In fiscal year 2023-2024, the ages of residents in continuing care facilities (usually long-term care facilities in residential or hospital-based settings) in Canada averaged to around 83 years. Residents in hospital-based continuing care were slightly younger than those in residential facilities, with residents in Manitoba having the highest average age.

How many people live in nursing homes? As of 2024, there were around 1.2 million residents in nursing homes across the United States. The states with the highest numbers of residents in certified nursing facilities were, by far, California and New York, with over 99,000 and 98,000 residents, respectively. On the other hand, Alaska had the lowest number of nursing home residents. Occupancy rates and recovery The COVID-19 pandemic significantly impacted nursing home occupancy rates nationwide. Prior to the pandemic, the median occupancy rate for skilled nursing facilities hovered around 80 percent. However, this figure plummeted to 67 percent by 2021. As of July 2024, occupancy rates for certified nursing homes have begun to recover, reaching 77 percent. This gradual increase suggests a slow but steady return to pre-pandemic levels. Quality concerns and financial penalties Despite the crucial role nursing homes play, quality issues persist in some facilities. In 2024, Aspen Point Health and Rehabilitation in Missouri faced 208 substantiated complaints, the highest number nationwide. Financial penalties for serious violations can be severe, as evidenced by the 1.41 million U.S. dollar fine imposed on Siesta Key Health And Rehabilitation Center in Florida over a three-year period. These cases underscore the ongoing challenges in maintaining high standards of care across the industry.

Emerging research on family caregiving and institutionalization has emphasized that families do not disengage from care responsibilities following a relative's admission to residential long-term care settings. The Residential Care Transition Module (RCTM) provided 6 formal sessions of consultation (one-to-one and family sessions) over a 4-month period to those family caregivers who had admitted a cognitively impaired relative to a residential long-term care (RLTC) setting (nursing home, assisted living memory care unit). The mixed method, randomized controlled trial of RCTM aimed to decrease family caregivers' emotional and psychological distress, placement-related strain, and increase relative's transitions back to the community. The RCTM is a psychosocial intervention designed for families following RLTC placement to help families better navigate the residential care transitions of relatives with Alzheimer's disease or a related dementia.This longitudinal dataset was self-reported by caregivers about themselves and their care recipients over a 12-month period. The data include 133 variables and 240 cases.Demographic variables in this data file include participant treatment/control group assignment, age, gender, race, marital status, education, income, employment status, and relationship to the care recipient. Additionally, it includes care recipient age, gender, race, marital status, education, income, Medicaid status, type of residence, dichotomous dementia diagnosis, and time since placement in long-term care. Besides the summary scores of the scales described later, the data also include information on caregiver general health, sleep, emotional difficulties, and bereavement status. It also provides information on caregiver and care recipient adjustment to residential long-term care and the amount and length of typical visits by the caregiver to the care recipient. The number and average length of intervention and ad hoc sessions are included as well.

The mean and median age of long stay residents, as well as at the time of admission and discharge, by main client group.

In 2023, the number of residents in welfare facilities for the elderly requiring long-term care amounted to approximately 593 thousand. At the same time, there were around 96 thousand residents in moderate-fee homes.

This table provides an overview of the key figures on health and care available on StatLine. All figures are taken from other tables on StatLine, either directly or through a simple conversion. In the original tables, breakdowns by characteristics of individuals or other variables are possible. The period after the year of review before data become available differs between the data series. The number of exam passes/graduates in year t is the number of persons who obtained a diploma in school/study year starting in t-1 and ending in t.

Data available from: 2001

Status of the figures:

2024: Most available figures are definite. Figures are provisional for: - causes of death; - youth care; - persons employed in health and welfare; - persons employed in healthcare; - Mbo health care graduates; - Hbo nursing graduates / medicine graduates (university).

2023: Most available figures are definite. Figures are provisional for: - perinatal mortality at pregnancy duration at least 24 weeks; - diagnoses known to the general practitioner; - hospital admissions by some diagnoses; - average period of hospitalisation; - supplied drugs; - AWBZ/Wlz-funded long term care; - physicians and nurses employed in care; - persons employed in health and welfare; - average distance to facilities; - profitability and operating results at institutions. Figures are revised provisional for: - expenditures on health and welfare.

2022: Most available figures are definite. Figures are revised provisional for: - expenditures on health and welfare.

2021: Most available figures are definite, Figures are revised provisional for: - expenditures on health and welfare.f

2020 and earlier: All available figures are definite.

Changes as of 4 July 2025: More recent figures have been added for: - causes of death; - life expectancy; - life expectancy in perceived good health; - self-perceived health; - hospital admissions by some diagnoses; - sickness absence; - average period of hospitalisation; - contacts with health professionals; - youth care; - smoking, heavy drinkers, physical activity; - overweight; - high blood pressure; - physicians and nurses employed in care; - persons employed in health and welfare; - persons employed in healthcare; - Mbo health care graduates; - Hbo nursing graduates / medicine graduates (university); - expenditures on health and welfare; - profitability and operating results at institutions.

Changes as of 18 december 2024: - Distance to facilities: the figures withdrawn on 5 June have been replaced (unchanged). - Youth care: the previously published final results for 2021 and 2022 have been adjusted due to improvements in the processing. - Due to a revision of the statistics Expenditure on health and welfare 2021, figures for expenditure on health and welfare care have been replaced from 2021 onwards. - Due to the revision of the National Accounts, the figures on persons employed in health and welfare have been replaced for all years. - AWBZ/Wlz-funded long term care: from 2015, the series Wlz residential care including total package at home has been replaced by total Wlz care. This series fits better with the chosen demarcation of indications for Wlz care.

When will new figures be published? New figures will be published in December 2025.

The number of people switching from home to inpatient care has risen again following the containment of the coronavirus. The additional expenditure for hygiene concepts and staff and the simultaneous reduction in income, for example due to unoccupied care home places, put pressure on the profit margin of care homes. In recent years, care homes have also had to deal with a shortage of skilled workers and a reform of the healthcare system with various new regulations. Between 2020 and 2025, industry turnover fell by an average of 0.2% per year. The industry was able to compensate for the slump in turnover during the pandemic years.Care homes are under economic pressure. In addition to the after-effects of the coronavirus pandemic, high energy costs and inflation as well as rising wages have been additional cost drivers in recent years. Furthermore, the social welfare organisations only settle uncovered care home costs after long processing times. The cost increases, which cannot be fully refinanced, are leading to the closure of numerous care homes. Cost pressure and the worsening staff shortage are also expected to lead to occupancy freezes and capacity cuts in the current year and result in further closures. For 2025, an increase in turnover of 1.9% compared to the previous year and total turnover of 35.1 billion euros is therefore expected.Due to demographic change and the increasing life expectancy of the population, the care market is characterised by stable growth. The rise in the number of households with people over the age of 65 and the increasing number of people in need of care in Germany are ensuring a constant demand for care places and will favour a positive sales trend in the sector. This is another reason why sales are expected to grow by an average of 2.4% per year until 2030. Total turnover is expected to amount to 39.5 billion euros in 2030. However, the rising number of people in need of care is offset by an insufficient number of qualified nursing staff, which could widen the care gap. There is already a shortage of skilled workers in the industry today, which could worsen in the coming years.

This statistic shows the average nursing home revenue and net income comparing the states of Arizona and Florida to the national average, as of 2015. As of that year, nursing homes in Arizona generated an average of ***** million U.S. dollars in revenue. Among Americans over the age of 65, almost ** percent will require long-term care. As the U.S. senior population grows, there will be increased pressure from the quantity and quality of long-term health care facilities.

Health, medical care and caregiving include average life expectancy at birth, age of death - mean, age of death - median, cancer death age - mean, cancer death age - median, mortality rate (all causes of death), malignant tumor mortality rate, accidental injury mortality rate, deliberate self-harm (suicide) mortality rate, infant mortality, maternal mortality rate, number of maternal deaths, number of prenatal inspection declarations for pregnant women, breast cancer screening in women aged 45-69 within 2 years, number of HIV infections, smoking rate among population aged 18 and above, actual placement of service personnel in disability welfare service institutions, long-term care, nursing and residential care institutions, actual number of residents in day care services - elderly with dementia, number of day care service cases - elderly with disabilities.

According to Cognitive Market Research, the global Retirement Home Services market is growing at a compound annual growth rate (CAGR) of 3.90% from 2023 to 2030. Rising Global Life Expectancy Is Driving The Growth of the Market

People are living longer lives than they were a few decades ago. This is due to low rates of cardiovascular and infectious disease mortality. The majority of deaths in the world were caused by three primary health conditions: ischemic heart disease, chronic obstructive pulmonary disease (COPD), and stroke.

Since the 1990s, the average number of fatalities has grown. The number of people dying from illnesses such as heart disease has increased as the world population has grown.

The decrease in age-specific mortality rates for various illnesses is evidence of the healthcare industry's success.Life expectancy increases as a result of breakthroughs in public healthcare facilities and significant developments in the healthcare business, as well as higher living standards, increased nutrition, better education, and lifestyle changes. An individual's global average age is mostly determined by living conditions and place of residence. These factors will boost market growth during the forecast period.

Technological Developments Will Boost Market Expansion

During the forecast period, technological advancements in long-term healthcare are anticipated to propel market expansion. This is brought on by the increase in Internet usage, which has sparked the development of online marketplaces, mobile apps, and mHealth. There is a rising need for support services including smartphone apps, trackers, wearables, communication tools, and smart alarms. These tools allow nurses and caregivers to monitor, document, and observe patients as well as connect with medical specialists.The use of computer and mobile phone-based patient data management among these technologies is spreading throughout long-term care.

Apps that create electronic health records (EHRs) and mobile health records (MHRs) are now available, making it simpler for consumers and healthcare professionals to access and exchange health information.

(Source:health-e.in/blog/phr-apps-india/)

The main technological advancements are mHealth and mobile-based healthcare applications that produce electronic health records (EHRs) and mobile health records (MHRs). When there are medical emergencies, other technologies, like alarm integration methods, are employed to notify service providers and caregivers. As they lessen the dependency on carers, smart houses are becoming more popular in industrialized nations. Thus, the market's expansion over the course of the forecast period will be fueled by the rising acceptance of such cutting-edge technical solutions.

The Aspects of the Retirement Home Services Market are Limitingits Growth

Negative Reputation Of Retirement Homes Is A Significant Barrier To Market Growth

Though living in the comfort of one's own home is always preferable, living in an old age home has its advantages. However, just a few old age facilities provide the bare minimum of quality for a comfortable stay. The cost of services supplied by old age homes is heavily influenced by the quality of those services. Many individuals enroll in retirement homes that lack basic infrastructure and services because they cannot afford the hefty service fees. Residents at nursing facilities are rarely given privacy. The environment in certain nursing facilities frequently results in despair, boredom, neglect, and, in some cases, abuse.

Impact of COVID-19 on The Retirement Home Services Market

Due to the risk of getting the virus in communal living arrangements, the pandemic has reduced demand for retirement homes. However, the epidemic has increased demand for retirement homes that provide specialized nursing care services. Retirement homes that provide specialized services for nursing care are growing more popular as individuals seek a safe and comfortable place to live. Introduction of Retirement Home Services

A retirement home is a multi-residence living complex designed for the elderly, sometimes known as an old people's home or old age home. Everyone or a couple resides in a room or suite of rooms that is akin to an apartment. There are more facilities in the building. This will include places for gathering, eating, playing, and receiving some kind of healt...

This statistic shows the average annual per-person payments for health and long-term care services for people above the age of 65 years suffering from Alzheimer's or other dementias in the United States, as of 2015, by place of residence. The average annual per-person payment made by Medicare for such services in residential facilities was 25,600 U.S. dollars.

Abstract Objective: to analyze the relationship between the level of frailty and sociodemographic and health characteristics among elderly residents of a long-term care facility (LTCF) in Ribeirão Preto, São Paulo, Brazil. Method: this descriptive and cross-sectional study included 56 elderly persons living in a LTCF. Data were collected from April to June 2016. A questionnaire addressing sociodemographic and health profiles was used together with the Mini-Mental State Examination, the Tilburg Frailty Indicator, the Barthel Index, and the Geriatric Depression Scale (GDS-15). Descriptive statistics were applied. The normality of the continuous variables was tested using the Shapiro-Wilk test. Spearman’s correlation was used for the continuous variables with frailty as the dependent variable. Result: Most elderly individuals were female (57.1%); the average age was 77.77; and 35.7% were widowed. In terms of health, 55.4% presented cognitive deficit; 62.5% had depression symptoms; 75.0% were considered frail; 42.9% had suffered falls in the last 12 months; and the individuals scored an average of 68.30 in the Barthel Index. A positive correlation between the frailty score and the GDS-15 (r=0.538; p=0.00) was observed, while a negative correlation was found between frailty and the Barthel Index (r=-0.302; p=0.02). Conclusion: increased frailty among institutionalized elderly persons is correlated with the presence of depressive symptoms and inferior performance of basic activities of daily living. The results of the present study can support the planning of care provided to elderly individuals living in LTCFs and encourage broader assessments of these individuals.

The immune response is known to wane after vaccination with BNT162b2, but the role of age, morbidity and body composition is not well understood. We conducted a cross-sectional study in long-term care facilities (LTCFs) for the elderly. All study participants had completed two-dose vaccination with BNT162b2 five to 7 months before sample collection. In 298 residents (median age 86 years, range 75–101), anti-SARS-CoV-2 rector binding IgG antibody (anti-RBD-IgG) concentrations were low and inversely correlated with age (mean 51.60 BAU/ml). We compared the results to Health Care Workers (HCW) aged 18–70 years (n = 114, median age: 53 years), who had a higher mean anti-RBD-IgG concentration of 156.99 BAU/ml. Neutralization against the Delta variant was low in both groups (9.5% in LTCF residents and 31.6% in HCWs). The Charlson Comorbidity Index was inversely correlated with anti-RBD-IgG, but not the body mass index (BMI). A control group of 14 LTCF residents with known breakthrough infection had significant higher antibody concentrations (mean 3,199.65 BAU/ml), and 85.7% had detectable neutralization against the Delta variant. Our results demonstrate low but recoverable markers of immunity in LTCF residents five to 7 months after vaccination.

In 2022, residential care in the United Kingdom was most expensive in the South East, Scotland, and London with weekly fees of over *** British pounds. Care homes vary in the type of services they offer to elderly people. Residential care homes, for instance, are suitable for adults who are mostly independent but could use some assistance in day to day living such as dressing, washing, doing laundry or taking medicine. Nursing homes, on the other hand, offer 24-hour medical supervision. An ageing population increases the importance of retirement living properties and services that suit the needs of residents.

BackgroundFor the oldest-old residents around their 90s living in facilities, quality end-of-life care is crucial. While an association between reduced food intake and death is known, specific patterns of intake changes before death are not well-documented.AimsThis study aims to classify food intake changes among residents in Japan’s special nursing homes during the 6 months before death, enabling precision care for each group using routinely recorded data.MethodsSixty-nine deceased older adults from five special nursing homes were studied over 3.5 years (January 2016 to June 2020). Criteria included: at least six months’ residency before death, ability to eat orally during the study period, and death within the facility. We created a time-series dataset for 69 participants, documenting their average weekly food intake (on a scale of 0-10). Subsequently, we used cluster analysis to identify clusters of change in the average weekly food intake from the 6 months before death.ResultsEligible residents’ mean age was 89.7 ±  6.7 years, and 79.7% were female. Cluster analysis classified 4 clusters of decline in food intake changes during the last 6 months before death: immediate decrease (n = 14); decrease from 1 month before death (n = 24); decrease from 3 months before death (n = 7); and gradual decrease for 6 months before death (n = 24).ConclusionThis study identified four groups of food intake prior to death. Recognizing food intake clusters in practical settings can help manage and provide appropriate end-of-life care in facilities with few medical providers but many care providers.

These population projections were prepared by the Australian Bureau of Statistics (ABS) for Geoscience Australia. The projections are not official ABS data and are owned by Geoscience Australia. These projections are for Statistical Areas Level 2 (SA2s) and Local Government Areas (LGAs), and are projected out from a base population as at 30 June 2022, by age and sex. Projections are for 30 June 2023 to 2032, with results disaggregated by age and sex.

Method The cohort-component method was used for these projections. In this method, the base population is projected forward annually by calculating the effect of births, deaths and migration (the components) within each age-sex cohort according to the specified fertility, mortality and overseas and internal migration assumptions. The projected usual resident population by single year of age and sex was produced in four successive stages – national, state/territory, capital city/rest of state, and finally SA2s. Assumptions were made for each level and the resulting projected components and population are constrained to the geographic level above for each year.
These projections were derived from a combination of assumptions published in Population Projections, Australia, 2022 (base) to 2071 on 23 November 2023, and historical patterns observed within each state/territory.

Projections – capital city/rest of state regions The base population is 30 June 2022 Estimated Resident Population (ERP) as published in National, state and territory population, June 2022. For fertility, the total fertility rate (at the national level) is based on the medium assumption used in Population Projections, Australia, 2022 (base) to 2071, of 1.6 babies per woman being phased in from 2022 levels over five years to 2027, before remaining steady for the remainder of the projection span. Observed state/territory, and greater capital city level fertility differentials were applied to the national data so that established trends in the state and capital city/rest of state relativities were preserved. Mortality rates are based on the medium assumption used in Population Projections, Australia, 2022 (base) to 2071, and assume that mortality rates will continue to decline across Australia with state/territory differentials persisting. State/territory and capital city/rest of state differentials were used to ensure projected deaths are consistent with the historical trend. Annual net overseas migration (NOM) is based on the medium assumption used in Population Projections, Australia, 2022 (base) to 2071, with an assumed gain (at the national level) of 400,000 in 2022-23, increasing to 315,000 in 2023-24, then declining to 225,000 in 2026-27, after which NOM is assumed to remain constant. State and capital city/rest of state shares are based on a weighted average of NOM data from 2010 to 2019 at the state and territory level to account for the impact of COVID-19. For internal migration, net gains and losses from states and territories and capital city/rest of state regions are based on the medium assumption used in Population Projections, Australia, 2022 (base) to 2071, and assume that net interstate migration will trend towards long-term historic average flows.

Projections – Statistical Areas Level 2 The base population for each SA2 is the estimated resident population in each area by single year of age and sex, at 30 June 2022, as published in Regional population by age and sex, 2022 on 28 September 2023. The SA2-level fertility and mortality assumptions were derived by combining the medium scenario state/territory assumptions from Population Projections, Australia, 2022 (base) to 2071, with recent fertility and mortality trends in each SA2 based on annual births (by sex) and deaths (by age and sex) published in Regional Population, 2021-22 and Regional Population by Age and Sex, 2022. Assumed overseas and internal migration for each SA2 is based on SA2-specific annual overseas and internal arrivals and departures estimates published in Regional Population, 2021-22 and Regional Population by Age and Sex, 2022. The internal migration data was strengthened with SA2-specific data from the 2021 Census, based on the usual residence one year before Census night question. Assumptions were applied by SA2, age and sex. Assumptions were adjusted for some SA2s, to provide more plausible future population levels, and age and sex distribution changes, including areas where populations may not age over time, for example due to significant resident student and defence force populations. Most assumption adjustments were made via the internal migration component. For some SA2s with zero or a very small population base, but where significant population growth is expected, replacement migration age/sex profiles were applied. All SA2-level components and projected projections are constrained to the medium series of capital city/rest of state data in Population Projections, Australia, 2022 (base) to 2071.

Projections – Local Government Areas The base population for each LGA is the estimated resident population in each area by single year of age and sex, at 30 June 2022, as published in Regional population by age and sex, 2022 on 28 September 2023. Projections for 30 June 2023 to 2032 were created by converting from the SA2-level population projections to LGAs by age and sex. This was done using an age-specific population correspondence, where the data for each year of the projection span were converted based on 2021 population shares across SA2s. The LGA and SA2 projections are congruous in aggregation as well as in isolation. Unlike the projections prepared at SA2 level, no LGA-specific projection assumptions were used.

Nature of projections and considerations for usage The nature of the projection method and inherent fluctuations in population dynamics mean that care should be taken when using and interpreting the projection results. The projections are not forecasts, but rather illustrate future changes which would occur if the stated assumptions were to apply over the projection period. These projections do not attempt to allow for non-demographic factors such as major government policy decisions, economic factors, catastrophes, wars and pandemics, which may affect future demographic behaviour. To illustrate a range of possible outcomes, alternative projection series for national, state/territory and capital city/rest of state areas, using different combinations of fertility, mortality, overseas and internal migration assumptions, are prepared. Alternative series are published in Population Projections, Australia, 2022 (base) to 2071. Only one series of SA2-level projections was prepared for this product. Population projections can take account of planning and other decisions by governments known at the time the projections were derived, including sub-state projections published by each state and territory government. The ABS generally does not have access to the policies or decisions of commonwealth, state and local governments and businesses that assist in accurately forecasting small area populations. Migration, especially internal migration, accounts for the majority of projected population change for most SA2s. Volatile and unpredictable small area migration trends, especially in the short-term, can have a significant effect on longer-term projection results. Care therefore should be taken with SA2s with small total populations and very small age-sex cells, especially at older ages. While these projections are calculated at the single year of age level, small numbers, and fluctuations across individual ages in the base population and projection assumptions limit the reliability of SA2-level projections at single year of age level. These fluctuations reduce and reliability improves when the projection results are aggregated to broader age groups such as the five-year age bands in this product. For areas with small elderly populations, results aggregated to 65 and over are more reliable than for the individual age groups above 65. With the exception of areas with high planned population growth, SA2s with a base total population of less than 500 have generally been held constant for the projection period in this product as their populations are too small to be reliably projected at all, however their (small) age/sex distributions may change slightly. These SA2s are listed in the appendix. The base (2022) SA2 population estimates and post-2022 projections by age and sex include small artificial cells, including 1s and 2s. These are the result of a confidentialisation process and forced additivity, to control SA2 and capital city/rest of state age/sex totals, being applied to their original values. SA2s and LGAs in this product are based on the Australian Statistical Geography Standard (ASGS) boundaries as at the 2021 Census (ASGS Edition 3). For further information, see Australian Statistical Geography Standard (ASGS) Edition 3.

Made possible by the Digital Atlas of Australia The Digital Atlas of Australia is a key Australian Government initiative being led by Geoscience Australia, highlighted in the Data and Digital Government Strategy. It brings together trusted datasets from across government in an interactive, secure, and easy-to-use geospatial platform. The Australian Bureau of Statistics (ABS) is working in partnership with Geoscience Australia to establish a set of web services to make ABS data available in the Digital Atlas of Australia.

Contact the Australian Bureau of Statistics If you have questions or feedback about this web service, please email geography@abs.gov.au. To subscribe to updates about ABS web services and geospatial products, please complete this form. For information about how the ABS manages any personal information you provide view the ABS privacy policy.

Data and geography references Source data publication: Population Projections, Australia, 2022 (base)

In 2020, is was forecast the number of nursing home beds needed to fulfill demand by 2030 amounted to 75 thousand beds in Sweden, Finland, and Denmark. Based on the number of older people and the forecast average care need, it was estimated that between 2020 and 2030, Sweden should create 35 thousand nursing home beds to answer the demand.

Emergency hospital admissions for fracture neck of femur, indirectly age standardised ratio, 65 years and over, persons.

Rationale Hip fracture is a debilitating condition. Only one in three sufferers return to their former levels of independence and one in three ends up leaving their own home and moving to long-term care. Hip fractures are almost as common and costly as strokes, and the incidence is rising. In the UK, about 75,000 hip fractures occur annually at an estimated health and social cost of about £2 billion a year. The National Institute for Health and Clinical Excellence (NICE) has projected the incidence to increase by 34% in 2020, with an associated increase in annual expenditure (NICE Guideline last accessed 12/04/2017). The average age of a person with hip fracture is about 83 years, and about 73 percent of fractures occur in women. There is a high prevalence of comorbidity in people with hip fracture (NHFD Report 2013). The National Hip Fracture Database reports that mortality from hip fracture is high, about one in ten people with a hip fracture die within 1 month and about one in three within 12 months. NICE has produced a quality standard that covers the management and secondary prevention of hip fracture in adults (18 years and older). The standard is designed to drive measurable improvements in the three dimensions of quality: patient safety, patient experience, and clinical effectiveness for fragility, fracture of the hip, or fracture of the hip due to osteoporosis or osteopenia.

Definition of numerator Emergency admissions with an admission method (ADMIMETH in list '21', '22', '23', '24', '25', '28', '2A','2B', '2C', '2D); defined by a primary diagnosis (ICD10) code of S720, S721 or S722 and patient classification 'ordinary' (1 or 2), episode status is equal to 3, epiorder is equal to 1. These values have not been published due to disclosure control (see 'Disclosure control' section for further details).

Definition of denominator Applying the reference (England) age specific rates to the registered local population to give number of expected admissions. These values have not been published due to disclosure control (see 'Disclosure control' section for further details).

Caveats NHS Digital has identified a data quality issue affecting HES data for Nottingham University Hospitals Trust (NUH) in the financial year 2016 to 2017. Over 30 percent of records from this trust did not have a valid geography of residence assigned. PHE have flagged the areas affected by this issue as the values should be treated with caution. For more details, see: NHS Digital

Many western European countries rely heavily on home care or informal methods to care for the elderly. In 2020, nearly ************* German elderly people potentially received informal care, while ************ received home care, and *********** were formally cared for by an institution. Elderly care in Italy and France also relied heavily on informal care. Why does Europe rely on informal care? Informal care is typically delivered within families and households and while difficult to quantify is very common. Indeed, an important share of healthcare expenditure is spent on long-term residential care in European countries. Therefore, some governments encourage and incentivize informal care to reduce healthcare expenditure by the state. For instance, Italian workers are granted up to ** days of paid leave per year to provide care to dependent relatives, while French employees are entitled to ** days of paid leave. In addition, the extent of informal care can also be the result of economic factors. In 2019, the average monthly cost of care homes reached ************** euros in some European countries. A sustainable strategy for European healthcare systems? The elderly population is expected to grow significantly in Europe. In 2020, Italy had notably the highest old-age dependency ratio in Europe, with a rate of **** people aged over ** to 100 people of working age. Furthermore, the ability of many families to assist elderly relatives is decreased with the loss of multi-generational household culture in modern Western Europe. Finally, some health conditions linked to elderly age require specialist nursing and a residential care setting. Therefore, although a heavy reliance on informal care can reduce healthcare costs, it could be a risky strategy to hold on in the long run.