Suomeksi

Mechanism Test: HE 38/2025 — Welfare Region Funding

Elias Kunnas

Subject: Government bill HE 38/2025 — Amendment to the Act on the Funding of Welfare Regions (Finnish). HE = hallituksen esitys, government bill.
Date: 2 March 2026
Status: Passed (Committee report HaVM 17/2025)
Classification: Pre-enactment audit (premortem). Funding changes apply to 2026–2027.

Context for international readers

In 2023, Finland transferred healthcare, social services, and rescue services from 309 municipalities to 21 welfare regions (hyvinvointialue, HVA). These regions have constitutional service obligations (§19 of the Finnish Constitution) but no taxing authority — all funding comes from central government via a formula. The regions serve 5.6 million people with an annual budget of approximately €27 billion.

HE 38/2025 modifies the funding formula. This mechanism test evaluates whether the formula changes produce their stated outcomes when actors respond rationally to the incentives created.

Note: Bill excerpts throughout are translated from Finnish. Original text is available in Finnish.

The bill in its own words

This tab contains only the government bill's own statements and those of institutional respondents. No original analysis.

Stated objectives

The proposed changes aim, in accordance with the government programme of Prime Minister Petteri Orpo, to incentivize welfare regions to promote residents' health and wellbeing. The proposed modifications to the region-specific funding determinants also aim to improve the targeting of funding while safeguarding the preconditions for organizing services, and to increase the predictability of funding.

— HE 38/2025, Main content
Original bill text (translated from Finnish)

The bill proposes amending the Act on the Funding of Welfare Regions. The purpose of the amendments would be, in accordance with the government programme of Prime Minister Petteri Orpo, to incentivize welfare regions to promote residents' wellbeing and health. The proposed changes to welfare region-specific funding determinants would also aim to improve the targeting of funding while safeguarding the preconditions for organizing services, and to increase the predictability of funding. Additionally, the bill would implement one-off savings measures concerning transition adjustments as outlined in the public finances plan.

— HE 38/2025, Main content (Esityksen pääasiallinen sisältö)

The bill makes four changes:

  1. Health promotion funding increase: The share of funding allocated to health and wellbeing promotion rises from ~1% to 1.5%. This is deducted half from the per-capita component and half from the needs-based component.
  2. Sector weight update: Healthcare weight decreases by 3.6 percentage points; social services increases by 2.1 and elderly care by 1.5. Based on 2023 actual costs (§13(3)).
  3. Two-year average: Service need coefficients are calculated as a two-year average instead of a single year (§14(3)).
  4. Transition adjustment cuts: One-off savings of €15M (2026) and €20M (2027), targeted at regions whose funding is not at risk (§39). In practice, this targets only Helsinki.
Original bill text on transition adjustments (translated from Finnish)

"To implement the savings outlined in the public finances plan, transition adjustments would be temporarily cut in 2026 and 2027. The temporary amendment would affect only those welfare regions receiving transition adjustment supplements whose reduction would not endanger sufficient funding for organizing statutory services, taking into account the amount of calculated funding allocated to the region through retrospective adjustment and the realized costs according to financial statements. For these regions, the phasing of the transition adjustment supplement that equalizes the difference between 2022 municipal costs and the region's calculated funding would be changed by €24 per resident in 2026 and €30 per resident in 2027."

— HE 38/2025, Esityksen pääasiallinen sisältö (Main content)

The bill's own impact assessment

Assessed at the national level, the magnitude of the proposed fiscal savings is quite small relative to the level of welfare region funding. For example, the proposed cut of €15 million for 2026 is 0.1% of the approximately €27 billion in funding for that year.

— HE 38/2025, Constitutional assessment

Regions thus compete with each other, and the outcome is a so-called zero-sum game, because the funding distributed on the basis of this criterion does not increase at the national level, even if all regions perform better.

— HE 38/2025, §15 detailed rationale
Original bill text (translated from Finnish)

"In scoring the indicators, a region's points are affected not only by changes in that region's own indicators, but also by how the situation changes relative to other regions. Regions thus compete with each other, and the outcome is a so-called zero-sum game (nollasummapeli), because the funding distributed on the basis of this criterion does not increase at the national level, even if all regions perform better. This basic principle is included in the current funding regulation."

— HE 38/2025, §15 säännöskohtaiset perustelut (detailed rationale)

The changes in funding between 2024 and 2025 proved to be quite large. From the perspective of funding stability and predictability, large changes are problematic.

— HE 38/2025, §14 detailed rationale

Institutional statements

Public consultation 27 Jan — 7 Mar 2025. Statements requested from welfare regions, City of Helsinki, HUS Group, Ministry of Social Affairs and Health, Ministry of the Interior, THL (National Institute for Health and Welfare), Statistics Finland, National Land Survey, and Hyvil Oy.

THL (on transition adjustments):

The proposed model does not incentivize producing a surplus in the future, is unpredictable, and breaks agreed-upon rules.

— THL statement, HE 38/2025 p. 67

City of Helsinki and HUS Group (on transition adjustments):

The financial position of regions should not be used as a basis for cutting funding. The proposed targeting method does not incentivize regions to aim for a balanced result. The proposal significantly complicates financial management and erodes general trust in the functionality and fairness of the funding system.

— City of Helsinki statement

Western Uusimaa Welfare Region:

The proposal undermines trust in the stability of the funding model and the principle of predictability and technical calculation methodology.

— Western Uusimaa welfare region statement

Pirkanmaa Welfare Region:

Rather than one-off cuts, the funding mechanism itself should be changed if it is found that funding allocation is not equitable.

— Pirkanmaa welfare region statement

Helsinki and Vantaa-Kerava (on health promotion coefficient):

Absolute figures should be used, because particularly for some indicators, examining relative differences means that the work done by regions may not affect funding, since structural differences between regions are so large.

— Joint statement by City of Helsinki and Vantaa-Kerava welfare region

Rescue services risk coefficient (multiple respondents):

Due to inadequate impact assessment, it is impossible to take a position on whether the changes to funding criteria are justified in their effects.

— Multiple respondents, HE 38/2025

Administrative Committee report (HaVM 17/2025): The responsible committee's report.

Constitutional Committee precedents

The Constitutional Law Committee has held that budget constraints cannot be used to restrict the availability of statutory services.

— PeVL 26/2017, p. 22

The sufficiency of state funding and its correct targeting are in a decisive position in safeguarding the proper performance of tasks assigned to welfare regions.

— PeVL 15/2018, p. 21

Note: The Constitutional Law Committee emphasizes both the funding principle (the state's obligation to secure regional funding) and equality (funding allocation must correspond to service needs). These two requirements can be in tension with each other.

The bill's own concessions

  • The health promotion coefficient's data foundation is incomplete: "At this stage, regions still have, among other things, differences in recording practices and data delivery arising from information systems." The bill acknowledges that the coefficient's data foundation is not yet reliable.
  • The health promotion coefficient is a zero-sum game: The bill itself states that health promotion funding "is a so-called zero-sum game, because the funding distributed on the basis of this criterion does not increase at the national level, even if all regions perform better."
  • The transition adjustment cut targets essentially only Helsinki: The bill acknowledges this directly — the cut "would target only the City of Helsinki's transition adjustment supplement in 2026 and 2027."
  • Large funding changes are problematic: The bill acknowledges that changes between 2024–2025 funding "proved to be quite large" and are "problematic."
  • Response to consultation feedback was only partial: The bill states that based on consultation feedback, "the rationale concerning the grounds for targeting the cut has been supplemented" — but the mechanism itself was not changed.

Root cause

The cost of the status quo

The current funding model produces problems that the bill legitimately attempts to address:

  • Incorrect sector weights. The 2021 law's sector weights do not match actual costs. Healthcare weight is too high, social services and elderly care too low. This distorts funding allocation relative to actual service needs.
  • Post hoc adjustment surprises. The retrospective adjustment has produced large one-off corrections (regions received "too much" or "too little"), undermining predictability and budgeting.
  • Weak health promotion coefficient. The current coefficient does not incentivize regions to invest in health and wellbeing promotion, because producing absolute improvement is difficult for regions already performing at a high level.
  • Imprecise rescue service funding criteria. Using actual accidents as a funding criterion creates a perverse incentive not to invest in prevention.

These problems are real. The question is whether HE 38/2025's chosen corrective mechanisms produce new problems — and if they do, these must be identified and addressed regardless of whether they exceed the magnitude of the original problem.

The bill's assumed causal chain

HE 38/2025 rests on an implicit causal model in which updating the funding formula's parameters is assumed to be a sufficient solution:

  • Problem: The funding model does not match reality (2021 assumptions vs. 2023 actuals). This produces funding shortfalls and poor predictability.
  • Solution: Update the formula's parameters: shift sector weight toward elderly care, smooth fluctuations with a two-year average, switch the health promotion coefficient to relative measurement, and apply a technical correction by cutting from those who received "too much."
  • Assumed outcome: Funding better matches regions' "actual" needs and becomes more predictable. Regions respond to the relative health promotion coefficient and other parameters by improving their operations, thereby bending the cost curve.

Problematic assumption: The bill assumes that welfare regions are static actors whose only problem is the "wrong amount" of money. It ignores the dynamic behavioral response: when the formula changes, regions do not continue as before with better funding — they begin optimizing their behavior according to the new formula. For example, cutting the surplus teaches regions to avoid producing surpluses.

Alternative causal chains

The mechanism analysis identifies competing causal chains that explain the same status quo problems (cost growth, funding imbalances) through different root causes — leading to different interventions:

1. Architectural causal chain (Soft budget constraint)
The root cause is not parameter obsolescence but architecture: welfare regions have constitutional service obligations (Constitution §19) without taxing authority. The state is the payer of last resort. This guarantees a soft budget constraint (Kornai). Tuning the formula's parameters is futile, because the regions' real incentive is always to exceed the budget — the state cannot let them fail. Cost growth is a rational adaptation to the architecture, not a formula error. (This is textbook public finance that every Ministry of Finance official knows. The fact that current legislation cannot resolve it does not make it irrelevant as a root cause.)

Original bill text — Constitutional assessment (translated from Finnish)

"The government bill must be assessed in relation to the funding principle applicable in the relationship between the state and welfare regions, connected to regional self-government as provided in Constitution §121... Additionally, particular attention must be paid to the preconditions for organizing adequate social and health services referred to in Constitution §19(3)... and to the state's ultimate obligation under Constitution §22 to secure the preconditions for the realization of fundamental rights."

"The Constitutional Law Committee has held that budget constraints cannot be used to restrict the availability of statutory services (PeVL 26/2017, p. 22)."

"In a decisive position in safeguarding the proper performance of tasks assigned to welfare regions is precisely the sufficiency of state funding and its correct targeting (PeVL 15/2018, p. 21)."

— HE 38/2025, Perustuslakiarvio (Constitutional assessment)

2. Information causal chain (Funder blindness)
The state is the funder but not the service organizer — the region organizes and delivers services. But the funder lacks the substantive capacity to evaluate what it gets for its €27 billion: the actual cost-quality ratio of service production by region. Because the state cannot evaluate substantively, it steers through a mechanical formula. When reality does not obey the formula, the state does not build its evaluation capacity — it adds new parameters and cutoffs to the formula. (Formula-based steering has so far been the only objective allocation method — the alternative is discretionary bureaucracy, which is susceptible to different distortions. Both are structural problems, not choices.)

3. Political causal chain (Too big to fail)
The transition from the municipal structure to the welfare region structure created units that are too big for the state to let fail ("too big to fail") but too remote from residents for local democratic cost discipline. When responsibility is decentralized to regions but funding is centralized with the state, a free-rider problem emerges: each region's rational strategy is to maximize its own consumption from the state's common pool.

Scope

This test evaluates the bill's funding mechanisms — not the existence of the welfare region system. Updating the funding model is necessary: the 2021 funding act's assumptions (sector weights, service need coefficients, among others) do not match actual costs. The need for updating is genuine.

The question is whether the chosen funding mechanisms create incentives that support efficient service production, or whether they create predictable behavioral responses that undermine the system's long-term functioning.

Capital stock effects

The bill treats funding almost exclusively as fiscal capital transfers between regions. The following effects are missing:

Constitutional service obligation without taxing authority (binding constraint). Welfare regions have constitutional service obligations (Constitution §19) but no taxing authority. The state is the payer of last resort. This guarantees a soft budget constraint at the level of physics — it is not a mechanism design error but a consequence of the architecture. All funding formula adjustments operate within this constraint.

Original bill text — Constitutional framework (translated from Finnish)

"The Constitutional Law Committee has stated that in regions without taxing authority, unlike municipalities, the decisive factor in securing the proper performance of assigned tasks is precisely the sufficiency of state funding and its correct targeting (PeVL 15/2018, p. 21). The Constitutional Law Committee has held it essential that the funding for social and health services adequately corresponds to service needs (PeVL 17/2021, paragraph 96, PeVL 15/2018, p. 23)."

"The Constitutional Law Committee has emphasized that the provision [Constitution §19(3)] obliges public authorities to secure the availability of services. The provision thus means a requirement for adequate provision of services to residents in different parts of the country (PeVL 17/2021, paragraph 72, PeVL 26/2017, p. 33)."

— HE 38/2025, Perustuslakiarvio (Constitutional assessment)

Purchaser competence — substitution by formula. The state steers the welfare region system by adjusting funding formula parameters, because it lacks the substantive capacity to evaluate the cost-quality ratio of service production. HE 38/2025 is the latest formula update in a long series. The state adds coordination layers (new parameters, coefficients, cutoffs) to manage behavior whose root cause is the absence of substantive steering capacity. Coordination costs grow faster than steering capacity.

Trust in funding predictability. One-off transition adjustment cuts (§39) and savings measures targeting specifically the regions that produced surpluses erode trust in funding stability. When predictability is lost, regions shift to short-sighted "spend everything" mode. This is irreversible norm destruction: a culture of fiscal responsibility collapses in one budget cycle but takes a generation to rebuild.

Citizens' trust in the system (moral capital). If citizens see their region "saved" money and lost funding as a result, the legitimacy of the entire welfare region system weakens. This is a separate capital stock effect from institutional trust.

Workforce availability and competence. The funding model shifts emphasis toward heavy care (social services and elderly care weights increase) at the expense of lighter preventive healthcare. Over the long term, this reduces the attractiveness and resources of preventive work, which increases demand for heavy care — a self-reinforcing cycle.

Regional equality. The transition adjustment cut targets practically only Helsinki (p. 67). The funding model's "corrections" are de facto transfers from one region to others.

Mechanism design errors

1. Efficiency penalty — soft budget constraint

Mechanism: Transition adjustments are cut by a one-off €15M (2026) and €20M (2027) from regions whose funding is assessed as not being at risk (§39). In practice, this targets only Helsinki, which is the only region that has produced a surplus and received "too much" funding relative to costs through the retrospective adjustment.

Original bill text — §39 (translated from Finnish)

§39 — Temporary reduction of transition adjustment supplement in 2026 and 2027

"Notwithstanding the provisions of §35(4), the difference between calculated and realized costs to be added to funding shall be reduced by a maximum of €54 per resident in 2026 and a maximum of €70 per resident in 2027 from those welfare regions where the reduction does not endanger sufficient funding for organizing services, taking into account the amount of calculated funding allocated to the region in 2025 and 2026 on the basis of the retrospective adjustment referred to in §10, as well as the region's surplus or deficit according to the 2023 and 2024 financial statements."

— HE 38/2025, §39 säännöskohtaiset perustelut (detailed rationale)

Problem: From the Ministry of Finance perspective, this is a correction of a technical calibration error in the 2021 funding act: Helsinki received more funding than its actual healthcare costs warranted, and this is being corrected. This is technically justified.

But the correction's MECHANISM produces an incentive effect regardless of whether the correction is technically correct. A welfare region observes: surplus → targeted cut. A rational welfare region concludes: better to run a controlled deficit than a surplus, because a deficit protects funding while a surplus reduces it. It does not matter whether the cut is a "technical correction" or a "punishment" — the incentive effect is the same.

This is the classic manifestation of a soft budget constraint: regions know that the state cannot let them go bankrupt due to constitutional service obligations. Efficiency is not rewarded — it is punished.

Counterargument: The state has an assessment procedure (Welfare Region Act §123) that enables forcing a savings program, dismissing management, and ultimately forcing a merger with another region. This is a hard budget constraint for deficit-running regions. But the assessment procedure targets deficits, not inefficiency — it does not reward an efficient region, it punishes a loss-making one. The incentive to produce a surplus (and thereby expose oneself to a targeted cut) does not increase even though the consequences of deficit are severe.

In the consultation feedback, Helsinki and THL specifically warned about this incentive effect (pp. 67–68). The bill did not respond substantively.

Prediction: Regions capable of producing surpluses will stop doing so. Over the long term, the system's overall cost level rises because the incentive to improve efficiency has been removed. One-off cuts become recurring because budget pressure does not disappear.

Fix: If a region produces a surplus, it should be allowed to retain a portion (e.g. 50%) as an investment reserve. Funding cuts should not target regions that have demonstrated efficiency — they should target those that have not.

2. Health promotion coefficient ceiling

Mechanism: The health promotion coefficient shifts from absolute change to relative change (§15(4)). A region earns points based on how much it improves relative to its own baseline.

Original bill text — §15 rationale (translated from Finnish)

"For outcome indicators, the calculation method is proposed to be changed in the regulation so that instead of absolute change (difference), the calculation would be based on region-specific relative change. In other words, the difference between two observation years would be proportioned to the baseline year level. This would incentivize even regions already in a good situation and ensure that they too have the opportunity to achieve higher scores."

"Regions thus compete with each other, and the outcome is a so-called zero-sum game, because the funding distributed on the basis of this criterion does not increase at the national level, even if all regions perform better."

— HE 38/2025, §15 säännöskohtaiset perustelut (detailed rationale)

Problem: Relative change was chosen with justification: an absolute level would reward only regions with an already healthy population (Helsinki, Western Uusimaa) and leave the worst-performing regions (Eastern Savo, Kainuu) with zero incentive to improve. Relative change is the only way to motivate regardless of starting level.

But the problem with relative change is an efficiency ceiling: regions that have already achieved a high level must do exponentially more work to achieve the same relative improvement. Physiological and social limits make indefinite "relative improvement" impossible at the top.

At worst, this creates a theoretical incentive to let results temporarily deteriorate ("sandbagging"), so that the relative improvement the following year produces a health promotion bonus. In practice, the probability of sandbagging is low: the health promotion coefficient's share of total funding is marginal (~1%), and there is no empirical precedent in Nordic countries for a healthcare organization deliberately worsening its results for a marginal funding advantage. The problem is nonetheless structural: the coefficient measures incorrectly even if its weight is arbitrarily small and even if nobody actually sandbags.

The more likely side effect is knowledge hoarding: because health promotion funding is a fixed pool and the metric is relative, a region's rational move is to not share successful innovations with other regions. Another region's improved result raises the average and worsens your own relative ranking. The mechanism does not merely prevent individual region development — it actively punishes system-level learning.

Prediction: High-performing regions will systematically receive worse health promotion coefficients than low-performing ones, regardless of absolute performance level. This is a transfer from efficient regions to inefficient ones — based not on need but on relative change. Additionally, inter-regional sharing of best practices will decrease, because sharing knowledge is contrary to rational self-interest in a zero-sum game.

Fix: Combine relative and absolute components: absolute level receives weight (rewards high achievement) and relative change receives weight (rewards improvement). Neither works alone.

3. Sector weight feedback loop

Mechanism: Sector weights are updated based on 2023 actual costs (§13(3)). Healthcare weight decreases by 3.6 percentage points, social services increases by 2.1, and elderly care by 1.5.

Original bill text — §13 rationale (translated from Finnish)

"§13(3) provides for sector-specific weights used in determining the calculated costs based on the needs of healthcare, elderly care, and social services. According to §13(4), sector weights must be updated at least every three years. The weights were last updated in 2023, so they must be updated by the beginning of 2026 at the latest."

"The weights for healthcare, elderly care, and social services costs are proposed to be updated taking into account the most recent available cost data. The data would be based on welfare regions' service-class-specific financial statement data for 2023 reported to the State Treasury."

In 2023, social and healthcare net costs were distributed as follows: Healthcare 55.284%, Elderly care 21.205%, Social services 23.511%.

— HE 38/2025, §13 säännöskohtaiset perustelut (detailed rationale)

Problem: The law mandates updating sector weights based on actual costs — Constitution §19 requires that funding correspond to actual service needs. The Ministry of Finance does not "choose" to increase elderly care weight; demographics choose it.

But the statutory mandate does not eliminate the feedback loop: actual costs rise → sector weight update increases elderly care weight → funding is directed even more toward heavy care → preventive healthcare loses relative funding → weakened prevention increases demand for heavy care. The statutory obligation to use actual costs (rather than a target service structure) IS the mechanism design error — it makes the feedback loop mandatory.

This is not merely a reallocation of funding — it is an extinction debt in preventive care organizational capacity. Current primary healthcare capacity is inherited from past investments. The shift of funding toward heavy care means the pipeline — recruitment, training, organizational development in primary healthcare — breaks. The stock still appears functional (current employees are doing their work), but the replacement rate R0 < 1.0. The visible collapse comes with a delay: 10–15 years, when the current expertise base has burned out or shifted to heavy care, and no new competence has been grown to replace it. Recovery time: a generation, because preventive care experiential expertise (public health work, long-term follow-up, prevention program management) cannot be formally taught but emerges from experience.

Prediction: Preventive work's relative funding declines over the long term, increasing cost pressure in precisely those services whose costs prevention would have contained. Over the long term, total costs rise. Visible capacity crisis in the mid-2030s.

Fix: Separate current cost structure (measures what is) from target service structure (measures what should be) in sector weights. Tie a portion of funding to preventive work indicators whose weight does not decrease even when actual costs shift toward heavy care.

4. Data lag — two-year cache

Mechanism: Service need coefficients are calculated as a two-year average going forward (§14(3)). Year 2026 funding is based on 2022 and 2023 data.

Original bill text — §14(3) rationale (translated from Finnish)

"§14(3) provides for the data used in determining region-specific service need coefficients for healthcare, elderly care, and social services... The provision is proposed to be amended so that region-specific service need coefficients would be taken into account based on two years of data: the year preceding the financial year and the year preceding that. The region-specific service need coefficient would be the average of these service need coefficients."

"From 2026 onwards, the calculation would thus always use the most recent available data from two years. For example, in 2026, the funding based on need factors would be determined based on the average of regional need coefficients calculated from 2022 and 2023 data."

Background: "The 2025 funding was instead determined according to §14(3) based on one year of data, namely 2022. The changes between 2024 and 2025 funding proved to be quite large. From the perspective of funding stability and predictability, large changes are problematic."

— HE 38/2025, §14 säännöskohtaiset perustelut (detailed rationale)

Problem: Averaging is a genuine improvement over the status quo: it reduces the one-off fluctuations from retrospective adjustments that regions have criticized. This directly addresses the predictability that regions have requested.

But averaging slows responsiveness: if a region experiences a sudden demographic change or cost pressure, funding responds with a three-year lag at 50% effectiveness. This is a deliberate tradeoff: stability (cheap cache) at the cost of responsiveness.

Additionally, averaging creates an upcoding incentive: regions benefit from coding diagnoses at the highest possible level consistently, because the average slows the "detection" of funding decreases.

Prediction: Moderate risk. Averaging is a justified stability objective, but its interaction with other mechanisms (especially the health promotion coefficient's lag) creates a total lag where funding responds to reality years late.

Fix: Add a mechanism for detecting sudden changes: if a region's service need index changes by more than X% in one year, apply the most recent data instead of the average.

5. Diagnosis inflation in service need coefficients (Goodhart's Law)

Mechanism: Welfare region funding is based on service need coefficients (§14), calculated from the population's coded morbidity (THL's data foundation). Billions of euros are allocated directly based on how sick a region's population appears to be in coded terms.

Original bill text — §14 on service need coefficients (translated from Finnish)

"The central determinant of social and healthcare funding based on service need is provided for in §14 of the Funding Act. According to §14(1), welfare region service need coefficients for healthcare, elderly care, and social services are calculated based on need factors related to diseases and socioeconomic factors that describe service needs and costs, their weight coefficients, and the sector-specific weights referred to in §13(3). Need factors and their weight coefficients are attached to the Act."

"Need factors cover morbidity data, age structure, socioeconomic factors, and other background information. The need factors in the current Funding Act are based on THL's 2022 research... THL calculates service need coefficients for healthcare, elderly care, and social services annually for each welfare region based on the most recent register data."

"The morbidity data affecting region-specific service need coefficients are in practice based on data from three years prior. The service need coefficients used in 2025 funding are based on diagnosis data describing 2022 morbidity."

— HE 38/2025, Nykytila §2.1.2

Problem: According to Goodhart's Law, when a metric (diagnosis codes) becomes the basis for funding, the metric itself becomes a target for optimization. This is a well-documented phenomenon internationally: in the US Medicare system, upcoding (recording diagnoses as more severe than clinically warranted) produced an estimated $6.7 billion in excess costs annually (Geruso & Layton 2020). The same phenomenon occurs in Germany's DRG system. In Finland's funding model, a rational region invests in coding optimization: coding consultants, prioritizing clinical staff's documentation time, systematic review of diagnostic classifications. The population appears sicker without clinical change.

Counterargument: THL's coefficients are based on multiple variables (age structure, morbidity indices, socioeconomic structure), not solely on diagnosis codes. Harmonization of coding practices (Hilmo guidelines) reduces the opportunity for gaming.

Counterargument assessment: Multivariate design makes optimization harder but does not prevent it — every variable based on coded data is susceptible to the same dynamic. Hilmo guidelines are process controls, not structural barriers: guidelines specify how to code but cannot prevent the systematic selection of more severe codes in clinically ambiguous cases (of which there are many).

Prediction: Needs-based funding creates slowly growing diagnosis inflation, where all regions optimize their coding upward. Because the coefficients are relative, the aggregate effect balances out — but the nature of the activity changes: clinical work's emphasis shifts from treatment to documentation. This is an invisible cost that does not appear in any metric.

Fix: Validate service need coefficients against clinical review (sample auditing, where coding is compared to patient records). Anomaly detection for coding changes (sudden rise in morbidity index without demographic change → audit). In the long term: partially decouple the funding model from coded morbidity, shifting toward outcome-based metrics.

Overall picture

The bill's mechanism design errors are not individual parameter problems — they are manifestations of the same architecture: the state steers by formula because it lacks the substantive capacity to steer by content. Individual parameter decisions are often technically justified (Helsinki's transition adjustment correction, statutory sector weight update, the choice of a relative health promotion coefficient). But their combined effect produces a system where efficiency leads to punishment: surplus → cut (error 1), high performance → worse coefficient (error 2), high care costs → higher weight (error 3), data lag conceals effects of changes (error 4), diagnosis codes steer funding allocation optimization (error 5).

A rational welfare region concludes: consume everything, do not improve efficiency, do not invest in prevention. This is norm destruction whose recovery time is a generation: a culture of fiscal responsibility collapses in one budget cycle but takes a generation to rebuild.

The bill's one-off savings (€15M + €20M) are marginal in the €27.1 billion total funding. But the signal effect is disproportionate: it tells all regions what happens to the one that tries to be efficient.

Undercapitalized reinsurer structure: The welfare region sector functions as a structural reinsurer to which multiple ministries (Finance, Social Affairs & Health, Economic Affairs & Employment) transfer correlated structural risk without giving the sector the tools to absorb this risk. HE 38's efficiency penalty combined with concurrent welfare reform bills' sanction incentives (HE 112/2025 and HE 116/2025 tighten benefit conditions, pushing marginal recipients out of municipal support systems → their unresolved needs transfer as higher-cost cases to welfare regions' social and health services) and §39's saver's penalty (regions cannot buffer investment reserves) creates a situation where all other actors' externalized structural risks — marginalization, prevention neglect, demographic shocks — are channeled to the welfare region sector, but the sector has neither the resources, tools (no taxing authority, no borrowing capacity), nor funding formula incentives to manage these risks. A mathematically certain crisis: costs rise, funding shrinks, deficits force cuts, cuts worsen problems, the feedback loop accelerates.

Cross-sector connection: HE 189/2025 (extension of deficit coverage deadline) addresses the next iteration of the same funding architecture. The welfare regions' combined deficit for 2023–2024 is €2.45 billion. The funding architecture's incentive structure — where efficiency is punished and deficits are cushioned — produces deficit accumulation, and the state's response (relaxing the rules) deepens the same incentive structure. Together, HE 38 and HE 189 form a self-reinforcing cycle.

Explain or fix

  1. Why is funding cut from a region that produces a surplus, while funding is secured for a deficit-running region — does this not produce an incentive for inefficiency?
  2. How does the health promotion coefficient reward a region that has already achieved a high level, when sustaining relative improvement is statistically impossible to maintain indefinitely?
  3. Why is the sector weight update based on actual costs rather than a target service structure — does this not cement current inefficiencies through the funding model?

AI-assisted analysis. Predictions are mechanism-model-based assessments, not empirical facts. Producer: Elias Kunnas.

→ Alternative tab: alternative mechanisms, comparison to the bill, constraint analysis, and overall alternative.

→ Sources tab: all sources, statements, methodology, and provenance.

Alternative mechanism design

Mechanism error 1: Efficiency penalty

Alternative mechanism: Investment reserve and shared surplus. If a region produces a surplus, it does not lose it to a targeted cut but retains, for example, 50% as a regional investment reserve. The reserve is earmarked for one-time investments that reduce future costs (e.g. developing preventive care or technology). Requires a monitoring mechanism: a bare "reserve" without earmarking and ex-post evaluation becomes running costs.

Rationale: This transforms the soft budget constraint's "use it or lose it" dynamic. It creates a positive incentive to seek savings, because success does not lead to punishment but to growth of one's own future capacity.

Tradeoff: In the short term, the state loses the ability to plug its own budget gap by extracting the most efficient regions' surpluses. Short-term fiscal optimization is sacrificed for the system's long-term vitality. Additionally, monitoring the reserve adds administrative burden.

Compare to the bill

Bill's mechanism (§39)

Targeted transition adjustment cut from surplus-producing regions as a technical correction. Teaches regions that efficiency is punished.

Alternative mechanism

Shared surplus. Part of the savings remains with the region as an investment reserve. Teaches regions that efficiency pays for itself.

Mechanism error 2: Health promotion coefficient ceiling

Alternative mechanism: Combined coefficient. Of the health promotion funding, 50% is allocated based on absolute performance level (rewards high achievement) and 50% based on relative improvement (rewards raising the baseline).

Rationale: A purely relative coefficient creates a "sandbagging" incentive and punishes top-performing regions that have reached a physiological ceiling, as described in mechanism error 2. A combined coefficient incentivizes the weakest to improve without punishing those whose results are already excellent.

Tradeoff: The worst-performing regions receive less health promotion bonus funding than they would under a purely relative model. Their catch-up is marginally slower if they rely solely on additional state funding.

Compare to the bill

Bill's mechanism (§15)

Rewards exclusively relative change from own history. Creates a physiological ceiling for top-performing regions.

Alternative mechanism

Rewards both absolute level and relative improvement. Motivates everyone regardless of starting position.

Mechanism error 3: Sector weight feedback loop

Alternative mechanism: Target-based sector weights. Sector weights are not fully tied to historical actual costs; instead, a target minimum weight for preventive work (e.g. primary healthcare) is defined in law. This weight is protected: it does not decrease even when the region's heavy service costs grow beyond it.

Rationale: The current mechanical update creates a self-reinforcing cycle (as described in mechanism error 3) where heavy care absorbs funding through the formula. The state must steer the system toward a target structure, not merely validate and reinforce failure that has already occurred.

Tradeoff: Regions with disproportionately high demand for (and cost of) heavy services face tighter budget discipline sooner. The formula is less "fair" toward existing inefficiency.

Compare to the bill

Bill's mechanism (§13)

Mechanical weight update based on actual costs. Validates and funds the heavy care cost crisis.

Alternative mechanism

Partial anchoring to target service structure. Protects the prevention share regardless of actual cost overruns.

Mechanism error 4: Data lag — two-year cache

Alternative mechanism: Averaging with a sudden-change trigger. Under normal conditions, a two-year average is used (stabilizes funding). If a region's service need index or population base changes suddenly beyond an agreed threshold (e.g. a major shock within one year), the formula automatically switches to using the most recent data instead of the cache.

Rationale: The average is correct for stability, but as mechanism error 4 shows, it exposes the system to dangerous blindness in shock situations. The trigger combines the cache's benefits with the ability to respond to realities when needed.

Tradeoff: The formula becomes more complex, and threshold breaches can cause sharp funding jumps, slightly undermining perfect predictability.

Compare to the bill

Bill's mechanism (§14)

Unconditionally mechanical two-year average. Responds with a lag even to drastically changed reality.

Alternative mechanism

Two-year average equipped with a trigger. Provides stability but can override blindness at the moment of major structural change.

Overall alternative

Patching individual formula errors is symptomatic treatment. A mechanism-realist overall architecture would acknowledge the soft budget constraint's destructive effects and build a "hard constraint box" into the system's core.

In the overall alternative, state funding would not be a single massive opaque pool but would be split into two parts:
1. Base funding, which secures the constitutional minimum service level but is rigidly needs-calibrated and slowly responsive.
2. Capacity funding, which is isolated within a hard budget constraint. It is not distributed formulaically to everyone but directed as long-term investments to those regions that can demonstrably raise productivity and effectiveness.

Prerequisite: Capacity funding requires the state to have substantive expertise to evaluate which investments actually raise productivity — precisely the purchaser competence whose absence is the root cause of the current formula-based steering (see Root Cause). This capacity does not emerge spontaneously. Building it requires (a) an independent evaluation unit with clinical and operational expertise (cf. Sweden's Myndigheten för vård- och omsorgsanalys), and (b) a transition period in which capacity funding starts with a small share and expands as evaluation capacity matures. Without this, capacity funding becomes another formula.

Constraint analysis

A: Within current constraints

Without major legislative changes, the state cannot fully break the soft budget constraint. But mechanism errors can be addressed through the normal amendment process of the funding act (the same process used to draft HE 38/2025): a) introducing investment reserves requires amending §39, b) changing the health promotion coefficient to a combined coefficient requires amending §15 and the funding regulation, c) setting a target floor for sector weights requires amending §13. These are legislative changes, but of the same magnitude as HE 38/2025 itself — not constitutional-level reforms.

B: If the constraint is lifted

The following changes exceed the authority of a single funding act bill. The mechanism analysis nonetheless identifies them as necessary if Level A parameter corrections fail to break the cost spiral — and the evidence so far suggests they will not:

  • Taxing authority (regional tax): If regions receive taxing authority, the responsibility for spending money and local democratic accountability are united. The soft budget constraint is partially reversed when overruns are directly visible on the region's own residents' tax bills. The state no longer needs to micromanage funding through a formula when taxpayers do it by voting.
  • Service obligation flexibility (Constitution §19 scaling): If the constitutional interpretation allows the precise definition of a national minimum service package — and gives regions freedom to prioritize everything above it more freely — regions gain a real mechanism to adjust their expenditures. Currently, regions cannot legally flex their obligations, so they flex by maintaining queues and demanding additional funding, which is destructive to the state's overall capacity.

Broader frame

The funding model's fundamental problem is not in individual parameters but in the architecture: welfare regions have constitutional service obligations but no taxing authority. The state is the payer of last resort. This guarantees a soft budget constraint regardless of the funding formula's details. The funding formula can mitigate or worsen the problem, but cannot eliminate it.

A structural solution would require either (a) taxing authority for welfare regions or (b) flexibility in service obligations. These changes exceed a single bill's authority — but if parameter corrections repeatedly fail, the architectural change shifts from politically impossible to inevitable.

Sources

All sources and institutional materials for this mechanism test in one place. Finland has no service that aggregates the statements, analyses, and positions concerning a single government bill — this section does it manually.

Government bill

  • HE 38/2025 — Government bill to Parliament for an Act amending the Act on the Funding of Welfare Regions (Finlex, full text, in Finnish)
  • HE 38/2025 — Parliamentary proceedings and documents (in Finnish)

Legislation being amended

Committee work

  • HaVM 17/2025 — Administrative Committee report (in Finnish)

Statements and institutional positions

  • THL (National Institute for Health and Welfare) — Statement on HE 38/2025 (cited in the bill's consultation feedback, pp. 67–68)
  • City of Helsinki / Helsinki welfare region — Statement on HE 38/2025
  • Western Uusimaa welfare region — Statement
  • Pirkanmaa welfare region — Statement
  • City of Helsinki and Vantaa-Kerava welfare region — Joint statement on rescue service funding cuts

Background materials

Academic references

  • Kornai, J. (1986). "The Soft Budget Constraint." Kyklos, 39(1), 3–30. The foundational analysis of why organizations that cannot be allowed to fail lose efficiency incentives.
  • Geruso, M. & Layton, T. (2020). "Upcoding: Evidence from Medicare on Squishy Risk Adjustment." Journal of Political Economy, 128(6), 2427–2465. Empirical evidence of diagnosis inflation in needs-based funding systems.

Methodology and provenance

The test is based on the full legal text (99 pp.) of HE 38/2025 and the bill's own impact assessment and consultation feedback. The mechanism scan covered the full legal text with AI assistance. The analysis applied a systems-theoretic framework (soft budget constraint, incentive analysis, feedback loops).

Provenance: Claims explicitly cited to sources in the text (Helsinki and THL statements, Welfare Region Act) are institutional observations. Points cited to page numbers and sections are the bill's own statements. Everything else — especially the mechanism error analysis, predictions, and proposed fixes — is original mechanism test analysis. Predictions are mechanism-model-based assessments, not empirical facts.

Producer: Elias Kunnas.

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