Hospital Episode Statistics Inpatient and Maternity (England), 1989- : ADRN

<p>Abstract copyright ADRN and data collection copyright owner.</p><div class="ExternalClassB4585116C42D4E478834B97C93A2304A"><div class="ExternalClassF3195852D1EB48E78A3D3C8153C44270" style="text-align&#58;justify;"><p>Hospital Episode Statistics (HES) is a data warehouse that details admissions to all NHS trusts in England, including acute hospitals, primary care trusts and mental health trusts. HES information is stored as a large collection of separate records – one for each period of care – in a secure data warehouse. The information is collected into three main datasets&#58; Inpatient (including maternity), Outpatient and Accident &amp; Emergency. The data is collected during a patient’s time at hospital and is submitted to allow hospitals to be paid for the care they deliver. HES data is designed to enable secondary use for non-clinical purposes.</p><p>The Inpatient (including maternity) dataset provides a wide variety of information on admissions to NHS hospitals including patient details, when and where they were treated, care period, diagnosis, discharge, and geographical data. It also contains finished and unfinished episodes for every consultant, nurse and midwife. The data is collected by the Secondary Uses Service (SUS) who liaise with health care providers and commissioners. Typically, there are more than 15 million records in the Inpatient dataset.</p><p>The dataset covers all patient admissions (including maternity) to NHS Trusts in England. It does not cover accident &amp; emergency attendances or outpatient admissions (there are separate datasets for these), or the admission of English patients to hospitals outside of England. Primary care data is also not included.</p><p>The <strong><em>Inpatient dataset </em></strong>has been produced annually since 1989/90 covering the period 1st April to 31st March of each year. The database is updated annually and availability and summary information is published in December, following the previous financial year.</p><p>You must take care when conducting time series analysis of any HES datasets as variable inconsistencies may occur. You may need to look out for changes in the structure of an NHS organisation or Trust, new coding schemes introduced and ‘Best Practice’ procedures being changed or updated. As information is collected directly from NHS organisations, there could be data quality issues specific to a particular year as well. </p><p>As the Inpatient dataset is widely used by Government departments and other key stakeholders, data quality is of paramount importance. Regular checks are applied throughout the year and where problems occur the HES data quality team contact the individual Trusts. At the end of each financial year both a manual and automatic clean is applied to all HES data. Manual cleans occur through the application of specific rules at a Trust level. Some Trusts also specify their own rules to correct data as well. Automatic cleans are a set of rules which are applied to the dataset as a whole where data appears to be either inconsistent or invalid.</p><p>All HES datasets are reliant on hospitals and Trusts to provide accurate and reliable information, however data inconsistencies will remain and HSCIC do their best to reduce these shortcomings through vigorous data quality checks. When conducting longitudinal analyses please find out and take into account any geographical boundary changes for hospitals and Trusts.</p><p><strong>Research Usage and Linkage</strong></p><p>The size, complexity and richness of the Inpatient dataset provides enormous flexibility for wide ranging research purposes. For example it can be used to look at regional variations in waiting times and performance of Hospitals and Trusts and numbers of different operating procedures. It can also be used to provide detailed information on different patient diagnoses, outcomes and injuries, such as hip replacements, alcohol and drug related conditions, broken limbs, pregnancy, malnutrition and death.</p><p>The Government, Department for Health, NHS and many other organisations use the dataset to a wide extent to inform and evidence decisions for resource allocation, policy development, performance management and accountability purposes. It is also used by the Healthcare Commission to publish performance indicators for NHS organisations and respond to parliamentary questions.</p><p>HES data also feeds into the Compendium of Clinical and Health Indicators (formerly known as the Public Health Common dataset) and is widely used by clinical researchers for health research.</p><p>In theory, all HES and HSCIC datasets can be linked together as they contain unique identifiers such as National Health Service Number, year of birth, sex, name and postcode. HSCIC has a dedicated Data Linkage and Extract Service to perform the linkage and matching process. </p><p>HSCIC routinely linked datasets together to provide better decisions about care, improve quality and safety standards and identify developing trends in population health. These are as follows&#58;</p><p><em>1. Hospital Episode Statistics linked to Patient Reported Outcome Measures</em></p><p>Data from PROMs questionnaires alone allows for a wide range of basic analysis but is limited by the lack of more detailed information about patients and their hospital stays. Linking PROMs to hospital inpatient episodes data from HES gives a much richer data set which provides the ability to analyse the data by patient demographics and by the extensive procedure and diagnosis information which are present in HES. </p><p><em>2. Hospital Episode Statistics linked to Mortality Data from the Office for National Statistics </em></p><p>Linking HES data to mortality data from the Office for National Statistics permits the analysis of deaths in and outside hospital for all patients with a record in HES. It is also a rich source of data for analysis on a wide range of subjects including outcomes of hospital care, such as postoperative mortality. </p><p><em>3. Hospital Episode Statistics linked to Mental Health Minimum Data Set</em></p><p>The linkage between HES and MHMDS is provided as a bridging file which enables mental health records to be matched with records in HES through a pseudonym that protects the identity of individual patients. This enables analysis of acute patient pathways for mental health service users in England, which could be used to assess equality of access or identify opportunities for service improvement. </p><p>The HES datasets has been linked to other external datasets with varying degrees of success. For example, the inpatient admissions dataset has been linked with the General Practice Research database for in depth analysis of primary care and hospitalisation, and also linked to police records to analyse the circumstances and medical consequences of road accidents. It has also been linked with the STATS19 Road Accident dataset and the Millennium Cohort Study. Consent has also been requested to link HES data to the English Longitudinal Study of Ageing and the Health Survey for England.</p></div>