Introduction
Article: Marasinghe, K. (2015). Computerized Clinical Decision-support Systems to Improve Medication Safety in Long-term Care Homes: A Systematic Review. British Medical Journal Open 5(5)
This article focused on assessing the value and effectiveness of incorporating a clinical decision support system in the processes of care. Mainly, the author’s research problem concerned a systematic review of the value and role of a computerized clinical decision support system (CCDSS) in improving the safety of medication in the context of long-term care homes (Marasinghe, 2015). A clinical decision support system is a computerized platform used to improve the quality of care in clinical environments through support in the process of clinical decision-making. This benefit occurs because the system offers recommendations relating to issues such as medicine dosages, avoidance of medication in certain circumstances, and guidance in the diagnosis of illnesses and interpretation of health data among others. Recognizing the growing popularity and integration of CCDSS in modern healthcare environments, the author sought to investigate its role and significance in promoting the safety of medication in older populations, particularly in a long-term care environment (Marasinghe, 2015).
The author implemented the qualitative method of systematic review to achieve the objective. She used three groups of keywords (relating to long-term care, computerized computer decision support, and medication safety) to search for relevant articles in different databases, including Scopus, Cochrane, EMBASE, and MEDLINE. The chosen articles concerned environments of long-term healthcare services and evaluated the effects of CCDSS in the improvement of medication safety (Marasinghe, 2015). The review of the studies represented an important focus in the author’s plan because of its capacity to yield particular patterns and themes concerning the role of CCDSS as a technology that could influence improvements in the effectiveness of long-term care. A critical indication of this effectiveness was the safety of medication (hence the minimization of errors in prescription, dosage, and cases of adverse drug interactions (Marasinghe, 2015). The evidence in reviewed articles was that CCDSS improves the quality of the decisions of prescription and reduces the risks of injuries and negative drug effects in long-term care settings (Marasinghe, 2015). The incorporation of CCDSS in long-term care settings is essential in the context of growing demand for long-term care in the older population. The author argues that this scenario presents an increased workload for healthcare professionals, observing that it is no longer adequate to rely only on the judgment of physicians regarding the safety of the medication. These results pointed to the significant and direct role of CCDSS as a healthcare technology in fostering the accuracy of healthcare professionals’ decision-making in prescriptions of medicine, and hence higher levels of safety in prescribed medication in the management of chronic health conditions (Marasinghe, 2015).
Evaluation of Research Methods
Although the author did not perform an elaborate literature review, she appraised the focuses, findings, and conclusions of several previous studies in the introduction as a way of building the context or background for the study. In particular, the paper did not feature a dedicated section with a heading for the review of literature. Part of the problem in the lack of an elaborate literature review, as the author acknowledges, is the limited published literature on the topic. As a relatively new technology, the clinical decision-support system has received little attention in the medical literature, more so in the setting of long-term care (Marasinghe, 2015). The author acknowledges that the topic of CCDSS in the management of chronic conditions is likely to receive increasing attention in the future. This is because of the rising demand for both the long-term care and technological solutions to improve its quality and effectiveness.
The theme of research in the article is highly relevant in the context of emerging needs and trends in the modern society and healthcare environment. According to the author, as the aging population grows, so does the prevalence of chronic conditions that require long-term care. An aging population and the rising prevalence of chronic diseases that demand healthcare services in the long term is likely to cause increased pressure in the roles and performances of healthcare professionals. In turn, this pressure could yield an elevated probability of error in both the short and long terms (Marasinghe, 2015). The article’s theme, concerning an assessment of the value of CCDSS as a healthcare technology in enhancing the effectiveness of care, is pertinent in the context of arguments that technological innovations represent suitable and cost-effective ways of improving the experiences of members of the society, especially in relation to common challenges in their lives. In the case of this article and its focus, the challenge concerns the desire to reduce errors in the decision-making of healthcare professionals in the prescriptions of medicines, which have adverse effects on the safety of these medicines in the management of chronic diseases. Indeed, this means that the author addresses a highly relevant topic in healthcare, especially considering the increasing focus of the society and healthcare field, specifically on exploiting technological advances to improve the lives of people and societies by addressing prevailing and emerging problems. Technology in the healthcare field has enormous promise in improving the quality of healthcare and promoting evidence-based care, especially regarding modeling healthcare processes on the needs of individuals.
In the article, Marasinghe (2015) applied a qualitative approach, specifically avoiding an experimental model of study and instead conducting a systematic analysis of the findings in other articles. The approach contrasts with that in experimental and quasi-experimental designs, in which the researchers apply empirical studies to estimate causal impacts of specific interventions. In effect, the author’s assessments and conclusions were contingent on the accuracy and validity of those of the other researchers. An experimental or quasi-experimental approach would have offered direct empirical evidence for the author’s assessments.
The author utilized a sample of seven articles from the different databases searched. The author identified the seven articles from a possible total of 38, choosing to exclude the other articles due to duplications and ineligibility for full-text screening (Marasinghe, 2015). Five of the seven articles reviewed adopted the random-controlled trial model, thereby enhancing their quality and validity in assessing the role and effectiveness of CCDSS in minimizing medication errors in long-term care. The authors in the reviewed articles used samples that were hugely diverse and relatively large. The samples comprised 813, 833, 1118, 274, 445, 1196, and 5628 participants (Marasinghe, 2015). The structured process of selecting the studies, along with the fact that the selected studies had relatively large samples, meant that the sampling was unbiased and adequately reliable to yield scientific and sufficiently representative samples.
Overall, the work appears practical and adequately representative of the target population. The author’s systematic review and findings regarding the effectiveness of CCDSS in improving the effectiveness of managing chronic conditions and reducing the occurrence of prescription errors are hugely practical and applicable. This is since the reviewed studies and the discussions of their authors were effective in establishing the potential of the CCDSS in minimizing medication errors in long-term care. As a result, it is clear that the incorporation of CCDSS in long-term care settings is potentially beneficial and effective. Nevertheless, further research on implementation and effectiveness is necessary to evaluate the role and significance of the technology in long-term care settings more effectively.
The article is straightforward and easy to understand. Nonetheless, the author could have utilized empirical evidence through a direct study of the relationship between application of CCDSS and reduced medication errors in long-term care, rather than depending on the findings and conclusions of other researchers. The use of primary data would have strengthened the trustworthiness of the author’s findings, arguments, and conclusions about the role and effectiveness of CCDSS in minimizing medication errors in long-term care.
Conclusion
The importance of this study in the context of relevant health issues in the modern society relates to its focus on CCDSS as a potential technological solution to the challenges of increasing prevalence of chronic diseases that require long-term care and the health needs of an aging population. These trends have caused an increasing workload for health professionals, making it inadequate to rely only on the decision-making and judgment abilities of these professionals in long-term care. In this context, the article’s focus on CCDSS is relevant because of the technology’s capacity to support clinical decision-making and reduce the probability of physicians’ errors. In the article, the author’s use of a qualitative research approach (regarding a systematic review of other research articles), rather than using direct evidence from an empirical study, undermines the trustworthiness of her arguments and conclusions. An experimental or quasi-experimental approach would have offered direct empirical evidence for the author’s assessments. Nonetheless, the author’s arguments and findings are practical and applicable since the review established the potential of CCDSS in improving the quality of long-term care and minimizing medication errors.
References
Marasinghe, K. (2015). Computerized Clinical Decision-support Systems to Improve Medication Safety in Long-term Care Homes: A Systematic Review. British Medical Journal Open 5(5). Retrieved from http://bmjopen.bmj.com/content/bmjopen/5/5/e006539.full.pdf