Assignment

Running Head: METHODOLOGY 2

ASSIGNMENT 2

Methodology

Introduction

Artificial Intelligence (AI) and associated technologies have become more commonplace in business and society. They are now being used in the healthcare industry. There is a lot of guarantee for these technologies to revolutionize healthcare companies' patient treatment and administrative operations. Numerous studies have already shown that AI can do as well as or better than humans at critical healthcare activities such as illness diagnosis. As early as today, AI can detect dangerous tumors better than radiologists, helping scientists build cohorts for expensive clinical studies. There are a few motivations behind why we feel it will be many years before AI replaces humans in broad medical processes.

It is no wonder that healthcare executives are concerned about cybersecurity, given that hackers are increasingly focusing on this valuable data. Hospitals throughout the globe are already benefiting from artificial intelligence and machine learning to reduce administrative costs and enhance patient care. When it comes to cybersecurity, the usage of artificial intelligence (AI) is becoming more commonplace. Despite these challenges, hostile AI applications, which operate against security systems, and are an increasing danger, are still a problem for AI deployment in healthcare security. To protect data security and patient safety, it is indeed imperative that we stay on top of these challenges (Lee, 2021). With the introduction of AI diagnostics, medications, prospective smart devices, and intelligent delivery methods, this article aims to demonstrate how AI breakthroughs might help alter health care systems. Coverage will also include how AI might help secure critical health care data from cyberattacks.

Research Paradigm

An interview protocol with a list of questions to be asked to various healthcare experts, such as nurses, physicians, and even other healthcare workers, is the method of choice for the qualitative research. With an interview, the interviewee can provide enough information about AI innovation to help transform health care systems. For example, how it can be used in the diagnosis and how it can be used in medicines, smart devices, intelligent delivery methods, and cyber security and protection of sensitive healthcare information. Using open-ended questions in an interview will allow you to get as much information as possible from your subject since they do not restrict their responses. This includes the interviewee's physical traits, emotions, and verbal and nonverbal indicators. More precise and comprehensive data may be obtained using the chosen device.

Research or Project Design

A qualitative technique was used to gather the data for this study. The data collected was qualitative. The researcher prepared an open-ended questionnaire about AI innovation, and interviews were used to administer it. These recordings were transliterated for further analysis. Most participants' responses were captured when they were trying to describe their knowledge of AI innovation and how they have witnessed AI being utilized to secure sensitive health care information from cyber threats. Depending on how quickly the participants could complete the questions, each session lasted between 30 and 50 minutes.

Sampling Procedures and Data Collection Sources

Every participant has worked or is now working at a medical facility. All participants were required to sign a consent form outlining the study's goal and providing them with the option of skipping any questions that they found too difficult to answer honestly. Participants were gathered through social media advertisements and referrals from relevant educational and professional backgrounds. There were 35 volunteers in total, with ages ranging from 24 to 57 for the males and 12 for the girls. AI advancements and how to protect critical health care information from cyber dangers were questioned about employee awareness, and 20 replied yes, and 15 said no. While 18 replied yes and 17 said no when asked if they have taken or participated in any data security training offered by their universities.

The participants' responses were dealt with in a single segment, which was qualitative in nature. It was necessary to do qualitative data analysis of open-ended questions to better understand the participants' responses. To assist with the analysis of AI development, the research concentrated on detecting a pattern, trend, or any other similar concepts (Arora, 2021). Utilizing this strategy, the specialist had the option to find commonalities and patterns. As a result, we began to compile a preliminary summary or picture of the participants' perspectives on how AI innovation has affected their workplace, particularly concerning healthcare information security and rhetoric. While also searching for the alternative viewpoints or insights they held on AI.

To answer our research questions, the top-level approaches were mostly focused on (1) How has AI innovation aided the healthcare industry? While utilizing AI, what are some of the essential safeguards to secure critical healthcare data from cyber threats? (3) How do you deal with data breaches at your healthcare facility? Is there any downside to employing AI innovations instead of its advantages? According to the participants' responses, several subcategories were formed, although it was noted that the above are all high-level categories that are all clustered.

Data Organization Plan

The responses acquired from the interviews conducted previously are to be arranged as per the specific professions of the participants or interviewees for the researcher to properly understand the general perspectives of different health professionals about Ai innovation, especially those that work in health institutions.

References

Arora, A. (2020). Conceptualising artificial intelligence as a digital healthcare innovation: an introductory review. Medical Devices (Auckland, NZ), 13, 223.

Lee, D., & Yoon, S. N. (2021). Application of artificial intelligence-based technologies in the healthcare industry: Opportunities and challenges. International Journal of Environmental Research and Public Health, 18(1), 271.