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Clinical Coding for non coders

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1 Clinical Coding for non coders
A brief overview of clinical coding and the role of the Clinical Classifications Service

2 How to view this presentation
Clicking in the top right of each slide will navigate through the notes. Only once all the notes have been viewed the ‘next page’ icon will appear. Use and to navigate backwards and forwards through the slides. For optimum viewing avoid the keyboard controls and use the mouse only.

3 The background to Clinical Coding
The history of diagnostic and interventional classifications

4 What is Clinical Coding?
The translation of medical terminology, as written by the clinician to describe a patient’s complaint, problem, diagnosis, treatment or reason for seeking medical attention, into a coded format which is nationally and internationally recognised. Clinical Coders are highly trained specialists who develop the skills throughout their career to accurately record a patient’s healthcare problems and interventions using a classification system of diseases (ICD-10) and procedures (OPCS-4). Medical terminology ICD-10 codes Clinical Coding is the translation of medical terminology, as written by the clinician to describe a patient’s complaint, problem, diagnosis, treatment or reason for seeking medical attention, into a coded format which is nationally and internationally recognised. Coders are highly trained specialists who develop the skills throughout their career to accurately record patient’s healthcare problems and interventions using a classification system of diseases (ICD-10) and procedures (OPCS-4).

5 John Graunt - Weekly Bills of Mortality
John Graunt, a physician, was the first to start collecting data on the number of patients dying and what they were dying from. That was in the seventeenth century, and the information he collected became known as the ‘Weekly Bills of Mortality’. LONDON week ending 31st January 1634 The Disease and Casualties this week Abortive 2 Executed 33 Overlaid 2 Aged 36 Feaver 10 Quinsie 1 Bedridden 1 Flox and smallpox 5 Rickets 8 Bloody flux 1 Found dead in the street Rising of the lights 8 Bruised 1 (an infant) 1 Scowering 1 Cancer 1 French pox 1 Scurvy 2 Chilbed 3 Gripping in the guts 13 Stillborn 9 Chrisoms 19 Jaundices 1 Stone 1 Consumption 77 Infants 18 Stopping of the Convulsions 44 Killed with a fall 3 stomach 3 Cough 2 Murthered 1 Suddenly 6 Dropsie Teeth 16 Windie 3 Worms 1 Males 107 Males 213 Christened Female 109 Buried Female 196 Plague 0 In all 216 In all 409 Deceased in the burials this week - 63 Parishes clear of the plague Parishes infected - 20 Consumption: later became known as tuberculosis Overlaid: In olden times, several children used to share the same bed. This term would suggest that one person turning over may have caused suffocation in another. Teeth: Extremely poor dental hygiene as was prevalent in those times often led to death as bacterial infection from the teeth and gums can spread to other parts of the body, particularly the heart. Rising of the lights: In the past lights was a term for the lungs, so rising of the lights suggests choking or breathlessness. Messages from someone who has original accounts suggest that rising of the lights nearly always occurred in women who had recently given birth. So it could mean either Post partum depression or hysteria Pulmonary embolus. This, as you can see, is very basic information. The terminology has advanced a lot since then. Gripping in the guts / Stopping of the stomach: Probably referred to types of bowel / digestive obstruction. The collection of information about diseases is by no means a recent innovation. John Graunt, a physician, was the first to start collecting data on the number of patients dying and what they were dying from. That was in the seventeenth century, and the information he collected became known as the ‘Weekly Bills of Mortality’. This, as you can see, is very basic information. The terminology has changed just a little since then! Discuss some of these terms. For example: Consumption: later became known as tuberculosis Gripping in the guts / Stopping of the stomach: Probably referred to types of bowel / digestive obstruction. Overlaid: In olden times, several children used to share the same bed. This term would suggest that one person turning over may have caused suffocation in another. Rising of the lights: In the past lights was a term for the lungs, so rising of the lights suggests choking or breathlessness. Messages from someone who has original accounts suggest that rising of the lights nearly always occurred in women who had recently given birth. So it could mean either Post partum depression or hysteria Pulmonary embolus. Teeth: Extremely poor dental hygiene as was prevalent in those times often led to death as bacterial infection from the teeth and gums can spread to other parts of the body, particularly the heart.

6 Florence Nightingale – Notes on Hospitals
“I am fain to sum up with an urgent appeal for adopting … some uniform system of publishing the statistical records of hospitals. There is a growing conviction that in all hospitals, even in those which are best conducted, there is a great and unnecessary waste of life … In attempting to arrive at the truth, I have applied everywhere for information, but in scarcely an instance have I been able to obtain hospital records fit for any purposes of comparison … If wisely used, these improved statistics would tell us more of the relative value of particular operations and modes of treatment than we have means of ascertaining at present.” Notes on Hospitals, London: Longman, Green, Roberts, Longman and Green, 1863. Florence Nightingale attempted to collect information about the outcome of care. In the beginning she developed her own method of recording outcomes using the three distinct groups. They are all pretty self explanatory: 1. Relieved = the patient was discharged having been cured of the medical condition they had been suffering from 2. Not relieved = the patient had been discharged but had not been relieved of the medical condition they were suffering from 3. Died = speaks for itself! During the Crimean War, diseases such as typhus, typhoid, cholera, and dysentery were rife in the army hospitals. Many more soldiers were dying from diseases than from wounds. Nightingale played an active role during the War and worked towards improvements in sanitation, nutrition, and activity for the patients of the hospitals. Death rates were reduced dramatically with the introduction of such measures. Later, Nightingale kept meticulous records of the number of deaths, and the causes of deaths, so that on her return to Great Britain she could justify the need for improving conditions in hospitals. In 1858 Florence Nightingale became the first female member of the Royal Statistical Society. Florence Nightingale attempted to collect information about the outcome of care. In the beginning she developed her own method of recording outcomes using the three distinct groups. They are all pretty self explanatory: 1. Relieved = the patient was discharged having been cured of the medical condition they had been suffering from 2. Not relieved = the patient had been discharged but had not been relieved of the medical condition they were suffering from 3. Died = speaks for itself! Diseases such as typhus, typhoid, cholera, and dysentery were rife in the army hospitals. Many more soldiers were dying from diseases than from wounds. Nightingale worked towards improvements in sanitation, nutrition, and activity for the patients of the hospitals. Death rates were reduced dramatically with the introduction of such measures. Later, Nightingale kept meticulous records of the number of deaths, and the causes of deaths, so that on her return to Great Britain she could justify the need for improving conditions in hospitals.

7 Development of the classification of disease
William Farr developed the ‘International Listing of Causes of Death’ in 1855 Subsequently revised in 1874, 1880 and 1886 The World Health Organisation (WHO) was entrusted with the ‘International Classification of Diseases’ (ICD) at its creation in 1948 and published the 6th version, ICD-6, that incorporated morbidity for the first time. ICD was consequently revised every 10 years until the ninth revision in 1975 ICD-10 was endorsed in May 1990. It is used in more than 100 countries and translated into 43 languages. Around the same time that Florence Nightingale was highlighting the desperate need for comparative hospital records, Dr William Farr, who worked for the General Register Office for England and Wales, became the first medical statistician. Based on the classification developed by William Cullen, Farr was appointed to develop an internationally applicable and uniform classification for the recording of causes of death. A committee, chaired by Jacques Bertillon ( ), took the International Listings developed by Farr further, increasing the classification to include over 200 groups of causes of death. The development of the International Lists of Diseases recognised the need to record not only mortality figures and diseases that did not necessarily cause death, but disability in the population. The sixth revision of the classification which included diseases and causes of death, was circulated to all national governments in 1946 and became known as the “International Classification of Diseases, Injuries and Causes of Death”. This classification was finally adopted by the World Health Organisation in 1948. It is the Office of National Statistics (ONS) in Fareham, Hampshire where all the coding of death certificates (Mortality coding) is performed. Hospital coders code for morbidity purposes only. Mortality: a measure of the number of deaths in a given population. Morbidity: a diseased state, disability, or poor health For more information on the history of Classifications please visit Dr William Farr, who worked for the General Register Office for England and Wales, became the first medical statistician. Based on the classification developed by William Cullen, Farr was appointed to develop an internationally applicable and uniform classification for the recording of causes of death. Farr’s classification was arranged under five group headings; epidemic diseases constitutional (general) diseases local diseases arranged according to anatomical site developmental diseases diseases directly as a result of violence The resulting classification was revised in 1874, 1880 and 1886, and although never really universally accepted, the general arrangement became the basis of the International Lists of Causes of Death. A committee, chaired by Jacques Bertillon ( ), took the International Listings developed by Farr further, increasing the classification to include over 200 groups of causes of death. The development of the International Lists of Diseases recognised the need to record not only mortality figures and diseases that did not necessarily cause death, but disability in the population. The sixth revision of the classification which included diseases and causes of death, was circulated to all national governments in 1946 and became known as the “International Classification of Diseases, Injuries and Causes of Death”. This classification was finally adopted by the WHO in 1948. Since then ICD has been revised numerous times over the decades, the most current revision is ICD-10 (tenth revision) which was endorsed in May It is used in more than 100 countries and translated into 43 languages. NB: It is the Office of National Statistics (ONS) down in Fareham, Hampshire where all the coding of death certificates (Mortality coding) is performed. Hospital coders code for morbidity purposes only.

8 Development of the classification of procedures
The first statistical classification of surgical procedures was introduced in the UK in 1944 Over subsequent decades it was periodically revised, culminating in the introduction of the OPCS-4 classification which was fully implemented across the NHS in 1990. As OPCS-4.2 no longer accurately reflected many of the procedures being performed in the UK, a program of revisions was implemented. Since the implementation of OPCS-4.3 in April 2006 there have been four further revisions to OPCS-4. OPCS-4.7 was implemented in 2014 with a further revision, OPCS-4.8 due for implementation on 1st April 2017 The OPCS-4 classification follows the same chapter and code structure as ICD-10 with similar rules and conventions, but it is only used by health professionals in the UK and is developed and maintained by NHS Digital Clinical Classifications Service. Due to the advancements of procedures and interventions in the modern day, countries have adopted their own classification of procedures. In the UK procedures and interventions are classified using OPCS-4. It is based on the earlier Office of Population Censuses and Surveys Classification of Surgical Operations and Procedures (4th revision), and retains the OPCS abbreviation. The first statistical classification of surgical procedures was introduced in the UK in 1944 Over subsequent decades it was periodically revised, culminating in the introduction of the OPCS-4 classification which was fully implemented across the NHS in 1990. As OPCS-4.2 no longer accurately reflected many of the procedures being performed in the UK, a program of revisions was implemented. Since the implementation of OPCS-4.3 in April 2006 there have been four further revisions to OPCS-4. OPCS-4.7 was implemented in 2014 with a further revision due for implementation in April 2018

9 The importance of coded data
The coding process and how data is used

10 Current Classifications – ICD-10 & OPCS-4
‘A classification is a systematic arrangement of like entities based on differing characteristics’ The classifications we use in clinical coding are the ‘International Classification of Diseases and Related Health Problems – Tenth Revision’ (ICD-10) and ‘Office of Population Censuses and Surveys Classification of Interventions and Procedures – Fourth Revision’ (OPCS-4). Groups ‘like’ entities together in a standardised medical language Provides a structured framework for statistical information Governed by rules and conventions Nationally and internationally recognised Classifications provide us with a tool to interpret large amounts of information in a format which can be easily tabulated, aggregated, interpreted and analysed. The format ensures the information is comparable, consistent and easily manipulated. For more information on ICD-10 and to view the ICD-10 browser please click on the image The classifications we use in clinical coding are the ‘International Classification of Diseases and Related Health Problems – Tenth Revision’ (ICD-10) and ‘Office of Population Censuses and Surveys Classification of Interventions and Procedures – Fourth Revision’ (OPCS-4). Classifications = a systematic arrangement of like entities based on differing characteristics Classifications provide us with a tool to interpret large amounts of information in a format which can be easily tabulated, aggregated, interpreted and analysed. The format ensures the information is comparable, consistent and easily manipulated. Classification This is a category, arrangement, group, section or organisation. It is a list of concepts belonging to a group. The list of concepts can be arranged in a hierarchy. Classifications are not regularly updated. Both ICD-10 and OPCS-4 are examples of classifications.

11 The coding and collection process
You will cover Hospital Episode Statistics (HES) again during the next few slides. You can also find out more information at the end of this presentation Coded data is a pivotal function of the NHS as this provides detailed data on many different aspects of a patient’s care. You will look at the uses of coded data on the next slides. Patient admitted to hospital, diagnosed, treated and discharged The medical record is accessed by the Clinical Coder and the relevant information for the patient’s hospital stay is extracted including: Main condition treated or investigated Secondary diagnoses Any relevant procedures or interventions The medical and interventional terminology is analysed and translated into a coded format using ICD-10 and OPCS-4 After the information is coded onto the hospital’s information system the data is uploaded to the data warehouse known as Secondary Uses Service (SUS) From SUS data Hospital Episode Statistics (HES) and the National Tariff Payment System (previously Payment by Results (PbR)) data is generated All the data from the patient’s hospital stay is uploaded to the Secondary Uses Service (SUS) which is the single, comprehensive secure data warehouse for healthcare data in England. HES extracts are taken from the Secondary Uses Service (SUS) data warehouse on a monthly basis, at pre-arranged dates during the year. Each extract is cumulative and contains data submitted for the financial year so far, i.e. month 1 will only contain the data submitted with an activity date in April, but month 6 will contain data submitted with an activity date from April to September.  HES represents a series of fixed positions aligned to extracted data, while SUS is continuously updated whenever data is submitted. This is why there can be differences between SUS and HES even when looking at the same time period. National Tariff data is sourced from SUS data which is the same source as used for HES data. There are a number of differences between National Tariff data and HES data. The first difference relates to the cumulative nature of the HES extract with the year to date being extracted each time whereas National Tariff data is not cumulative and simply takes a single monthly snapshot at a given point in time (known as 'freeze') and never returns to extract that same data again in the future.  The process begins when the patient is admitted to hospital; an ‘episode of care’ is generated on the hospital’s Patient Administration System (PAS) which contains details of patient demographics, admission method, specialty and consultant. During the patient’s hospital stay they may be transferred under different specialities or Consultants, each one of these transfers will generate a ‘Consultant Episode’ and will require coding by the Clinical Coder in the Coding department once the patient is discharged. On discharge the coding department is notified of the patient’s discharge through the PAS system and this is then available to code. The Coder will access the patient’s medical record (this could be handwritten notes in a set of case notes or typed documents in an Electronic Patient Record (EPR)). Coders are highly trained to know what relevant information needs to be extracted, analysed and coded. The medical terminology is translated into a coded format and added to the PAS system. Coded data is a pivotal part of the function of the NHS as this provides detailed data on many different aspects of a patient care. We will look at the uses of coded data on the next slides. The process begins when the patient is admitted to hospital; an ‘episode of care’ is generated on the hospitals PAS system which contains details of patient demographics, admission method, specialty and consultant. During the patients hospital stay they may be transferred under different specialities or consultants, each one of these transfers will generate a ‘consulant episode’ and will require coding by the coder in the coding department once the patient is discharged. On discharge the coding department are notified of the patient discharge through the PAS system and this is then available to code. The Coder will access the patient’s medical record (this could be handwritten notes in a casenote or an electronic patient record (EPR)). Coders are highly trained to know what relevant information needs to be extracted, analysed and coded. The medical terminology is translated into a coded format and added to the PAS system. All the data from the patients hospital stay is uploaded to the Secondary Uses Service (SUS) which is the single, comprehensive secure data warehouse for healthcare data in England. HES extracts are taken from the Secondary Uses Service (SUS) data warehouse on a monthly basis, at pre-arranged dates during the year. Each extract is cumulative and contains data submitted for the financial year so far, i.e. month 1 will only contain the data submitted with an activity date in April, but month 6 will contain data submitted with an activity date from April to September.  HES represents a series of fixed positions aligned to extracted data, while SUS is continuously updated whenever data is submitted. This is why there can be differences between SUS and HES even when looking at the same time period. National Tariff data is sourced from SUS data which is the same source as used for HES data. There are a number of differences between the National Tariff data and HES data. The first difference relates to the cumulative nature of the HES extract with the year to date being extracted each time whereas National Tariff data is not cumulative and simply takes a single monthly snapshot at a given point in time (known as 'freeze') and never returns to extract that same data again in the future. 

12 The uses of coded data - Statistical
Coded information can be used in a statistical manner to provide accurate and uniform data which can be utilised in many areas of healthcare. Statistical (Indirect Care) Resource management & casemix planning Commissioning National tariff payment system and HRG4+ Epidemiological / aetiological studies Clinical indicators Health trends Indirect care of the patient is supported by a Classification Allows each individual Trust to plan and allocate resources according to the casemix of their patients. The aim of the National Tariff Payment System is to provide a transparent, rules-based system for paying Trusts. It rewards efficiency, supports patient choice and diversity and encourages activity for sustainable waiting time reductions. Payment are linked to activity and adjusted for casemix. Importantly, this system ensures a fair and consistent basis for hospital funding rather than being reliant principally on historic budgets and the negotiating skills of individual managers. HRG v4+ codes signify clinically similar treatments that use common levels of healthcare resource (iso-resource). An information management tool, their development is to support the National Tariff Payment System. Allows health care specialists to analyse frequency of occurrence of diseases and identify at risk populations based on demographic and geographical coded data. For example, epidemiologists can use coded data to analyse where lung cancers most commonly occur in the UK, and then assess why this may be. Allows health care specialists to analyse frequency of occurrence of diseases and identify at risk populations based on demographic and geographical coded data. For example, epidemiologists can use coded data to analyse where lung cancers most commonly occur in the UK, and then assess why this may be. Coded data provides an income for the Trusts by securing funding from the Treasury. Inaccurate coded data may result in a failure to secure the funds necessary to provide services which meet the needs of the population. Provides information with which to monitor Trust performance against other Trusts, thus ensuring equality for patients, implementation of best practice and addressing bad practice. Examples of clinical indicators include patients re-admitted to hospital following discharge after stroke or myocardial infarction. Coded information can be used in a statistical manner to provide accurate and uniform data which can be utilised in many areas of healthcare. Commissioning - Coded data provides an income for the Trusts by securing funding from the Treasury. Inaccurate coded data may result in a failure to secure the funds necessary to provide services which meet the needs of the population. Resource management and casemix planning - allows each individual Trust to plan and allocate resources according to the casemix of their patients. Clinical Indicators - provides information with which to monitor Trust performance against other Trusts, thus ensuring equality for patients, implementation of best practice and addressing bad practice. Examples of clinical indicators include patients re-admitted to hospital following discharge after stroke or myocardial infarction. Epidemiology, aetiology and health trend evaluations - allows health care specialists to analyse frequency of occurrence of diseases and identify at risk populations based on demographic and geographical coded data. For example, epidemiologists can use coded data to analyse where lung cancers most commonly occur in the UK, and then assess why this may be. National Tariff Payment System (version 4.0 HRGs) - The aim of the National Tariff Payment System is to provide a transparent, rules-based system for paying trusts. It will reward efficiency, support patient choice and diversity and encourage activity for sustainable waiting time reductions. Payment will be linked to activity and adjusted for casemix. Importantly, this system will ensure a fair and consistent basis for hospital funding rather than being reliant principally on historic budgets and the negotiating skills of individual managers. Confirm that HRG v4 codes signify clinically similar treatments that use common levels of healthcare resource (iso-resource). An information management tool, they are currently being developed to support the National Tariff Payment System.

13 The uses of coded data - Clinical
Cost analysis, treatment effectiveness and outcome measurements all provide additional clinical information to improve patient care on both a local and national level. Coded information can also be used for clinical purposes. Clinical use of clinical coded data is direct care of the patient and is most significantly supported by a Terminology, you will look at the difference between a classification and a terminology later in this presentation. Clinical (Direct Care) Clinical Audit Clinical governance Cost analysis Clinical Decision Support Outcome measurement Treatment effectiveness Provides coded information for comparisons of patient care and measurement of outcomes within specialties. Trusts can use coded information to analyse internal performance, to assist best practice and to address problem areas in the treatment of patients. Direct care of the patient is most significantly supported by a Terminology (SNOMED CT) SNOMED CT (a terminology) provides clinicians with the knowledge and person-specific information they need to care for their patients. Coded information can also be used for clinical purposes, such as: Clinical Governance - Trusts can use coded information to analyse internal performance to assist best practice and to address problem areas in the treatment of patients. Clinical Audit - provides coded information for comparisons of patient care and measurement of outcomes within specialties. Cost analysis, treatment effectiveness and outcome measurements - all provide additional clinical information to improve patient care on a local and national level. Outcome measurement is becoming increasingly important within the NHS. These include Clinical Indicators, e.g. number of re-admissions following discharge after MI or stroke. Currently healthcare professionals, in the main, use paper records. Doctors, nurses and other healthcare professionals record clinical details about the patient and the direct care they receive (could be in primary, secondary or community care). Clinical coders (in secondary care) abstract information about the patient’s main condition, relevant co-morbidities and treatment/procedures carried out to translate into classification codes. Clinical use of clinical coded data is direct care of the patient and is most significantly supported by a Terminology

14 Hospital Episode Statistics (HES)
HES is a data warehouse containing details of all admissions, outpatient appointments and Accident and Emergency (A&E) attendances at NHS hospitals in England. This 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, that is used for non-clinical purposes, of this administrative data. The benefits of HES: monitor trends and patterns in NHS hospital activity assess effective delivery of care support local service planning provide the basis for national indicators of clinical quality reveal health trends over time inform patient choice determine fair access to health care develop, monitor and evaluate government policy support NHS and parliamentary accountability HES is a data warehouse containing details of all admissions, outpatient appointments and A&E attendances at NHS hospitals in England. This 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, that is use for non-clinical purposes, of this administrative data. The benefits of HES: monitor trends and patterns in NHS hospital activity assess effective delivery of care support local service planning provide the basis for national indicators of clinical quality reveal health trends over time inform patient choice determine fair access to health care develop, monitor and evaluate government policy support NHS and parliamentary accountability

15 This snapshot shows high level primary diagnosis data which can be drilled down into specific detail. The data shows the top 10 diagnoses that patients were treated for during We know that patients were treated or investigated for these conditions because the Coder follows the ‘primary diagnosis definition’ which stipulates that ‘…the first field of a coded clinical record must contain the main condition treated or investigated during the relevant episode of healthcare’. Snapshot of HES data The top 10 diagnoses for Admitted Patient Care in England, This shows the average age of a patient diagnosed with pneumonia Primary diagnosis: 3 character code and description Finished consultant episodes Male Female Mean age Emergency Elective Other Total 18,731,987 8,359,373 10,370,257 53 1,593,592 369,747 611,417 J18 Pneumonia, organism unspecified 447,396 223,446 223,943 74 14,010 123 Z38 Liveborn infants according to place of birth 425,787 212,341 213,372 - 923 38 99,672 R10 Abdominal and pelvic pain 331,376 104,127 227,231 42 85,909 2,039 1,624 N39 Other disorders of urinary system 327,773 128,193 199,571 70 26,299 1,788 107 R07 Pain in throat and chest 308,988 158,835 150,141 58 121,408 1,178 851 H26 Other cataract 241,315 102,097 139,190 418 3,867 15 J44 Other chronic obstructive pulmonary disease 219,771 104,579 115,190 73 13,734 103 31 C50 Malignant neoplasm of breast 197,877 1,193 196,677 2,567 11,331 56 H25 Senile cataract 172,287 72,014 100,268 75 83 2,512 16 M54 Dorsalgia (back pain) 167,268 62,309 104,942 57 19,517 4,062 193 There are many instances where patients are admitted with symptoms such as abdominal pain and chest pain but a definitive diagnosis cannot be reached. There are various reasons for this and coders are trained to look out for a definitive diagnosis in the medical record Evidence that men can also develop breast cancer There are vast amounts of data reported in HES and much analysis is performed on the data such as average length of stay and average age of patient, which is also broken down to age range. This snapshot shows high level primary diagnosis data which can be drilled down into specific detail. The data shows the top 10 diagnoses that patients were treated for during We know that patients were treated or investigated for these conditions because the coder’s follow the ‘primary diagnosis definition’ which stipulates that …the first field of a coded clinical record must contain the main condition treated or investigated during the relevant episode of healthcare’. Other data shown here includes the admission method and the sex of the patient so it gives an idea of just how many patients are admitted over the course of the year.

16 The future of Clinical Coding
ICD-11 and SNOMED CT

17 ICD-11 is currently in development; the testing phase is a thorough process to ensure the classification is fit for purpose and that it is an improvement on ICD-10. ICD-11 development The World Health Organization (WHO) is currently developing the 11th revision of ICD. WHO will brief the World Health Assembly in May 2018 and if ICD-11 is accepted countries can choose to adopt the new classification. The purpose of ICD-11 is to better reflect progress in health sciences and medical practice which are continuously evolving and will evolve at the same rate going forward. It is designed to be used in electronic health information systems and aligns with other classifications and terminologies such as ICD-O (International Classification of Disease for Oncology) and SNOMED-CT. To view the ICD-11 browser please click on the image

18 SNOMED CT SNOMED CT is a clinical terminology
Clinical Coders are not directly involved with SNOMED CT. However, the Government’s latest white paper Personalised Health and Care 2020 endorses the move to adopt a single clinical terminology – SNOMED CT – to support direct management of care into the entire health system by 2020. SNOMED CT SNOMED CT is a clinical terminology A structured list of terms for use in clinical practice. These terms describe the care and treatment of patients and cover areas like diseases, operations, treatments, drugs and healthcare administration. This allows for detailed recording of treatment. Clinical Terminologies are designed for use with an electronic system and are used to support direct management of care i.e. clinical use. Cross-maps are already provided from SNOMED CT concepts  to ICD-10 and OPCS-4. If the decision is taken to implement ICD-11, cross-maps will also be provided to ICD-11. Think back to the earlier slides that highlighted the difference between statistical and clinical use of data For more information on SNOMED CT please visit the SNOMED CT webpage To aid Clinical Coders the Clinical Classifications Service produce a product known as the cross-maps. This provides probable classification codes for a ‘clinical meaning’ but still relies on the classification expertise of the coder to select the most appropriate codes based on the full information in the patient record to support statistical data.

19 SNOMED CT and clinical classifications
SNOMED CT and clinical classifications are complementary and serve different purposes. Neither a clinical terminology nor a clinical classification can, by itself, serve all the purposes for which health information is currently used or will be used in the future. Remember: SNOMED CT is the vocabulary for use by clinicians in an Electronic Patient Record (EPR). It is recorded at the point of care and is focussed on what a clinician wants to record about the patient. ICD-10 and OPCS-4 are recorded after the event and focusses on what we need to count for statistical and epidemiological analyses. SNOMED CT is dynamic and updated twice a year to keep up with the latest developments in healthcare. ICD-10 and OPCS-4 are only updated every three years. This ensures stability for consistent and comparable analyses of population health across time. So the products are complimentary…not competing. Clinical use of data is supported by a terminology (SNOMED CT) Statistical use of data is supported by classifications (ICD-10/ICD-11 and OPCS-4)

20 The Clinical Classifications Service
Our key responsibilities, product development and support

21 Our Role Develop and maintain standards
The team at the Clinical Classifications Service is made up of Classifications Specialists who hold a vast amount of expert knowledge in all aspects of Clinical Coding. All specialists are Accredited Clinical Coders by background and some are also approved Clinical Coding Auditors and/or Trainers. Our Role Develop, issue and maintain the standards relating to all clinical classification data in use in the NHS (ICD-10 and OPCS-4) promoting the consistency of classification as a key part of delivering a patient-centred health service. Develop and maintain standards Centre of expertise and point of contact Product support helpdesk ICD-10 and OPCS-4 SNOMED CT cross maps Clinical coding audit methodology Training and accreditation World Health Organisation Collaborating Centre Provide the centre of expertise and a point of contact for national and international coding classifications work Deliver Classifications and Coding Standards Support giving official resolutions to all clinical coding queries Develop and maintain an extensive portfolio of associated products (including cross maps from SNOMED CT concepts to ICD-10 and OPCS-4) Drive data quality by developing and delivering top notch clinical coding audit methodology Provide an education, training and accreditation programme for clinical coders to support an individual coder's continuous professional development to become a trainer or auditor or manager Conduct comprehensive quality assurance exercises on the developing ICD-11

22 Product Support and Development
Classifications and Coding Standards Support and the national clinical coding query mechanism ICD-10 and OPCS-4 files and supporting tools such as metadata files National standard clinical coding reference materials UK Coding Review Panel providing guidance and developing national clinical coding standards National Clinical Coding Qualification (UK) and associated materials Clinical coding audit methodology, Code of Practice and workshops Clinical classifications training service – a portfolio of courses and training materials to support coders and trainers ICD-11 Working Group The Clinical Classifications Service is responsible for a whole host of products, some of which are shown here.

23 NHS Digital Terminology and Classifications
Further information If you are interested in finding out more information about anything covered in this presentation please visit the sites below: NHS Digital Terminology and Classifications ICD-10 OPCS-4 HES SUS WHO SNOMED CT

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