover and funding problem sits at the center of one of the report’s core findings, that IHS generally does not fund routine operations and maintenance for the water systems it helps build.

    IHS pays to construct the plant. It largely does not pay to keep qualified people running it afterward. The system gets built, the ribbon gets cut, and then the ongoing cost of the one thing that actually keeps water safe, namely a trained person watching the equipment, becomes the tribe’s problem alone, in communities that GAO’s own broader report describes as chronically underfunded relative to the tax base and financing options available to non tribal communities.

    What an Empty Operator Position Actually Costs

    GAO does not let this stay abstract. In 2025, two tribes experienced E. coli contamination in their water systems specifically because they lacked adequate operations and maintenance capacity, including not having enough qualified personnel on hand to ensure chlorination equipment was functioning properly.

    E. coli contamination in a drinking water system is not a paperwork violation; it is a direct threat of gastrointestinal illness and, in vulnerable populations, more serious health outcomes. In a separate 2024 incident, a different tribe lacked enough wastewater utility operators to perform routine maintenance on a lift station, and when the pump inevitably failed, the result was prolonged sewage overflow.

    These are not edge cases dredged up to make a point. They are what GAO explicitly identifies as the predictable consequence of a system where nearly half of a state’s tribal water utilities cannot keep a certified operator on staff, wired directly to a funding structure that pays for construction but not for the ongoing salaries needed to run what gets built.

    The connection between the abstract 46 percent figure and an actual gastrointestinal illness outbreak is not speculative; it is the same causal chain GAO lays out explicitly, funding gap, operator turnover, unmonitored equipment, contamination event.

    A Pilot Program, Finally Proposed

    GAO’s response here goes further than most of its recommendations elsewhere in the report, because this is the one place where GAO does not simply ask an agency to fix its own paperwork. GAO suggests Congress consider authorizing and directing IHS, working with tribes and in collaboration with EPA, to establish a pilot program that would actually help fund tribes’ routine operations and maintenance costs, specifically things like water operator salaries and the energy costs needed to run treatment equipment.

    It is worth noting what this recommendation implicitly concedes, that the current system, in which the federal government funds construction but not the staffing needed to safely operate what it built, is not working, and IHS itself has acknowledged its statutory authority does not currently extend to covering routine operations and maintenance costs at all.

    A pilot program is a modest first step relative to the scale of the problem GAO documents. Forty six percent is not a rounding error or a temporary staffing hiccup; it is essentially a coin flip on whether any given Alaska Native village’s water system currently has a certified professional watching over it. Every one of those vacant positions is a system running, or not running, on borrowed time, waiting for the next equipment failure nobody catches until people start getting sick.

    Source: U.S. Government Accountability Office, Tribal Water Infrastructure: Federal Agencies Should Better Track and Coordinate Their Assistance to Alaska Native Villages (GAO-26-107178, September 2026). The staffing gap is one of three structural failures in the same report. Tribes also contend with a forty-year statutory prohibition that bars IHS from connecting water to homes built with HUD housing funds, leaving communities to choose between homes without water or fewer homes. And when multiple agencies try to fund projects together, the absence of a standardized USDA-IHS interagency agreement adds nearly $100,000 in overhead per project — overhead that produces no water, no pipe, and no certified operator.

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  • GAO Measured the Delay; A Judge Had Already Called It Illegal

    The Numbers GAO Was Willing to Count

    The Government Accountability Office released a report this week on FEMA‘s Building Resilient Infrastructure and Communities program, the agency’s flagship pre disaster mitigation grant, and the numbers it counted are damning enough on their own terms. As of March 2025, FEMA had awarded 1,245 BRIC subgrants worth about $2.5 billion, which sounds respectable until you notice that figure is half of the $4.8 billion Congress actually made available. Of what had been awarded, FEMA had reimbursed $62 million and closed out exactly 37 subgrants. The median time for FEMA to finish reviewing a subapplication and award the money, GAO found, is 7 to 9 months. Another 700 subapplications, tied to roughly $2.2 billion, were sitting in the second of FEMA’s two review stages with no decision made at all.

    GAO quotes communities saying, in the mild register that federal audit reports reserve for people who are furious but trying to stay eligible for future funding, that these timeframes “could extend project timelines and increase costs.” The report’s seven recommendations are the standard genre of fix; identify efficiencies in the subapplication review, apply lessons learned to communication, establish performance goals. All reasonable. All aimed at a process problem.

    Here is the sentence in the report that is doing more work than it appears to be doing. From April 2025 to March 2026, FEMA awarded no subgrants and obligated no funds. Eleven months, stated as a fact about program administration, sitting inside a report about review timelines.

    What Happened Between April and March

    That eleven month gap was not FEMA finishing its paperwork slowly. It was FEMA terminating the program.

    On April 4, 2025, FEMA formally ended BRIC, cancelling pending applications going back to fiscal year 2020 and moving to redirect the money elsewhere, a move detailed in the federal court’s later ruling on the matter. BRIC is not a discretionary line item FEMA can turn off by memo. It is funded through direct congressional appropriations under the Infrastructure Investment and Jobs Act and set asides from the Disaster Relief Fund under the Stafford Act, which is precisely what a coalition of states argued when they sued that July.

    On December 11, 2025, U.S. District Judge Richard Stearns agreed with them, and did not agree gently. He ruled that FEMA’s termination violated the Further Consolidated Appropriations Act of 2024, the constitutional separation of powers, the Appropriations Clause, and the Administrative Procedure Act, and issued a permanent injunction ordering the program restored. FEMA did not restore it. Two months later, the same states had to go back to court and ask a judge to force compliance with his own order, which the Washington state attorney general’s office documented in March 2026, when Judge Stearns issued an enforcement order giving FEMA 21 days to publish a new funding notice. FEMA published it on March 25, 2026, three weeks past the deadline it had already been given twice.

    So the eleven months in GAO’s report is not a measurement of bureaucratic friction. It is the interval between an unlawful act and a federal court forcing its reversal, with an extra two months tacked on for the agency’s noncompliance with its own defeat. GAO’s highlights page does not use the words termination, lawsuit, or injunction. It uses the word timeframes.

    The plaintiffs were not abstractions. Maryland’s attorney general noted that the termination left more than $80 million in BRIC funding for the state in question, including flood mitigation work for Crisfield and South Baltimore. Arizona’s attorney general listed 25 selected projects worth $9.8 million, among them a $4.6 million infrastructure project in Buckeye. These were not requests still being drafted. They were projects that had cleared FEMA’s review and were waiting on a check, from a government that had already told the public the check was cancelled.

    FEMA’s Version of the Same Year

    FEMA’s own account of this period, issued as a public notice to states, tribes, and territories, tells a different story than the one a federal judge told. It explains that BRIC “became bogged down in bureaucracy, focused on climate change initiatives, and riddled with inefficiencies” under the previous administration, which is why Secretary Kristi Noem “directed FEMA to conduct a methodical evaluation of the program.” The notice adds that FEMA will resume normal operations “once the lapse in appropriations has ended,” folding the government shutdown into the same sentence as the agency’s own program suspension, as though the two were the same kind of interruption.

    Nowhere in FEMA’s telling does a judge find that the agency broke the law. The “methodical evaluation” and the illegal termination occupy the exact same calendar days; FEMA simply gets to narrate them as a virtue rather than a defeat. This is the closest thing this story has to a punchline. A federal court says the government violated the separation of powers to shut down a program Congress funded. The agency responsible calls it stewardship.

    Reapply, Please

    The 700 subapplications GAO found stalled in review as of March 2025 were caught in that stage precisely when the termination hit. The program that eventually reopened is not, procedurally, the one they applied to. FEMA’s own fact sheet for the restored funding opportunity states plainly that “previous subapplications submitted for the initial Fiscal Year 2024 BRIC funding opportunity will not be reviewed,” and instructs applicants to “review, update, and resubmit in accordance with this new funding opportunity.”

    Communities that had already cleared FEMA’s first review stage, in some cases years earlier, were told their applications no longer exist. Whatever work went into a benefit cost analysis, a scope of work, a local match commitment, has to be redone against new evaluation criteria FEMA wrote after Congress had already appropriated the money for the old ones.

    None of GAO’s seven recommendations addresses this, because GAO’s mandate is process efficiency, not legality, and by the time its auditors were writing, the termination was already adjudicated elsewhere. What the report actually documents, whether it means to or not, is what happens to an audit’s own numbers when a program spends nearly a year not existing. The 7 to 9 month review time GAO flags as the problem to fix was, for the 700 communities caught in it, the least of their delays. They were not waiting on FEMA to finish reading their file. They were waiting on FEMA to admit the file still counted.

    Sources: Government Accountability Office, Building Resilient Infrastructure and Communities: FEMA Should Improve Subgrant Review Timelines (GAO-26-107774, September 2026); Washington v. FEMA, U.S. District Court, Memorandum and Order (December 11, 2025); Washington State Attorney General, Court Order Enforcing BRIC Ruling (March 2026).

  • The Department Started Fixing Its Data, Then Fired the People Fixing It

    Late in 2024, the Department of Education did something almost unheard of in federal data governance. It admitted a flaw in one of its own signature statistics and started building the fix. Officials began requiring states to report the number of students enrolled in a school across the full school year, the same timeframe already used to count chronically absent students, instead of the single frozen October snapshot that had been producing chronic absenteeism rates north of one hundred percent. It was a small, boring, correct decision. Then the Department gutted the office responsible for finishing it, and decided the fix wasn’t worth finishing after all.

    A Reorganization With a Body Count

    In March 2025, the Department announced a reduction in force and reorganization. The numbers, drawn from Office of Personnel Management data cited in GAO’s report, are not subtle. The Institute of Education Sciences, the statistical and research arm responsible for the EDFacts data collection that produces chronic absenteeism figures, went from 191 staff at the end of calendar year 2024 to 28 staff at the end of 2025, a reduction of more than 85 percent. The Office of Elementary and Secondary Education, which officials told GAO serves as data steward for the chronic absenteeism collection specifically, lost 43 percent of its workforce over the same period.

    Officials were direct with GAO about the sequence of events. They began the enrollment fix in late 2024. They later decided not to proceed, “due to staffing changes at the agency.” That sentence, delivered without elaboration, is doing an enormous amount of work. It is the Department’s own explanation for why a known, documented flaw in a nationally reported education statistic will keep producing implausible numbers indefinitely. Not because the fix was hard. Because the people assigned to do it no longer worked there.

    The Burden That Was Already Being Carried

    What makes the abandonment particularly hard to defend on the merits, as opposed to the staffing chart, is how little the fix would have actually cost anyone. States are already required to identify which students were enrolled in a given school for at least 10 days, because that is the threshold used to determine who counts as chronically absent in the first place. GAO interviewed an outside expert on chronic absenteeism data who made the obvious point plainly, since states are already identifying and collecting these enrollment figures internally to comply with an existing requirement, reporting that same number to EDFacts, rather than the separate October 1 snapshot, would add minimal additional burden.

    This is not a case of the Department discovering a fix that would require new infrastructure, new surveys, or new cooperation from fifty-one state agencies that would rather not be bothered. The data was already sitting in state files. The only missing step was an internal decision, at the Department, to accept it as the new denominator and update the collection specification accordingly. That decision got made, reversed, and shelved, all inside about a year, and the reversal had nothing to do with the states.

    It is also worth noting what this same reorganization did not spare. The same Department that could not staff a straightforward denominator fix also suspended its consolidated monitoring of ESEA fiscal and programmatic requirements across all fifty one states in 2026, the subject of a separate finding in this same GAO report. These are not two unrelated cost-cutting decisions that happened to land in the same document. They are two downstream consequences of one upstream event, a reduction in force large enough to leave the agency unable to sustain either its oversight function or its data quality commitments, at the same time, in the same fiscal year. When an agency loses eighty five percent of a statistical office’s staff, it does not get to treat the resulting gaps as a series of isolated, defensible tradeoffs. It has one explanation, repeated in two different sections of the same audit.

    A Strategic Plan That Reads Differently in Hindsight

    The Department’s own Strategic Plan for fiscal years 2022 through 2026 identifies strengthening agencywide data governance as a stated goal, and names improving the quality of data collected from grantees and subrecipients as one of the strategies for getting there. GAO quotes this language back at the Department in its report, not unkindly, but not gently either. An agency does not get credit for a data governance strategy it wrote down and then failed to staff.

    The Department’s public defense of the current approach, offered in its formal response to GAO’s recommendations, does not mention the reduction in force at all. It says only that the Department has “chosen to continue working with currently reported EDFacts data elements, highlighting limitations as needed, rather than imposing additional reporting burden on states.” That framing casts the decision as a considered tradeoff between data quality and administrative burden. GAO’s own reporting elsewhere in the same document shows it was not a tradeoff at all. It was a project that started, ran into a staffing cliff, and stopped, and the public explanation retroactively describes the stopping point as a choice.

    There is a version of this story where an agency looks at its own reduced capacity, decides which existing commitments it can no longer keep, and says so plainly to Congress and the public. There is another version where the agency keeps the sentence about “highlighting limitations as needed” and quietly drops the sentence about staffing changes into an interview with an auditor, where it will only surface if someone reads a forty page report closely enough to notice the connection. The Department picked the second version. GAO just happened to be reading closely, and the version of events available to anyone who does not read forty page audit reports, meaning most parents, most school board members, and most of Congress, is still just the tidy line about choosing not to impose additional burden on states.

    Source: U.S. Government Accountability Office, K-12 Education: Actions to Improve Oversight of Key Federal Programs and Address High Chronic Absenteeism (GAO-26-107920, September 2026). Related: Eighteen Billion Dollars, and Nobody Assigned to Watch It and A Chronic Absenteeism Rate of 125 Percent Is Still an Official Federal Statistic.

  • HUD Arrested 491 Fugitives in Subsidized Housing. Its Own Audits Show How They Got There.

    The Department of Housing and Urban Development’s inspector general spent much of 2026 helping federal agents hunt fugitives living in federally assisted housing.

    By the time the nationwide effort was tallied, 491 people had been arrested.

    But the arrests raise a question considerably larger than the operation itself: How did so many wanted people wind up inside the federal housing-assistance system, and how did investigators find them after they were there?

    HUD’s Office of Inspector General announced Oct. 5 that its nationwide “Operation Clean House” had resulted in 491 arrests through a series of enforcement operations conducted with the U.S. Marshals Service and state and local law-enforcement agencies.

    The arrests included people wanted for offenses ranging from drug trafficking, weapons crimes and aggravated assault to rape, murder and child sex offenses. Authorities also seized 10 firearms.

    The national announcement, however, is only the final chapter of an enforcement campaign that unfolded city by city throughout 2026.

    And viewed alongside a series of HUD OIG audits released during the same period, Operation Clean House exposes an uncomfortable contrast inside the federal housing system: investigators proved remarkably capable of finding wanted fugitives after they were associated with federally assisted housing while auditors were simultaneously finding serious weaknesses in the systems intended to determine who should be receiving assistance in the first place.

    Building Operation Clean House

    Operation Clean House was not a single nationwide raid.

    Instead, HUD OIG worked with the U.S. Marshals Service and other agencies in a succession of local operations targeting fugitives connected to federally assisted housing.

    An early operation in Columbus, Ohio, targeted people with active felony warrants who were residing in government-subsidized housing. HUD OIG later reported that operations in Columbus and Minneapolis together resulted in 55 arrests of people residing in HUD-assisted housing.

    In Memphis, another operation resulted in 24 arrests. HUD OIG said the majority of those arrested were current HUD program participants who were taken into custody inside HUD housing.

    Kansas City followed with 40 arrests during a five-day operation targeting violent or repeat offenders associated with HUD-assisted properties or leaseholders.

    Philadelphia produced another 41 arrests of fugitives residing in federally subsidized properties.

    Then came Cleveland.

    During a two-week operation in September, authorities arrested 75 people. According to the U.S. Marshals Service, 68 were fugitives identified as using HUD housing. Seven additional people with outstanding felony warrants were encountered during the operation.

    That distinction matters.

    HUD OIG’s nationwide figure of 491 represents arrests resulting from Operation Clean House. It should not automatically be interpreted as 491 HUD beneficiaries who were illegally receiving housing assistance.

    The government’s own descriptions show that the population swept up by the operation was more complicated.

    But Cleveland also provides one of the clearest clues about what was happening behind the scenes.

    According to the Marshals Service, investigators worked with HUD OIG to “develop information about wanted fugitives living in HUD housing” before conducting the operation.

    Exactly how they developed that information remains unclear.

    The Other Half of the Story

    Six days before announcing the 491 arrests, HUD OIG released three audits examining tenant eligibility and related controls at major housing authorities in Washington, Chicago and Los Angeles.

    Together, HUD OIG said the audits identified more than $4.3 million in improper payments associated with deficiencies involving criminal-background screening, immigration verification and other eligibility controls. The finding extends a pattern this publication has tracked: The $1.4 Billion HUD Couldn’t Be Bothered to Count.

    The findings provide an illuminating backdrop to Operation Clean House.

    At the District of Columbia Housing Authority, auditors identified 17 lifetime registered sex offenders participating in housing programs. Thirteen, according to OIG, had been improperly admitted despite a mandatory federal prohibition.

    HUD paid more than $1.6 million in housing assistance associated with those 13 individuals.

    Auditors also identified 13 participants with ineligible immigration status who benefited from another $869,877 in assistance. Another 178 participants could not have their immigration status verified because of problems involving use of the federal Systematic Alien Verification for Entitlements, or SAVE, system.

    The problems were not confined to Washington.

    At the Housing Authority of the City of Los Angeles, HUD OIG examined a population of approximately 98,000 tenants and found at least $770,701 in housing assistance had been paid for 15 tenants subject to lifetime sex-offender registration requirements who were ineligible when they entered the programs.

    In Chicago, auditors found five lifetime registered sex offenders had been admitted to housing programs. OIG also found required criminal-background checks had not been conducted after admission for 14 of the 59 household members auditors reviewed.

    Taken together, the audits describe something considerably more consequential than isolated paperwork errors.

    They show weaknesses in the eligibility and screening machinery responsible for policing access to federally subsidized housing at the same time federal agents were conducting a nationwide campaign to locate fugitives within that system.

    Arrested Does Not Mean Ineligible

    There is an important distinction here.

    A criminal record does not automatically disqualify someone from receiving federal housing assistance, and the fact that someone was arrested during Operation Clean House does not establish that the person was improperly receiving benefits.

    HUD OIG itself examined the issue in a September report concerning criminal-activity requirements across federal rental-assistance programs.

    The rules vary depending on the program and circumstances. Some criminal conduct can result in discretionary eviction or denial of assistance, while federal law establishes mandatory restrictions in particular situations, including certain lifetime sex-offender registration requirements and methamphetamine-related offenses in federally assisted housing.

    That makes Operation Clean House more complicated than a simple story about criminals receiving taxpayer-funded housing.

    It also makes the unanswered questions more important.

    How many of the 491 people arrested were actual HUD beneficiaries?

    How many were authorized members of assisted households?

    How many were unauthorized occupants?

    How many were guests or other people simply located at HUD-assisted properties?

    How many arrests resulted in eligibility reviews?

    How many households subsequently lost assistance?

    How many cases uncovered false information, undisclosed household members, housing fraud or improper federal payments?

    The Oct. 5 announcement does not provide those figures.

    How Did HUD Find Them?

    There is another unanswered question buried underneath the entire operation.

    HUD OIG and the Marshals Service clearly possessed some mechanism for connecting wanted fugitives with federally assisted housing.

    The government has described the results without explaining much about the machinery that produced them.

    It is not clear from the publicly available records whether investigators compared fugitive or warrant databases against HUD beneficiary information, whether the Marshals Service supplied target lists that HUD OIG checked against housing records, whether individual public housing authorities performed searches, or whether investigators relied primarily on addresses and conventional fugitive investigations.

    Nor is it clear whether Operation Clean House represents a temporary enforcement initiative or an ongoing data-matching capability.

    The question is particularly relevant because HUD OIG has separately told Congress that it wants greater technological capability to analyze large datasets and identify fraud.

    In its fiscal 2027 budget justification, OIG described Operation Clean House among its enforcement efforts while also seeking resources for artificial-intelligence capabilities that could help investigators parse large datasets and identify fraud more efficiently.

    There is no public evidence establishing that artificial intelligence was used during Operation Clean House.

    But the documents point toward an inspector general increasingly interested in using large-scale data analysis as an investigative tool.

    That makes understanding exactly how Clean House identified its targets more than a matter of curiosity.

    A Successful Operation, and an Unfinished Accounting

    Measured purely by arrests, Operation Clean House was substantial.

    Nearly 500 people were taken into custody. Some were wanted for extremely serious crimes. Federal, state and local agencies cooperated across numerous cities, and dangerous fugitives were removed from communities.

    But HUD OIG itself has supplied the reason not to stop counting at 491.

    Its audits show that housing authorities have sometimes failed to conduct required background checks, admitted prohibited individuals and made millions of dollars in improper assistance payments.

    Operation Clean House demonstrated that federal investigators could find wanted fugitives connected to federally assisted housing.

    The audits raise the more uncomfortable question of why some people who should never have been admitted to housing programs were able to pass through the front door.

    And the government has yet to explain fully how many of the 491 arrests exposed failures in the housing system itself.

    For now, taxpayers have been given an arrest total.

    The program-integrity accounting is still missing.

    Sources

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  • A Chronic Absenteeism Rate of 125 Percent Is Still an Official Federal Statistic

    There are two kinds of numbers a federal agency can publish. There is the kind that is wrong because the world is complicated and measurement is hard. And there is the kind that is wrong because the agency built the measurement out of two pieces that were never designed to fit together, and kept publishing it anyway. The Department of Education’s chronic absenteeism rates, the only nationally comparable figures on how many American students are missing significant school, are the second kind. Some of them exceed one hundred percent. The Department knows this. It has known for a while. It has decided, as of this year, not to fix it.

    The Government Accountability Office’s review of Department data found implausible chronic absenteeism rates, meaning more students reported chronically absent than were recorded as enrolled, in roughly 2.5 percent of schools nationwide using 2022 to 2023 data, the most recent year available. That is GAO’s word, implausible, chosen with the sort of restraint auditors reserve for things that would otherwise require a stronger one.

    Two Clocks, One Number

    The mechanics are almost embarrassingly simple once laid out. To calculate a chronic absenteeism rate, the Department divides the number of students identified as chronically absent by the number of students enrolled. The chronically absent count is tallied over the entire school year, students who missed ten percent or more of the days they were enrolled, at any point, for any reason. The enrollment count, on the other hand, is captured on a single day, October 1, and never updated. A student who enrolls in November and racks up chronically absent status by May is counted in the numerator of a rate whose denominator was frozen months before that student ever showed up.

    In a stable school with a fixed roster, this barely matters. In a school where students are constantly moving in and out, it produces nonsense. GAO’s own illustrative example makes the point better than any explanation could. A school with 100 chronically absent students and 80 enrolled on October 1 reports a chronic absenteeism rate of 125 percent. Using the number of students who were actually enrolled for at least 10 days over the full year, the same school’s real rate is 66 percent, itself alarming, but at least a number that exists inside the bounds of arithmetic. Somewhere between those two figures sits the actual scale of a real problem, and the Department has chosen to publish the version that cannot possibly be correct.

    The Department’s own EDFacts documentation contains a data note warning users that rates calculated this way may be inflated. Which is one way of describing a nationally reported statistic that occasionally exceeds the maximum value a percentage is capable of holding.

    The Schools Where It Breaks Hardest

    The mismatch is not evenly distributed, and where it concentrates tells its own story. Schools identified for Comprehensive Support and Improvement, meaning the lowest performing schools in the country, the ones this data is supposed to help states target, had implausible rates in nearly 13 percent of cases, compared to about 2 percent for non-CSI schools. These are precisely the schools where students change addresses and schools most often, and precisely the schools where accurate absenteeism data would matter most for deciding where to send help.

    Shared-time schools fare even worse. These serve students who split their day between two buildings, often for career and technical education programs, and can end up double-counted as absent in one building while attending the other. More than 30 percent of shared-time schools had implausible rates, against under 2 percent everywhere else. The variation between states is its own indictment of data quality. Delaware, Idaho, Maryland, Missouri, North Carolina, and Rhode Island each report zero shared-time schools with implausible rates. Pennsylvania reports implausible rates in 62 of its 63 shared-time schools, 98 percent. States are not disagreeing about a close call here. They are simply not reporting the same phenomenon the same way, because nobody at the Department has told them how. Education, GAO notes dryly, provides states with guidance on how to report enrollment for shared-time students, but not on how to report their chronic absenteeism, an oversight nobody apparently noticed until an outside auditor went looking.

    A Known Limitation Is Still a Limitation

    In 2024, the Department began requiring states to report the number of students enrolled over the full school year, the same timeframe already used for the chronic absenteeism count, which would have let it calculate a rate that actually means what it claims to mean. It abandoned that effort before completion. GAO’s report ties the reversal to staffing reductions inside the Institute of Education Sciences, whose workforce fell by more than 85 percent between the end of 2024 and the end of 2025.

    In its formal response to GAO’s draft recommendation on this point, the Department did not dispute any of the math above. It disputed the need to change anything, writing that the mismatch is “a known limitation that is already documented,” and that it has chosen to keep working with the data elements it already collects rather than add reporting burden on states. GAO’s counter is worth sitting with, since states already have to identify which students were enrolled at least 10 days in order to calculate the chronically absent count required for EDFacts in the first place. The number the Department is declining to collect is a number states are already generating internally to comply with an existing requirement. The Department is not avoiding new work. It is avoiding one additional column in a spreadsheet the states are already filling out, and calling the result a documented limitation rather than an unfinished fix.

    Documenting a flaw is not the same as correcting it, and a data note buried in a technical appendix does not travel with the number once a school board, a state legislature, or a local reporter pulls it out to argue that a particular school is failing its students at a rate of 125 percent. The number will be believed. It just will not be true.

    Source: U.S. Government Accountability Office, K-12 Education: Actions to Improve Oversight of Key Federal Programs and Address High Chronic Absenteeism (GAO-26-107920, September 2026). Related: Eighteen Billion Dollars, and Nobody Assigned to Watch It, and The Department Started Fixing Its Data, Then Fired the People Fixing It.

  • New York’s Medicaid System Paid for 1,375 People Who Weren’t There to Receive It

    The Department of Health and Human Services Office of Inspector General has a specific bureaucratic talent, which is finding the exact place where a state government stopped paying attention. This month it found one in Albany.

    According to audit report OAS-25-02-074, New York’s Medicaid program made $7,551,670 in capitation payments, $6,164,734 of it the federal government’s share, to managed care organizations on behalf of 1,375 Medicaid enrollees who were, for the period in question, incarcerated in state prison.

    Every one of them. Not a sample that suggested a wider problem, not a statistical extrapolation dressed up as certainty.

    OIG reviewed all 1,375 incarcerated enrollees identified in the audit period and found unallowable payments attached to every single one. A capitation payment is a flat monthly fee the state pays an MCO per enrollee, regardless of whether that enrollee shows up for a checkup, a filling, or anything else, because the point of managed care is to buy access, not usage.

    Which means the payment keeps generating on autopilot long after the person it was meant to cover has been removed from the population it was meant to serve, unless somebody tells the system to stop. Nobody told the system to stop.

    The Machine That Forgot How to Check

    Federal law is not ambiguous about this. An inmate of a public institution can stay enrolled in Medicaid, but the federal government will not pick up the tab for managed care coverage while that person is locked up, full stop, with the single exception of inpatient care in an actual medical institution.

    New York’s own contracts with its MCOs say the same thing in plainer language, disenroll someone the moment the state learns they are in a Department of Corrections and Community Supervision facility, effective the first full month of incarceration.

    The mechanism that was supposed to catch this is a monthly match between DOCCS prison rosters and the Welfare Management System, cross referencing Social Security numbers, dates of birth, and names. It broke twice.

    First, New York built system overrides during the pandemic to preserve the continuous enrollment guarantee that came with an enhanced federal match, and those overrides apparently never learned that the incarceration exclusion was never part of the deal the continuous enrollment condition was suspending. The state kept people covered who were never supposed to be eligible for managed care reimbursement to begin with, pandemic rule or not.

    Second, and more damning for how mundane it is, the matching algorithm choked on typos. A missing suffix. An extra space in a last name. A transposed digit in a birth date. These are not sophisticated fraud vectors. They are the kind of clerical noise every large database in America generates by the hour, and New York’s system treated a formatting inconsistency as grounds to keep cutting checks.

    A State That Has Done This Dance Before

    What makes the New York report distinct from its predecessors in this same audit series is not the dollar figure, which is modest by federal standards, but the fact that this specific state has been down this specific road with startling regularity.

    In 2020, HHS-OIG found New York had made an estimated $23.3 million in capitation payments on behalf of Medicaid enrollees who were already dead, a population even less capable of using their benefits than an inmate.

    In 2021, a separate audit found New York owed roughly $9.3 million after paying more than one MCO for the same beneficiary in the same month because its systems couldn’t recognize that two Medicaid ID numbers belonged to a single human being.

    Three audits, three different failure modes, one common denominator: a state that pays managed care organizations by the head count and does not maintain a head count anyone can trust.

    Dead enrollees, duplicated enrollees, incarcerated enrollees, it hardly matters which population falls through, because the underlying defect is the same unmonitored pipe between eligibility data and payment data.

    New York’s own Office of the Medicaid Inspector General had already caught a version of this specific incarceration problem at a single managed care plan back in 2020, identifying more than $1.2 million in overpayments in an internal audit, which means the state’s own watchdog knew the pattern existed years before the federal one showed up with a spreadsheet covering the entire state.

    Ohio’s state auditor found roughly $101 million in improper capitation payments tied to incarcerated enrollees when it reviewed every payment made over three fiscal years, a wider net than New York’s audit, and a bigger number as a result.

    Illinois, audited under the same federal series as New York, sampled 100 incarcerated enrollees, found unallowable payments attached to 48 of them, and projected an estimated $9.5 million statewide. What separates New York’s report is the completeness of the miss. Illinois missed on roughly half its sample. New York missed on all of it.

    Somebody Will Get Around to Asking for the Money

    New York’s official response to the audit, filed by the Department of Health’s executive deputy commissioner, is a masterclass in saying quite a lot while committing to almost nothing. The state did not concur. It did not decline to concur.

    It described, at length, what it has done and what it might do, which in bureaucratic correspondence functions as a kind of grammatical tense reserved for actions that may never conjugate into the past.

    The state’s Office of the Medicaid Inspector General says it is analyzing the payments OIG identified to confirm the encounter data, after which it will pursue whatever the analysis supports, subject to the due process rights of the providers being asked to give the money back.

    This is not stonewalling exactly. It is closer to a promise to eventually check the math on somebody else’s math.

    On the systemic fix, New York’s answer is that the specific pandemic-era override problem should not recur, since the continuous enrollment mandate that necessitated it has expired, which is true and also beside the point, since the demographic mismatch problem that let typos slip incarcerated people past the filter has nothing to do with COVID rules and everything to do with a matching algorithm that has apparently never been asked to tolerate a hyphen. The state says it is exploring a manual review process for near misses. Exploring, in this context, is doing a great deal of work.

    OIG’s response, tucked at the end of the report, amounts to a shrug dressed in institutional language: we acknowledge the steps taken and planned, we still found the money missing, our recommendations stand. Which is the entire relationship between a federal inspector general and a state Medicaid agency in miniature.

    One side documents the leak with forensic precision. The other side describes, in the conditional mood, its intention to look for the bucket.

    Sources: HHS Office of Inspector General, New York Made Unallowable Managed Care Capitation Payments on Behalf of Incarcerated Medicaid Enrollees (OAS-25-02-074, 2026); HHS OIG, New York State Medicaid Capitation Payments After Beneficiaries’ Deaths (2020).

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  • Eighteen Billion Dollars, and Nobody Assigned to Watch It

    The Elementary and Secondary Education Act asks the Department of Education to do a great many things for the nation’s schoolchildren. Monitor how the money is spent is not, technically, one of them. Not with any specificity, anyway. Congress wrote a provision meant to improve oversight of ESEA funds that never actually orders the Department to monitor anyone, sets no required method, and specifies no frequency.

    It is the legislative equivalent of telling a teenager to “keep the house clean” and then being surprised, four years later, when the sink is a biohazard.

    The Government Accountability Office spent from November 2024 to September 2026 looking into how the Department watches over roughly twenty-seven billion dollars a year in K12 funding, ostensibly to examine chronic absenteeism policy. What it found along the way is a much bigger story than absent children.

    In 2026, the Department of Education suspended its most comprehensive monitoring strategy for ESEA programs entirely. Thirty two of fifty one states have not undergone consolidated monitoring since the Department fully implemented the strategy in 2019. Officials could not tell GAO when monitoring might resume, or what would replace it, or really much of anything, other than a promise that a 2027 monitoring plan is coming “in early fall 2026.”

    The Word That Isn’t in the Statute

    Consolidated monitoring was the Department’s flagship tool for checking whether states receiving ESEA money, the great majority of it flowing through Title I, were actually complying with fiscal and programmatic requirements. It is a broad, single streamlined review of key ESEA programs, the kind of audit that catches the boring, unglamorous compliance failures before they become the interesting, headline generating kind.

    GAO’s report is careful to note that the statute intended to strengthen this oversight does not “explicitly direct Education to monitor grantees,” nor does it set “specific requirements regarding the method or frequency of monitoring and oversight activities.” Officials told GAO, more or less accurately, that they have broad discretion in how they carry out oversight responsibilities and that nothing legally compels them to do it any particular way.

    This is the sort of statutory gap that exists in dozens of federal programs and rarely matters, because agencies tend to keep doing the thing they were doing regardless of whether a statute makes them do so. It matters here because the Department stopped anyway, and did so with no announced replacement, no interim safeguard, and no explanation beyond “developing plans for future monitoring activities.”

    Discretion is a wonderful thing to have written into law, right up until an agency uses it to simply not act.

    Title I, Part A alone accounted for over eighteen billion dollars of the roughly twenty seven billion in ESEA formula funding in fiscal year 2025, about two thirds of the total. GAO’s own prior work, cited in this report, has already flagged the decentralized structure of state administered programs like Title I as a fraud vulnerability.

    Suspending the primary mechanism for catching fiscal noncompliance in a decentralized, state administered, multibillion dollar program is not a small administrative housekeeping decision. It is the removal of the one instrument that was checking whether the money went where Congress said it should.

    Half the States, Half the Time, and Two Findings That Stuck

    Even before the 2026 suspension, the Department’s coverage was thinner than the “comprehensive” branding suggests. Of the thirty six states that chose to include chronic absenteeism as an indicator in their statewide accountability systems, only fourteen, under forty percent, had been monitored for compliance with the relevant indicator and support and improvement plan requirements since 2019.

    Two of those fourteen, Maryland and New Mexico, actually turned up violations. Maryland could not demonstrate that any of its school quality indicators, including chronic absenteeism, meaningfully differentiated performance among schools, and New Mexico was not ensuring its support and improvement plans were informed by the chronic absenteeism indicator at all, as required.

    Maryland has since fixed its paperwork. New Mexico, as of this report, has not.

    Separately, on the more universal chronic absenteeism reporting requirements that apply to every state regardless of accountability system choice, the Department monitored twenty six of fifty one states between 2019 and 2025, and found missing required data in seven of them (Idaho, Mississippi, Nebraska, New Hampshire, Texas, Vermont, and Washington).

    When GAO independently reviewed the 2025 report cards of those same seven states, meaning after the Department’s corrective actions were supposed to have taken effect, it still could not find required chronic absenteeism data on one state’s report card and could not find state level subgroup data on another. The corrective action, in other words, did not fully correct.

    None of this is presented by GAO as scandalous in itself. Monitoring programs find problems; that is the point of monitoring programs. What is scandalous, or at least deeply irresponsible, is stopping the monitoring right as the backlog of unresolved findings was still being worked through, and doing so for a reason no more specific than institutional reorganization.

    Congress Gets to Own This One Too

    GAO’s response to all this is characteristically restrained. It is making three recommendations to the Department, resume comprehensive monitoring, fix a data reliability problem in how chronic absenteeism rates are calculated, and issue guidance for shared time schools.

    One “matter for congressional consideration” is asking lawmakers to consider “clearly articulating ESEA monitoring requirements” so that the next Department that finds itself with unlimited discretion and limited enthusiasm cannot simply decline to use it.

    The Department’s own written response, reproduced in the report, disagreed with the recommendation to resume monitoring, insisting it never stopped overseeing states at all and that consolidated monitoring is only “one aspect” of its work, citing more than one hundred other monitoring and oversight activities carried out since 2019.

    GAO’s rebuttal, delivered with the flat patience of an auditor who has heard this argument before, notes that the alternative activities described are “limited in scope” and “substantively different than systematically assessing compliance with ESEA requirements more broadly.”

    Translated out of GAO diplomacy, that reads as yes, you did some things; no, they were not the thing that was suspended; and no, a promised 2027 plan does not retroactively cover the eighteen months in between.

    Congress wrote itself an escape hatch on oversight language decades ago, confident, presumably, that no administration would ever actually walk through it. The Individuals with Disabilities Education Act and the Child Care and Development Block Grant program both contain explicit, mandatory monitoring requirements, proof that Congress knows perfectly well how to write a statute that does not leave this to agency discretion.

    ESEA does not have that language, and now it has a live demonstration of exactly what that omission costs. Eighteen billion dollars, and for the moment, nobody assigned to watch it.

    Source: U.S. Government Accountability Office, K-12 Education: Actions to Improve Oversight of Key Federal Programs and Address High Chronic Absenteeism (GAO-26-107920, September 2026). Related: A Chronic Absenteeism Rate of 125 Percent Is Still an Official Federal Statistic and The Department Started Fixing Its Data, Then Fired the People Fixing It.

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