During framing the prospectus of my doctoral study development process, I mainly concerned over the improvement of patient care through electronic medical record (EMR) system as proposed by study of Denny et al. (2013). The reason I selected this topic is, manual record for entering patient information can lead to a number of manual errors leading to negative infliction of patient's health (Burwell, 2015). Therefore, I formulated my study towards evaluating the manner in which EMR influence the efficacy in catering comprehensive health needs of patients. In order to frame a unique aim of the study, I went through recently published peered reviewed journals based on the topic of EMR. I found that there are no significant mixed method study analyzing the relationship between the implementation of EMR and clinical productivity and patient care improvement. Considering this research gap, I erected the main research question of the study. In order to answer my research question, I proposed incorporation of the primary quantitative data and subsequent analysis of the quantitative data through statistical methods in order to reveal the various dimensions of the study while reflecting on the patient oriented outcomes.
My question to the faculty chair is how I should organize my raw quantitative data in order to draw an appropriate conclusion. I would also like to ask which form of statistical test would be more suitable for this kind of study like whether it will be Paired test, independent test or ANOVA test. I am also planning to compare data in the grounds of manual data entry and data entry through EMR, so I will be highly grateful, if my fellow colleagues of the doctoral study development process help me out with the nature of the statistical test that will be helpful in data comparison.
Burwell, S. M. (2015). Setting value-based payment goals—HHS efforts to improve US health care. N Engl J Med, 372(10), 897-899.
Denny, J. C., Bastarache, L., Ritchie, M. D., Carroll, R. J., Zink, R., Mosley, J. D., ... & Basford, M. A. (2013). Systematic comparison of phenome-wide association study of electronic medical record data and genome-wide association study data. Nature biotechnology, 31(12), 1102.