KEMETIC MINDS SPECIAL REPORT
Health & Policy | August 6, 2026
Emergency rooms nationwide are seeing more patients and holding them longer than at any point in three decades of federal tracking — but the crisis does not look the same in every state. In the ten states that have declined to adopt the Affordable Care Act’s Medicaid expansion — Alabama, Florida, Georgia, Kansas, Mississippi, South Carolina, Tennessee, Texas, Wisconsin, and Wyoming, all Republican-controlled — the defining problem is not that the ER down the street is slower. It is that, for a growing number of rural communities, there is no ER down the street left to visit. This report walks through 30 years of federal emergency-care data, shows exactly where the crisis is concentrated, reports an honest and sometimes counterintuitive finding about in-hospital wait times, and lays out concrete, sourced paths toward fixing it.

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Thirty Years of Growing Strain
Emergency department visits nationwide climbed from an estimated 90.3 million in 1996 to 145.6 million in 2016 — a 61.2% increase in two decades, far outpacing U.S. population growth over the same period — and the most recent CDC estimate puts annual visits at 155.4 million[1]. Wait times climbed alongside volume: a peer-reviewed analysis of federal survey data found the average wait to see an ED physician rose 4.1% per year between 1997 and 2004, with waits for patients having a heart attack rising even faster, at 11.2% per year[2]. On a more recent, methodologically comparable measure, the national median time a patient spends in the ED before leaving rose from about 138 minutes in 2014 to roughly 160–163 minutes in 2022–2024, before ticking down slightly to 161 minutes in the 12 months ending June 2025[3].
Figure 2
Three Decades of Emergency Department Strain: National Visit Volume vs. Median Time in the ED, 1996–2025
Hover any point for detail. Wait-time series begins in 2014 (comparable CMS/NHAMCS methodology); 1997-2004 saw a separately documented +4.1%/year rise not shown on this axis.
Chart: Kemetic Minds. Sources: CDC/NCHS Emergency Department Fast Facts; CMS Timely and Effective Care national data.
None of this is an abstraction to the people living it. In a 2025 national poll, 43% of U.S. adults said they would delay or avoid emergency care specifically because of concerns about boarding — being held in the ED, often for hours, after a decision has been made to admit them — and 44% said they or a loved one had personally experienced a prolonged wait for an inpatient bed, with 16% of those reporting a wait of 13 hours or more[4].
Where the Crisis Actually Concentrates: Closures, Not Speed
The Cecil G. Sheps Center at the University of North Carolina, the nation’s most cited tracker of this data, counts 197 rural hospital closures or conversions to non-inpatient facilities since 2005 — 109 complete closures and 88 conversions, totaling 6,782 lost beds[5]. The distribution across states is sharply uneven, and it lines up closely with a single, objective, and easily verified policy line: whether a state adopted the ACA’s Medicaid expansion.
The ten states that have not adopted the expansion — Alabama, Florida, Georgia, Kansas, Mississippi, South Carolina, Tennessee, Texas, Wisconsin, and Wyoming[6] — account for 87 of the 197 closures nationwide, or 44%, despite being just one-fifth of all states. Texas alone has lost 22 rural hospitals since 2005, more than any other state in the country[5].
Figure 1
Rural Hospital Closures and Conversions Since 2005, by State (Top 11)
Hover any bar for detail. Scroll to zoom, drag to pan.
Chart: Kemetic Minds. Source: Cecil G. Sheps Center for Health Services Research, UNC (2026), data current as of December 2025.
The mechanism is not mysterious. Hospitals in non-expansion states absorb more uncompensated care because more of their patients are uninsured: the uninsured rate in non-expansion states is 14.5%, nearly double the 8.0% rate in expansion states, and 42% of the nation’s non-elderly uninsured population lives in just those ten states[7]. A rural hospital running on thin margins loses that math fastest, and an emergency department cannot exist without the hospital attached to it.
The Honest, Counterintuitive Finding
It would be tempting to assume the ERs that remain open in these ten states are also the slowest. The current CMS “Timely and Effective Care” data does not support that. Averaged across the ten non-expansion states, the median time a patient spends in the ED is 151.2 minutes, versus 169.9 minutes in the 41 expansion states and Washington, D.C. The share of patients who leave without being seen — a marker of overcrowding severe enough that people give up and go home — is also slightly lower in non-expansion states (1.9%) than in expansion states (2.3%)[3].
Figure 3
Among Hospitals Still Open: In-ED Speed Is Not Worse in Non-Expansion States
CMS “Timely and Effective Care” state averages, most recent 12-month reporting period. Hover for exact values.
Chart: Kemetic Minds. Source: Centers for Medicare & Medicaid Services, Timely and Effective Care — State dataset (measures OP-18a, OP-22).
This is not evidence that non-expansion states have solved anything. It is evidence that the two problems are different problems. In states with dense, high-demand urban hospital systems (Maryland tops the country at 250 minutes; Washington, D.C. at 5 hours 29 minutes), the crisis shows up as in-building throughput — overcrowded EDs that cannot move admitted patients upstairs fast enough[3]. In many non-expansion states, particularly their rural counties, the crisis shows up earlier in the pipeline: whether an ED exists to drive to at all. A shorter median wait time at a hospital 45 minutes farther away than the one that used to be down the road is not an improvement for the patient having a heart attack in the car.
What Losing the ER Actually Costs
The research on what happens after a rural hospital closes is more mixed than either side of this debate typically admits, and reporting that honestly matters more than picking the more dramatic number. An earlier, widely cited study of 92 California hospital closures between 1995 and 2011 found rural closures raised inpatient mortality by 5.9% overall, with mortality for stroke patients rising 3.1% and for heart-attack patients rising 4.5% — effects that were larger still for Medicaid patients and racial minorities[8]. A more recent, larger national study using Medicare data on 2013–2020 closures found no statistically significant change in 30-day mortality or average travel distance following a closure, but did find hospitalization rates rose by roughly 112 additional admissions per quarter per 10,000 older beneficiaries in affected counties — consistent with patients traveling farther, but to functioning alternative hospitals rather than going without care[9].
Read together, the fairest conclusion is that a rural hospital closure is a serious, disruptive event whose worst-case outcomes (delayed treatment for a stroke or heart attack, where minutes decide survival) are well documented in at least one rigorous dataset, even where the average, population-wide mortality effect is harder to detect nationally. The risk is not evenly distributed: it falls hardest on whichever patient’s 20-minute drive becomes a 60-minute drive on the specific day their condition cannot wait.
Finding Solutions
- Medicaid expansion is the single most direct lever on the table. It is the policy variable most closely tied to the closure gap in this data; state legislatures and ballot initiatives in the ten remaining non-expansion states are the concrete, trackable place this changes.
- Rural Emergency Hospital (REH) conversion is a federal designation, created in 2023, that lets a struggling rural hospital keep operating a 24/7 emergency department and outpatient services while giving up inpatient beds it can no longer sustain — a middle path between full closure and full operation that community leaders and hospital boards can request today.
- Support state-level “ED boarding” transparency rules. CMS’s new Emergency Care Access and Timeliness measure, finalized for 2026 hospital reporting, is a direct result of public and advocacy pressure — continued pressure at the state level can extend similar reporting to hospitals CMS doesn’t cover.
- Know your nearest actual ED before you need it. The Sheps Center’s rural closure map is public and searchable by county — check it now, not during an emergency, especially if you live more than 20 minutes from the nearest hospital.
- Push for telehealth and mobile-integrated health investment. Paramedicine and virtual urgent-care triage programs cannot replace a physical ED for trauma, but they measurably reduce unnecessary ED trips for the non-emergency visits that also crowd out urgent ones.
- Contact your member of Congress about EMS and rural health funding specifically — 93% of U.S. adults call emergency medical services essential and 89% favor more government funding for EDs, paramedics, and EMS, which is about as close to bipartisan consensus as health policy gets right now[4].
Kemetic Minds Analysis
The most useful thing this data does is correct a lazy version of the story before it spreads. Emergency care in non-expansion states is not simply “worse” in every measurable way — on raw in-building speed, it is currently a bit better on average. What is worse, sharply and verifiably worse, is access: whether an emergency room exists within a reasonable drive at all. That distinction matters because it points to a different, more specific fix. Throughput problems in dense expansion-state hospitals need staffing, bed capacity, and boarding-transparency solutions. The rural closure crisis concentrated in non-expansion states needs the coverage-and-reimbursement fix that keeps a thin-margin rural ED’s doors open in the first place. Thirty years of data point in the same direction on that second problem: uninsured patients and uncompensated care are the specific pressure that closes rural EDs, and Medicaid expansion is the specific policy that has been shown, repeatedly, to relieve it.
References
- National Center for Health Statistics. (2026). Emergency department visits. Centers for Disease Control and Prevention. cdc.gov ↩
- Wilper, A. P., Woolhandler, S., Lasser, K. E., McCormick, D., Cutrona, S. L., Bor, D. H., & Himmelstein, D. U. (2008). Waits to see an emergency department physician: U.S. trends and predictors, 1997–2004. Health Affairs, 27(Suppl 1), w84–w95. healthaffairs.org ↩
- Centers for Medicare & Medicaid Services. (2026). Timely and effective care — state [Data set]. data.cms.gov ↩a ↩b ↩c
- American College of Emergency Physicians. (2025). New poll: Alarming number of patients would avoid emergency care because of boarding concerns. acep.org ↩a ↩b
- Cecil G. Sheps Center for Health Services Research, University of North Carolina at Chapel Hill. (2026). Rural hospital closures. shepscenter.unc.edu ↩a ↩b
- KFF. (2026). Status of state Medicaid expansion decisions. kff.org ↩
- KFF. (2025). Key facts about the uninsured population. kff.org ↩
- Gujral, K., & Basu, A. (2019). Impact of rural and urban hospital closures on inpatient mortality (NBER Working Paper No. 26182). National Bureau of Economic Research. nber.org ↩
- Hoffman, G. J., Ha, J., Fan, Z., & Li, J. (2025). Associations between rural hospital closures and acute and post-acute care access and outcomes. Health Services Research, 60(3), e14426. doi.org/10.1111/1475-6773.14426 ↩
Methodology: “Non-expansion states” is used throughout as an objective, verifiable proxy for “red states” — all ten are currently Republican-controlled and voted Republican in the most recent presidential election, and Medicaid-expansion status is a matter of public record, not characterization. Rural closure counts and the state breakdown are sourced directly from the Sheps Center’s public closures database (updated December 2025). CMS wait-time and left-without-being-seen figures are pulled directly from the CMS “Timely and Effective Care — State” public dataset (most recent release). ED visit volume and 1997–2004 wait-time growth figures are drawn from CDC/NCHS and a peer-reviewed Health Affairs analysis, respectively. Mortality-impact findings from two studies with different data, geography, and time periods are both reported, including where they disagree, rather than citing only the more dramatic figure. No figures were estimated or sourced from Wikipedia.
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