Evaluating openEHR for storing computable representations of electronic health record phenotyping algorithms

Electronic Health Records (EHR) are data generated during routine clinical care. EHR offer researchers unprecedented phenotypic breadth and depth and have the potential to accelerate the pace of precision medicine at scale. A main EHR use-case is creating phenotyping algorithms to define disease status, onset and severity. Currently, no common machine-readable standard exists for defining phenotyping algorithms which often are stored in human-readable formats. As a result, the translation of algorithms to implementation code is challenging and sharing across the scientific community is problematic. In this paper, we evaluate openEHR, a formal EHR data specification, for computable representations of EHR phenotyping algorithms.Comment: 30th IEEE International Symposium on Computer-Based Medical Systems - IEEE CBMS 201

Association between clinical presentations before myocardial infarction and coronary mortality: a prospective population-based study using linked electronic records.

BACKGROUND: Ischaemia in different arterial territories before acute myocardial infarction (AMI) may influence post-AMI outcomes. No studies have evaluated prospectively collected information on ischaemia and its effect on short- and long-term coronary mortality. The objective of this study was to compare patients with and without prospectively measured ischaemic presentations before AMI in terms of infarct characteristics and coronary mortality. METHODS AND RESULTS: As part of the CALIBER programme, we linked data from primary care, hospital admissions, the national acute coronary syndrome registry and cause-specific mortality to identify patients with first AMI (n = 16,439). We analysed time from AMI to coronary mortality (n = 5283 deaths) using Cox regression (median 2.6 years follow-up), comparing patients with and without recent ischaemic presentations. Patients with ischaemic presentations in the 90 days before AMI experienced lower coronary mortality in the first 7 days after AMI compared with those with no prior ischaemic presentations, after adjusting for age, sex, smoking, diabetes, blood pressure and cardiovascular medications [HR: 0.64 (95% CI: 0.57-0.73) P < 0.001], but subsequent mortality was higher [HR: 1.42 (1.13-1.77) P = 0.001]. Patients with ischaemic presentations closer in time to AMI had the lowest seven day mortality (P-trend = 0.001). CONCLUSION: In the first large prospective study of ischaemic presentations prior to AMI, we have shown that those occurring closest to AMI are associated with lower short-term coronary mortality following AMI, which could represent a natural ischaemic preconditioning effect, observed in a clinical setting. CLINICAL TRIALS REGISTRATION: Clinicaltrials.gov identifier NCT01604486

Temporal trends and patterns in heart failure incidence: a population-based study of 4 million individuals

Background: Large-scale and contemporary population-based studies of heart failure incidence are needed to inform resource planning and research prioritisation but current evidence is scarce. We aimed to assess temporal trends in incidence and prevalence of heart failure in a large general population cohort from the UK, between 2002 and 2014. Methods: For this population-based study, we used linked primary and secondary electronic health records of 4 million individuals from the Clinical Practice Research Datalink (CPRD), a cohort that is representative of the UK population in terms of age and sex. Eligible patients were aged 16 years and older, had contributed data between Jan 1, 2002, and Dec 31, 2014, had an acceptable record according to CPRD quality control, were approved for CPRD and Hospital Episodes Statistics linkage, and were registered with their general practice for at least 12 months. For patients with incident heart failure, we extracted the most recent measurement of baseline characteristics (within 2 years of diagnosis) from electronic health records, as well as information about comorbidities, socioeconomic status, ethnicity, and region. We calculated standardised rates by applying direct age and sex standardisation to the 2013 European Standard Population, and we inferred crude rates by applying year-specific, age-specific, and sex-specific incidence to UK census mid-year population estimates. We assumed no heart failure for patients aged 15 years or younger and report total incidence and prevalence for all ages (&gt;0 years). Findings: From 2002 to 2014, heart failure incidence (standardised by age and sex) decreased, similarly for men and women, by 7% (from 358 to 332 per 100 000 person-years; adjusted incidence ratio 0·93, 95% CI 0·91–0·94). However, the estimated absolute number of individuals with newly diagnosed heart failure in the UK increased by 12% (from 170 727 in 2002 to 190 798 in 2014), largely due to an increase in population size and age. The estimated absolute number of prevalent heart failure cases in the UK increased even more, by 23% (from 750 127 to 920 616). Over the study period, patient age and multi-morbidity at first presentation of heart failure increased (mean age 76·5 years [SD 12·0] to 77·0 years [12·9], adjusted difference 0·79 years, 95% CI 0·37–1·20; mean number of comorbidities 3·4 [SD 1·9] vs 5·4 [2·5]; adjusted difference 2·0, 95% CI 1·9–2·1). Socioeconomically deprived individuals were more likely to develop heart failure than were affluent individuals (incidence rate ratio 1·61, 95% CI 1·58–1·64), and did so earlier in life than those from the most affluent group (adjusted difference −3·51 years, 95% CI −3·77 to −3·25). From 2002 to 2014, the socioeconomic gradient in age at first presentation with heart failure widened. Socioeconomically deprived individuals also had more comorbidities, despite their younger age. Interpretation: Despite a moderate decline in standardised incidence of heart failure, the burden of heart failure in the UK is increasing, and is now similar to the four most common causes of cancer combined. The observed socioeconomic disparities in disease incidence and age at onset within the same nation point to a potentially preventable nature of heart failure that still needs to be tackled. Funding: British Heart Foundation and National Institute for Health Research

Comparison of random forest and parametric imputation models for imputing missing data using MICE: a CALIBER study.

Multivariate imputation by chained equations (MICE) is commonly used for imputing missing data in epidemiologic research. The "true" imputation model may contain nonlinearities which are not included in default imputation models. Random forest imputation is a machine learning technique which can accommodate nonlinearities and interactions and does not require a particular regression model to be specified. We compared parametric MICE with a random forest-based MICE algorithm in 2 simulation studies. The first study used 1,000 random samples of 2,000 persons drawn from the 10,128 stable angina patients in the CALIBER database (Cardiovascular Disease Research using Linked Bespoke Studies and Electronic Records; 2001-2010) with complete data on all covariates. Variables were artificially made "missing at random," and the bias and efficiency of parameter estimates obtained using different imputation methods were compared. Both MICE methods produced unbiased estimates of (log) hazard ratios, but random forest was more efficient and produced narrower confidence intervals. The second study used simulated data in which the partially observed variable depended on the fully observed variables in a nonlinear way. Parameter estimates were less biased using random forest MICE, and confidence interval coverage was better. This suggests that random forest imputation may be useful for imputing complex epidemiologic data sets in which some patients have missing data

A 10-year prognostic model for patients with suspected angina attending a chest pain clinic.

BACKGROUND AND OBJECTIVE: Diagnostic models used in the management of suspected angina provide no explicit information about prognosis. We present a new prognostic model of 10-year coronary mortality in patients presenting for the first time with suspected angina to complement the Diamond-Forrester diagnostic model of disease probability. METHODS AND RESULTS: A multicentre cohort of 8762 patients with suspected angina was followed up for a median of 10 years during which 233 coronary deaths were observed. Developmental (n=4412) and validation (n=4350) prognostic models based on clinical data available at first presentation showed good performance with close agreement and the final model utilised all 8762 patients to maximise power. The prognostic model showed strong associations with coronary mortality for age, sex, chest pain typicality, smoking status, diabetes, pulse rate, and ECG findings. Model discrimination was good (C statistic 0.83), patients in the highest risk quarter accounting for 173 coronary deaths (10-year risk of death: 8.7%) compared with a total of 60 deaths in the three lower risk quarters. When the model was simplified to incorporate only Diamond-Forrester factors (age, sex and character of symptoms) it underestimated coronary mortality risk, particularly in patients with reversible risk factors. CONCLUSIONS: For the first time in patients with suspected angina, a prognostic model is presented based on simple clinical factors available at the initial cardiological assessment. The model discriminated powerfully between patients at high risk and lower risk of coronary death during 10-year follow-up. Clinical utility was reflected in the prognostic value it added to the updated Diamond-Forrester diagnostic model of disease probability

The impact of the coronary collateral circulation on mortality: a meta-analysis

Aims The coronary collateral circulation as an alternative source of blood supply has shown benefits regarding several clinical endpoints in patients with myocardial infarction (MI) such as infarct size and left ventricular remodelling. However, its impact on hard endpoints such as mortality and its impact in patients with stable coronary artery disease (CAD) is more controversial. The purpose of this systematic review and meta-analysis was to explore the impact of collateral circulation on all-cause mortality. Methods and results We searched MEDLINE, EMBASE, ISI Web of Science (2001 to 25 April 2011), and conference proceedings for studies evaluating the effect of coronary collaterals on mortality. Random-effect models were used to calculate summary risk ratios (RR). A total of 12 studies enrolling 6529 participants were included in this analysis. Patients with high collateralization showed a reduced mortality compared with those with low collateralization [RR 0.64 (95% confidence interval 0.45-0.91); P= 0.012]. The RR for ‘high collateralization' in patients with stable CAD was 0.59 [0.39-0.89], P= 0.012, in patients with subacute MI it was 0.53 [0.15-1.92]; P= 0.335, and for patients with acute MI it was 0.63 [0.29-1.39]; P= 0.257. Conclusions In patients with CAD, the coronary collateralization has a relevant protective effect. Patients with a high collateralization have a 36% reduced mortality risk compared with patients with low collateralizatio

Methods for enhancing the reproducibility of biomedical research findings using electronic health records.

BACKGROUND: The ability of external investigators to reproduce published scientific findings is critical for the evaluation and validation of biomedical research by the wider community. However, a substantial proportion of health research using electronic health records (EHR), data collected and generated during clinical care, is potentially not reproducible mainly due to the fact that the implementation details of most data preprocessing, cleaning, phenotyping and analysis approaches are not systematically made available or shared. With the complexity, volume and variety of electronic health record data sources made available for research steadily increasing, it is critical to ensure that scientific findings from EHR data are reproducible and replicable by researchers. Reporting guidelines, such as RECORD and STROBE, have set a solid foundation by recommending a series of items for researchers to include in their research outputs. Researchers however often lack the technical tools and methodological approaches to actuate such recommendations in an efficient and sustainable manner. RESULTS: In this paper, we review and propose a series of methods and tools utilized in adjunct scientific disciplines that can be used to enhance the reproducibility of research using electronic health records and enable researchers to report analytical approaches in a transparent manner. Specifically, we discuss the adoption of scientific software engineering principles and best-practices such as test-driven development, source code revision control systems, literate programming and the standardization and re-use of common data management and analytical approaches. CONCLUSION: The adoption of such approaches will enable scientists to systematically document and share EHR analytical workflows and increase the reproducibility of biomedical research using such complex data sources

Type 2 diabetes and incidence of cardiovascular diseases: a cohort study in 1·9 million people.

BACKGROUND: The contemporary associations of type 2 diabetes with a wide range of incident cardiovascular diseases have not been compared. We aimed to study associations between type 2 diabetes and 12 initial manifestations of cardiovascular disease. METHODS: We used linked primary care, hospital admission, disease registry, and death certificate records from the CALIBER programme, which links data for people in England recorded in four electronic health data sources. We included people who were (or turned) 30 years or older between Jan 1, 1998, to March 25, 2010, who were free from cardiovascular disease at baseline. The primary endpoint was the first record of one of 12 cardiovascular presentations in any of the data sources. We compared cumulative incidence curves for the initial presentation of cardiovascular disease and used Cox models to estimate cause-specific hazard ratios (HRs). This study is registered at ClinicalTrials.gov (NCT01804439). FINDINGS: Our cohort consisted of 1 921 260 individuals, of whom 1 887 062 (98·2%) did not have diabetes and 34 198 (1·8%) had type 2 diabetes. We observed 113 638 first presentations of cardiovascular disease during a median follow-up of 5·5 years (IQR 2·1-10·1). Of people with type 2 diabetes, 6137 (17·9%) had a first cardiovascular presentation, the most common of which were peripheral arterial disease (reported in 992 [16·2%] of 6137 patients) and heart failure (866 [14·1%] of 6137 patients). Type 2 diabetes was positively associated with peripheral arterial disease (adjusted HR 2·98 [95% CI 2·76-3·22]), ischaemic stroke (1·72 [1·52-1·95]), stable angina (1·62 [1·49-1·77]), heart failure (1·56 [1·45-1·69]), and non-fatal myocardial infarction (1·54 [1·42-1·67]), but was inversely associated with abdominal aortic aneurysm (0·46 [0·35-0·59]) and subarachnoid haemorrhage (0·48 [0·26-0.89]), and not associated with arrhythmia or sudden cardiac death (0·95 [0·76-1·19]). INTERPRETATION: Heart failure and peripheral arterial disease are the most common initial manifestations of cardiovascular disease in type 2 diabetes. The differences between relative risks of different cardiovascular diseases in patients with type 2 diabetes have implications for clinical risk assessment and trial design. FUNDING: Wellcome Trust, National Institute for Health Research, and Medical Research Council

Long term health care use and costs in patients with stable coronary artery disease : a population based cohort using linked electronic health records (CALIBER)

Aims To examine long term health care utilisation and costs of patients with stable coronary artery disease (SCAD). Methods and results Linked cohort study of 94,966 patients with SCAD in England, 1st January 2001 to 31st March 2010, identified from primary care, secondary care, disease and death registries. Resource use and costs, and cost predictors by time and 5-year cardiovascular (CVD) risk profile were estimated using generalised linear models. Coronary heart disease hospitalisations were 20.5% in the first year and 66% in the year following a non-fatal (myocardial infarction, ischaemic or haemorrhagic stroke) event. Mean health care costs were £3,133 per patient in the first year and £10,377 in the year following a non-fatal event. First year predictors of cost included sex (mean cost £549 lower in females); SCAD diagnosis (NSTEMI cost £656 more than stable angina); and co-morbidities (heart failure cost £657 more per patient). Compared with lower risk patients (5-year CVD risk 3.5%), those of higher risk (5-year CVD risk 44.2%) had higher 5-year costs (£23,393 vs. £9,335) and lower lifetime costs (£43,020 vs. £116,888). Conclusion Patients with SCAD incur substantial health care utilisation and costs, which varies and may be predicted by 5-year CVD risk profile. Higher risk patients have higher initial but lower lifetime costs than lower risk patients as a result of shorter life expectancy. Improved cardiovascular survivorship among an ageing CVD population is likely to require stratified care in anticipation of the burgeoning demand