Technological development as an issue in healthcare Description of the Health Care Problem The dynamic and ever-evolving nature of healthcare technology may become a challenge when integrating technologies such as electronic health records (EHRs), telemedicine, artificial intelligence (AI), and wearable devices into the healthcare system. Besides offering immense potential for revolutionizing healthcare delivery, these technologies come with their complexities and limitations that require attention and thoughtful solutions. Significant concerns have emerged from the increased use of technology that may have potential health implications, such as compromised patients' privacy as the digitalization of health information introduces vulnerabilities to cyber threats and unauthorized access. The introduction of Artificial intelligence (AI) in decision-making poses challenges to maintaining patient trust and ensuring fair and unbiased healthcare practices. Workforce-related challenges arise as the technological evolution accelerates, forcing healthcare professionals to continually adapt to new systems by undergoing extensive training to navigate complex digital interfaces. This shift increases the risk of information overload and the erosion of traditional doctor-patient relationships due to increased reliance on technology. This rationale creates a sense of why there needs to be a balance between harnessing the benefits of innovation and addressing the associated health implications. This comes with another challenge of ensuring equitable access for all individuals, regardless of socioeconomic or demographic factors. Exploration of the Chosen Topic
The issue of rapid technological development in healthcare impacts various aspects of patient care, clinical workflows, and organizational structures in ways that if not addressed can lead to
unintended consequences. Some consequences include potential health implications, such as compromised patient privacy, data security concerns, and disruptions to the traditional doctorpatient relationship. The human resource is affected as the healthcare professionals to adapt continually to new systems and methodologies. Examining Assumptions
Assumptions surrounding technological development in healthcare may include the belief that newer technologies always equate to better patient care or increased efficiency without considering potential disruptions to the established workflows. There might also be an assumption that all healthcare professionals are equally adept at navigating and utilizing advanced technological tools, overlooking the varied levels of digital literacy within the workforce. Questioning these assumptions is important in understanding the challenges posed by technological development and ensuring that solutions address the diverse needs and concerns of healthcare providers and patients. Analyzing Evidence
Studies and reports by Lee & Yoon (2021) highlight the potential benefits and challenges associated with technological development in healthcare. The evidence suggests that while technology can significantly enhance diagnostic capabilities, treatment options, and patient engagement, it also introduces risks and concerns such as cybersecurity threats, unauthorized access to sensitive health information, and the potential for algorithmic biases (Lee & Yoon, 2021). The transition to electronic health records introduces concerns about unauthorized access to patient data where inappropriate use of health information by malicious actors or even internal breaches within healthcare organizations can undermine patient privacy (Arafa et al., 2023). Evidence also suggests that over-reliance on technology may impact the patient-provider relationship, potentially diminishing the human touch essential in healthcare (Driscoll, 2018).
This could also cause a digital divide due to the varying levels of access to healthcare technologies among different demographic groups hence raising equity concerns. Identification of Possible Causes
The increasing reliance on digital systems and interconnected devices in healthcare introduces vulnerabilities to cybersecurity threats where hackers may target health systems, compromising the integrity and confidentiality of patient data. The very nature of digital systems, often interconnected for seamless data exchange, creates vulnerabilities that can be exploited by malicious actors driven by various motives ranging from financial gain to activism. As health records transition from traditional paper formats to electronic systems, the risk of unauthorized individuals gaining entry to these digital repositories becomes a major consideration (Shah & Khan,2020). The risk intensifies when healthcare organizations implement inadequate security measures or experience lapses in access controls leading to weak encryption and insufficient authentication protocols. These vulnerabilities can be exploited by individuals with malicious intent who if undetected can result to serious data breaches consequently eroding trust in the healthcare system as a whole. Artificial intelligence equipment is developed through continuous training (Chang, 2023). If the training datasets used to develop these algorithms contain inherent biases, whether based on demographics, socio-economic factors, or historical disparities in healthcare, the algorithms can inadvertently learn and perpetuate these biases. A good example is a scenario where a dataset predominantly represents a certain demographic group, the algorithm may be more accurate in predicting health outcomes for that group while being less reliable for others. These Biases in AI
algorithms can perpetuate existing healthcare disparities and exacerbate inequalities If they are not carefully designed and trained on diverse dataset. Resistance to change is a barrier that the integration of new technologies in healthcare may face, notwithstanding its promising transformative benefits. This resistance,, if addressed, may impede the efforts to adopt new technology into the existing workflows, affecting the realization of potential advantages. One primary cause of resistance is the unfamiliarity healthcare professionals may have with new technologies that may be perceived as disruptive and challenging to navigate, especially if the technology has a steep learning curve.
References 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. Arafa, A., Sheerah, H. A., & Alsalamah, S. (2023). Emerging Digital Technologies in Healthcare with a Spotlight on Cybersecurity: A Narrative Review. Information, 14(12), 640. Driscoll, M. A., Knobf, M. T., Higgins, D. M., Heapy, A., Lee, A., & Haskell, S. (2018). Patient experiences navigating chronic pain management in an integrated health care system: A qualitative investigation of women and men. Pain Medicine, 19(suppl_1), S19-S29. Shah, S. M., & Khan, R. A. (2020). Secondary use of electronic health record: Opportunities and challenges. IEEE access, 8, 136947-136965.
Chang, A. (2023). The role of artificial intelligence in digital health. In Digital health entrepreneurship (pp. 75-85). Cham: Springer International Publishing.