Please detail in this section what statistical test you would use to analyze the data you propose to collect (in the Research Method section). Why would you plan to use this particular test? How would you interpret this statistic and this data as it relates to your hypothesis/null hypothesis and the overall meaning for you healthcare topic?
please see the attachments. it has to relate to health information Management.
I only need half a page with references.
RESEARCH CONCEPTS OF HIM (LITERATURE REVIEW) 2
Health IT traces its root back to the 1920s where during this period, healthcare professionals realized that having documentation of patient care would not only benefit the patients but would go a milestone in benefiting the providers as well (Ashley, 2015). These patient records entail all the details, complications as well as the outcome of patients care. Since then, health information technology has seen tremendous upgrades and has become an essential segment in health care. Over time, the use of technology in healthcare has led to improved patient diagnosis and care. The healthcare industry has reaped the most significant benefits from the widespread use of new technologies. As a result, it has helped people live longer and saved countless lives (Ashley, 2015).
Quality and patient safety in healthcare departments have embraced health IT to thwart reportable occurrences, detect them, and take action on incidents considered inevitable. The application of health IT is novice, especially where since healthcare companies are at a fix identifying which areas to put their resources. Take, for example, the Covid 19 crisis. International hospitals and the majority of healthcare facilities have been facing disastrous financial encounters directly associated to COVID. The use of HIT would thus play an essential role in curbing future pandemics considering that it enables communication amid medical practitioners, advances medication protection, reporting, and endorses quality of healthcare through augmented access (Ashley, 2015). Thus, this literature review aims to identify the significance of health information technology in human health in its widely used spectrum.
Statistic from the American Hospital Association, healthcare systems, especially in America, will lose more than 200 billion dollars in income yearly which translates to an average of nearly fifty billion on average. To make matters worse, providing an adequate healthcare response may cost low and average income nations as much as US$52 billion per year (or US$8.60 per person). This load has affected US patient care, operations, and surgical results, where there are the most COVID-19 new cases every day. World Bank predicts that global growth would be reduced by almost 8%, with poorer nations bearing the brunt of the blow. The United Nations estimates that the world economy will be hit with a bill of approximately $2 trillion this year. In general, healthcare institutions across the globe struggled because of a lack of preparation. There was a severe shortage of healthcare personnel, personal protective equipment (PPE), essential equipment in hospitals, sanitizing supplies, and even clean drinking water. Health organizations across the globe have been forced to develop new critical strategies for pandemic preparation due to the inadequacies revealed by COVID-19 (Kaye et al. 2020).
Through Health information technology came the understanding that healthcare, like other sectors, can utilize data to improve human knowledge of what seemed to be uncontrolled costs and unexpected results in the healthcare industry itself. For the first time in almost couple of decades of data collection, analysis, and mash-up, it's vital to look further from the knowledge and understanding provided by data but rather establish a considerable utilization of data for probable courses, particularly in regards to healthcare quality as well as patient safety. This is especially true when it comes to patient safety. When it comes to the value of healthcare Information Technology in terms of reducing costs and improving quality of care, the evidence is mixed. There are a lot of similarities between the healthcare quality and patient safety areas and those of the credit card sector when it comes to business intelligence and predictability (Feldman et al., 2018).
Health information technology encompasses various tools, from basic charting to more sophisticated decision assistance and interaction with medical equipment. Numerous possibilities for improving and changing healthcare are presented by health information technology, including decreasing human error, in order to raise the standard of clinical outcomes, streamline care organization, and collective practice efficacy. A lot has changed in health IT since the initial publication of the IOM research, including data regarding the effect of health IT on patient safety that varies in strength (Alotaibi & Federico, 2017).
Reliability in healthcare revolves around a "failure-free operation over time" and is a three-segment cycle that includes fiasco avoidance and detection, and process reform. Information systems have been used in other healthcare settings to offer real-time reporting while providing continuous monitoring. This means that considering the role of health IT in guaranteeing patient safety and quality of treatment is a logical step. Studies show that healthcare administrations are utilizing health IT to improve healthcare quality. They have supplanted redesign allowing for the implementation of health IT after a potential event has occurred that compromises healthcare quality and doesn’t necessitate restructure. In the form of alerts, health IT starts to stop the pharmacist from filling a potentially hazardous order once it occurs in the electronic health record (Feldman et al., 2018). Therefore, it is vital to acknowledge that there are various applications of health IT. However, health IT has no limitations, and its significance can go wide and beyond our understanding medically.
Prevention using Health IT.
Preventing quality and wellbeing incidents entails using IT to prevent them from occurring in the first place. It's helpful to have reminders and alerts set up automatically to make important information available while making clinical choices (Grissinger, 2016). As a common method for using health IT to avoid missing quality and patient safety incidents, these alerts are included in the EHRs (electronic health record). There has been a 12 percent rise in well-child immunizations, a twenty two percent increase in vaccination delivery, as well as a 22 percent reduction in medicine prescription mistakes due to immunization notifications, for instance (Bundy et al. 2013). Using soft stops to detect quality or patient safety issues may be very beneficial. They may provide options, but in most cases, acknowledging the warning is all that's needed to continue, especially in covid 19 related cases and diagnostics.
On the other hand, a hard stop prohibits an action that may be harmful to the patients. A hard stop would enable the process to continue, but only if the user takes substantial necessary action, such as calling or consulting with a specialist. Due to challenges such as alert fatigue, insufficient implementation, soft-stops may be disregarded or overridden in certain situations. The use of hard stops has been proven to be more effective in altering a risky plan or avoiding a potentially harmful intervention when they are well planned (Coiera et al., 2016).
Identification of safety and quality happenings
It includes detecting the impending occurrence of quality and safety incidents. As health insurance costs rise, healthcare systems are under growing pressure to save costs while improving patient outcomes. Such kind of pressure can exist in the form of tiered payment schemes that reward strategies that achieve or surpass specific performance standards. These payers are putting more and more pressure on providers by refusing to reimburse them for services they deem unneeded or above and beyond what is considered "standard care." Information technology in healthcare may be used to identify patient groups in whom reimbursement is less than anticipated, such as the amount of time needed to be in the hospital after a specific operation. It's important to give careful attention to understanding any unexpected effects when using health IT, even if it may generate data and dashboards useful for decision-making on payment patterns and practices for durations of stay for that illness. Unintended readmissions, for instance, are an essential statistic to monitor while decreasing the duration of stay.
Health IT usage to effectively cope with COVID 19 catastrophe.
Health IT is essential, especially during this period since the virus is here to stay as it has already set its root. There are two key and fundamental strategies that would help curb and effectively cope with the crises, especially in the healthcare sector. First is the prevention of the swift blowout of the virus by slowing the transmission rate, and second is the development of effective medicine (the vaccine) for the virus. These two strategies can be easily achieved and implemented through the aid of Health IT founded on the amalgamation and complementary distribution of big data, AI (artificial intelligence), cloud technology, blockchain expertise, smart wearable devices, and IoT (the internet of things).
COVID-19 may be controlled by using healthcare IT convergence to its full potential. Physical contact encourages the spread of the virus, and it also increases the risk of medical personnel being infected, which is against the fight against the virus. As a result, preventing the fast transmission of COVID-19 requires limiting physical contact (Griggs et al., 2018). It's also critical to monitor one’s body's temperature and overall wellness regularly. IoT-enabled smart wearables make it feasible to monitor an individual's health in real-time without having to make physical contact with a doctor (Griggs et al., 2018). These devices make it possible for individuals to access internet networks at any time and from any location, allowing them to share healthcare data with their medical specialists at any time and from any location without having to make physical contact.
In order to gather and exchange healthcare data in real-time regarding SARS-CoV-2 patients or presumed infected individuals through data originating from intelligent wearable devices, large medical data repositories as well as healthcare information security would be needed. By combining cloud and blockchain technologies, scalable medical big data repositories can be protected while yet being scalable. Smart wearable devices that continuously gather healthcare data on individuals suspected of having COVID-19 infection, combined with artificial intelligence (AI), may offer more sophisticated functionalities helpful for monitoring COVID-19 more efficiently and precisely (Xia et al. 2017).
The convergence of healthcare IT may help speed up the development of a COVID-19 medication. Medical researchers may have an increasingly difficult time developing a treatment since the illness changes with time, necessitating more sophisticated biological analysis, as well as cooperation between different healthcare institutions across the world to create the medication. Smart wearables, linked to the cloud and the Internet of Things, can provide the medical data necessary for big data needed to study COVID-19's changes (Xia et al., 2017). Biomedical extensive data gathered from smart wearable devices may be analyzed efficiently using AI, including machine learning technology combined with cloud and the internet of things technologies. By enhancing the security and speed of medical data gathering and sharing, blockchain, IoT, and cloud technologies may help healthcare companies collaborate globally on global R&D (research and development) projects to create COVID-19 medicine (Griggs et al. 2018).
Big data extraction, cloud technology, AI implementation, blockchain technology, the internet of things, and intelligent wearable gadgets in healthcare IT may work synergistically to combat the COVID-19 when combined successfully. As a result, we are hopeful that the convergence of healthcare IT will help avoid the fast spread of COVID-19 and create a medication that is effective as quickly as feasible. On the other hand, the limitation of this research is that health IT is still a comprehensive technology that requires massive further research to implement the convergence of health IT and implement it to have better success in combating and eradicating COVID 19 if possible. However, a review of literature from this paper ascertains that health IT is the future of healthcare in terms of medication and the development of COVID 19 medication that will free the world from the jaws of the pandemic now and in the future.
Alotaibi, Y. K., & Federico, F. (2017). The impact of health information technology on patient safety. Saudi medical journal, 38(12), 1173.
Ashley B. (2015, March 23). Health information management history: Past, present & future. Rasmussen University – Online and On-Campus | Rasmussen University. Retrieved September 30, 2021, from https://www.rasmussen.edu/degrees/health-sciences/blog/health-information-management-history/#:~:text
Bundy, D. G., Persing, N. M., Solomon, B. S., King, T. M., Murakami, P. N., Thompson, R. E., … & Miller, M. R. (2013). Improving immunization delivery using an electronic health record: the ImmProve project. Academic pediatrics, 13(5), 458-465.
Coiera, E., Ash, J., & Berg, M. (2016). The unintended consequences of health information technology revisited. Yearbook of medical informatics, 25(01), 163-169.
Feldman, S. S., Buchalter, S., & Hayes, L. W. (2018). Health information technology in healthcare quality and patient safety: literature review. JMIR medical informatics, 6(2), e10264.
Griggs, K. N., Ossipova, O., Kohlios, C. P., Baccarini, A. N., Howson, E. A., & Hayajneh, T. (2018). Healthcare blockchain system using smart contracts for secure automated remote patient monitoring. Journal of medical systems, 42(7), 1-7.
Grissinger, M. (2016). Small effort, big payoff: Automated maximum dose alerts with hard stops. Pharmacy and Therapeutics, 41(2), 82.
Kaye, A. D., Okeagu, C. N., Pham, A. D., Silva, R. A., Hurley, J. J., Arron, B. L., … & Cornett, E. M. (2020). Economic impact of COVID-19 pandemic on health care facilities and systems: international perspectives. Best Practice & Research Clinical Anaesthesiology.
Xia, Q., Sifah, E. B., Smahi, A., Amofa, S., & Zhang, X. (2017). BBDS: Blockchain-based data sharing for electronic medical records in cloud environments. Information, 8(2), 44.
RESEARCH CONCEPTS FOR HIM 3
I would use observation as the research method to test my hypothesis. Investigators use the qualitative approach of observation to track the behavior of subjects in a real-world setting. More accurate information is the goal of this sort of study. It is effective because a researcher may collect data on individuals' actions rather than their statements. Moreover, it is suitable for this research because it can be carried out on a technology after it has already been introduced and is being incorporated in a specific area of the medical field; which is suitable because my research is on health IT. However, it is important to note that observational research fills a significant gap in healthcare research, serving as a veritable tool to experimental research (Ostropolets, 2021).
I chose this method because it is a suitable alternative to experimental investigations. Moreover, it works best because as a researcher I will not be interacting with or manipulating the study subjects, but rather I’ll be merely watching and recording their responses. Additionally, I t is less difficult to replicate so I can be able to re-conduct it for a more accurate analysis; incorporating these methods results in the most compelling evidence to support decision-making. When collected information and methodology from observational research are used, it is possible to save money and time whilst still obtaining high-quality data to help support or disprove the hypothesis.
Jenny Gong, B. S., Kristina Garrels, M. D., & Johnbuck Creamer, M. D. A Curriculum to Promote Smarter Use of Observational Data.
Ostropolets, A., Zachariah, P., Ryan, P., Chen, R., & Hripcsak, G. (2021). Data Consult Service: Can we use observational data to address immediate clinical needs?. Journal of the American Medical Informatics Association, 28(10), 2139-2146.
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