As discussed previously, in addition to the data specifically relating to medicines and their properties, EP systems require data schemas to describe details of diagno- sis, contraindications and side-effects, in order to provide the most comprehensive functionality.
Third-party Drug Data
Decision Support Module
Decision Support
Data Prescribing &
Administration User Interface
Drug Database
Drug Data Demographic
Data
Prescribing Support Data
Prescribing Support Data (Disease Scoring, Monitoring etc) Patient
Administration System Clinical Users
Fig. 5.1 EP data architecture
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Coding Systems for EP Concepts 79
The discipline of health informatics has developed to analyse and systematise health and disease related information and, with time, a number of clinical coding systems have evolved to describe health and medicine concepts in a machine- readable manner. 1 Many of the coding systems have their historical origins in the need to classify and enumerate medical events for public health purposes. Many of these have relevance to EP systems and are discussed below.
The International Classification of Diseases (ICD) is a multiple axis disease classification schema which is published and administered by the World Health Organisation. It is now in its tenth revision (ICD 10). This schema has its origins in the work of William Farr, the first medical statistician for the General Register Office of England and Wales, in the mid-nineteenth century. He saw the need for a classification system for diseases to enable mortality statistics to be collected on an ongoing basis. Initially the schema was designed to record causes of death, but was subsequently developed to list diseases and disorders causing consider- able morbidity. Nevertheless, the classification continued to be used for the pragmatic purpose of collecting epidemiological data, and it is still used by WHO for making international comparisons of health statistics. The schema is therefore a practical classification, rather than a theoretical one, and it may require adjustments to allow finer levels of detail to be expressed in certain applications. ICD 10 coding is often used as the coding system for diseases and diagnoses assigned to patients in electronic medical records, and would be the point of reference for EP decision support tools giving contraindication/precau- tion checking or drug – disease interaction checking, based on patient record information. ICD 10 codes are of particular concern in EP applications where there is a clear requirement for production of reports or statistical returns. An example of this would be oncology systems for the management of oncology and haematology clinics, where there is a major political need to report epidemio- logical data. In the UK, this is facilitated by the agreed National Cancer Data Set, which was established to eliminate reporting inconsistencies between different UK Cancer Registries. 2
Diagnosis related groups (DRGs) were developed in the US by the Healthcare Finance Administration as a means of assigning a cost of treatment to a patient’s diagnosis. They were developed to enable calculation of Medicaid reimbursement costs. DRGs are based upon ICD Clinical Modification (ICD-CM) codes in ICD 9 or ICD 10. Appropriate ICD codes are refined by placing them in diagnostic cate- gories and then grouping them into subgroups that reflect consumption of resources, criteria for treatment and potential complications. Thus patients are assigned a DRG from a relatively small number of DRG codes. DRGs are used routinely in the US and have been adapted in other countries where a reimbursement algorithm has been required. They are designed for hospital inpatients and do not provide a suitable means of assessing the costs of chronic disease care. Availability of a DRG designation for a patient, together with actual medicine cost data from an EP sys- tem may permit a variance analysis of projected costs and actual costs of inpatient treatment within the US context.
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Read Codes (subsequently called Clinical Terms) were developed in the UK to enable clinicians (mainly in general practice) to code events in the electronic patient record, and thus enable statistical auditing of the patient care process in pri- mary care. Read Codes have latterly been owned and administered by the UK govern ment. Read Codes have changed considerably both in their terminology and in their structure during their lifespan. Version 1 of the Read Codes was a strictly hierarchical schema. In version 2, the structure was changed so that they more closely approximated ICD 9 disease codes and OCPS 4 procedure codes. Version 3 of the Read Codes was, in contrast with version1, a compositional schema, where each term could be augmented by qualifier terms.
Read codes have been used extensively to code for diagnosis, problems and medicine prescribing in GP systems in the UK. However, they have not been used routinely in secondary care applications, largely because they were developed for primary care use. A key issue in the use of Read Codes has been the increasing potential for lack of concept control with combination terms, in the latter versions.
However, many primary care (GP) systems map prescribed medicines to their respective Read Codes, and Read Codes may therefore have a role in facilitating communication between primary care and secondary care systems in the UK.
The Systematised Nomenclature of Medicine (SNOMED) is administered by the College of American Pathologists, and was derived from classifications of tumour and pathology nomenclature used by the College. SNOMED is designed to be a comprehensive, computer processable terminology to support all medical concepts.
SNOMED is in use in over 40 countries. Principally, it is a hierarchical, multiple axis schema, but it also allows composition of complex terms from simple terms, so is partly compositional, and it has the facility of cross-referencing between terms in the schema. SNOMED International (SNOMED III) incorporates almost all ICD 9 terms, so reports can be generated in ICD 9 format.
In 1999, the College of American Pathologists and the UK National Health Service announced their plan to converge SNOMED and Clinical Terms (Read Codes) version 3 into a single terminology. The stated intention was to avoid dupli- cation of effort and to create a universal, international terminology to support elec- tronic patient records. The first version of the combined terminology – SNOMED Clinical Terms – was released in 2002, and it has been adopted as the standard ter- minology for UK Connecting for Health healthcare applications. 3 Third-party drug data suppliers are working to map their datasets to international terminologies such as SNOMED-CT, in order to provide intraoperability with other systems in the area of more advanced decision support, for example contraindications, dose/indication checking and drug – disease interactions.
An important area of data standardisation is the development of HL7 (Health Level 7), which is an XML-based terminology, 4 designed for the purpose of model ling healthcare processes, and producing a common terminology for all concepts in health care, to provide an industry standard for intraoperability across all healthcare applications. Many healthcare IT systems are marketed as “ HL7 compliant ” . However, development of the message formats to enable extensive and comprehensive description of healthcare processes is an ongoing and gradual
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Coding Systems for EP Concepts 81
process. This is because (a) HL7 message formats are being designed to model all healthcare scenarios, not just those involving pharmacy and therapeutics, (b) there is a need for consistency in the consensus-forming process and (c) major semantic assumptions need to be made and understood by the international HL7 commu- nity, at each stage of the HL7 design process in different domains. Recently, there have been initiatives to make closer links between SNOMED-CT concepts and HL7 message formats, in order to achieve greater semantic intraoperability in healthcare applications. 5 Specifically in the area of pharmaceuticals, the Dictionary of Medicines and Devices (dm+d) has been developed to describe concepts associ- ated with the use of specific medicines and devices for the diagnosis and treatment of patients. 6 The dm+d is integrated with SNOMED Clinical Terms and would enable applications dealing with medicines – such as hospital EP systems, and hos- pital and community pharmacy systems – to exchange information with a common terminology. The dm+d is the medicines terminology for the UK Connecting for Health programme, and will enable intraoperability of systems in the UK NHS IT initiative. The first part of the dm+d work was the Primary Care Drug Dictionary, which was launched by the UK Prescription Pricing Authority in 2003. The first version of the full dm+d, for medicines used in primary care and secondary care, together with some prescribable devices, was released in 2004.
In order to support all aspects of the prescribing, supply and administration of medicines, the dm+d is structured into a number of related concepts as shown in Fig. 5.2 .
The dm+d data structure enables EP systems to differentiate at the data level between the concepts of medicine prescribing, administration and supply, which is important to provide rich functionality at each stage in the medicines management process. It will enable users to identify prescribed medicines of the EP system clearly and unambiguously, which will impact on the risk management aspects of
Amoxicillin
Amoxicillin 250mg Capsules
Amoxicillin 250mg Capsules (APS)
Amoxicillin 250mg Capsules (APS) (21 pack) Amoxicillin
250mg Capsules (21 pack)
VTM - Virtual Therapeutic Moiety
VMP - Virtual Medicinal Product
AMP - Actual Medicinal Product
VMPP - Virtual Medicinal Product Pack
AMPP - Actual Medicinal Product Pack Fig. 5.2 dm+d structure
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EP system use. dm+d will also provide a common platform for analysis of prescribing data in both primary and secondary care in the UK, something that cannot be done at present. This will have important implications for commissioning and care management.