We conclude that the MTHFR-coding polymorphism at A1298C is associated with renal decline in African-Americans with hypertensive nephrosclerosis and is supported by a veteran cohort with a primary care diagnosis of hypertension. Further investigation is needed to confirm such findings and to determine what molecular mechanism may contribute to this association.
We describe methods for capturing and analyzing EHR use and clinical workflow of physicians during outpatient encounters and relating activity to physicians' self-reported workload. We collected temporally-resolved activity data including audio, video, EHR activity, and eye-gaze along with post-visit assessments of workload. These data are then analyzed through a combination of manual content analysis and computational techniques to temporally align streams, providing a range of process measures of EHR usage, clinical workflow, and physician-patient communication. Data was collected from primary care and specialty clinics at the Veterans Administration San Diego Healthcare System and UCSD Health, who use Electronic Health Record (EHR) platforms, CPRS and Epic, respectively. Grouping visit activity by physician, site, specialty, and patient status enables rank-ordering activity factors by their correlation to physicians' subjective work-load as captured by NASA Task Load Index survey. We developed a coding scheme that enabled us to compare timing studies between CPRS and Epic and extract patient and visit complexity profiles. We identified similar patterns of EHR use and navigation at the 2 sites despite differences in functions, user interfaces and consequent coded representations. Both sites displayed similar proportions of EHR function use and navigation, and distribution of visit length, proportion of time physicians attended to EHRs (gaze), and subjective work-load as measured by the task load survey. We found that visit activity was highly variable across individual physicians, and the observed activity metrics ranged widely as correlates to subjective workload. We discuss implications of our study for methodology, clinical workflow and EHR redesign.
Introduction
Ageing patients with haemophilia (PWH) develop cardiovascular risk factors impacting care. Little is known about the prevalence of diabetes in PWH and its relation to other comorbidities.
Aim
To examine the risk of diabetes for adult PWH compared to men from the general United States population (National Health and Nutrition Examination Surveys [NHANES]) and outpatients attending a Veterans Affairs Medical Center (VAMC) clinic.
Methods
Retrospective cross‐sectional design. PWH from four haemophilia centres (n = 690) were matched with random samples from NHANES and VAMC. Diabetes (yes/no) was the outcome, while age, body mass index (BMI), race and Hepatitis C (HCV; by serology) and human immunodeficiency virus (HIV) positivity were covariates. We fitted semiparametric generalized additive models (GAMs) in order to compare diabetes risk between cohorts.
Results
Younger PWH were at lower risk of diabetes than NHANES or VAMC subjects irrespective of BMI. However, the risk of diabetes rose in older PWH and was closely associated with HCV. For HCV‐negative subjects, the risk of diabetes was considerably lower for PWH than NHANES and VAMC subjects. The difference persisted after controlling for BMI and age, indicating that the low risk of diabetes in PWH cannot be explained by lean body mass alone.
Conclusion
Since many ageing PWH are HCV positive and therefore at heightened risk for diabetes, it is important to incorporate diabetes screening into care algorithms in Haemophilia Treatment Centers, especially since PWH are not always followed in primary care clinics.
The Veterans Affairs Hypertension Primary Care Longitudinal Cohort (VAHC) was initiated in 2003 as a pilot study designed to link the VA electronic medical record system with individual genetic data. Between June 2003 and December 2004, 1,527 hypertensive participants were recruited. Protected health information (PHI) was extracted from the regional VA data warehouse. Differences between the clinic and mail recruits suggested that clinic recruitment resulted in an over-sampling of African Americans. A review of medical records in a random sample of study participants confirmed that the data warehouse accurately captured most selected diagnoses. Genomic DNA was acquired non-invasively from buccal cells in mouthwash; ~ 96.5 per cent of samples contained DNA suitable for genotyping, with an average DNA yield of 5.02 ± 0.12 micrograms, enough for several thousand genotypes. The coupling of detailed medical databases with genetic information has the potential to facilitate the genetic study of hypertension and other complex diseases.
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