Name
Capella University
NURS-FPX 8012 Nursing Technology and Health Care Information Systems
Prof. Name
Date
Distortion of patient data can lead to significant ethical and legal consequences. One of the primary issues is the violation of patient privacy, as the right to privacy may be compromised if data is inaccurately represented within the healthcare sector. Patients expect that their personal and medical information will remain confidential and will not be disclosed without their consent (Balynska et al., 2021). Breaches in confidentiality can occur when data is misrepresented, potentially endangering the patient’s privacy.
Inaccuracies in data can also result in malpractice within healthcare organizations. Providing false information due to low compliance with medical software may contribute to malpractice issues. Both legal and ethical standards mandate that healthcare professionals deliver accurate and truthful information to their patients. Nursing codes of ethics emphasize the need for professionals to provide care in alignment with ethical standards (Ilkafah et al., 2021). Miscommunication among healthcare staff can lead to misdiagnoses and improper treatments, ultimately compromising patient safety. Additionally, professional misconduct can negatively impact clinical outcomes and harm the overall performance of healthcare organizations.
Healthcare professionals are responsible for acting with honesty and integrity when interacting with patients. If they fail in this duty and patient information is leaked, the patient has the right to pursue legal action. Harm resulting from breaches of Protected Health Information (PHI) could lead to compensation claims for pain, medical expenses, and other damages. Serious ethical and legal consequences may arise for healthcare professionals if they intentionally violate privacy laws concerning patient information (Choi et al., 2019). To prevent legal or ethical issues, healthcare providers must safeguard the accuracy and confidentiality of patient data.
Failure to address risks within healthcare organizations can lead to problems such as poor patient care quality, financial instability, and low staff morale. Patient safety can be jeopardized by medication errors, which result in negative patient outcomes. A patient might take legal action, harming the reputation of a healthcare organization. HIPAA violations are a compliance risk that must be addressed to avoid penalties, lawsuits, and damage to the organization’s reputation. Risks to healthcare organizations may also affect financial performance if operational risks, such as ineffective staffing, are not mitigated. Therefore, addressing risks within healthcare organizations is essential to ensuring patient and staff safety, maintaining regulatory compliance, and achieving financial stability. Proactively identifying and mitigating risks allows organizations to achieve their mission of providing high-quality patient care.
Upgrading electronic health record (EHR) systems can streamline healthcare processes, improve efficiency, and reduce costs by automating processes, minimizing paperwork, and preventing errors. Enhanced EHR systems provide real-time, data-driven insights that assist healthcare professionals in making better decisions and improving patient outcomes (Rhoades et al., 2022). By streamlining workflows through effective training in EHR usage, healthcare staff can prioritize more complex tasks and save time (Nuamah et al., 2020). Proper EHR training involves understanding how to input and retrieve data and familiarizing staff with system features. Ongoing instructions and support can help staff become more comfortable with the system and use it efficiently.
Patient identification systems ensure that clinical records are accurate and up-to-date. Using unique patient identifiers helps healthcare professionals avoid duplicating records or merging data from different patients, which can lead to errors and confusion. Accurate data is essential for delivering safe, effective care and supporting clinical decision-making (Riplinger et al., 2020).
Multifactor authentication (MFA) is another tool that helps protect patient data under HIPAA rules and regulations. Healthcare providers are required by HIPAA to safeguard patients’ personal health information from unauthorized access or disclosure. MFA is a security measure that requires authorized users to provide a password or PIN to access patient records. By implementing MFA, healthcare providers can improve patient data security and reduce the risk of data breaches (Bahache et al., 2022).
Implementing change in healthcare organizations requires a diverse and skilled team, as well as adequate financial and material resources. Effective change management ensures that organizations adopt new procedures, policies, and regulations that can improve patient outcomes, such as reducing wait times, enhancing care coordination, and raising the standard of care (Milella et al., 2021). Change management can also lead to cost savings by improving the efficiency of healthcare processes, reducing waste, and better utilizing resources. It ensures compliance with evolving regulatory standards and policies.
The Lewin change model is a well-known framework for managing organizational change in healthcare settings. This model consists of three stages: unfreezing, changing, and refreezing (Harrison et al., 2021). In the case of poor IT infrastructure and low software compliance, change is necessary to ensure EHR systems function effectively to maintain patient data consistency. Effective communication and collaboration among stakeholders are crucial for driving positive change in healthcare organizations, which ultimately improves patient outcomes and elevates care standards.
The ADKAR (Awareness, Desire, Knowledge, Ability, and Reinforcement) model is another approach to managing change and achieving successful outcomes (Balluck et al., 2020). Healthcare organizations must communicate the justification for the change and explain how it benefits patients, employees, and the organization. Emphasizing the advantages of the change to staff is critical for gaining their support. Organizations must also inform staff about upcoming changes in procedures, systems, or technology and provide the necessary training or coaching to implement the change. The final step involves reinforcing the change by monitoring its progress, offering feedback, and rewarding staff for successfully implementing it.
The Allen Clinic experienced issues with EHR management due to inadequate staff training and poor IT infrastructure. Applying the aforementioned change management strategies will improve patient outcomes, staff satisfaction, and organizational performance. The change will also enhance collaboration between stakeholders, who will work towards a shared vision of raising care standards by effectively addressing identified risks in the organization.
Bahache, A. N., Chikouche, N., & Mezrag, F. (2022). Authentication schemes for healthcare applications using wireless medical sensor networks: A survey. SN Computer Science, 3(5). https://doi.org/10.1007/s42979-022-01300-z
Balluck, J., Asturi, E., & Brockman, V. (2020). Use of the ADKAR and CLARC change models to navigate staffing model changes during the COVID-19 pandemic. Nurse Leader, 18(6). https://doi.org/10.1016/j.mnl.2020.08.006
Balynska, O., Teremetskyi, V., Zharovska, I., Shchyrba, M., & Novytska, N. (2021). Patient’s right to privacy in the health care sector. Georgian Medical News, 321, 147–153. https://pubmed.ncbi.nlm.nih.gov/35000925/
Choi, S. J., Johnson, M. E., & Lehmann, C. U. (2019). Data breach remediation efforts and their implications for hospital quality. Health Services Research, 54(5), 971–980. https://doi.org/10.1111/1475-6773.13203
Harrison, R., Fischer, S., Walpola, R. L., Chauhan, A., Babalola, T., Mears, S., & Le-Dao, H. (2021). Where do models for change management, improvement and implementation meet? A systematic review of the applications of change management models in healthcare. Journal of Healthcare Leadership, 13(13), 85–108. https://doi.org/10.2147/jhl.s289176
Ilkafah, I., Mei Tyas, A. P., & Haryanto, J. (2021). Factors related to implementation of nursing care ethical principles in Indonesia. Journal of Public Health Research, 10(2). https://doi.org/10.4081/jphr.2021.2211
Milella, F., Minelli, E. A., Strozzi, F., & Croce, D. (2021). Change and innovation in healthcare: Findings from literature. ClinicoEconomics and Outcomes Research, 13, 395–408. https://doi.org/10.2147/ceor.s301169
Nuamah, J. K., Adapa, K., & Mazur, L. (2020). Electronic health records (EHR) simulation-based training: A scoping review protocol. BMJ Open, 10(8), e036884. https://doi.org/10.1136/bmjopen-2020-036884
Rhoades, C. A., Whitacre, B. E., & Davis, A. F. (2022). Higher electronic health record functionality is associated with lower operating costs in urban—but not rural—hospitals. Applied Clinical Informatics, 13(3), 665–676. https://doi.org/10.1055/s-0042-1750415
Riplinger, L., Piera-Jiménez, J., & Dooling, J. P. (2020). Patient identification techniques – approaches, implications, and findings. Yearbook of Medical Informatics, 29(1), 81–86. https://doi.org/10.1055/s-0040-1701974
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