Browsing by Subject "EHR"
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Item Bodyweight Changes During COVID-19 for Patients Diagnosed with Depression: A Retrospective Cohort Study(2022-05) Arellano Villanueva, Elias; Fulda, Kimberly; Franks, Susan; Schranz, DamonBackground: The COVID-19 pandemic led to an unprecedented lockdown of millions of Americans from the spring of 2020 to the fall of 2020 This lockdown exacerbated the mental and physical health status of millions of individuals worldwide. Studies done on the impact of COVID-19 on mental health and body weight have been important to our understanding of the effects of the pandemic. However, these studies on depression and BMI change have not identified a possible direction of the causality of the relationship between depression and body weight as affected by lockdown measures during a pandemic. Therefore, this study examined whether a diagnosis of depression is associated with changes in BMI during the COVID-19 pandemic for adults (aged ≥ 18 years). Methods: A retrospective cohort study design using EHR data from a family medicine university clinic was utilized. Adults > 18 years who visited the clinic within a 6-month period prior to lockdown and at least once in the 6-month post-lockdown period were included. Diagnosis of depression, BMI, and potential confounding variables were obtained from EHR. Mann-Whitney U was used to compare the median change in BMI between depressed and non-depressed patients Simple linear regression was used to identify the relationship between diagnosis of depression and BMI change. Multiple linear regression was used to control for age, sex, race/ethnicity, medications, and chronic conditions; and to predict age effects in BMI change while stratified by diagnosis of depression and no diagnosis of depression. Results: Statistical analysis showed that there was a significant difference in BMI changes (p=<0.001) between the group diagnosed with depression and the group with no depression. Similarly, a diagnosis of depression significantly predicted BMI changes (p = >0.001]). This significance was maintained even while including confounding variables in the model (p=0.009). Further statistical analysis showed that age between 31 and 50 significantly predicted BMI changes in those patients with no depression while controlling for confounding variables (p = 0.027). Conclusion: This study demonstrated that individuals with depression had significant changes in BMI during the COVID-19 pandemic and age predicted these changes in middle-aged adults (30-50 years old). The significance of this finding places importance in identifying and following up with individuals with a depression diagnosis given the effects on their BMI in extended isolation periods. Future studies could investigate other variables that might impact BMI change to influence the directionality of this relationship. Providing insight into this relationship could enable providers to inform patients that might be at risk for these types of changes over extended periods of isolation, and hopefully result in positive patient health outcomes.Item Physician Champion Role in an Electronic Health Record Implementation, a Case History(2010-05-01) Luchetski, Janice E.; O'Neill, LiamThe electronic health record (EHR) is an array of computer applications that is being touted as a key patient safety, quality and hospital efficiency initiative. Due to the complexity of the health care environment, the implementation of an EHR can be challenging especially if health care providers, in particular physicians, are not supportive of the process. Physicians play a key role in the provision of health care and should be involved in all phases of the implementation process. Variations of EHR acceptance have been widely documented highlighting the importance of a well-planned implementation process. Theoretical frameworks, such as Roger’s Science of Diffusion of Innovation, provide guidance on how process changes can be successfully incorporated into organizations and the physician champion role can be utilized as an extensive of the theory. To illustrate how an EHR implementation can employ the physician champion role to achieve widespread adoption, a case history of a 724 bed, private not for profit hospital will be presented. The rest of this paper will be organized as follows: In the first section a review of the history of the EHR; in the second section, a discussion of barriers to implementation; in the third section, an overview of the Science of Diffusion of Innovation; in the forth section, the presentation of the physician champion role; in the fifth section a recommendation for the physician role in an EHR implementation; and in the sixth section, the case history of an actual EHR implementation.