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Introduction
The development of the medical sphere allows improving the population’s quality of life. Modern technology trends are becoming an integral part of progress in health care. They provide additional opportunities for screening and disease prevention, analyzing a large amount of data, drawing up an effective treatment plan, and other physician and patients’ activities. The purpose of this paper is to study the literature on the effectiveness of electronic health records (EHR) for the provision of medical services and to compile an annotated bibliography for the sources reviewed. Despite some difficulties in introducing new technologies into the already established routine of treating patients, their use has a predominantly positive effect on outcomes and efficiencies.
Annotated Bibliography
Kruse, C. S., & Beane, A. (2018). Health information technology continues to show positive effect on medical outcomes: Systematic review. Journal of Medical Internet Research, 20(2), e41. Web.
EHR along with computerized physician order entry (CPOE) clinical decision support (CDS), and other systems is a type of health information technology (HIT). Assuming a connection between the introduction of HIT and improved treatment outcomes, the researchers conducted a review of the literature of the five-year period before the publication date using strict selection criteria. The authors identified twelve different categories of technologies used in the reviewed studies (clinical decision support systems, telemedicine and software programs, and other methods). These findings suggest more diverse types of technology than previously analyzed in similar studies.
It was found that the use of HIT will continue to be promoted by both hospital staff and policymakers. Such a conclusion is justified by the effectiveness of technologies; for example, the authors determined that 81% of the researches achieved positive outcomes (Kruse &Beane, 2018). The results prove that the hypothesis of the positive effect of technology on treatment outcomes is correct.
The senior author of the article has many publications that trace interest in the use of technology in medicine. The publication in the peer-reviewed journal also evidences the reliability of the source. It is of interest to researchers of the effectiveness of new systems in treating patients and their utility. Moreover, the article may be relevant for policymakers that seek to find out whether the costs of implementing modern systems correspond to the expected results. The source’s appropriateness to the studied topic is determined by the significant amount of literature that has been reviewed, analyzed, and synthesized. The results provide an opportunity to understand general trends and identify directions for further research.
Kruse, C. S., Mileski, M., Vijaykumar, A. G., Viswanathan, S. V., Suskandla, U., & Chidambaram, Y. (2017). Impact of electronic health records on long-term care facilities: Systematic review. JMIR Medical Informatics, 5(3), e35. Web.
The authors of the article are checking the efficacy and utility of electronic health records for both hospital functioning and patient care quality in long-term care (LTC) facilities. To achieve the objectives, an analysis of the literature on the presented topic was carried out. The authors explain that the need for effective LTCs is justified by aging populations and the importance of long-term treatment for them (Kruse et al., 2017).
The majority of reviewed studies state that EHRs should enable more efficient services through accurate and truthful information and reduced error potential. Analysis of the literature suggests a positive effect of EHR on document flow. However, only a few studies evidence significant improvements in LTC efficacies and their patients’ and staff’s satisfaction. The problem can be related to the long-term adaptation to the system implementation.
Since no improvements in the outcomes were noticed in the LTCs, it is worth noting the critical lessons learned from this study. Medical facilities of various types cannot equally adapt to the implementation of EHR. LTCs may require additional modifications or time to learn and get more effective results. The source may be of interest to LTCs’ administrations, researchers, and EHR developers. The article is relevant to the studied topic, as it identifies potential problems of introducing new systems and the presence of unique features of their use in medical institutions of various types.
Graber, M. L., Byrne, C., & Johnston, D. (2017). The impact of electronic health records on diagnosis. Diagnosis, 4(4), 211-223. Web.
The authors of this study drew attention to the fact that many citizens applying to the hospital may receive an incorrect diagnosis. In their work, they study how EHR can affect the diagnosis process. The researchers determined that there is both a positive and negative effect of electronic records on the diagnosis. For example, their advantage is that patient information will be readily available to professionals and provide decision support (Graber et al., 2017). An example of the disadvantage of EHRs is that they create an overload of information and take too much time (Graber et al., 2017). The lessons to be learned from the paper are that EHR requires further improvement and has great potential to benefit the diagnosis process.
Making the right diagnosis is the key to effective patient care and treatment. The introduction of EHR technologies is designed to simplify this process so that more patients can be successfully helped. For this reason, this source is vital for the study – it demonstrates both the achievements of electronic records and aspects that still need to be worked on. The article is of interest to researchers, hospital administrations, and health information technology developers.
Zhao, J., Feng, Q., Wu, P., Lupu, R. A., Wilke, R. A., Wells, Q. S., Denny, J., & Wei, W. Q. (2019). Learning from longitudinal data in electronic health record and genetic data to improve cardiovascular event prediction. Scientific Reports, 9(1), 1-10. Web.
Electronic records’ task is not only to effectively manage the data received about the patient and store it in one place. The study by Zhao et al. (2019) is an example of the successful use of EHR to predict the possibility of disease. Cardiovascular disease is a common cause of death, and the ability to anticipate it will save many lives. The authors used longitudinal data in the electronic health records, genetic data, and ACC/AHA equation to determine cardiovascular disease risk (Zhao et al., 2019). Examples of data used from EHR include laboratory results and drug history (Zhao et al., 2019). Their findings prove the positive impact of leveraging the potential of EHR, which has not yet been sufficiently exploited.
The source is crucial for the study of this topic as it reveals another aspect of EHR use – the prediction of diseases. Calculating their possible appearance will make the work of doctors on illness prevention more effective. As a result, the widespread use of such a function would be beneficial to the nation’s health. The article is of interest to researchers and doctors, in particular cardiology specialists.
Conclusion
In conclusion, the technologies significantly change all spheres of human life, and especially medicine. For example, the use of electronic health records (EHR) can greatly simplify the treatment and increase its effectiveness, as demonstrated in articles by Zhao et al. (2019) and Kruse and Beane (2018). However, a detailed study by Graber et al. (2017) of the advantages and disadvantages of using electronic medical records suggests that they still have many improvements and changes in the future. Moreover, as the study by Kruse et al. (2017) showed, EHR usefulness may depend on the type of medical facility and require additional time to bring results. Thus, the introduction of any new technologies requires staff training and time for adaptation, but results will make efforts worthwhile.
References
Graber, M. L., Byrne, C., & Johnston, D. (2017). The impact of electronic health records on diagnosis. Diagnosis, 4(4), 211-223. Web.
Kruse, C. S., & Beane, A. (2018). Health information technology continues to show positive effect on medical outcomes: Systematic review. Journal of Medical Internet Research, 20(2), e41. Web.
Kruse, C. S., Mileski, M., Vijaykumar, A. G., Viswanathan, S. V., Suskandla, U., & Chidambaram, Y. (2017). Impact of electronic health records on long-term care facilities: Systematic review. JMIR Medical Informatics, 5(3), e35. Web.
Zhao, J., Feng, Q., Wu, P., Lupu, R. A., Wilke, R. A., Wells, Q. S., Denny, J., & Wei, W. Q. (2019). Learning from longitudinal data in electronic health record and genetic data to improve cardiovascular event prediction. Scientific Reports, 9(1), 1-10. Web.
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