Part I — Situation overview

The state of Hungarian healthcare moved to the top of both the professional and the political agenda at the end of May 2026. At a Budapest professional conference the new healthcare state secretary, Lívia Ilku, put it this way: the new healthcare institutional system must be built in parallel with managing the crisis already under way — “we are building the ministry brick by brick, this is a time-consuming task, we ask for patience”. The state secretary held out the prospect of reviving professional-financing institutions modelled on the former standalone medicines agency and health-insurance fund (the old OGYI and OEP), and of an open partnership with the sector. At the same forum the president of the Hungarian Medical Chamber (MOK — the doctors’ mandatory professional body), Péter Álmos, put it more sharply: the system is already on the brink of collapse, and so primary care needs strengthening, health-worker pay needs settling, and the unsustainable hospital structure needs immediate transformation. In the chamber president’s vivid image: “while the house is being built, the roof is on fire”.

The dispute really sharpened around a single sentence: according to the MOK president, there are hospitals that ought to be closed, because the current structure is untenable. This statement immediately brought to the surface the old, false dilemma — “hospital closure” versus “keep everything” — while in the background real, structural tensions accumulate: the nurse shortage, the system that became “top-heavy” after the 2023 doctors’ pay rise, and, in the background, the difficulties in blood-product supply flagged by ATV. The situation is aggravated by the fact that the new healthcare ministry is itself only now being built — its leadership is managing the crisis of the functioning system and the institutional rebuilding at the same time.

In MIAK’s reading, the character of the problem is not whether we should close a hospital, but whether we have the courage to decide on the basis of data where there is a genuine need for inpatient capacity, and where strong primary care is the better answer. “Closure” and “keep everything” are equally political slogans; the policy question is the evidence-based rearrangement of capacity — in such a way that the retention of the nursing workforce is not harmed in the process, because that is precisely the weakest link in the system.

Part II — Literature audit

Before turning to MIAK’s concrete proposals, it is worth fixing the evidence framework in which the capacity and workforce question can be interpreted. The European Observatory on Health Systems’ summary titled Policy Brief 66 — by Greenley, Linda Aiken (American nursing researcher, professor at the University of Pennsylvania, leading researcher of the link between the nurse/patient ratio and patient safety), Sermeus and Martin McKee — shows that a fall in the share of registered nurses directly increases patients’ mortality risk; this is the gravest consequence of the system’s “top-heaviness”. The OECD report Health at a Glance — Europe 2024 gives the scale of the problem: the EU struggles with a shortage of 1.2 million doctors, nurses and midwives, and a resilient healthcare system requires additional investment equivalent to about 0.6% of gross domestic product (GDP). The WHO’s European Health Report 2024 fixes the patient-side stake: in some member states more than 20% of households face catastrophically high health expenditure. The detailed literature treatment — by author, with quotations — can be found in section 6.4 Literature in detail.

Part III — MIAK’s concrete proposal

MIAK proposes three measurable measures that, instead of the hospital-closure dispute, build on the parallel treatment of structure and workforce.

3.1 Evidence-based capacity review — reorganisation instead of closure (within 12 months)

The question of inpatient capacity must be decided not by a political slogan, but by data. MIAK proposes a capacity review carried out institution by institution by an independent, professional body, which on the basis of care volume, quality indicators (complication and readmission rates) and geographical access establishes where there is a genuine need for active inpatient care, and where strong primary care (GP, outpatient specialist clinic) is the better solution. This is not a “closure list”, but a re-allocation: the freed-up resource is turned to strengthening primary care and the emergency system. Within the framework of E3 (waiting-list transparency), the review must rest on real-time, public waiting-list data, so that the patient can see where the queue is shorter.

3.2 Nurse-retention package — strengthening the weakest link (over 3 years, in stages)

The system’s “top-heaviness” stems from the lag in the pay of nurses and health workers after the 2023 doctors’ pay rise. MIAK proposes the introduction of the E6 (nurse-retention package): raising the nursing minimum wage to 65% of the medical minimum wage over three years, a clinical career path (not only managerial advancement), professional autonomy and a burnout-prevention programme. According to the Aiken evidence (see 6.4.1) this is not “welfare spending”, but a patient-safety intervention: an adequate nurse/patient ratio directly reduces hospital mortality. The package raises expenditure in the short run, but with improving retention and the easing of doctors’ overload it is fiscally neutral or positive in the medium term.

3.3 Strong primary care and a digital backbone (in the first half of the government cycle)

The key to a lasting easing of hospital pressure is the strengthening of primary care: filling GP practices and building up prevention and chronic-disease care reduces the need for hospital admission. This is supported by E2 (a unified digital healthcare system) and E1 (AI-supported diagnostics): interoperable patient data reduces duplicated examinations, and diagnostic-imaging AI frees up scarce specialist capacity. Strengthening primary care is at the same time the only intervention that substantially reduces access inequality — the difference in care according to place of residence.

The shared principle of the three proposals is that the healthcare turnaround is not a single dramatic decision (closure or lifeline), but a coherent, data-driven transition: capacity must be kept where it is needed, the workforce must be retained, and primary care must be built up. According to the evidence of Policy Brief 66, structure and workforce cannot be separated — any transformation of the hospital structure is safe only if the nurse/patient ratio improves, not worsens.

Part IV — Expected impacts and risks

Dimension Expected impact Risk
Economy / financing Nurse pay settlement (~HUF 80–100 billion/year) pays off in the medium term with improving retention; AI and the digital system reduce duplication Pay settlement raises expenditure in the short run; the return materialises only over several years
Society Shortening waiting lists, better access, declining outflow of nurses A misreading of “hospital closure” may breed local protest and fears over the security of care
Healthcare system The evidence-based rearrangement of the structure gives more resilient, patient-safer care If reorganisation happens before workforce retention, the nurse/patient ratio may worsen and mortality risk may rise

The main dilemma lies in the order of the reorganisation. If the capacity review precedes the strengthening of the workforce, the system loses stability at exactly the worst moment — according to the Aiken evidence, a worsening nurse/patient ratio is a direct mortality risk. This is why MIAK proposes a parallel — indeed, a workforce-retention-first — sequencing: first retention, then allocation. The proposal tips to the risk side if politics chooses the swift, spectacular step of “closure” instead of the slow but sustainable transition — or if, because of the financing constraint, the pay settlement is left undone, and the “we ask for patience” rhetoric becomes a lasting postponement.

Part V — Measurability and summary

5.1 What is worth tracking? (suggested KPIs)

MIAK proposes tracking the following performance indicators (KPIs, in English: Key Performance Indicator) — in 12–24 months these will show whether the turnaround is real:

  • whether the annual rate of nurse outflow falls (target: halved by 2030), and whether the nurses-per-10,000-population ratio rises from the current ~64 toward the EU average (85);
  • whether the share of waiting lists longer than 30 days falls, and whether oncological care begins within 14 days of diagnosis in a growing share of cases;
  • the fill rate of primary care (GP practices) — whether the number of unfilled districts falls;
  • whether the amenable-mortality indicator approaches the EU average.

We stress: these are suggested measurement points that are worth tracking — not government commitments.

5.2 Summary

MIAK’s message to the decision-maker: the “hospital closure vs. keep everything” pseudo-debate must be closed, and in its place the evidence-based rearrangement of capacity, nurse retention and strong primary care must be launched in parallel — putting workforce strengthening first. The request to the public is that we hold to account not the dramatic one-sentence statements, but the measurable results (nurse outflow, waiting lists, primary-care fill rates).

This topic moves two MIAK foundational values. Data-drivenness is concerned because capacity decisions must be taken on the basis of care and quality data, not ideological slogans — otherwise politics chooses the spectacular but harmful step. And universal representation, because strong primary care and equality of access are the only way to ensure that place of residence does not decide who gets good care — healthcare equity is for MIAK not a slogan, but a measurable goal.

Part VI — Justifications and further sources

6.1 Press framing by spectrum

The economic press (Portfolio) highlighted the dual task: building the new institutional system and simultaneously managing the crisis under way, contrasting the state secretary’s and the chamber’s positions. The public-affairs band (24.hu, HVG) emphasised the human and institutional drama — HVG put the chamber president’s “while the house is being built, the roof is on fire” image into its headline, 24.hu the transformation of the governance system. The pro-government conservative band (Mandiner) chose as its frame the continuous, “I have been saying it for years” warning and the dramatic situation picture. ATV directed attention to a concrete, rarely discussed detail, the difficulties in blood-product supply. Across the whole spectrum it is common that no band disputes the fact of the crisis — the difference is in the framing of responsibility and solution; in MIAK’s data-driven reading the solution is not rhetorical, but structural.

6.2 Facts and data

  • According to the OECD’s estimate, the EU struggled with a shortage of 1.2 million doctors, nurses and midwives in 2022.
  • The additional investment needed for a resilient healthcare system is, according to the OECD, about 0.6% of GDP on the EU average compared with the pre-pandemic level.
  • The Hungarian nurses-per-10,000-population ratio is about 64, against the 85 EU average.
  • According to the Aiken European study, a 10% fall in the share of registered nurses increases the odds of patient death by ~11%.
  • According to the WHO, in some member states more than 20% of households face catastrophically high health expenditure.

6.3 Policy aspects

  • Healthcare (programme points) — nurse retention, waiting-list transparency, digital system, AI diagnostics;
  • Employment policy (background material) — the retention of the healthcare workforce and the health-worker career path;
  • Economy (background material) — the sustainability of healthcare financing and the return on investment.

6.4 Literature in detail

6.4.1 Linda Aiken and co-authors: Strengthening Europe’s Nursing Workforce

The European Observatory on Health Systems’ publication titled Policy Brief 66 systematises the patient-safety consequences of the nurse shortage. The key finding from a study covering six European countries: “every 10% decrease in the share of registered nurses was associated with an 11% increase in the odds of patient death” — and it did not matter whether the decrease was caused by cutting headcount or by adding non-registered workers. A higher share of registered nurses was, in addition, associated with greater patient satisfaction, lower burnout and less job dissatisfaction. In the Hungarian situation this means: any transformation of the hospital structure is safe only if the nurse/patient ratio improves in the process — the retention package is therefore not a social question, but a precondition of patient safety.

📖 Source: Greenley, Aiken, Sermeus, McKee: Strengthening Europe’s Nursing Workforce — Strategies for Retention (Policy Brief 66, European Observatory, 2024)

6.4.2 OECD: Health at a Glance: Europe 2024

The OECD report gives the scale of the structural challenge: “The EU faces a healthcare workforce shortage, with an estimated 1.2 million doctors, nurses and midwives missing in 2022.” According to the report the shortage is the joint effect of demographic ageing and difficult working conditions — burnout, retention difficulties — and requires intervention on three fronts: expanding training capacity, improving working conditions, and the productivity-raising application of innovation (digitalisation, AI). The OECD specially stresses: the 0.6% GDP investment needed for a resilient system “is dwarfed by the economic and social cost of fragile and understaffed healthcare systems”. The Hungarian turnaround plan must address precisely these three fronts at once.

📖 Source: OECD: Health at a Glance: Europe 2024

6.4.3 WHO: European Health Report 2024

The report of the WHO European Region fixes the patient-side stake: “Health systems are under enormous pressure, while health and care workers experience unprecedented challenges.” According to the report these tensions hold back progress toward universal health coverage, and in some member states more than 20% of households are forced to give up other basic needs — housing, heating, education — because of health expenditure. In the Hungarian context this is a warning: the structural transformation cannot come at the expense of access and financial protection — the yardstick of the reform is, ultimately, whether the patient gets care in time and affordably.

📖 Source: WHO: European Health Report 2024

6.5 International comparison

There are several established European models for handling the capacity and workforce question. Denmark, with its “free hospital choice” system (if the waiting time exceeds 30 days, the patient is entitled to private or foreign care with state financing), cut waiting lists by about 40% over five years — a combination of transparency and choice. In nurse retention, the American and Irish Magnet® hospitals (an accreditation model built on professional autonomy and participatory decision-making) show measurably better retention rates and lower risk-adjusted mortality. These models cannot be imported without modification, but they prove: the nurse/patient ratio and the waiting list are not a “natural given”, but a function of a policy decision.

Healthcare

  • E6 — Nurse-retention package
  • E3 — Waiting-list transparency
  • E2 — Digital healthcare system
  • E1 — AI-supported diagnostics

6.7 Source register

Press sources (MIAK press monitor, 29 May 2026 — topic 2):

Knowledge-base references (literature):

  • 📖 Greenley, Aiken, Sermeus, McKee: Strengthening Europe’s Nursing Workforce — Strategies for Retention (Policy Brief 66)
  • 📖 OECD: Health at a Glance: Europe 2024
  • 📖 WHO: European Health Report 2024

Note: the visible text of the blog does not show the books’ local file path — only the author and title.

MIAK internal materials:

  • MIAK policy area: Healthcare (programme points; programme point ID: E6)
  • MIAK policy area: Employment policy (background material)
  • MIAK policy area: Economy (background material)
  • MIAK press monitor, 29 May 2026 — topic 2, score: 85/100

Additional public data sources:

  • KSH (Hungarian Central Statistical Office) health statistics, NEAK capacity data, OECD Health Statistics 2025

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