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Veterans’ Health
Published in James Matheson, John Patterson, Laura Neilson, Tackling Causes and Consequences of Health Inequalities, 2020
In the UK, primary care information technology systems use Read codes to detail various conditions and information in a patient’s records. There are specific codes pertaining to previous military service. A study of over 40,000 patients at several primary care centres noted the prevalence of military veterans with a Read code in their records was 8.7%. After a period of brief training for staff at the practices using an online training module, and an advertising campaign to encourage veterans to make their status known, the number of veterans identified and coded increased nearly 200% [16]. The identification of veterans and knowledge of their specific health issues from increased awareness through staff training seeks to improve the overall health of service leavers. This principal has been crystallised in collaboration between the Royal College of General Practitioners and NHS England [17]. The scheme is called the Military Veteran Aware Accreditation and encourages primary care providers to identify a lead for veterans’ health. The lead will have received extra training in the health needs of veterans or may be a veteran themselves. The lead will encourage the identification and recording of veterans as well as acting as a link for patients and colleagues to access the various support services available.
The link between record keeping and an EPR
Published in Deb Thompson, Kim Wright, Developing a Unified Patient Record, 2018
In an EPR it is essential to record clinical information in a structured way rather than as free text. According to van Bemmel and Musen5 ‘if data are not structured, the EPR is decreased to, at best, an intelligent word processor’. Information for Health1 recommends the introduction of a common coding language to provide the structure needed. As previously explained, existing coding structures are not flexible enough to fulfil the need. Read Codes, a recent and more flexible system used in primary care, is better suited to the task, as it contains clinical terms as well as codes. However, in order to ensure that the system maintains its flexibility, the national strategy names the system of the future as SNOMED CT. This system combines the best of Read Codes, version 3, with SNOMED RT, a coding system developed and used in America. SNOMED CT will provide clinicians with a way of using clinical language to code rather than having to conform to a system with terminology meaningless to them.
Computerising patient records
Published in Alan Gillies, Bev Ellis, Nick Lowe, Building an Electronic Disease Register, 2018
Alan Gillies, Bev Ellis, Nick Lowe
Read Codes were developed by Dr James Read, hence the name. They are a set of coded terms for use in clinical practice. They have a number of key features which make them the standard system for clinical coding in the UK primary care NHS: Read Codes were developed for primary carethe codes are arranged in a hierarchical structure, so that an extensive clinical terminology can be readily accessed and used by computer softwareRead Codes are updated every 3 months, except for drugs which are updated every monthRead Codes can be cross referenced to all other major systems, e.g. ICD, OPCS, BNF, ATC, etc.coding only works if everyone talks the same language, Read Codes are the UK NHS standard, therefore all other reasons are redundant.
Rationale and design of a European epidemiological post-authorization safety study (PASS) program: rivaroxaban use in routine clinical practice
Published in Expert Opinion on Drug Safety, 2020
Luis Alberto García-Rodríguez, Mari-Ann Wallander, Leif Friberg, Ana Ruigomez, Tania Schink, Irene Bezemer, Ron Herings, Saad Shakir, Alison Evans, Miranda Davies, Kiliana Suzart-Woischnik, Pareen Vora, Yanina Balabanova, Montse Soriano-Gabarró, Gunnar Brobert
For each of the safety and effectiveness outcomes, except all-cause mortality, patients must be admitted to hospital with a diagnostic or procedure code indicative of the outcome of interest. The codes used are specific to each of the data sources and include Read codes, International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) and International Classification of Diseases, Tenth Revision (ICD-10) codes, German claim codes for outpatient services and procedures (Einheitlicher Bewertungsmaßstab [EBM] codes, German Operations and Procedures Coding System [OPS] codes), and Nordic Medico-Statistical Committee (NOMESCO) procedure codes (Supplemental Table S1). Database-specific strategies are used for ascertainment of all-cause mortality, including Read codes, patient registration status or death information recorded in THIN, record of the date of death in the PHARMO Database Network, death recorded as the reason for hospital discharge or termination of insurance in GePaRD [23], and death recorded in the Cause of Death Register for Sweden.
The effect of smoking on outcomes following primary total hip and knee arthroplasty: a population-based cohort study of 117,024 patients
Published in Acta Orthopaedica, 2019
Gulraj S Matharu, Sofia Mouchti, Sarah Twigg, Antonella Delmestri, David W Murray, Andrew Judge, Hemant G Pandit
Patients were initially identified using the Clinical Practice Research Datalink (CPRD) GOLD, which has been described previously (Bayliss et al. 2017). CPRD represents one of the largest databases of longitudinal primary care medical records worldwide. It contains anonymized patient data from 4% of the current UK population (over 2 million patients from 269 contributing practices) (Herrett et al. 2015). Practices’ spread ensures CPRD is representative of the wider UK population for age, sex, and ethnicity. Read Codes are used to enter clinical information (medical history, prescription data, hospital admissions, and interventions), which are standard clinical terminologies used within UK primary care (Benson 2011). CPRD therefore provides a detailed record of both primary and secondary care (Bayliss et al. 2017). The validity and quality of data captured within CPRD have been previously well described (Herrett et al. 2015). A systematic review of validation studies assessing the validity of diagnoses in CPRD identified a large number of studies across a wide range of over 183 different diagnoses and overall estimates of validity were high (Herrett et al. 2010). Aspects of data quality in English primary care are enhanced by the Quality and Outcomes Framework, an incentive payment program for primary care physicians, which encourages recording of key data items (for example smoking status).
Construction and validation of a morbidity index based on the International Classification of Primary Care
Published in Scandinavian Journal of Primary Health Care, 2022
Hogne Sandvik, Sabine Ruths, Steinar Hunskaar, Jesper Blinkenberg, Øystein Hetlevik
The list of health conditions from Barnett et al. was defined by one or more Read codes and in some cases also by drug treatment. We created a list of 38 morbidities defined by corresponding ICPC-2 codes (Table 1), and made the following adaptations: Omitted two of the 40 morbidities, bronchiectasis, because no corresponding ICPC-2 code exists; and treated constipation, because primary care databases do not necessarily contain information on drug prescription. Furthermore, we defined painful conditions as specific long-term musculoskeletal and neurological morbidities that usually include a substantial symptom burden. Similar adaptions were also used for other morbidity groups, such as defining them solely with diagnostic codes and no knowledge of prescriptions.