Dental Attendances to General Medical Practitioners in Wales: A 44 Year-Analysis

One-third of the UK population is composed of problem-oriented dental attenders, seeking dental care only when they have acute dental pain or problems. Patients seek urgent dental care from a range of health care professionals, including general medical practitioners. This study aimed to identify trends in dental attendance at Welsh medical practices over a 44-y period, specifically in relation to dental policy change and factors associated with repeat attendance. A retrospective observational study was completed via the nationwide Secure Anonymised Information Linkage (SAIL) Databank of visits to general medical practice in Wales. Read codes associated with dental diagnoses were extracted for patients attending their general medical practitioner between 1974 and 2017. Data were analyzed with descriptive statistics and univariate and multivariable logistic regression. Over the 44-y period, there were 439,361 dental Read codes, accounting for 288,147 patient attendances. The overall attendance rate was 2.60 attendances per 1,000 patient-years (95% CI, 2.59 to 2.61). The attendance rate was negligible through 1987 but increased sharply to 5.0 per 1,000 patient-years in 2006 (95% CI, 4.94 to 5.09) before almost halving to 2.6 per 1,000 in 2017 (95% CI, 2.53 to 2.63) to a pattern that coincided with changes to National Health Service policies. Overall 26,312 patients were repeat attenders and were associated with living in an area classified as urban and deprived (odds ratio [OR], 1.22; 95% CI, 1.19 to 1.25; P < 0.0001) or rural (OR, 0.84; 95% CI, 0.83 to 0.85; P < 0.0001). Repeat attendance was associated with greater odds of having received an antibiotic prescription (OR, 2.53; 95% CI, 2.50 to 2.56; P < 0.0001) but lower odds of having been referred to another service (OR, 0.75; 95% CI, 0.70 to 0.81; P < 0.0001). Welsh patients’ reliance on medical care for dental problems was influenced by social deprivation and health policy. This indicates that future interventions to discourage dental attendance at medical practitioners should be targeted at those in the most deprived urban areas or rural areas. In addition, health policy may influence attendance rates positively and negatively and should be considered in the future when decisions related to policy change are made.

GP coding behaviour for non-specific clinical presentations: a pilot study

BackgroundClinical coding is an integral part of primary care. Disease incidence studies based on primary care electronic health records (EHRs) rely on the accuracy of these codes. Current code validation methods are not appropriate for non-specific conditions and provide limited information about GPs' decision-making behaviour around coding. Qualitative methods could offer insight into decision-making behaviour around coding of patients with non-specific conditions.AimTo investigate the decision-making behaviour of GPs when applying Read codes to non-specific clinical presentations, using Lyme disease as a case example.Design & settingA pilot study was undertaken, involving masked semi-structured interviews of eight GPs in the North West of England.MethodSemi-structured interviews were carried out based on 11 clinical cases representative of Lyme disease presentations. Discrete answers were described descriptively. Interview transcripts were analysed using a thematic approach.ResultsThemes underpinning GPs’ coding behaviour included: GP personal and professional experience; clinical evidence; diagnostic uncertainty; professional integrity and defensive practice; and patient-sourced health information and beliefs. GPs placed Lyme disease on their differential diagnosis list for five cases; in only two cases would GPs select a Lyme disease related Read code.ConclusionGPs were reluctant to code with specific diagnostic Read codes when they were presented with patients with vague or unfamiliar symptomology. This masked questionnaire methodology offers a new approach to validate incidence figures, based on Read codes of non-specific conditions. The reluctance to code poses many problems for primary care EHRs research. Further research is needed to understand what drives GPs’ coding behaviour.

Validation study of bullous pemphigoid and pemphigus vulgaris recording in routinely collected electronic primary healthcare records in England

ObjectivesThe validity of bullous pemphigoid and pemphigus vulgaris recording in routinely collected healthcare data in the UK is unknown. We assessed the positive predictive value (PPV) for bullous pemphigoid and pemphigus vulgaris primary care Read codes in the Clinical Practice Research Datalink (CPRD) using linked inpatient data (Hospital Episode Statistics (HES)) as the diagnostic benchmark.SettingAdult participants with bullous pemphigoid or pemphigus vulgaris registered with HES-linked general practices in England between January 1998 and December 2017. Code-based algorithms were used to identify patients from the CPRD and extract their benchmark blistering disease diagnosis from HES.Primary outcome measureThe PPVs of Read codes for bullous pemphigoid and pemphigus vulgaris.ResultsOf 2468 incident cases of bullous pemphigoid and 431 of pemphigus vulgaris, 797 (32.3%) and 85 (19.7%) patients, respectively, had a hospitalisation record for a blistering disease. The PPV for bullous pemphigoid Read codes was 93.2% (95% CI 91.3% to 94.8%). Of the bullous pemphigoid cases, 3.0% had an HES diagnosis of pemphigus vulgaris and 3.8% of another blistering disease. The PPV for pemphigus vulgaris Read codes was 58.5% (95% CI 48.0% to 68.9%). Of the pemphigus vulgaris cases, 24.7% had an HES diagnosis of bullous pemphigoid and 16.5% of another blistering disease.ConclusionsThe CPRD can be used to study bullous pemphigoid, but recording of pemphigus vulgaris needs to improve in primary care.

P0469VALIDATING THE DIAGNOSTIC ACCURACY OF MEMBRANOUS NEPHROPATHY IN THE HEALTH IMPROVEMENT NETWORK (THIN) DATABASE

Background and Aims Membranous nephropathy (MN) is among the most common causes of nephrotic syndrome in adults worldwide. Despite this, there is currently no robust data on the epidemiology of MN in the UK population. The Health Improvement Network (THIN) is an electronic medical record database that holds longitudinal anonymised patient records for over 17 million patients and has shown to be generalisable to the UK regarding demographics and crude prevalence’s of major conditions. To our knowledge, accuracy of the read codes for glomerular disease is yet to be validated. This will be the first study into MN validating the diagnostic accuracy using the THIN database. Method THIN database was interrogated for patients with MN using read codes. Two cohorts were considered: Definite cohort, defined as read codes expected to correspond to a diagnosis of MN, and Probable cohort, defined as read codes that could correspond to a diagnosis of MN. In order to confirm the diagnosis of MN, a short questionnaire was sent to the GP practice of a randomly selected cohort of patients asking if the diagnosis of MN was correct, and that the diagnosis had been confirmed by a specialist renal centre, with or without a renal biopsy. Results 267 patients with a record of MN were identified from the THIN database. 235 of the patients had Definite cohort read codes, with a mean age at diagnosis of 57 years. There were 155 (66.2%) male and 79 (33.8%) female patients. 32 patients were identified in the Probable cohort. GP questionnaires were sent to 71 randomly selected patients with 61 responses (85.9% response rate). This represented 23% (n=53) of the total Definite cohort and 25% (n=8) of the total Probable cohort. Of the 61 returned questionnaires, an MN diagnosis was confirmed in 96% (n=51) of patients with a definite read code and 25% (n=2) with a probable read code. Amongst the confirmed MN diagnoses in the Definite cohort, 88% (n=45) of the patients had primary MN. Conclusion The THIN database is a valid data resource for studying MN in patients with a read code from the Definite cohort list. Read codes from the Probable cohort list cannot be used unless confirmed on a case by case basis such as through the GP. The results of this study will feed into a larger project with an aim to describe accurately the epidemiology of MN in the UK population, and report the incidence and prevalence of specific secondary associations of MN. Once these factors are fully understood, diagnostic and care pathways for MN can be developed.

Should diverticulitis be managed in primary care? An audit on the management of diverticulitis in primary care.

BackgroundThe prevalence of diverticulosis and acute diverticulitis is increasing in developed countries. For those with diverticulosis the lifetime risk of developing acute diverticulitis is about 4–25%. Mild, uncomplicated diverticulitis can be, and often is, managed safely in a primary care setting, avoiding unnecessary admission.AimTo evaluate management of suspected diverticulitis in primary care against standards set by the National Institute for Health and Care Excellence (NICE) and review admission rates following primary care management.MethodAn electronic search on EMIS Web using Read codes ‘diverticulitis’, ‘diverticulosis’, and ‘diverticular disease’, with a specified period of 2017–2019. All consultations with suggestions of an infective flare of diverticular disease were included in the study. Clinical data from the consultations were extracted and retrospectively audited.ResultsA total of 64 patients were identified with diverticular disease or diverticulosis. Of those, 42% (n = 27) presented to primary care with presenting complaints suspicious of diverticulitis. A total of 64 consultations were reviewed, as several patients presented more than once in the study period. Of the consultations reviewed, 12.5% (n = 8) resulted in referral to the surgical assessment unit. Antibiotics were prescribed after 68.4% (n = 39) of consultations. Bloods for inflammatory markers were performed after 19.3% (n = 11) of consultations. Only 3.5% (n = 2) of patients were reviewed within the recommended 48-hour timeframe. Only 3.5% (n = 2) of patients subsequently deteriorated and required admission.ConclusionThe management of diverticulitis in this primary care centre is not fully concordant with NICE guidelines. There is a need to improve adherence, in particular antibiotic regimen when deciding to prescribe antibiotics.

FRI0198 OCULAR MORBIDITY IN PATIENTS WITH PMR AND GCA IN THE UK - A CPRD STUDY

Background:Visual loss is the most serious consequences of a diagnosis of polymyalgia rheumatic (PMR) and giant cell arteritis (GCA). To date, information on the occurrence of eye disease in GCA has been based almost exclusively on small hospital-based patient series. Furthermore the lack of control group for these studies results in a lack of relative risk estimates for visual loss.There are no accurate data on the prevalence and nature of eye complications among patients in the community. Patients with GCA may be exclusively managed in the primary care setting without referral for either temporal artery biopsy or ophthalmic department examination. Currently the incidence and prevalence of eye complications within this group are unknown.Objectives:Examine the absolute rate and relative risk of ocular morbidity, in a longitudinal community setting, in patients with PMR and or GCA including visual loss, AOIN including optic atrophy, cataract and glaucoma identified from Read codes in the (Clinical Practice Research Datalink) CPRD dataset.Methods:Construction of a disease cohort of incident diagnoses of PMR and GCA from patients in the CPRD matched to controls on age, sex (+/- 2 years) and practice location. Diagnosis were identified by CPRD researchers of those individuals between January 1997 to December 2015, with a minimum age at diagnosis of 50 years. Those with both a diagnosis of PMR and GCA were analysed in the GCA group. The outcomes of ocular morbidity included Read codes for severe visual impairment (multiple codes covered: blindness, severe visual impairment, registered partially sighted, issue of certificate of visual impairment, examination findings of 4/60 or worse), anterior ischaemic optic neuropathy (including codes of optic neuropathy and atrophy but not codes of glaucomatous atrophy), cataract, cataract extraction and glaucoma. Statistically modelling with Cox proportional hazards was used to generate hazard ratios for ocular morbidity taking account of censorship through death and moving out of area.Results:We identified 30,714 individuals with PMR (20,270 women; 66%) with a mean age at diagnosis of 72.9 year (sd 9.1) and 6,104 with GCA (4,309 women; 70.6%) with a mean age of 72.1 years (sd 9.4). Of those diagnosed with GCA 1,669 were also diagnosed with PMR. Using Read codes for severe visual impairment and blindness 5.9% of patients with GCA and 2.7% with PMR had this complication compared with 1.6% of the matched controls. The hazard ratio for the various ocular morbidities and by cases of PMR or GCA are shown in the table below:Ocular morbidityPMR HR (95% CI) p valueGCA HR (95% CI) p valueSevere visual impairment1.76 (1.60, 1.94) p=<0.0013.55 (3.10, 4.08) p=<0.001Anterior ischaemic optic atrophy3.37 (2.15, 5.31) p=<0.00136.33 (25.19, 52.39) p=<0.001Cataract2.18 (2.04, 2.32) p=<0.0012.48 (2.22, 2.78) p=<0.001Cataract operation2.11 (1.97, 2.25) p=<0.0012.41 (2.13, 2.72) p=<0.001Glaucoma2.10 (1.91, 2.32) p=<0.0012.50 (2.10, 2.97) p=<0.001Conclusion:These community-based national data on risk of ocular morbidity in PMR and GCA show for the first time the risk of various ocular morbidities are increased for both groups. In addition this are the first estimates of relative risk compared to an age and sex matched population. These data are crucial for providing information to patients about their relative risk of ocular morbidity following a diagnosis of PMR or GCA.Acknowledgments:We would like to thank Dr Helen Strongman at the CPRD for carrying out patient searchers. We thank Dr Ferran Espuny Pujol for completion of the linkage request for dates of death.Disclosure of Interests:Max Yates: None declared, Allan Clark: None declared, Richard Watts: None declared, Alex MacGregor: None declared, Sarah Mackie Grant/research support from: Roche (attendance of EULAR 2019; co-applicant on research grant), Consultant of: Sanofi, Roche/Chugai (monies paid to my institution not to me)

General practice recording of adverse childhood experiences: a retrospective cohort study of GP records

BackgroundAdverse childhood experiences (ACEs) are linked to negative health outcomes in adulthood. Poor engagement with services may, in part, mediate the association between adverse outcomes and ACEs. While appointment recording is comprehensive, it is not yet known if or how ACEs are recorded in the GP clinical record (GPR).AimTo investigate recording of ACEs in the GPR and assess associations between available ACE-related Read codes and missed appointments.Design & settingRetrospective cohort study of 824 374 anonymised GPRs. Nationally representative sample of 136 Scottish general practices; data collected 2013–2016.MethodRead codes were mapped onto ACE questionnaire and wider ACE-related domains. Natural language processing (NLP) was used to augment capture of non-Read-coded ACEs. Frequency counts and proportions of mapped codes, and associations of these with defined levels of missing GP appointments, are reported.ResultsIn total, 0.4% of patients had a record of any code that mapped onto the ACE questionnaire, contrasting with survey-reported rates of 47% in population samples. This increased only modestly by including inferred ACEs that related to safeguarding children concerns, wider aspects of ACEs, and adult consequences of ACEs. Augmentation via NLP did not substantially increase capture. Despite poor recording, there was an association between ever having an ACE code recorded and higher rates of missing GP appointments.ConclusionGeneral practices would require substantial support to implement the recording of ACEs in the GPR. This study adds to the evidence that patients who often miss appointments are more likely to be socially vulnerable.

Defining a GP consultation

IntroductionThe method used to define a GP-consultation using routine data will vary depending on the data source and research question. However, without consensus the approach will be tackled by numerous researchers and invariably result in different definitions. The LUCI study is assessing outcomes of childhood UTI using routine data sources. Objectives and ApproachWe are interested in GP urine sampling rate and re-consultation rate. The GP dataset includes multiple clinical (acute, routine monitoring, prescribing, results) and administrative codes. A GP consultation therefore needed to be defined. GP read code frequencies for our study cohort of children were produced. One researcher reviewed the codes that represented 80% of the data and classified them as a consultation or not. Where there was uncertainty this was independently reviewed by two clinicians and discrepancies agreed by the management team. ResultsWe will present the decisions and assumptions made for this study in defining a GP consultation. 25,623 Read Codes represented the consultations for our study cohort of which 460 codes represented 80% of the consultations. The remaining 20% of codes represented <0.032% of records each. The 460 Read Codes were reviewed and following independent review and agreement from the management group 149 Read Codes were excluded. These were grouped into the following categories Administrative (e.g. Incoming Mail Processing, Ethnicity codes), Vaccinations, Child Health (e.g. First Smiled), Asthma and Medication Review. The GP consultations to be included in the analysis were then restricted to exclude these codes. This has been an important step in cleaning and understanding the data prior to analysis. Conclusion/ImplicationsA consultation was defined for this study however there will be pros and cons to this method. In lieu of a consensus approach to the method this work is the first step to sharing approaches to help researchers with the same challenge.

Identification of validated case definitions for medical conditions used in primary care electronic medical record databases: a systematic review

Objectives Data derived from primary care electronic medical records (EMRs) are being used for research and surveillance. Case definitions are required to identify patients with specific conditions in EMR data with a degree of accuracy. The purpose of this study is to identify and provide a summary of case definitions that have been validated in primary care EMR data. Materials and Methods We searched MEDLINE and Embase (from inception to June 2016) to identify studies that describe case definitions for clinical conditions in EMR data and report on the performance metrics of these definitions. Results We identified 40 studies reporting on case definitions for 47 unique clinical conditions. The studies used combinations of International Classification of Disease version 9 (ICD-9) codes, Read codes, laboratory values, and medications in their algorithms. The most common validation metric reported was positive predictive value, with inconsistent reporting of sensitivity and specificity. Discussion This review describes validated case definitions derived in primary care EMR data, which can be used to understand disease patterns and prevalence among primary care populations. Limitations include incomplete reporting of performance metrics and uncertainty regarding performance of case definitions across different EMR databases and countries. Conclusion Our review found a significant number of validated case definitions with good performance for use in primary care EMR data. These could be applied to other EMR databases in similar contexts and may enable better disease surveillance when using clinical EMR data. Consistent reporting across validation studies using EMR data would facilitate comparison across studies. Systematic review registration PROSPERO CRD42016040020 (submitted June 8, 2016, and last revised June 14, 2016)

Machine-learning based identification of undiagnosed dementia in primary care: a feasibility study

BackgroundUp to half of patients with dementia may not receive a formal diagnosis, limiting access to appropriate services. It is hypothesised that it may be possible to identify undiagnosed dementia from a profile of symptoms recorded in routine clinical practice.AimThe aim of this study is to develop a machine learning-based model that could be used in general practice to detect dementia from routinely collected NHS data. The model would be a useful tool for identifying people who may be living with dementia but have not been formally diagnosed.Design & settingThe study involved a case-control design and analysis of primary care data routinely collected over a 2-year period. Dementia diagnosed during the study period was compared to no diagnosis of dementia during the same period using pseudonymised routinely collected primary care clinical data.MethodRoutinely collected Read-encoded data were obtained from 18 consenting GP surgeries across Devon, for 26 483 patients aged >65 years. The authors determined Read codes assigned to patients that may contribute to dementia risk. These codes were used as features to train a machine-learning classification model to identify patients that may have underlying dementia.ResultsThe model obtained sensitivity and specificity values of 84.47% and 86.67%, respectively.ConclusionThe results show that routinely collected primary care data may be used to identify undiagnosed dementia. The methodology is promising and, if successfully developed and deployed, may help to increase dementia diagnosis in primary care.