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Data set notes

European Health for All database

Indicators: 565

Updated: 18 October 2024

Contact: Data and Digital Health Unit (DDH)

The following abbreviations are used in the indicator titles:

• SDR: age-standardized death rates (see HFA-DB user manual/Technical notes, page 13, for details)

• FTE: full-time equivalent

• PP: physical persons

• PPP$: purchasing power parities expressed in US $, an internationally comparable scale reflecting the relative domestic purchasing powers of currencies.

More information: http://www.euro.who.int/en/data-and-evidence/databases/european-health-for-all-database-hfa-db

Indicator notes

Average length of stay, all hospitals
Indicator code: E992901.T

Total number of occupied hospital bed-days divided by the total number of admissions or discharges. Length of stay (LOS) of one patient = date of discharge - date of admission. If these are the same dates, then LOS is set to one day. ALOS (Average length of stay) should preferably be provided to the accuracy of hundreds, i.e. 0.01.

For countries participating in the Joint Eurostat / OECD / WHO Europe data collection on health care activities (for year 2012 those were: Austria, Belgium, Bulgaria, Croatia, Cyprus, Czech Republic, Denmark, Estonia, Finland, France, Germany, Greece, Hungary, Iceland, Ireland, Israel, Italy, Latvia, Lithuania, Luxembourg, Malta, Netherlands, Norway, Poland, Portugal, Romania,, Slovak Republic, Slovenia, Spain, Sweden, Switzerland, The former Yugoslav Republic of Macedonia, Turkey and United Kingdom), following definition was used:

Hospital aggregates: Inpatient care

b) Inpatient care average length of stay (ALOS) (all hospitals)

Average length of stay (ALOS) is calculated by dividing the number of bed-days by the number of discharges during the year (see definition for hospital ALOS below). Only the overall average length of stay in all hospitals is requested (no breakdown by diagnostic categories)._

Country/Area notes

Albania

Ministry of Health.

Armenia

Source of data: National Health Information Analytic Center, Ministry of Health of the Republic of
Armenia http://moh.am/?section=static_pages/index&id=625&subID=824,29.
Data collected annually, reference period: 31 December.

Austria

See indicator 992952.

Belgium

Source: Federal Public Service of Public Health, Food Chain Safety and Environment. Health Care
Facilities Organization (DG1), Minimal Clinical Data for 2007 is provisional data.

Bosnia and Herzegovina

Available up to the war time on yearly. Source: CSO war period just for the part of FBIH. Public
Health Institute of Federation of B&H; Department for Health Statistics and Informatics
Public Health Institute of Republic of Srpska- Department for Social medicine, with Health
Organization and Health Economics. Law on health evidence and statistical research in health. Annual
report of hospitals.
Department for Health of Brcko District

Czechia

Source: Institute of Health Information and Statistics of CR (IHIS CR). Survey on bed resources of
health establishments and their exploitation. Coverage: Data relates to General hospitals and
Specialized therapeutic institutes (excluding Balneologic institutes).
Deviation from the definition: Hospitalized newborns are included.
Break in time series: Until 1999 data covers only establishments of the Health Sector. From 2000
data covers also health establishments of other central organs.

Denmark

Data from 1995 onwards include psychiatric departments.

Estonia

Bed-days are divided by the total number of discharges. Source: annual reporting, National Institute
for Health Development.

Finland

Source: Hospital Discharge Register, THL (National Institute for Health and Welfare).

Georgia

Source: National Centre for Disease Control and Public Health of Georgia (NCDC) (http://www.ncdc.ge)

Germany

Data refer to ALOS in all types of hospitals (HP1.1, 1.2 and 1.3) and all sectors (public,
not-for-profit and private). Included are general hospitals, mental health hospitals and prevention
and rehabilitation homes. Long-term nursing care facilities are excluded. ALOS is calculated by
dividing the bed-days by the \number of cases\". The \"number of cases\" is equal to the sum of
admissions plus the discharges including deaths divided by 2. As of reporting year 2002 the number
of admissions and discharges includes day cases (patients admitted for a medical procedure or
surgery in the morning and released before the evening). Source: Federal Statistical Office

Hungary

Source until 2003: Center for Health Care Information (GYOGYINFOK). The data is the case number of
department discharges. Source from 2004: National Institute for Strategic Health Research (ESKI) and
the data is the average length of stay at the hospitals.

Iceland

The same hospitals as in indicator 275210 and 992952. Day care included to some extent before 1989.
Newborns (Z38) are excluded from 2008 and onwards. Source: The Directorate of Health / The Ministry
of Health and Social Security.

Break in series in 2008 due to the fact that data in the National Patient Discharge Register has
been updated /corrected.

Until 2008 newborns (Z38) have been included. This will be corrected next year along with other
corrections.

Ireland

Source: Health Service Executive. Data prior to 2006 comes from the Department of Health and
Children. The number of bed days used divided by the number of in-patients discharged (including
deaths, excluding day cases). The in-patient ALOS refers to all specialties, regardless of length of
stay, in HSE Network acute public hospitals, public and private psychiatric hospitals,
district/community public hospitals and other public hospitals not elsewhere classified. Beds in
private hospitals are not included. Break in Series: Public and private psychiatric hospitals are
included since 2004. District/community public hospitals and other public hospitals not elsewhere
classified are not included from 2009.

Israel

Includes all hospitals. Source: Department of Health Information, Ministry of Health.

Italy

Source: Ministry of Health. Data are referred to hospitals under indicator 275210. Clinical data
gathered in the hospital discharges database are coded with the following versions: until 2005 with
ICD9-CM version 1997, from 2006 to 2008 with ICD9-CM version 2002, since 2009 with the ICD9-CM
version 2007.

Lithuania

Source: Up to 2000: LHIC annual report data. From 2001: HI HIC data from annual reports and
Compulsory Health Insurance Database (for day cases). Coverage: Up to 2000: including day cases.
From 2001: excluding day cases.

Malta

Figures relate to public hospitals only.

Montenegro

Source: Institute of Public Health.

Netherlands

Breaks in series: 2002 and later includes healthy new born infants if mother was inpatient. Source
for 2006 and later is annual reports, Social Accountint and National Medical Registration. Includes
mental hospitals. Bed-days of newborns are excluded in the calculation. Statistics Netherlands:
Statistics of intramural health care; National Medical Registration.

North Macedonia

Source: Institute for Public Health (IPH).

Poland

Source: Ministry of Health.

Portugal

Source of data: National Statistical Institute Coverage: National

Romania

Calculated as: (Number occupied bed-days)/Number admissions+patients at beginning of calculation
period)

Serbia

Source: Institute of Public Health of Serbia.

Slovenia

Institute of Public Health of the Republic of Slovenia, Ljubljana 1996.

Spain

Total number of occupied hospital bed-days / total number of discharges. Source up to 1996:
National Statistics Institute and Ministry of Health and Consumer Affairs. Statistics on Health
Establishments Providing Inpatient Care. Source from 1996:Ministry of Health and Consumer Affairs
(www.msc.es/)

Sweden

Source: National Patient Register NBHW.

Switzerland

Computation according to ALOS. Source of data: FSO Federal Statistical Office, Neuchatel; Hospitals
Statistics; yearly census.
Coverage: Full coverage of hospitals.
Deviation from the definition: -
Estimation method: -
Break in time series: -

Türkiye

Source: General Directorate of Curative Services. Method: Average length of stay in the Ministry of
Health, university, and private hospitals.

Turkmenistan

Source of data: Administrative medical statistics, form 14 ?Report on hospital activity?.
Calculation method: Total number of occupied hospital bed-days divided by the total number of
discharges.

Ukraine

For hospitals under Ministry of Health only.
Source: Centre of Health Statistics, Ministry of Health

United Kingdom

Source of Data: England - NHS Information Centre.
Scotland - - NHS National Services Scotland, Information Services Division (ISD).
Wales - NHS Wales Informatics Service (NWIS), Patient Episode Database.
N. Ireland - Department for Health, Social Services and Public Safety, KH03.

Coverage: Data is for inpatients only and excludes day patients. Data is for NHS activity or NHS
commissioned activity in the independent sector.

Estimation Method: Scotland could not provide 2010 data due to data completeness issues and so this
figure has been estimated using 2009 data for Scotland. This figure will be revised when 2010 data
for Scotland is available.

Break in Time Series: Data from 2000 onwards is not comparable with data from prior to this. This
is due to work conducted to improve compliance with definitions and consistency of methodologies
across the four parts of the UK.
Scotland - Changes in total length of stay are due to the improvement in the methodology for
combining SMR04 and Geriatric long stay (GLS) records with acute SMR01 records. This is due to
incomplete fields on SMR04 and GLS which are required to define complete hospital spells. There is
also a slight problem with identifying in-patients on SMR02 as all maternities are counted as
in-patients even though there may be a stay of 0 days.
2010 - All data is financial year data with the exception of Scotland whose data is calendar year.

General notes

What is the Average Length of Stay in All Hospitals?

The average length of stay in hospitals is a critical healthcare indicator that measures the average number of days a patient spends in a hospital during a single admission. This metric is essential for understanding hospital efficiency, patient care quality, and overall healthcare system performance. By analyzing this data, healthcare providers and policymakers can identify trends, allocate resources more effectively, and implement strategies to improve patient outcomes and hospital management. The average length of stay is influenced by various factors including the severity of the medical condition, the type of treatment received, and the healthcare policies in place.

How to Calculate the Average Length of Stay in All Hospitals?

To calculate the average length of stay in hospitals, healthcare analysts divide the total number of patient days spent in the hospital by the number of admissions over a specific period. The formula is straightforward: Average Length of Stay = Total Patient Days / Total Admissions. This calculation provides a clear picture of how long, on average, patients are hospitalized, which is crucial for assessing hospital performance and planning. Accurate data collection and processing are vital for this calculation to ensure that the results are reliable and reflect the true state of hospital operations.

Importance of the Average Length of Stay in All Hospitals

The average length of stay in hospitals is more than just a number; it is a significant health system performance indicator. Shorter stays can indicate efficient care and good patient outcomes, whereas longer stays may point to potential issues in patient management or hospital processes. Health systems use this data to optimize hospital bed management, improve patient care, and reduce healthcare costs. Additionally, understanding this metric helps in strategic planning and resource allocation, ensuring that hospitals can meet the demands of patient care without compromising quality.

Strengths and Limitations of the Average Length of Stay in All Hospitals

While the average length of stay is a valuable metric for hospital management and healthcare analysis, it comes with its own set of strengths and limitations.

Strengths

The primary strength of measuring the average length of stay lies in its ability to provide insights into hospital efficiency and patient care. It helps healthcare providers identify potential areas for improvement in treatment processes and patient management. Furthermore, this metric is beneficial for benchmarking performance across different hospitals and health systems, fostering a competitive environment that can lead to enhanced healthcare services.

Limitations

However, the average length of stay has limitations that must be considered. This metric can be skewed by extreme values, such as unusually long or short stays, which may not accurately represent the general patient experience. Additionally, it does not account for the complexity of individual cases; patients with severe or multiple health issues might require longer stays, which could unfairly reflect on the hospital's performance metrics. Moreover, external factors such as healthcare policies, availability of technology, and socioeconomic conditions can also influence the average length of stay, making it challenging to compare across different regions or countries effectively.

In conclusion, while the average length of stay is a crucial indicator for hospital and healthcare system performance, it must be interpreted with an understanding of its broader context and limitations. By doing so, healthcare providers can better utilize this metric to enhance patient care and operational efficiency.