Measuring Quality and Outcomes in Sweden’s Older People’s Care System

A municipality can know how many older people receive home help, how many live in special housing and how many services were delivered without yet knowing whether those services are producing good lives. Activity data describe what the system does. Outcome evidence asks what difference that activity makes.

This distinction is central to the Swedish care system explored through the Sweden Ageing, Long-Term Care & Community Support Knowledge Hub. Sweden has extensive national statistics, open comparisons, municipal healthcare indicators, service-level surveys and recurring national questions about how older people experience home help and special housing. Yet its 290 municipalities organise services differently, people enter care with different needs and many important outcomes are difficult to reduce to one number.

The measurement challenge therefore extends beyond collecting more data. Leaders need to distinguish structures from processes, activity from outcomes and legitimate local variation from unequal quality. They need to know whether greater service use reflects worsening need or better access, whether low incident rates indicate safer care or weaker reporting, and whether a high satisfaction score conceals poor experience among particular groups.

The stronger opportunity lies in connecting national comparison with individual follow-up, professional judgement and lived experience. Measurement should help Sweden answer not only whether services were provided, but whether older people remained independent where possible, felt secure and respected, experienced continuity and received support that adapted when their circumstances changed.

Quality cannot be represented by one indicator

Older people’s care produces several different forms of value, and these do not always move in the same direction.

A service may improve safety by increasing supervision while reducing autonomy. Home help may maintain people successfully at home while service intensity rises because needs have become more complex. A special-housing setting may reduce serious incidents while residents report limited influence over daily routines.

Measurement therefore requires a balanced view.

Useful quality evidence can describe:

• whether people can access support when eligible;
• whether agreed services are implemented reliably;
• whether care is safe and clinically appropriate;
• whether staff continuity and competence are sufficient;
• whether people experience dignity, influence and security;
• whether independence and functioning are maintained where possible; and
• whether persistent inequalities or unwarranted variation are reducing.

No single measure answers all of these questions.

This is why quality data, KPIs and performance metrics need to be interpreted as a portfolio rather than a league table.

Sweden’s Open Comparisons create a national reference point

Socialstyrelsen’s Öppna jämförelser, or Open Comparisons, provide one of Sweden’s central infrastructures for comparing social services and municipal healthcare.

Within older people’s care, indicators and key figures can be examined across municipalities, counties and nationally. The system is intended to support follow-up and development by showing differences, trends and comparisons between areas with similar conditions.

This is especially valuable in a decentralised system.

Municipalities retain substantial responsibility for organisation and delivery, but common national indicators make it possible to ask whether apparently local performance is unusual when compared with peers.

The correct use of comparison is analytical rather than punitive.

A difference should create a question before it creates a judgement. Population characteristics, geography, service models and recording practices can all influence results. A municipality with greater service intensity may be serving a population with greater need rather than operating inefficiently.

Conversely, consistently weaker results across several related indicators deserve investigation even where local explanations exist.

Open comparison therefore creates visibility, but local interpretation remains essential.

2026 results show the continuing challenge of individual outcome follow-up

Sweden’s 2026 Open Comparisons provide a useful illustration of the gap between system-level data and structured understanding of individual outcomes.

More municipalities are using individbaserad systematisk uppföljning, or individual-based systematic follow-up, within older people’s care. However, it remains far from universal.

In 2026, 22 per cent of municipalities reported using this approach to follow the needs of the target group, 24 per cent to examine support or interventions provided to individuals, and 20 per cent to follow the results of those interventions for individuals.

The direction is positive compared with the previous year, but the figures illustrate an important strategic issue.

A national system can possess extensive statistics about service use while many local organisations still lack mature processes for connecting individual need, intervention and outcome systematically.

That connection is particularly important under Sweden’s knowledge-based social-services direction.

Without individual follow-up, organisations can know that a person received home help without knowing whether the intervention maintained independence, reduced risk or achieved the person’s own objectives.

Individual-based systematic follow-up can connect practice with local knowledge

Individual-based systematic follow-up is not simply another dataset.

Its purpose is to use information generated through individual work to build knowledge about the service itself. Individual needs, interventions and results can be aggregated to identify patterns across groups.

This creates an important bridge between person-centred care and strategic management.

For example, a municipality might examine whether people receiving a particular form of rehabilitative home support become more independent in selected daily activities, whether outcomes differ by age or neighbourhood, or whether one group repeatedly receives an intervention without achieving the intended result.

The process helps turn local experience into proven practice.

However, implementation needs to remain proportionate. Frontline workers should not be required to collect large quantities of information that cannot realistically be analysed or used.

A strong measurement model begins with a meaningful question and collects the minimum information necessary to answer it.

This aligns with outcomes-focused and goal-led support. Outcomes become more credible when the person’s objectives can be traced from assessment through intervention to review.

A municipality discovers that identical service volumes produce different outcomes

Two groups of older people receive similar levels of home help after hospital discharge. At service level, the packages appear almost identical.

Individual follow-up shows a meaningful difference.

In one area, support is delivered alongside clear rehabilitation goals and staff are expected to encourage participation in daily tasks. More people subsequently reduce their level of assistance.

In another area, the same number of care hours is largely delivered through compensatory task completion. Support remains stable or increases.

The data do not prove that one model caused every difference. Population need and professional input also need examination.

But the variation provides a credible improvement question.

The municipality reviews rehabilitation access, workforce practice and how goals are communicated. It then tests whether aligning home-help support more closely with rehabilitation changes subsequent outcomes.

Measurement has therefore moved beyond comparing hours. It has identified how similar inputs may produce different trajectories and created a basis for learning.

The national survey gives older people a direct voice

One of Sweden’s most important quality mechanisms is the recurring survey Vad tycker de äldre om äldreomsorgen? — What Do Older People Think About Elderly Care?

The survey asks people aged 65 and over receiving home help or living in special housing about their experience of care.

Questions address issues that administrative records cannot capture adequately, including treatment by staff, influence, security, accessibility and overall experience.

This creates an important counterweight to operational data.

A municipality may know that visits were completed but not whether the person felt workers had enough time. A residential setting may know that activities were offered but not whether residents felt able to spend time outdoors or influence daily routines.

Experience data therefore contribute directly to service-user feedback and co-production.

The 2026 national survey cycle included around 220,000 older people receiving home help or living in special housing. At the time of this article, the latest completed national results remain those published from the 2025 survey, while the 2026 collection forms part of the ongoing measurement cycle.

The scale is significant, but the measurement still requires careful interpretation.

Survey evidence needs to account for who can and cannot respond

Older people’s care includes many people living with dementia, communication difficulty, severe frailty and sensory impairment. These characteristics can affect participation in surveys.

Family members may sometimes assist with responses or answer from their own perspective. This can provide valuable evidence, but family experience and the older person’s experience are not always identical.

A person with advanced dementia may also be unable to respond through a conventional questionnaire despite having a clear experience of whether care feels reassuring, rushed or distressing.

National surveys therefore need complementary local methods.

Observation, accessible conversations, smaller feedback exercises and knowledge of individual communication can make people visible who would otherwise disappear from outcome measurement.

The wider principles of accessible information and communication matter because an outcome framework is only as inclusive as the ways through which people can contribute.

2025 experience results illustrate why aggregate satisfaction is not enough

Sweden’s 2025 national survey demonstrates the value of looking beneath an overall satisfaction figure.

Some aspects of experience remained positive, including strong appreciation of staff treatment. Other indicators revealed more difficult issues. Relatives reported declining confidence in older people’s ability to influence care, while people in special housing reported mixed experiences around access to doctors, outdoor opportunities and knowing how to raise complaints.

These are different dimensions of quality.

A respectful workforce can coexist with limited personal influence. A pleasant residential environment can coexist with difficulty obtaining medical input. Strong overall satisfaction can therefore mask specific operational weaknesses.

The improvement implication is that municipalities should avoid reducing experience to one headline percentage.

Domain-level results create more useful questions.

If influence is declining, care planning and everyday routines may require examination. If access to doctors is weak in special housing, the region–municipality interface may be relevant. If people do not know how to complain, information and accessibility become the issue.

Measurement becomes useful when each result points towards an operational hypothesis.

Continuity deserves measurement because it shapes experience and safety

Continuity is particularly important in Swedish home help.

An older person may receive all agreed visits while seeing a large number of different workers. The service can therefore appear complete from an activity perspective while remaining fragmented relationally.

Measuring continuity helps expose this difference.

For people with dementia, communication difficulty or highly personal care needs, a smaller familiar staff group can improve trust and reduce the need to explain routines repeatedly. Familiar workers may also recognise changes in health or behaviour more readily.

Continuity therefore connects workforce resilience and continuity with outcomes for older people.

However, continuity measures also need interpretation.

A rural service may require different staffing arrangements because distance and small teams limit scheduling options. Absence and specialist tasks may make some variation unavoidable.

The meaningful question is whether the level of continuity is reasonable for the person’s needs and whether deterioration triggers action.

Municipal healthcare adds another layer of outcome measurement

Older people receiving municipal services often have substantial healthcare needs as well as social-care support.

Socialstyrelsen therefore also publishes Open Comparisons for municipal healthcare using annual survey information and register-based data. These measures can include organisational arrangements alongside indicators relating to diagnoses, fractures, medicines and other aspects of health.

This matters because the outcomes of older people’s care cannot be understood exclusively through social-service data.

Falls, medication use, hospitalisation, rehabilitation and clinical deterioration may all influence whether a person remains independent and safe.

Yet health indicators need the same interpretive discipline as social-care measures.

A high rate of recorded diagnoses may indicate greater illness burden or better recognition. Increased reporting of falls may indicate worsening safety or stronger reporting culture. Reduced hospital use may reflect successful support at home or barriers to accessing necessary care.

Metrics rarely explain themselves.

The stronger quality framework places clinical indicators alongside service information, workforce capacity and lived experience.

Avoided events are useful outcomes but difficult to attribute

Older people’s services often aim to prevent undesirable outcomes such as falls, hospital admissions, loss of independence and unplanned moves into special housing.

These are strategically important goals, but attribution is difficult.

If an older person avoids hospital for a year, it may reflect effective home support, stable health, strong family involvement, good primary care or simply a period without acute illness.

Conversely, a hospital admission is not automatically evidence of failure. Some admissions are necessary and appropriate.

Outcome measurement therefore needs to avoid crude incentives.

A service should never be encouraged to delay necessary hospital treatment merely because admission avoidance is measured positively.

The better question is whether potentially preventable deterioration was recognised and acted upon, and whether repeated use of urgent healthcare suggests a pathway that warrants review.

This is particularly relevant to hospital discharge and admission avoidance.

Outcome measures should support professional judgement rather than distort it.

A reduction in hospital admissions initially looks like success

A municipality observes that hospital admissions from several special-housing settings have fallen significantly.

At first, this appears to support the municipality’s goal of providing more care in place.

Leaders resist treating the decline as automatically positive.

They compare the result with mortality, clinical incidents, family feedback and access to medical assessment. One setting shows a healthy pattern: greater on-site clinical input and stronger anticipatory planning appear to have reduced avoidable transfers.

Another setting shows a more concerning picture. Families report difficulty obtaining medical review and several incidents indicate delayed escalation.

The same headline indicator therefore represents two very different realities.

In the first service, lower admission reflects better local capability. In the second, it may partly reflect access barriers.

The scenario illustrates why outcome measurement requires triangulation. Direction alone does not define quality. Leaders need enough connected evidence to understand why an indicator moved.

Independence is an important outcome but needs individual meaning

Maintaining independence is a recurring objective within Swedish ageing policy, rehabilitation and home-based support.

But independence should not be defined as absence of formal services.

An older person may receive substantial support and still retain meaningful independence because that assistance enables them to make decisions, participate in daily tasks and remain in their own home.

Another person may receive relatively little formal care while depending extensively on an exhausted spouse.

Service volume alone therefore says little about autonomy.

Measurement should examine what the person can do, what they want to do and whether support is enabling or unnecessarily replacing capability.

This aligns with outcomes, independence and community inclusion.

For rehabilitation, functional change can be measured directly. For long-term progressive conditions, maintaining ability may itself be a positive outcome.

An outcome system needs enough sophistication to recognise both improvement and successful maintenance.

Safety measures need to distinguish harm from reporting culture

Incidents, falls, medication errors and safeguarding concerns are essential quality measures.

Yet organisations with strong reporting cultures may appear to have more problems because workers record events consistently.

Low incident numbers can therefore be ambiguous.

They may indicate genuinely safe services, or they may indicate under-reporting.

This is why safety measurement needs context.

Leaders can examine severity, recurrence, near misses, reporting timeliness and whether investigations produce improvement. A temporary increase in incident reporting after staff training may actually represent stronger organisational visibility.

The wider principles of learning from incidents are therefore central to outcome interpretation.

The most useful safety indicator is not simply how many adverse events occurred, but whether the organisation understands them and reduces avoidable recurrence.

Workforce measures should be treated as leading indicators

Some of the most important quality signals appear before a poor outcome occurs.

High turnover, rising sickness absence, unstable management, increased temporary staffing and worsening continuity can all indicate that a service is becoming more fragile.

These are not direct outcomes for older people, but they are important leading indicators.

A municipality that waits until complaints or incidents rise may be identifying instability too late.

Strong dashboards therefore connect workforce and care data.

A service experiencing increased absence should prompt examination of missed visits, continuity and staff workload. A sharp rise in temporary staffing may require additional monitoring of errors, induction and person-specific knowledge.

The Quality Dashboard Builder offers organisations a practical framework for bringing such measures together. It is not a Swedish national reporting system, but it illustrates the value of viewing workforce, safety, experience and outcomes as related signals rather than independent datasets.

Equity needs to be visible inside outcome measurement

National averages can conceal unequal experience.

Older people differ by income, gender, migration background, language, disability, geography, housing situation and family support. These factors can influence both need and access.

A municipality may report strong overall satisfaction while one linguistic minority experiences difficulty understanding care information. Rural residents may receive the same formal entitlement but experience longer waits for professional support. People without relatives may struggle more with navigation than those with active family networks.

Outcome analysis therefore needs appropriate disaggregation where data quality and privacy allow it.

The purpose is not to create endless demographic reporting.

It is to identify whether apparently universal services produce systematically different experiences or outcomes for particular groups.

This is consistent with health inequalities and prevention. Equality of formal entitlement does not guarantee equality of practical access or effect.

A good overall satisfaction score conceals a language-access problem

A municipality receives strong overall results from older people using home help.

Local feedback from one neighbourhood is noticeably weaker, particularly around communication and understanding changes to visits.

When responses are examined alongside local population information, leaders identify that many older residents in the area have another first language.

The issue is not simply staff language competence. Written information, schedule changes and explanations of municipal processes are also difficult for some people to understand.

The municipality introduces more accessible communication options and strengthens support for staff working across languages.

Follow-up does not ask merely whether translated material was produced. It examines whether people report improved understanding and confidence.

This illustrates why equity measurement needs to move from inputs to outcomes. Providing information in another language is an intervention; the outcome is whether the person can actually use it.

Provider comparison can support choice but needs context

Where municipalities use external providers or choice arrangements, quality information can also influence how services are monitored and how people understand available options.

Comparative data have potential value, but simplistic rankings can mislead.

Providers may support populations with different levels of need. Small services can show large percentage changes because of a few cases. Survey response rates can vary substantially.

Municipalities therefore need proportionate provider assurance rather than assuming one score captures performance.

The Commissioner Evidence Builder can help organisations examining comparable purchaser-provider relationships define expected outcomes and evidence. It is not a Swedish regulatory or purchasing instrument, but the general principle applies: external provision needs clear evidence about quality and outcomes rather than activity alone.

Measurement can unintentionally change behaviour

Indicators influence organisations because people naturally focus on what is monitored.

This makes metric design consequential.

If services are rewarded primarily for visit punctuality, workers may feel pressure to leave one older person before an important conversation is finished in order to reach the next visit on time. If reducing care hours is treated automatically as a positive outcome, staff may feel pressure to reduce support even where ongoing assistance is appropriate.

Good measurement therefore needs balancing indicators and professional safeguards.

A punctuality measure can be considered alongside continuity and service-user experience. Reduced service intensity can be interpreted alongside functional outcomes and safety.

The question should always be whether the metric encourages the behaviour the system genuinely wants.

Person-centred outcomes need to start with person-centred goals

Outcome measurement becomes difficult when the intended outcome was never defined clearly.

Care plans may describe tasks without stating what those tasks are intended to achieve.

“Support with showering” is an intervention. “Maintain the ability to undertake personal care with minimal assistance” describes an outcome more clearly.

“Attend day activity twice weekly” is a service. “Maintain social contact and reduce isolation” explains why the service exists.

The distinction matters because reviews can otherwise confirm that activity occurred without assessing whether it helped.

The wider principles within support planning and reviews therefore connect directly with measurement.

Person-centred outcome frameworks do not require every objective to be quantified precisely. Some goals are qualitative. They do require enough clarity that the person, staff and reviewers understand what support is trying to achieve.

Digital systems can make outcome measurement more continuous

Traditional quality measurement often relies on periodic surveys, annual reports and retrospective analysis.

Digital care systems can make some information available closer to real time.

Electronic records may show changes in support intensity, missed interventions, repeated deterioration or patterns in service delivery. Scheduling systems can provide continuity and punctuality information. Welfare technology may generate safety information where its use is appropriate and agreed.

This creates potential for earlier intervention.

If an older person begins requiring substantially more unplanned assistance, a digital system could prompt review before the change becomes a crisis. If continuity suddenly deteriorates across one team, managers can respond without waiting for annual results.

However, continuous data also create risks.

More information can mean more alerts, greater administrative burden and stronger temptation to monitor what is easy rather than what matters.

The Digital Transformation Readiness Assessment can help organisations considering similar developments examine data, workforce adoption, governance and operational readiness. It is not a Swedish measurement framework, but it supports the principle that better analytics depend on reliable digital foundations.

Outcome data need to reach people who can act

Measurement creates no value if information stops inside a report.

Different levels of the system need different views.

A frontline team needs specific information about the people it supports and recurring operational problems. A municipal service manager needs patterns across teams. Political and senior administrative leadership need visibility of strategic risks, variation and whether major improvement priorities are producing results.

National agencies need aggregated information capable of identifying wider trends.

The challenge is preserving meaning as information moves upwards.

If a complex set of experiences is reduced to one green status indicator, decision-makers may receive reassurance without understanding underlying fragility.

Good governance therefore combines concise measures with sufficient explanation.

Organisations examining similar assurance structures can use the Governance Maturity Assessment to consider whether information, ownership and escalation are connected effectively. It is not specific to Swedish municipalities, but the underlying governance test is relevant: the right evidence needs to reach the level with authority to act.

Targets should create learning rather than defensive reporting

Targets can focus attention and make accountability visible.

They can also create defensive behaviour if used without context.

A municipality that sets a continuity target may encourage useful improvement. If managers fear judgement whenever the target is missed, they may focus on explaining the number rather than understanding the cause.

The stronger quality culture treats adverse variation as something to investigate.

This does not mean abandoning accountability. Persistent poor performance still requires escalation and action.

The distinction lies in whether measurement encourages learning before blame.

A mature system asks:

• What changed?
• Which people are affected?
• Is the variation expected or concerning?
• What explains it?
• Who can influence the cause?
• What will be tested?
• How will we know whether the response worked?

These questions turn performance management into improvement.

Small municipalities need measurement models they can sustain

Sweden’s municipalities vary substantially in population and organisational scale.

A sophisticated analytics model that is realistic for Stockholm, Gothenburg or Malmö may be disproportionate for a much smaller municipality.

Smaller municipalities still need robust outcome evidence, but the infrastructure may need to be shared or simplified.

Regional cooperation structures, national analytical support and common definitions can help reduce the need for every municipality to build specialist capability independently.

This is another reason national standardisation of core data can be valuable.

Standardising what an indicator means does not require standardising every local service model.

Local organisations can retain flexibility while using common measures to understand whether different approaches produce comparable outcomes.

A small municipality chooses fewer measures and uses them better

A small municipality develops a quality dashboard containing dozens of indicators because leaders want comprehensive assurance.

Over time, managers spend substantial effort updating the dashboard while few measures generate discussion or action.

The municipality redesigns the approach.

It retains a smaller strategic set covering access, continuity, workforce stability, serious safety issues, experience and selected individual outcomes. More detailed operational indicators remain available to service managers but are not automatically escalated.

For each strategic measure, ownership and response thresholds are clarified.

The amount of data considered by senior leaders decreases, but the quality of discussion improves.

One worsening continuity measure, previously hidden among many metrics, now triggers a focused review of staffing and scheduling.

The lesson is that measurement maturity is not demonstrated by the number of indicators collected. It is demonstrated by the ability to use evidence proportionately and act on meaningful signals.

Family experience can strengthen evidence without replacing the older person’s voice

Family members often observe care over long periods and across organisational boundaries.

Their perspective can therefore be valuable, particularly where an older person has advanced dementia or substantial communication difficulty.

Relatives may identify inconsistent staffing, poor coordination or changes that formal measures have not yet detected.

However, family experience is distinct from the older person’s own outcome.

A relative may prioritise greater supervision while the person values freedom. Families may also assess service quality partly through how well professionals communicate with them rather than solely through the person’s experience.

Both perspectives matter.

Strong measurement keeps them visible separately where possible rather than combining them into one assumed view.

Long-term sustainability needs outcome evidence as well as expenditure data

Sweden’s demographic transition increases the importance of understanding what municipal expenditure achieves.

Cost information is necessary, but cost alone cannot establish value.

A lower-cost home-help model may appear efficient while producing poor continuity, higher turnover and more emergency escalation. A preventive intervention may initially increase expenditure while helping people retain function and reducing later need.

Outcome measurement therefore becomes part of financial sustainability.

Leaders need to understand relationships between resource use, service intensity and results rather than treating each as a separate management topic.

The Digital Twin Scenario Modeller can help organisations explore comparable relationships between demand, workforce capacity, quality and future service stability. It is not based on Swedish municipal finance or care data, but the scenario principle is relevant when leaders need to test how different operating assumptions might affect future outcomes.

Outcome measurement will become more important as prevention expands

Sweden’s new Social Services Act places greater emphasis on preventive and accessible social services.

This creates a measurement challenge because prevention often aims to stop or delay something from happening.

A fall that does not occur, dependency that develops more slowly or loneliness that reduces before formal care becomes necessary can be difficult to attribute.

Preventive services should therefore avoid promising precision that the evidence cannot support.

They can still measure reach, participation, changes in relevant risk factors, self-reported outcomes and subsequent service patterns.

Over time, municipalities can compare trajectories and build stronger local evidence.

The aim should be credible learning rather than exaggerated claims of avoided cost.

Artificial intelligence may strengthen analysis but will not define quality

As Swedish social care becomes more data-rich, artificial intelligence and advanced analytics may increasingly help identify patterns in demand, workforce pressure, incidents or changing individual needs.

These technologies could support earlier review by identifying combinations of signals that human managers might struggle to detect across large datasets.

This remains an emerging opportunity rather than established national practice.

AI also creates governance questions around data quality, transparency, privacy and bias.

A predictive model trained on historical service use may reproduce existing inequalities if some groups previously had poorer access.

Most importantly, algorithms cannot decide what a good life means for an individual older person.

Technology may help measure, predict and prioritise. The definition of quality still requires human judgement, rights and person-centred values.

The stronger national measurement system connects three levels

Sweden’s future outcome infrastructure can be understood through three connected levels.

At individual level, assessment and review should establish whether support is achieving the person’s goals and responding to changing need.

At municipal and provider level, aggregated information should identify variation, service performance, equity and improvement priorities.

At national level, common indicators, surveys and registers should reveal wider trends and support evidence-based policy.

Each level depends on the others.

National indicators without good individual data become less meaningful. Individual care plans without aggregation limit organisational learning. Local dashboards without national comparison can make poor performance appear normal.

The strongest system therefore creates movement between all three.

International learning lies in combining comparison with interpretation

Sweden’s measurement arrangements are shaped by its decentralised municipalities, extensive national administrative infrastructure and tax-funded welfare system. Other countries may rely on insurance claims, regulator ratings, provider reporting or purchaser-specific outcome frameworks.

The institutional mechanisms therefore differ.

Several principles remain widely relevant.

First, activity should not be mistaken for outcome. Delivering care is not the same as demonstrating what the care achieved.

Second, national comparison is useful when it generates inquiry rather than simplistic ranking.

Third, lived experience should sit alongside safety and operational data because quality is partly defined by how care feels to the person receiving it.

Fourth, individual-level follow-up is essential if systems want to understand which interventions work for which people.

Fifth, workforce measures can provide leading warnings before quality deteriorates visibly.

Finally, measurement systems should be judged by what decisions they improve. Data accumulation is not an outcome in itself.

Conclusion

Sweden already possesses a substantial infrastructure for measuring older people’s care. Open Comparisons, municipal healthcare indicators, national statistics, service-level information and the recurring survey of people receiving home help and special housing provide visibility that a highly decentralised system needs. The next challenge is to make that evidence increasingly outcome-oriented.

The 2026 growth in individual-based systematic follow-up is encouraging, but its still limited reach shows how much development remains. Municipalities need to connect individual need, intervention and result more consistently while retaining the experience of older people who cannot easily participate through conventional measurement methods. Continuity, workforce stability, safety, independence and equity also need to be read together rather than as isolated indicators.

The strongest Swedish model will therefore not depend on finding one definitive quality score. It will combine national comparison with local interpretation, quantitative evidence with lived experience and retrospective reporting with earlier operational signals. It will also remain alert to the behaviours that metrics themselves create.

Ultimately, measurement should make care more understandable and improvable. The most valuable indicator is not the one that produces the cleanest dashboard, but the one that helps a municipality recognise where an older person’s experience is falling short, understand why, and make a change that can be shown to improve what happens next.