Identification of acute myocardial infarction from electronic healthcare records using different disease coding systems

Objective: To evaluate positive predictive value (PPV) of different disease codes and free text in identifying acute myocardial infarction (AMI) from electronic healthcare records (EHRs). Design: Validation study of cases of AMI identified from general practitioner records and hospital discharge diagnoses using free text and codes from the International Classification of Primary Care (ICPC), International Classification of Diseases 9th revision-clinical modification (ICD9-CM) and ICD-10th revision (ICD-10). Setting: Population-based databases comprising routinely collected data from primary care in Italy and the Netherlands and from secondary care in Denmark from 1996 to 2009. Participants: A total of 4 034 232 individuals with 22 428 883 person-years of follow-up contributed to the data, from which 42 774 potential AMI cases were identified. A random sample of 800 cases was subsequently obtained for validation. Main outcome measures: PPVs were calculated overall and for each code/free text. 'Best-case scenario' and 'worst-case scenario' PPVs were calculated, the latter taking into account non-retrievable/non-assessable cases. We further assessed the effects of AMI misclassification on estimates of risk during drug exposure. Results: Records of 748 cases (93.5% of sample) were retrieved. ICD-10 codes had a 'best-case scenario' PPV of 100% while ICD9-CM codes had a PPV of 96.6% (95% CI 93.2% to 99.9%). ICPC codes had a 'best-case scenario' PPV of 75% (95% CI 67.4% to 82.6%) and free text had PPV ranging from 20% to 60%. Corresponding PPVs in the 'worst-case scenario' all decreased. Use of codes with lower PPV generally resulted in small changes in AMI risk during drug exposure, but codes with higher PPV resulted in attenuation of risk for positive associations. Conclusions: ICD9-CM and ICD-10 codes have good PPV in identifying AMI from EHRs; strategies are necessary to further optimise utility of ICPC codes and free-text search. Use of specific AMI disease codes in estimation of risk during drug exposure may lead to small but significant changes and at the expense of decreased precision

Bleeding in cardiac patients prescribed antithrombotic drugs: Electronic health record phenotyping algorithms, incidence, trends and prognosis

Background Clinical guidelines and public health authorities lack recommendations on scalable approaches to defining and monitoring the occurrence and severity of bleeding in populations prescribed antithrombotic therapy. Methods We examined linked primary care, hospital admission and death registry electronic health records (CALIBER 1998–2010, England) of patients with newly diagnosed atrial fibrillation, acute myocardial infarction, unstable angina or stable angina with the aim to develop algorithms for bleeding events. Using the developed bleeding phenotypes, Kaplan-Meier plots were used to estimate the incidence of bleeding events and we used Cox regression models to assess the prognosis for all-cause mortality, atherothrombotic events and further bleeding. Results We present electronic health record phenotyping algorithms for bleeding based on bleeding diagnosis in primary or hospital care, symptoms, transfusion, surgical procedures and haemoglobin values. In validation of the phenotype, we estimated a positive predictive value of 0.88 (95% CI 0.64, 0.99) for hospitalised bleeding. Amongst 128,815 patients, 27,259 (21.2%) had at least 1 bleeding event, with 5-year risks of bleeding of 29.1%, 21.9%, 25.3% and 23.4% following diagnoses of atrial fibrillation, acute myocardial infarction, unstable angina and stable angina, respectively. Rates of hospitalised bleeding per 1000 patients more than doubled from 1.02 (95% CI 0.83, 1.22) in January 1998 to 2.68 (95% CI 2.49, 2.88) in December 2009 coinciding with the increased rates of antiplatelet and vitamin K antagonist prescribing. Patients with hospitalised bleeding and primary care bleeding, with or without markers of severity, were at increased risk of all-cause mortality and atherothrombotic events compared to those with no bleeding. For example, the hazard ratio for all-cause mortality was 1.98 (95% CI 1.86, 2.11) for primary care bleeding with markers of severity and 1.99 (95% CI 1.92, 2.05) for hospitalised bleeding without markers of severity, compared to patients with no bleeding. Conclusions Electronic health record bleeding phenotyping algorithms offer a scalable approach to monitoring bleeding in the population. Incidence of bleeding has doubled in incidence since 1998, affects one in four cardiovascular disease patients, and is associated with poor prognosis. Efforts are required to tackle this iatrogenic epidemic

Pediatric drug safety signal detection: a new drug-event reference set for performance testing of data-mining methods and systems

BACKGROUND: Better evidence regarding drug safety in the pediatric population might be generated from existing data sources such as spontaneous reporting systems and electronic healthcare records. The Global Research in Paediatrics (GRiP)-Network of Excellence aims to develop pediatric-specific methods that can be applied to these data sources. A reference set of positive and negative drug-event associations is required. OBJECTIVE: The aim of this study was to develop a pediatric-specific reference set of positive and negative drug-event associations. METHODS: Considering user patterns and expert opinion, 16 drugs that are used in individuals aged 0-18 years were selected and evaluated against 16 events, regarded as important safety outcomes. A cross-table of unique drug-event pairs was created. Each pair was classified as potential positive or negative control based on information from the drug's Summary of Product Characteristics and Micromedex. If both information sources consistently listed the event as an adverse event, the combination was reviewed as potential positive control. If both did not, the combination was evaluated as potential negative control. Further evaluation was based on published literature. RESULTS: Selected drugs include ibuprofen, flucloxacillin, domperidone, methylphenidate, montelukast, quinine, and cyproterone/ethinylestradiol. Selected events include bullous eruption, aplastic anemia, ventricular arrhythmia, sudden death, acute kidney injury, psychosis, and seizure. Altogether, 256 unique combinations were reviewed, yielding 37 positive (17 with evidence from the pediatric population and 20 with evidence from adults only) and 90 negative control pairs, with the remainder being unclassifiable. CONCLUSION: We propose a drug-event reference set that can be used to compare different signal detection methods in the pediatric population

Systematic review with meta‐analysis: risk of adverse cardiovascular events with proton pump inhibitors independent of clopidogrel

BACKGROUND: Clopidogrel's anti-platelet effects may be attenuated by a pharmacokinetic interaction with co-prescribed proton pump inhibitors, which inhibit oxidative pathways that convert clopidogrel into its active metabolites. Despite this, the impact of PPIs on cardiovascular risk in the absence of clopidogrel is not well defined. AIM: To report on a systematic review and meta-analysis of the association between PPIs and cardiovascular risk, independent of clopidogrel. METHODS: The databases of MEDLINE, EMBASE, Cochrane Central Register of Controlled Trials, Scopus, Web of Science, and ClinicalTrials.gov were systematically searched in October 2017. The primary outcome was association between PPI monotherapy and any adverse cardiovascular event. The secondary outcome was association between proton pump inhibitor monotherapy and acute myocardial infarction. Studies were excluded if they reported or did not adjust for concomitant anti-platelet therapy or involved participants aged less than 18 years. RESULTS: A total of 22 studies were included in the systematic review. Data from 16 studies were included in the meta-analysis (involving 447 408 participants). Of these, eight were randomised controlled trials, seven were observational studies and one was a retrospective analysis of a randomised controlled trial. An increased risk of any adverse cardiovascular event with PPI monotherapy was observed using pooled data from observational studies (risk ratio 1.25, 95% CI 1.11-1.42, I2 81%, P < 0.001), but not from randomised controlled trials (risk ratio 0.89, 95% CI 0.34-2.33, I2 0%, P = 0.85). CONCLUSION: There is no clear evidence of an association between PPI monotherapy and increased cardiovascular risk