Semantic computational analysis of anticoagulation use in atrial fibrillation from real world data

Atrial fibrillation (AF) is the most common arrhythmia and significantly increases stroke risk. This risk is effectively managed by oral anticoagulation. Recent studies using national registry data indicate increased use of anticoagulation resulting from changes in guidelines and the availability of newer drugs. The aim of this study is to develop and validate an open source risk scoring pipeline for free-text electronic health record data using natural language processing. AF patients discharged from 1st January 2011 to 1st October 2017 were identified from discharge summaries (N = 10,030, 64.6% male, average age 75.3 ± 12.3 years). A natural language processing pipeline was developed to identify risk factors in clinical text and calculate risk for ischaemic stroke (CHA2DS2-VASc) and bleeding (HAS-BLED). Scores were validated vs two independent experts for 40 patients. Automatic risk scores were in strong agreement with the two independent experts for CHA2DS2-VASc (average kappa 0.78 vs experts, compared to 0.85 between experts). Agreement was lower for HAS-BLED (average kappa 0.54 vs experts, compared to 0.74 between experts). In high-risk patients (CHA2DS2-VASc ≥2) OAC use has increased significantly over the last 7 years, driven by the availability of DOACs and the transitioning of patients from AP medication alone to OAC. Factors independently associated with OAC use included components of the CHA2DS2-VASc and HAS-BLED scores as well as discharging specialty and frailty. OAC use was highest in patients discharged under cardiology (69%). Electronic health record text can be used for automatic calculation of clinical risk scores at scale. Open source tools are available today for this task but require further validation. Analysis of routinely collected EHR data can replicate findings from large-scale curated registries.info:eu-repo/semantics/publishedVersio

Cognitive dysfunction and poor health literacy are common in veterans presenting with acute coronary syndrome: insights from the MEDICATION study

Lucas N Marzec,1 Evan P Carey,1 Anne C Lambert-Kerzner,1 Eric J Del Giacco,2 Stephanie D Melnyk,3 Chris L Bryson,4 Ibrahim E Fahdi,2 Hayden B Bosworth,3 Fran Fiocchi,5 P Michael Ho11Division of Cardiology, Denver VA Medical Center, Denver, CO, USA; 2Department of Medicine, Little Rock VA Medical Center, Little Rock, AR, USA; 3Department of Medicine, Durham VA Medical Center, Durham, NC, USA; 4Department of Medicine, Puget Sound VA Medical Center, Seattle, WA, USA; 5American College of Cardiology, Washington, DC, USABackground: Patient nonadherence to cardiac medications following acute coronary syndrome (ACS) is associated with increased risk of recurrent events. However, the prevalence of cognitive dysfunction and poor health literacy among ACS patients and their association with medication nonadherence are poorly understood.Methods: We assessed rates of cognitive dysfunction and poor health literacy among participants of a clinical trial that tested the effectiveness of an intervention to improve medication adherence in patients hospitalized with ACS. Of 254 patients, 249 completed the Rapid Estimate of Adult Literacy in Medicine, Revised (REALM-R) survey, an assessment of risk for poor literacy, and the St Louis University Mental Status (SLUMS) exam, a tool assessing for neurocognitive deficits, during ACS hospitalization. We assessed if SLUMS or REALM-R scores were associated with medication adherence.Results: Based on SLUMS score, 14% of patients were categorized as having dementia, and 52% with mild neurocognitive disorder (MNCD). Based on REALM-R score of ≤6, 34% of patients were categorized as at risk for poor health literacy. There was no association between poor health literacy and medication nonadherence. Of those with MNCD, 35.5% were nonadherent, compared to 17.5% with normal cognitive function and 6.7% with dementia. In multivariable analysis, cognitive dysfunction was associated with medication nonadherence (P=0.007), mainly due to an association between MNCD and nonadherence (odds ratio =12.2, 95% confidence interval =1.9 to 243; P=0.007). Cognitive status was not associated with adherence in patients randomized to the intervention.Conclusion: Cognitive dysfunction and risk for poor health literacy are common in patients hospitalized with ACS. We found an association between MNCD and medication nonadherence in the usual care group but not in the intervention group. These findings suggest efforts to screen for MNCD are needed during ACS hospitalization to identify patients at risk for nonadherence and who may benefit from an adherence intervention.Keyword: medication adherenc