Dataset Information

Patterns of routine primary care for osteoarthritis in the UK: a cross-sectional electronic health records study.

ABSTRACT: OBJECTIVE:To determine common patterns of recorded primary care for osteoarthritis (OA), and patient and provider characteristics associated with the quality of recorded care. DESIGN:An observational study nested within a cluster-randomised controlled trial. SETTING:Eight UK general practices who were part of the Management of Osteoarthritis in Consultations study. PARTICIPANTS:Patients recorded as consulting within the eight general practices for clinical OA. PRIMARY OUTCOMES:Achievement of seven quality indicators of care (pain/function assessment, information provision, exercise/weight advice, analgesics, physiotherapy), recorded through an electronic template or routinely recorded in the electronic healthcare records, was identified for patients aged ?45 years consulting over a 6-month period with clinical OA. Latent class analysis was used to cluster patients based on care received. Clusters were compared on patient and clinician-level characteristics. RESULTS:1724 patients (median by practice 183) consulted with clinical OA. Common patterns of recorded quality care were: cluster 1 (38%, High) received most quality indicators of care; cluster 2 (11%, Moderate) had pain and function assessment, and received or were considered for other indicators; cluster 3 (17%, Low) had pain and function assessment, and received or were considered for paracetamol or topical non-steroidal anti-inflammatory drugs; cluster 4 (35%, None) had no recorded quality indicators. Patients with higher levels of recorded care consulted a clinician who saw more patients with OA, consulted multiple times and had less morbidity. Those in the High cluster were more likely to have recorded diagnosed OA and have knee/hip OA. CONCLUSIONS:Patterns of recorded care for OA fell into four natural clusters. Appropriate delivery of core interventions and relatively safe pharmacological options for OA are still not consistently recorded as provided in primary care. Further research to understand clinical recording behaviours and determine potential barriers to quality care alongside effective training for clinicians is needed. TRIAL REGISTRATION NUMBER:ISRCTN06984617; Results.

SUBMITTER: Jackson H

PROVIDER: S-EPMC5778330 | biostudies-literature | 2017 Dec

REPOSITORIES: biostudies-literature

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Patterns of routine primary care for osteoarthritis in the UK: a cross-sectional electronic health records study.

Jackson Holly H Barnett Lauren A LA Jordan Kelvin P KP Dziedzic Krysia S KS Cottrell Elizabeth E Finney Andrew G AG Paskins Zoe Z Edwards John J JJ

BMJ open 20171229 12

<h4>Objective</h4>To determine common patterns of recorded primary care for osteoarthritis (OA), and patient and provider characteristics associated with the quality of recorded care.<h4>Design</h4>An observational study nested within a cluster-randomised controlled trial.<h4>Setting</h4>Eight UK general practices who were part of the Management of Osteoarthritis in Consultations study.<h4>Participants</h4>Patients recorded as consulting within the eight general practices for clinical OA.<h4>Pri ...[more]

PMID: 29289942

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Project description:IntroductionThe extent of preventable medication-related hospital admissions and medication-related issues in primary care is significant enough to justify developing decision support systems for medication safety surveillance. The prerequisite for such systems is defining a relevant set of medication safety-related indicators and understanding the influence of both patient and general practice characteristics on medication prescribing and monitoring.ObjectiveThe aim of the study was to investigate the feasibility of linked primary and secondary care electronic health record data for surveillance of medication safety, examining not only prescribing but also monitoring, and associations with patient- and general practice-level characteristics.MethodsA cross-sectional study was conducted using linked records of patients served by one hospital and over 50 general practices in Salford, UK. Statistical analysis consisted of mixed-effects logistic models, relating prescribing safety indicators to potential determinants.ResultsThe overall prevalence (proportion of patients with at least one medication safety hazard) was 5.45 % for prescribing indicators and 7.65 % for monitoring indicators. Older patients and those on multiple medications were at higher risk of prescribing hazards, but at lower risk of missed monitoring. The odds of missed monitoring among all patients were 25 % less for males, 50 % less for patients in practices that provide general practitioner training, and threefold higher in practices serving the most deprived compared with the least deprived areas. Practices with more prescribing hazards did not tend to show more monitoring issues.ConclusionsSystematic collection, collation, and analysis of linked primary and secondary care records produce plausible and useful information about medication safety for a health system. Medication safety surveillance systems should pay close attention to patient age and polypharmacy with respect to both prescribing and monitoring failures; treat prescribing and monitoring as different statistical processes, rather than a combined measure of prescribing safety; and audit the socio-economic equity of missed monitoring.

Project description:BACKGROUND:The nature of symptoms in the prodromal period of first episode psychosis (FEP) remains unclear. The objective was to determine the patterns of symptoms recorded in primary care in the 5 years before FEP diagnosis. METHODS:The study was set within 568 practices contributing to a UK primary care health record database (Clinical Practice Research Datalink). Patients aged 16-45 years with a first coded record of FEP, and no antipsychotic prescription more than 1 year prior to FEP diagnosis (n = 3045) was age, gender, and practice matched to controls without FEP (n = 12,180). Fifty-five symptoms recorded in primary care in the previous 5 years, categorised into 8 groups (mood-related, 'neurotic', behavioural change, volition change, cognitive change, perceptual problem, substance misuse, physical symptoms), were compared between cases and controls. Common patterns of symptoms prior to FEP diagnosis were identified using latent class analysis. RESULTS:Median age at diagnosis was 30 years, 63% were male. Non-affective psychosis (67%) was the most common diagnosis. Mood-related, 'neurotic', and physical symptoms were frequently recorded (> 30% of patients) before diagnosis, and behavioural change, volition change, and substance misuse were also common (> 10%). Prevalence of all symptom groups was higher in FEP patients than in controls (adjusted odds ratios 1.33-112). Median time from the first recorded symptom to FEP diagnosis was 2-2.5 years except for perceptual problem (70 days). The optimal latent class model applied to FEP patients determined three distinct patient clusters: 'no or minimal symptom cluster' (49%) had no or few symptoms recorded; 'affective symptom cluster' (40%) mainly had mood-related and 'neurotic' symptoms; and 'multiple symptom cluster' (11%) consulted for three or more symptom groups before diagnosis. The multiple symptom cluster was more likely to have drug-induced psychosis, female, obese, and have a higher morbidity burden. Affective and multiple symptom clusters showed a good discriminative ability (C-statistic 0.766; sensitivity 51.2% and specificity 86.7%) for FEP, and many patients in these clusters had consulted for their symptoms several years before FEP diagnosis. CONCLUSIONS:Distinctive patterns of prodromal symptoms may help alert general practitioners to those developing psychosis, facilitating earlier identification and referral to specialist care, thereby avoiding potentially detrimental treatment delay.

Project description:BackgroundAsthma management guidelines recommend a stepwise approach to instituting and adjusting anti-inflammatory controller therapy for children with asthma. The objective of this retrospective observational study was to describe prescribing patterns of asthma controller therapies for children in a primary care setting.MethodsData from the UK General Practice Research Database were examined for children with recorded asthma or recurrent wheezing who, from September 2006 through February 2007, were < or = 14 years old at the time of a first asthma controller prescription after > or = 6 months without a controller prescription. We evaluated demographic characteristics, asthma duration, comorbidities, asthma-related health care resource use, and prescribed daily dose of controller medication. In addition, physicians for 635 randomly selected patients completed a survey retrospectively classifying asthma severity at the prescription date and describing therapy and health care utilization for 6 prior months.ResultsWe identified 10,004 children, 5942 (59.4%) of them boys, of mean (SD) age of 8.0 (3.8) years. Asthma controller prescriptions were for inhaled corticosteroid (ICS) monotherapy for 9059 (90.6%) children; ICS plus long-acting beta2-agonist (LABA) for 698 (7.0%); leukotriene antagonist monotherapy for 91 (0.9%); ICS plus leukotriene antagonist for 55 (0.6%); and other therapy for 101 (1.0%), including 45 (0.45%) children who were prescribed LABA as monotherapy. High doses of ICS (> 400 microg) were prescribed for 44/2140 (2.1%) children < 5 years old and for 420/7452 (5.6%) children > or = 5 years. Physicians reported asthma severity as intermittent for 346/635 (55%) patients and as mild, moderate, and severe persistent for 159 (25%), 71 (11%), and 11 (2%), respectively (severity data missing for 48 [8%]). The baseline characteristics and controller therapy prescriptions of the survey cohort were similar to those of the full cohort.ConclusionsPhysician classifications of asthma severity did not always correspond to guideline recommendations, as leukotriene receptor antagonists were rarely used and high-dose ICS or add-on LABA was prescribed even in intermittent and mild disease. In UK primary care, monotherapy with ICS is the most common controller therapy at all levels of asthma severity.

Project description:BackgroundWithin the Dutch health care system the focus is shifting from a disease oriented approach to a more population based approach. Since every inhabitant in the Netherlands is registered with one general practice, this offers a unique possibility to perform Population Health Management analyses based on general practitioners' (GP) registries. The Johns Hopkins Adjusted Clinical Groups (ACG) System is an internationally used method for predictive population analyses. The model categorizes individuals based on their complete health profile, taking into account age, gender, diagnoses and medication. However, the ACG system was developed with non-Dutch data. Consequently, for wider implementation in Dutch general practice, the system needs to be validated in the Dutch healthcare setting. In this paper we show the results of the first use of the ACG system on Dutch GP data. The aim of this study is to explore how well the ACG system can distinguish between different levels of GP healthcare utilization.MethodsTo reach our aim, two variables of the ACG System, the Aggregated Diagnosis Groups (ADG) and the mutually exclusive ACG categories were explored. The population for this pilot analysis consisted of 23,618 persons listed with five participating general practices within one region in the Netherlands. ACG analyses were performed based on historical Electronic Health Records data from 2014 consisting of primary care diagnoses and pharmaceutical data. Logistic regression models were estimated and AUC's were calculated to explore the diagnostic value of the models including ACGs and ADGs separately with GP healthcare utilization as the dependent variable. The dependent variable was categorized using four different cut-off points: zero, one, two and three visits per year.ResultsThe ACG and ADG models performed as well as models using International Classification of Primary Care chapters, regarding the association with GP utilization. AUC values were between 0.79 and 0.85. These models performed better than the base model (age and gender only) which showed AUC values between 0.64 and 0.71.ConclusionThe results of this study show that the ACG system is a useful tool to stratify Dutch primary care populations with GP healthcare utilization as the outcome variable.

Project description:BackgroundElectronic diabetes registers promote structured care and enable identification of undiagnosed diabetes, but they require consistent coding of the diagnosis in electronic medical records. We investigated the potential of electronic medical records to identify undiagnosed diabetes and to support diabetes management in a large primary care population in the United States.MethodsWe conducted a cross-sectional study and retrospective observational cohort analysis of primary care electronic medical records from a nationally representative US database (GE Centricity). We tested the feasibility of identifying patients with undiagnosed diabetes by applying simple algorithms to the electronic medical record data. We compared the quality of care provided to patients in the United States who had diabetes (coded and uncoded) for at least 15 months with the quality of care provided in England using a set of 16 indicators.ResultsWe included 11 540 454 electronic medical records from more than 9000 primary care clinics across the United States. Of the 1 110 398 records indicating diagnosed diabetes, only 61.9% contained a diagnostic code. Of the 10 430 056 records for nondiabetic patients, 0.4% (n = 40 359) had at least 2 abnormal fasting or random blood glucose values, and 0.2% (n = 23 261) of the remaining records had at least 1 documented glycated hemoglobin (HbA1c) value of 6.5% or higher. Among the 622 260 patients for whom information on quality-of-care indicators was available, those with a coded diagnosis of diabetes had a significantly higher level of quality of care than those with uncoded diabetes (p < 0.01); however, the quality of care was generally lower than that indicated in England.InterpretationWe were able to identify a substantial number of patients with uncoded diabetes and probable undiagnosed diabetes using simple algorithms applied to the primary care electronic records. Electronic coding of the diagnosis was associated with improved quality of care. Electronic diabetes registers are underused in US primary care and provide opportunities to facilitate the systematic, structured approach that is established in England.

Dataset Information

Patterns of routine primary care for osteoarthritis in the UK: a cross-sectional electronic health records study.

Publications

Patterns of routine primary care for osteoarthritis in the UK: a cross-sectional electronic health records study.

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