Skip to main content
UKCRC Health Research Classification System

Yan test editorial

Heading 2

Heading 3

Heading 4

Kim test anchor link 2

Lorem ipsum dolor sit amet, consectetur adipiscing elit. Fusce in eros cursus, pharetra nisi dignissim, tempus nibh. Etiam a imperdiet mauris, nec condimentum enim. Sed quis turpis ut ligula laoreet luctus nec vel tortor. Quisque tellus ante, sagittis sed lacus vulputate, hendrerit blandit diam. Vestibulum porta lacus nec odio elementum pharetra vitae nec sapien. Aenean purus mi, egestas in tempus at, sollicitudin ac augue. Nullam porttitor malesuada tincidunt. Praesent eu porttitor felis. Praesent odio lorem, fermentum et lacus eu, semper mattis tellus. Integer vitae urna est.

Use the font editing tools such as bullet points, numbered lists and pull in quotations etc… Oh yeah, and don’t forget internal, external and anchor links.

ANCHOR LINK TEST.

  • Lorem Ipsum has been the industry’s standard dummy text ever since the 1500s.
  • When an unknown printer took a galley of type and scrambled it to make a type specimen book.
  • INTERNAL LINK TEST (to health categories)
  • It has survived not only five centuries, but also the leap into electronic typesetting, remaining essentially unchanged.
  • It was popularised in the 1960s with the release of Letraset sheets containing Lorem Ipsum passages, and more recently with desktop publishing software like Aldus PageMaker including versions of Lorem Ipsum.
  • EXTERNAL LINK TEST

 

TEST 14 -include image in body of text with caption.

Lorem ipsum dolor sit amet, consectetur adipiscing elit. Fusce in eros cursus, pharetra nisi dignissim, tempus nibh. Etiam a imperdiet mauris, nec condimentum enim. Sed quis turpis ut ligula laoreet luctus nec vel tortor. Quisque tellus ante, sagittis sed lacus vulputate, hendrerit blandit diam. Vestibulum porta lacus nec odio elementum pharetra vitae nec sapien. Aenean purus mi, egestas in tempus at, sollicitudin ac augue. Nullam porttitor malesuada tincidunt. Praesent eu porttitor felis. Praesent odio lorem, fermentum et lacus eu, semper mattis tellus. Integer vitae urna est.

Random pulled in quotation-blah blah blah- something profound H3

Lorem ipsum dolor sit amet, consectetur adipiscing elit. Fusce in eros cursus, pharetra nisi dignissim, tempus nibh. Etiam a imperdiet mauris, nec condimentum enim. Sed quis turpis ut ligula laoreet luctus nec vel tortor. Quisque tellus ante, sagittis sed lacus vulputate, hendrerit blandit diam. Vestibulum porta lacus nec odio elementum pharetra vitae nec sapien. Aenean purus mi, egestas in tempus at, sollicitudin ac augue. Nullam porttitor malesuada tincidunt. Praesent eu porttitor felis. Praesent odio lorem, fermentum et lacus eu, semper mattis tellus. Integer vitae urna est.

Lorem ipsum dolor sit amet, consectetur adipiscing elit. Fusce in eros cursus, pharetra nisi dignissim, tempus nibh. Etiam a imperdiet mauris, nec condimentum enim. Sed quis turpis ut ligula laoreet luctus nec vel tortor. Quisque tellus ante, sagittis sed lacus vulputate, hendrerit blandit diam. Vestibulum porta lacus nec odio elementum pharetra vitae nec sapien. Aenean purus mi, egestas in tempus at, sollicitudin ac augue. Nullam porttitor malesuada tincidunt. Praesent eu porttitor felis. Praesent odio lorem, fermentum et lacus eu, semper mattis tellus. Integer vitae urna est.

Yan Test Editorial Table blah
blah blah blah blah blah
blah blah blah blah blah
blah blah blah blah blah
blah blah blah blah blah

Where does it come from? H3

  1. Contrary to popular belief, Lorem Ipsum is not simply random text.
  2. It has roots in a piece of classical Latin literature from 45 BC, making it over 2000 years old.
  3. Richard McClintock, a Latin professor at Hampden-Sydney College in Virginia, looked up one of the more obscure Latin words, consectetur, from a Lorem Ipsum passage, and going through the cites of the word in classical literature, discovered the undoubtable source.

Here is a test block quote Some people walk in the rain others just get wet. Lorem ipsum dolor sit amet, consectetur adipiscing elit. Fusce in eros cursus, pharetra nisi dignissim, tempus nibh. Etiam a imperdiet mauris, nec condimentum enim. Sed quis turpis ut ligula laoreet luctus nec vel tortor.

Heading 4

Lorem Ipsum comes from sections 1.10.32 and 1.10.33 of “de Finibus Bonorum et Malorum” (The Extremes of Good and Evil) by Cicero, written in 45 BC. This book is a treatise on the theory of ethics, very popular during the Renaissance. The first line of Lorem Ipsum, “Lorem ipsum dolor sit amet..”, comes from a line in section 1.10.32.

There are many variations of passages of Lorem Ipsum available, but the majority have suffered alteration in some form, by injected humour, or randomised words which don’t look even slightly believable. If you are going to use a passage of Lorem Ipsum, you need to be sure there isn’t anything embarrassing hidden in the middle of text. ANCHOR DESTINATION.

In this page:

 

Who uses the HRCS?

The HRCS has been used extensively in the UK, primarily among those funders that have participated in the quinquennial analysis series. Many now routinely classify all awards under HRCS, for both internal reporting and for reports in the public domain. Several funders also make their awards, and corresponding HRCS coding, publicly available (e.g. MRC awards via Gateway to Research, and NIHR via Journals Library).

As an open source classification system the HRCS is not restricted to the UK alone, and a number of research organisations have taken the HRCS for use internationally. However it is presently hard to track the who, where, how of this use is applied.

HRCS in routine reporting

The HRCS adoption by many UK funding organisations ensures it features in many annual reports or policy documents. Examples include:

Use of UK Health Research Analysis reports and datasets

This page is dedicated to use of the HRCS outside of the core report series. This use can vary considerably, from reports from funders who have participated in the analysis series to external organisations using HRCS-coded funder data to perform more elaborate analyses.

For citations and onward use of the public datasets from our main UK Health Research Analyses, please visit our Reports section.

Back to contents

HRCS in strategy and policy

Review of the Health Systems Research Initiative

In 2021, Technopolis Ltd was commissioned to conduct an independent, external review of the Health Systems Research Initiative (HSRI) by its funders; the UK Foreign, Commonwealth and Development Office (FCDO), the Medical Research Council (MRC), the Economic and Social Research Council (ESRC) and the Wellcome Trust. The aim was to understand the impact of the programme, its potential for future impact, and inform the design of future funding programmes. The HRCS was used to show the range of activities supported by the HSRI and compare full and foundation award types.

NIHR review of the Efficacy and Mechanism Evaluation (EME) programme

In November 2021, the National Institute for Health Research (NIHR) published  A 10-year impact assessment of the Efficacy and Mechanism Evaluation (EME) programme. This report made extensive use of HRCS coding to show the distribution of EME awards by both Health Category and Research Activity, comparing funding against UK DALY scores and other funders in the 2018 analysis.

Wellcome Review of Science 2020

In 2020 Wellcome published a landmark review of the way it supports science. The review includes a survey of 2,000 people from the research community and an analysis of the funding landscape. This included using HRCS data to compare the distribution of basic and translational research of Wellcome’s award portfolio to other UK and international research funders. 

MRC use of HRCS to facilitate in-depth analyses

The MRC has been routinely using classification by HRCS as a mechanism to build portfolios since 2006. More recently, the MRC’s use of this extensive classification has been used to facilitate deeper dives into their data, first into translational research and then prevention research.

In 2019, the MRC published a report on 10 years of translational research funding. A key component to this assessment was the use of HRCS to identify awards with translational intent outside of the already known strategic translational calls/schemes. This use of HRCS to ‘pre-filter’ extensive award data was used again in 2021, when assessing the landscape of prevention research alongside partners from the UK Prevention Research Partnership.

National Audit Office highlights HRCS as an example of inter-funder coordination

In 2017, the National Audit Office’s report on Cross-government funding of research and development highlighted the HRCS and it’s use in nationwide landscape reporting as a effective exemplar of where funders have categorised research activities, developed a coherent picture of the funding landscape and used this to direct their investment (see case study on page 38).

Medical Research: What’s it worth? Estimating the economic benefits from medical research in the UK

This report commissioned in 2008 by the Medical Research Council, Wellcome Trust and Academy of Medical Sciences demonstrated major financial and social benefits from investment in medical research. The report also made a number of recommendations for future consideration, including the adoption of a standardised way of classifying research funding, citing the HRCS as an example. More information on the “What’s it worth?” report series can be found here.

A review of UK health research funding – Sir David Cooksey (December 2006)

In March 2006, the Chancellor of the Exchequer and the Secretaries of State for Health and Trade and Industry invited Sir David Cooksey to undertake an independent review to advise on the best design and institutional arrangements for the public funding of health research in the UK. The primary data source for this review was the HRCS data from the UK Health Research Analysis 2004/05.

Back to contents

HRCS: International Use

As an open source classification system the HRCS is not restricted to the UK alone, and a number of research organisations have taken the HRCS for use internationally. Examples of this include:

  • European Science Foundation recommending HRCS as international standard. In a policy briefing paper from 2011 the ESF reviewed a number of biomedical funding classification systems (OECD, ANZSRC, RCDC, MeSH, CSO and HRCS) and concluded that the use of the HRCS is encouraged as the leading approach for comparison and joint analysis of specifically health research portfolio information.
  • The US Health Research Alliance has 75 charitable and philanthropic members that fund health research many have contributed grant data to a new HRA Reporter database which is coded using the HRCS, and is used in their wider reporting on health research.
  • Presentations at international conferences including at EuroCRIS in 2013. Founded in 2002, EuroCRIS is an international not-for-profit association, that brings together experts on research information in general and research information systems (CRIS) in particular.

In particular, the Research Council of Norway and Norwegian Ministry of Health use the HRCS in many reporting processes, including:

  • Classification of scientific publication by the Health Research Classification System (HRCS). A pilot study (Nordic Institute for Studies of Innovation, Research and Education (NIFU) 2016, in Norwegian) – link here
  • Presented at the 21st Nordic workshop on bibliometrics and research policy, Copenhagen 2016 (slides and abstract in English) – link here
  • HelseOmsorg 21 monitor programme is an analysis of health research in Norway conducted by the Norweigan Research Council on behalf of the Ministry of Health. It combines data from the Research Council of Norway, Regional Health Authorities, the Cancer Society and EU health funding in Norway.

Back to contents

HRCS in Journal Publications

A selection of publications that reference the HRCS can be found on publication databases like Europe PubMed.

These include:

  • • Bryant et al. (2023). Mortality and mental health funding-do the dollars add up? Eating disorder research funding in Australia from 2009 to 2021: a portfolio analysis. Lancet Reg Health Wes Pac 10.1016/j.lanwpc.2023.100786
  • Dewing et al. (2022). The disparity between funding for eye research vs. the high cost of sight-loss in the UK. Eye 10.1038/s41433-022-02228-7
  • Vukugah et al. (2022). Research Questions and Priorities for Pediatric Tuberculosis: A Survey of Published Systematic Reviews and Meta-Analyses. Tuberc Res Treat 10.1155/2022/1686047
  • Perrin et al. (2021). Establishing the national top 10 priority research questions to improve diabetes-related foot health and disease: a Delphi study of Australian stakeholders. BMJ Open Diabetes Res Care 10.1136/bmjdrc-2021-002570
  • Gómez-Cebrián et al. (2021). Pharmacometabolomics by NMR in Oncology: A Systematic Review. Pharmaceuticals 10.3390/ph14101015
  • Hesselberg et al. (2021). Individual versus general structured feedback to improve agreement in grant peer review: a randomized controlled trial. Res Integr Peer Rev 10.1186/s41073-021-00115-5
  • Crowe et al. (2021). Are we asking the right questions? Working with the LGBTQ+ community to prioritise healthcare research themes. Res Involv Engagem 10.1186/s40900-021-00298-7
  • Cody et al. (2021). Funders’ responsibility to ensure value in research: a self-audit by the Health Research Board Ireland. HRB Open Res 10.12688/hrbopenres.13224.1
  • Gallo et al. (2020). Biomedical and health research: an analysis of country participation and research fields in the EU’s Horizon 2020. Eur J Epidemiol 10.1007/s10654-020-00690-9
  • Morciano et al. (2020). An analysis of the strategic plan development processes of major public organisations funding health research in nine high-income countries worldwide. Health Res Policy Syst 10.1186/s12961-020-00620-x
  • Clyne et al. (2020). Quality, scope and reporting standards of randomised controlled trials in Irish Health Research: an observational study. Trials 10.1186/s13063-020-04396-x
  • Masefield et al. (2020). Repurposing NGO data for better research outcomes: a scoping review of the use and secondary analysis of NGO data in health policy and systems research. Health Res Policy Syst   10.1186/s12961-020-00577-x
  • Kvalem et al. (2020). A complete overview of the PhD theses within the field of medicine and health science in Norway in 2018 by using the Health Research Classification System (HRCS). Research Square 10.21203/rs.2.24802/v1
  • Woelbert et al. (2019). How much is spent on mental health research: developing a system for categorising grant funding in the UK. The Lancet Psychiatry 10.1016/S2215-0366(19)30033-1 – note a methodology version of this report is available via the AMRC open research repository.
  • Goodwin et al. (2019). Intervention development and treatment success in UK health technology assessment funded trials of physical rehabilitation: a mixed methods analysis. BMJ Open 10.1136/bmjopen-2018-026289
  • Mollan et al. (2019). What are the research priorities for idiopathic intracranial hypertension? A priority setting partnership between patients and healthcare professionals. BMJ Open 10.1136/bmjopen-2018-026573
  • Chinnery et al. (2018). National Institute for Health Research (NIHR) Health Technology Assessment (HTA) Programme research funding and UK burden of disease. Trials 10.1186/s13063-018-2489-7
  • Glover et al. (2018). Estimating the returns to United Kingdom publicly funded musculoskeletal disease research in terms of net value of improved health outcomes. Health Res Policy Syst 10.1186/s12961-017-0276-7
  • Finer et al. (2018). Setting the top 10 research priorities to improve the health of people with Type 2 diabetes: a Diabetes UK-James Lind Alliance Priority Setting Partnership. Diabetic Medicine 10.1111/dme.13613
  • Blackburn et al. (2018). The extent, quality and impact of patient and public involvement in primary care research: a mixed methods study. Research Involvement and Engagement 10.1186/s40900-018-0100-8
  • Macías-Angel et al. (2017). [Classification of the scope of research projects on malaria funded by Colciencias during 1995-2005]. [spanish language paper]. Revista de Salud Publica 10.15446/rsap.v19n1.58957
  • Conroy et al. (2017). A cohort examination to establish reporting of the remit and function of Trial Steering Committees in randomised controlled trials. Trials 10.1186/s13063-017-2300-1
  • Sussex et al. (2016). Quantifying the economic impact of government and charity funding of medical research on private research and development funding in the United Kingdom. BMC Med 10.1186/s12916-016-0564-z
  • Hall et al. (2016). Research funding for addressing tobacco-related disease: an analysis of UK investment between 2008 and 2012. BMJ Open 10.1136/bmjopen-2016-011609
  • Roh et al. (2016). Mental health services and R&D in South Korea. Int J Ment Health Syst 10.1186/s13033-016-0077-3
  • Viergever et al. (2016). The 10 largest public and philanthropic funders of health research in the world: what they fund and how they distribute their funds. Health Res Policy Syst 10.1186/s12961-015-0074-z
  • Carter et al. (2016).  UK health research analyses and the benefits of shared data. Health Res Policy Syst 10.1186/s12961-016-0116-1
  • Guegan et al. (2016). Mapping public health research across the National Institute for Health Research 2006-2013. BMC Public Health 10.1186/s12889-016-3521-z
  • Adams et al. (2015). Ethical considerations in malaria research proposal review: empirical evidence from 114 proposals submitted to an Ethics Committee in Thailand. Malar J 10.1186/s12936-015-0854-5
  • Kinge et al. (2014). Are the Norwegian health research investments in line with the disease burden? Health Res Policy Syst 10.1186/1478-4505-12-64
  • Nicolau et al. (2012). Research questions and priorities for tuberculosis: a survey of published systematic reviews and meta-analyses. PLoS One 10.1371/journal.pone.0042479
  • Turner et al. (2012). Predicting the extent of heterogeneity in meta-analysis, using empirical data from the Cochrane Database of Systematic Reviews. Int J Epidemiol 10.1093/ije/dys041
  • Terry et al. (2012). Mapping global health research investments, time for new thinking–a Babel Fish for research data. Health Res Policy Syst 10.1186/1478-4505-10-28
  • • Rice (2011). The institutional review board is an impediment to human research: the result is more animal-based research. PEHM 10.1186/1747-5341-6-12
  • Collins (2011). A ten-year audit of traditional Chinese medicine and other natural product research published in the Chinese Medical Journal (2000-2009). Chin Med J (Engl) PMID:21740755
  • Conceição et al. (2011). Public health research systems in the European union. Health Res Policy Syst 10.1186/1478-4505-9-38
  • Davey et al. (2011). Characteristics of meta-analyses and their component studies in the Cochrane Database of Systematic Reviews: a cross-sectional, descriptive analysis.BMC Med Res Methodol 10.1186/1471-2288-11-160
  • Kanavos et al. (2010). The role of funding and policies on innovation in cancer drug development. Ecancermedicalscience 10.3332/ecancer.2010.164
  • Kubiak et al. (2009). Common definition for categories of clinical research: a prerequisite for a survey on regulatory requirements by the European Clinical Research Infrastructures Network (ECRIN). Trials 10.1186/1745-6215-10-95
  • Ahmed et al. (2010). Mapping Postgraduate Research at the University of Zambia: a review of dissertations for the Master of Medicine Programme. Med J Zambia PMC3604980
  • Eckhouse & Sullivan (2008). The state of academic cancer surgery in the UK. Mol Oncol 10.1016/j.molonc.2008.06.001
  • Mayor (2006). Report gives snapshot health research funding in the UK. BMJ 10.1136/bmj.332.7552.1230-a

Back to contents

Resources for HRCS Trainers

This page contains links to the resources used by HRCS trainers. It is intended as a central resource for those sufficiently experienced in HRCS coding to help them train additional staff in the use and application of HRCS.

These resources were originally developed by Dr. Andrew Speakman and Dr. Anna Smith, who were involved in the original UKCRC analysis in 2004/05 and maintain an interest in the HRCS. They have kindly agreed to allow their resources to be made more widely available and adapted as the use of HRCS grows and requirements for coding advice changes.

The current resources provided here were updated following training sessions conducted in November 2015 by Dr. James Carter, the project manager for the UK Health Research Analysis 2014. The trainer pack consists of three MS PowerPoint slide sets:

Main Presentation (.pptx Slides) – These provide an introduction for new coders to the background/history of the UKCRC and HRCS, alongside the main ‘approach to coding’ training slides.    Approximate course length = 1-1.5hrs.

Example Abstracts (.pptx Slides) – These provide the trainees with some example abstracts to code. The purpose is to guide the trainees through the process of coding using real abstracts, with some extensive guidance and discussion of the issues that might lead to incorrect or inappropriate coding.    Approximate course length = 1.5-2hrs.

Advanced Slideset (.pptx Slides) – These condense much of the information from the main guidance on the HRCS website into a training session format. This slideset is therefore designed for a more advance course, to refresh those who have experienced the ‘standard’ training by provide a greater level of detail for coders.    Approximate course length = 1.5-2hrs.

Further details, such as PDF handouts for trainees, can be found on the main HRCS Training page.

Otherwise contact us if you have further questions.

The following examples are of common mistakes or frequently asked questions from those new to HRCS coding. This advice is also available as a PDF.

Download the Common Mistakes PDF here

Contents

  1. Allocating too many codes and unequal percentages
  2. Falling for the investigator’s “sale pitch”
  3. Assigning Health Categories to reflect all pathogenic components or symptoms
  4. Basing the choice of Health Category solely on the organs affected by the disease
  5. Using the Disputed Aetiology and Other category as a dumping ground when you are not sure how to classify a study
  6. Automatically putting all inherited disorders in the Congenital Disorders category
  7. Avoiding the 1 Underpinning code group if a study looks at pain, immune responses, pregnancy or ageing
  8. Using the 3 Prevention code group for studies of the re-occurrence of a disease
  9. Automatically putting trials into the 6 Treatment Evaluation code group
  10. Use of 1.1 versus 2.1 for biological and endogenous factors
  11. Using the treatments code groups (5 Treatment Development or 6 Treatment Evaluation) for preventative interventions (3 Prevention)
  12. Inappropriate use of 4.1 and 4.2 in 4 Detection and Diagnosis code group

 

1.   Allocating too many codes and unequal percentages

Advice:   Unless there are very specific indications otherwise, you should apportion the percentages equally and allocate the minimum number of codes (1-2 (max. 4) Research Activity Codes and 1-5 Health Categories).

 

Remember:  There are simple rules to follow in order to enable the process to be repeated reliably by different coders.

 

2.   Falling for an investigator’s “sales pitch”

Advice:   Read the award abstract sceptically to find the main aim to be addressed during the lifetime of the award and ignore areas listed as ‘being relevant’ to the study. Often you can ignore the first paragraph about the past e.g.

  • “X is implicated in disorders of Y”
  • “X has been linked to Y”.

Similarly the last paragraph about the future can be a distraction:

  • “it is hoped that X will also lead to novel therapeutic opportunities in Z”
  • “X could subsequently inform the development of Z”

 

Remember:   The coding should be based on the main aim and the work to be undertaken during the lifetime of the award.

 

3.   Assigning Health Categories to reflect all pathogenic components or symptoms

Advice:   Code for the main disease being studied and consult the specific inclusion/exclusion criteria listed on the website.

Some example pitfalls are:

 

Remember:   Choose the Health Category associated with the purpose of the investigation or the overarching main disease.

 

4.   Basing the choice of Health Category solely on the organs affected by the disease

Advice:   Code for the main disease being studied and consult the specific inclusion/exclusion criteria listed on the website

Some example pitfalls are:

 

Remember:   Check the definition of the Health Category and the specific inclusion/exclusion criteria listed on the website.

 

5.    Using the Disputed Aetiology and Other category as a dumping ground when you are not sure how to classify a study

Advice:   The Disputed Aetiology and Other category should be used infrequently and in very specific circumstances for certain areas which are difficult to classify (e.g Gulf War Syndrome, some studies of social services).

 

Remember:   If a study has wide relevance to many health areas (more than five) then the Generic Health Relevance category is the one to consider assigning.

 

6.   Automatically putting all inherited disorders in the Congenital Disorders category

Advice:   The Congenital Disorders category covers physical abnormalities and congenital syndromes that are associated with multiple diseases and conditions e.g. cystic fibrosis. It excludes single disease disorders even when referred to as “congenital” e.g. a study of “congenital heart defects” present at birth should be coded as Cardiovascular. See guidance on congenital and multiple disorders for more details.

 

Remember:   Not all syndromes go in Congenital Disorders.

 

7.   Avoiding the 1 Underpinning code group if a study looks at pain, immune responses, pregnancy or ageing

Advice:   The 1 Underpinning code group is broad. In the original UK Health Research Analysis (2006) it accounted for more than one third of all funding. It covers studies in biology, psychology, economics, social science and chemistry. It also covers all studies of normal function, including pain, immune responses, pregnancy and ageing.

 

Remember:   Pain, immune responses, pregnancy and ageing are considered to be normal.

 

8.   Using the 3 Prevention code group for studies of the re-occurrence of a disease

Advice:   A study can describe itself as preventive but it may be focused on preventing the re-occurrence of an existing condition (secondary prevention). This is considered to be an extension of therapy and will usually be classified in the 6 Treatment Evaluation code group e.g. use of aspirin to prevent further adverse cardiovascular events or stroke in cardiovascular patients. See guidance on differentiating primary and secondary prevention for more details.

 

Remember:   The 3 Prevention code group is about the primary prevention of disease in healthy people.

 

9.   Automatically putting trials into the 6 Treatment Evaluation code group

Advice:   The 6 Treatment Evaluation code group covers all studies of therapeutic interventions in humans, often involving a clinical trial. But it does not include all trials in humans as there can be clinical trials testing the effects of preventive interventions, diagnostic devices and health services.

 

Remember:   The 6 Treatment Evaluation code group does not include all trials in humans.

 

10.   Use of 1.1 versus 2.1 for biological and endogenous factors

Advice:    Always remember the overarching code group criteria when coding studies of biological and endogenous factors:

  • Use 1 Underpinning group codes for all types of research into ‘normal’ functions and processes in ‘healthy’ humans or systems, i.e. research that underpins investigations into the cause or development of diseases.
  • Use 2 Aetiology group codes for the identification of determinants that are involved in the cause, risk or development of disease. Remember 2 Aetiology in HRCS goes beyond the dictionary definition; it also encompasses disease progression and life course.

Then consider the specific criteria under the guidance for 1.1 Normal biological development and functioning and 2.1 Biological and endogenous factors. For example, studies in Cancer and Infection are rarely 1 Underpinning (with some exceptions). Studies of basic immune responses, pain, wound healing and pregnancy not linked to disease/conditions should not be coded under 2 Aetiology (see Common Mistake #07, above).

Finally, always consider the primary aim of coding is to capture the main objective of the research taking place during the lifetime of the award with the minimum number of codes. While some studies of biological/endogenous factors can cover both 1 Underpinning and 2 Aetiology activities, it is more likely that initial underpinning investigations will precede research into causation and development.

e.g. Studies coded as 2.1 often involve comparisons to ‘normal’ functions and processes (i.e. as case:control comparisons). However such comparisons should not automatically require addition of 1.1 for the involvement of ‘normal’ comparators unless the research also encompasses establishing what ‘normal’ function can be as well.

 

Remember:  Always consider the code group criteria before assigning sub-codes, and the context of the research. Underpinning covers studies of normal function that underpins subsequent aetiological study.

 

11. Using the treatments code groups (5 Treatment Development or 6 Treatment Evaluation) for preventative interventions (3 Prevention)

Advice:   Some behaviours or conditions, such as smoking, obesity, alcohol consumption and drug misuse are considered a risk factor for other diseases. Therefore, interventions to reduce consumption or promote healthier behaviours should be coded as 3 Prevention, even if the target individual or group is already smoking, obese etc..

Studies should be coded to 5 Treatment Development or 6 Treatment Evaluation when the focus is treatment of an newly manifested or existing behaviour-related diseases – such as lung cancer for smokers, heart disease for the obese or alcohol/drug addiction.

5 Treatment Development or 6 Treatment Evaluation can also be used in cases of secondary prevention (see Common Mistake #08, above). Additional guidance on differentiating secondary and primary prevention is also available.

 

Remember:   consider the context of the study and what the ‘disease’ being treated is. Risk behaviours prior to disease should be coded to 3 Prevention, while treatments for risk-related diseases should be coded 5 Treatment Development or 6 Treatment Evaluation.

 

12. Inappropriate use of 4.1 and 4.2 in 4 Detection and Diagnosis code group

Advice:   Use 4.1 Marker discovery for pre-clinical investigation of potential diagnostics, which can include patient samples if they are being used in the diagnostic development phase. Use 4.2 Marker evaluation for clinical and applied testing in humans, once verified in the laboratory, often in a trial or studies that involve a group of people.

The term ‘biomarker’ can cause confusion when applying HRCS coding. In general a ‘biomarker’ refers to a specific molecule, gene or characteristic from which a physiological process can be identified. Use codes within 2 Aetiology for studies where markers are first identified (e.g. in epidemiology studies) or further assessed to determine how the molecule/gene/etc. contribute to the cause, risk or development of diseases. These studies will generally precede research to assess whether the biomarker can be then be used in a diagnostic setting.

 

Remember:   Use 4.1 for pre-clinical studies and 4.2 for clinical/applied studies. Not all ‘biomarker’ research is coded in 4 Detection and Diagnosis; preliminary identification and physiological assessment will typically be coded to 2 Aetiology.

Design and Aims of the HRCS

The Health Research Classification System (HRCS) is a system for classifying and analysing all types of biomedical and health related research. The HRCS was developed by the UKCRC Partners as a research management tool.

The HRCS is designed to answer strategic questions about investment across the broad spectrum of different research activities in different areas of health and disease funded by the Partners. Use of this single stable common classification system allows meaningful comparisons to be made within and between different research portfolios and allows funding trends to be monitored over time.

The aim of using the HRCS is to capture the centre of gravity or main objective of the research taking place within the lifetime of the award funding. Analysis of research coded by the HRCS provides an overview of the strategic focus of research investment.

The HRCS is not like other keyword systems which are designed to capture all facets of the research or potential downstream outcomes. These systems enable complex searches for research relevant to different areas but they cannot be used to accurately attribute research costs to individual categories.

Want to learn more about the origins of the HRCS?

See our history for the original development of the HRCS, while our reports pages will show you how the HRCS has been used to assess biomedical research funding in the UK in the last ten years.

Thinking of using the HRCS?

The HRCS is open source and available for all to use, see our conditions of use page for more details. If you are interested in learning how to apply HRCS coding to awards, our approach to coding page is the best place to start.

We’d also recommend our official terminology document if you’re considering integrating HRCS into management information systems.

Finally if you’re thinking of performing your own HRCS analysis, our analysis tools will provide some helpful pointers on how to replicate our data analysis methodology.

Want to learn more about how the HRCS is being used?

We recommend starting with our main report pages to see how the UK Health Research Analyses have used HRCS data to assess biomedical research funding in the UK in the last ten years. We also highlight how other individual funders make use of the HRCS, its dissemination internationally, and re-use of UK in our Use of the HRCS page.

Using the HRCS in your own organisation

The Health Research Classification System itself is open source. You are free to use and distribute the HRCS but you should not alter it or use it for commercial benefit.

Accordingly, all content on this website is licensed for use under a Creative Commons Attribution-NonCommercial-NoDerivs 2.0 England & Wales Licence.

 

Management of the HRCS

The UKCRC Health Research Analysis Forum (HRAF) oversees the maintenance and development of the HRCS in the UK, promotes its use and facilitates the conduct of health research analyses. For further information on any aspect of the HRCS, coding or reports, please contact us.

Management of the HRCS website is carried out by the Medical Research Council on behalf of the HRAF. See the website terms and conditions for further information.

The origins of Health Research Classification System (HRCS)

The HRCS was developed by UK Clinical Research Collaboration (UKCRC) partners in 2004. One of the partnership’s main aims was to develop a coordinated approach to health research funding. It was agreed that the first step should be the creation of a national picture of UK health research, but to do so required a universal system to classify health research award data.

The system was designed to produce a broad strategic overview of health research funding and developed after assessing existing classification systems to ascertain the full breadth of the biomedical and health research portfolios to be analysed. The HRCS builds on the WHO International Classification of Diseases and a cancer-based system (the Common Scientific Outline) but its breadth of coverage across all types of research and areas of health and disease is unique.

During and subsequent to its development, the HRCS has been used to classify many thousands of research awards covering the full spectrum of health research funding. The system has now been widely adopted by UK research funders to inform research management and to undertake prospective analyses. Several international funding organisations are now successfully using the system.

The UK Health Research Analyses 2004-2022


The UK Health Research Analysis (2004/05) was where the HRCS was first used to provide a landscape of ‘who funds what and where’ in the UK. Published in 2006, it was a major project which was unique in the global context and was used extensively to make strategic decisions on health research funding. It was followed by an analysis of additional charity funded health research, From Donation To Innovation (2004/05), published in 2007.

The second in this landscaping series, the UK Health Research Analysis 2009/10 was published in 2012. This report identified some significant changes in the UK health research landscape in the five years since the original national analysis from the same 12 largest funders of health research.

The third report in this series, the UK Health Research Analysis 2014, was published in August 2015. This provided a ten year timeline of UK health research funding in the public and charitable sector, with an expansion in participation to members of the Association of Medical Research Charities (AMRC) and the rest of the UK’s research councils.

We conducted a formal review of the HRCS and accompanying resources in 2017. This resulted in some substantial updates to the several guidance topics, creation of new topics for emerging research fields and a new, much improved HRCS website.

The fourth instalment in the report series, the UK Health Research Analysis 2018, was announced in January 2019 and eventually published in January 2020. This iteration expanded the pool of participating organisations from 64 to 146, bringing in more charities in/outside of the AMRC, other government departments, academies, learned societies and royal colleges.

The most recent report, the UK Health Research Analysis 2022, was announced in January 2023. Further increasing the participating organisations to 173, the fifth report in this series also expanded on the principles of data transparency to publish – for the first time – a complete dataset of both direct awards (used in the main analysis) and indirect supportive awards (assessed separately) with additional linkage to Research Organization Registry (ROR).

Introduction

The Health Research Classification System (HRCS) website is designed to incorporate all aspects of the use of HRCS; from the principles and guidance for coders to access to our reports to replicating the system in your own organisation. Below are some likely scenarios for users of this site, but you can always contact us if you have any specific questions.

Brand new to HRCS?

If you have never heard of the HRCS before and want to learn more, we suggest starting with the Purpose of the HRCS. This will give you some of the background to the ‘why’ and the ‘how’ of the HRCS. You may also want to read some of our reports, which demonstrate how the HRCS has been used across the UK.

Interested in HRCS coding?

If you are looking to start coding a research portfolio from scratch, the General Approach to Coding pages are for you. This should give you a basic overview of purpose and coding principles, before you dig into the dedicated Health Categories, Research Activities and Guidance pages.

You can also download the HRCS manual

There’s also the pages on training and common mistakes, which are very helpful for coding novices.

Are you an experienced HRCS coder?

You should find everything you need in our dedicated Health Categories, Research Activities and Guidance pages. We also recommend the search bar if you have a specific question, although you may need to try synonyms as well as acronyms!

Looking to replicate the HRCS analysis?

If you’re already familiar with our reports, and the associated published data, you may also be keen to learn how to perform similar analyses on your own data. There are some tools available that can help.

Want to learn more about how the HRCS has been used?

While the main focus for the HRAF group has been to oversea the production of our quinquennial reports, the HRCS itself has been used routinely by a large number of UK funders and internationally. See our Use of the HRCS page for more details. You’ll also find the data from our three main reports available for reuse, and we encourage you to do so.

If you still can’t find an answer to your query, please contact us.

What is HRCS training?

While the HRCS is designed to be an easy-to-use classification system, the subject matter for health research is sufficiently diverse that novice coders may struggle when first starting out applying HRCS coding. This website is designed, wherever possible, to guide a new coder on the best methods to use and to identify common areas for confusion.

To ensure that the HRCS is applied appropriately, we recommend those using HRCS coding on a regular basis become formally trained. These training sessions are largely organised through the Health Research Analysis Forum (HRAF), which monitors the HRCS on behalf of the UKCRC.

The HRAF endeavours to run regular training sessions in the use and application of HRCS coding, but this is dependent on demand and availability of a limited number of experienced trainers.

If you are interested in obtaining HRCS training, click here

Why attend HRCS training?

The main HRCS handbook and this website contain far more guidance than can be adequately covered in a training session. However most new coders find the basic principles difficult to grasp; there are nuances to any classification system that may not be apparent from simply reading the guidelines.

Attending the training sessions allows us to convey the ‘essence’ of coding, the main coding approaches used to reliably apply coding and identifies some of the more difficult aspects of coding or common mistakes made by inexperienced coders. We also explain more about the background to the system, it’s uses in the UK and the potential for future use on a global scale. Furthermore the training also includes an interactive sample abstract coding element, allowing coders to apply their newly learnt skills on real abstracts, with guidance from the trainers.

If you are interested in formal training, please contact us for further information.

Training Resources

Those that attend the training sessions are provided with handouts from the main training presentation, the core HRCS handbook, and some example abstracts to work through during this session.

Universal resources for training sessions will be available on the HRCS website in due course. It is our intention that this forms a central repository for training materials so that experienced coders can perform training themselves to new or inexperienced coders in a uniform fashion.

Those who have already attended can find resources from the latest training sessions here. These include:

Main Presentation (Slideset PDF) – this is normally issued as a paper handout to trainees and contains the background of UKCRC/HRCS and the main ‘Approach to Coding’ training slides.

Example Abstract (Slideset PDF) – these include the weblinks to the specific guidance topics discussed.

Example Abstract (Notes PDF) – to help resolve further queries and ‘show your working’ of how to reach the most appropriate codes required.

The main HRCS Handbook and Common Mistakes documents.

Please remember the abstract notes contain the ‘answers’ to the Example Abstract exercise. We recommend you keep these for your own reference, but avoid wider distribution. We strongly recommend new coders should be formally trained rather than learning as they go from training resources!

The aim of coding using the Research Activity Codes is to capture the main objective of the research taking place during the lifetime of the award and not the background or future potential downstream applications of the research (often referred to in the first or last sentence of the abstract).

To use HRCS consistently, always assign one of the 48 sub-codes e.g. 1.1 Biological – never just one of the eight top-level code groups e.g. 1 Underpinning – and use the minimum number of codes to reflect the main focus of the research.

Each assigned code is then given a percentage value adding up to 100%. Multiple codes should be equally apportioned e.g. two codes should be apportioned 50% each, three codes 33.3% each etc. Exceptions to this rule can be made in circumstances where different emphases of research aims are clearly stated in the research objectives, however unequal apportionments should be avoided if possible.

Use a maximum of two codes unless coding a large programme of research, in which case up to four codes can be used. If a programme has many diverse aims, use a resources and infrastructure code to cover these.

The most accurate and reproducible approach to assigning Research Activity Codes is to:

  • first establish the main aim or aims of the research
  • match each of these aims with the relevant main overarching code group (1-8) before trying to assign a sub-code
  • then select the appropriate sub-code within the chosen main code group that best reflects the aim of the research taking place

Attempting to code by initially trying to match a code from anywhere within the system to the research aim can result in coding inaccuracies. Codes may be repeated within the system and will have different meaning according to the context of the main code group they lie within. There are a number of research concepts that are repeated, including policy, trials and education.

Top