A basic model for assessing primary health care electronic medical record data quality

BACKGROUND: The increased use of electronic medical records (EMRs) in Canadian primary health care practice has resulted in an expansion of the availability of EMR data. Potential users of these data need to understand their quality in relation to the uses to which they are applied. Herein, we propose a basic model for assessing primary health care EMR data quality, comprising a set of data quality measures within four domains. We describe the process of developing and testing this set of measures, share the results of applying these measures in three EMR-derived datasets, and discuss what this reveals about the measures and EMR data quality. The model is offered as a starting point from which data users can refine their own approach, based on their own needs. METHODS: Using an iterative process, measures of EMR data quality were created within four domains: comparability; completeness; correctness; and currency. We used a series of process steps to develop the measures. The measures were then operationalized, and tested within three datasets created from different EMR software products. RESULTS: A set of eleven final measures were created. We were not able to calculate results for several measures in one dataset because of the way the data were collected in that specific EMR. Overall, we found variability in the results of testing the measures (e.g. sensitivity values were highest for diabetes, and lowest for obesity), among datasets (e.g. recording of height), and by patient age and sex (e.g. recording of blood pressure, height and weight). CONCLUSIONS: This paper proposes a basic model for assessing primary health care EMR data quality. We developed and tested multiple measures of data quality, within four domains, in three different EMR-derived primary health care datasets. The results of testing these measures indicated that not all measures could be utilized in all datasets, and illustrated variability in data quality. This is one step forward in creating a standard set of measures of data quality. Nonetheless, each project has unique challenges, and therefore requires its own data quality assessment before proceeding

Angiotensinergic innervation of the kidney: present knowledge and its significance.

Intrarenal neurotransmission implies the co-release of neuropeptides at the neuro-effector junction with direct influence on parameters of kidney function. The presence of an angiotensin (Ang) II-containing phenotype in catecholaminergic postganglionic and sensory fibers of the kidney, based on immunocytological investigations, has only recently been reported. These angiotensinergic fibers display a distinct morphology and intrarenal distribution, suggesting anatomical and functional subspecialization linked to neuronal Ang II-expression. This review discusses the present knowledge concerning these fibers, and their significance for renal physiology and the pathogenesis of hypertension in light of established mechanisms. The data suggest a new role of Ang II as a co-transmitter stimulating renal target cells or modulating nerve traffic from or to the kidney. Neuronal Ang II is likely to be an independent source of intrarenal Ang II. Further physiological experimentation will have to explore the role of the angiotensinergic renal innervation and integrate it into existing concepts