Electronic Health Records (EHRs) Are Easier To Read Than The

Electronic health records (EHRs) are easier to read than the paper charts of the past, but many complain that healthcare providers are focusing too much on the computer screen instead of the patient. Is this due to lack of skill or training, poor computer system design, or just the nature of computer charting? Is patient care suffering from the implementation of EHRs? Charting in an EHR consist of clicking boxes, do you feel this provides enough detail about the patient, condition, and events if there was a law suit? Hebda, Hunter and Czar (2019) identify three types of data that is currently being tracked by organizations (p. 46). Identify and explain another type of data, specific to your practice, that is being tracked by an organization. Why do you feel this data is important to track? Identify and discuss the organization that is tracking the data. Are there any ethical concerns with an outside organization tracking this data, explain and give examples? In this week’s discussion post, you identified and explain the topic selected for the project. Provide a description of your selected topic based on input from the discussion forum. What is your project, why is it relevant to this class, and why is it important to you? Identify an informatics/healthcare theory from pages 29-30 of the textbook that aligns with the project and explain why.

Paper For Above instruction

The implementation of electronic health records (EHRs) has revolutionized healthcare documentation, offering increased readability, accessibility, and data management capabilities. However, despite these advantages, concerns persist regarding the potential for EHRs to detract from direct patient-provider interactions. Many healthcare professionals argue that the focus on computer screens during patient encounters reduces the amount of meaningful engagement, leading to potential compromises in patient care. These concerns can be attributed to various factors, including inadequate training, poor system design, and the inherent limitations of computerized charting.

Firstly, the issue of provider distraction often stems from a lack of sufficient skill and training in utilizing EHR systems effectively. Healthcare providers may feel overwhelmed or frustrated when unfamiliar with navigation or documentation features, prompting them to overly focus on screen operations rather than patient communication. Adequate training programs that enhance proficiency with EHR functionalities can mitigate this problem by increasing confidence and efficiency, ultimately allowing providers to maintain better eye contact and interaction. Additionally, poor system design can exacerbate these issues. Systems that are unintuitive, cluttered, or lack user-friendly interfaces require more time and effort to document, which can tempt providers to rush through the process or focus solely on screen interactions (Fitzgerald et al., 2020). Conversely, well-designed systems that streamline workflow and minimize clicks can improve engagement by reducing cognitive load.

Furthermore, some argue that the nature of computer charting inherently influences the documentation process. Many EHRs rely on selecting from predefined boxes, drop-down menus, or checklists, which may not capture the nuanced details of patient encounters. This limitation raises concerns about whether such charting provides enough depth to withstand legal scrutiny or to fully portray complex clinical situations. For example, in cases of malpractice litigation, detailed narrative descriptions may be critical to demonstrate thorough care, which simplistic checkbox documentation might fail to provide (Hersh et al., 2018). Therefore, while EHRs enhance efficiency, they may also constrain the richness of documentation necessary for comprehensive understanding.

Beyond these issues, organizations track various types of data to monitor and improve healthcare quality. Hebda, Hunter, and Czar (2019) identify three primary data types: clinical, operational, and financial. An additional, specific type of data relevant to particular practice settings is patient-reported outcome measures (PROMs). In my practice—primary care—PROMs are collected regularly to assess the patient’s perspective on their health status, symptoms, and treatment efficacy. This data provides valuable insights into patient satisfaction, adherence, and real-world outcomes that are often overlooked by solely clinical or administrative data.

Tracking PROMs is crucial because it emphasizes patient-centered care, facilitating tailored interventions and improving treatment plans based on real-world feedback. For instance, in a primary care organization such as a community clinic, systematic collection of PROMs allows practitioners to monitor chronic disease management, mental health, and overall well-being. An organization like the Centers for Medicare & Medicaid Services (CMS) tracks such data as part of value-based care initiatives aiming to improve quality while controlling costs. Ethical considerations surrounding outside organizations tracking PROMs include concerns about privacy, consent, and data security. Patients must be adequately informed about how their data will be used, stored, and shared. For example, if a third-party vendor consolidates PROMs data for analytics, safeguards must be in place to prevent misuse or breaches that could compromise patient confidentiality (McGraw et al., 2019). Ethical practices demand transparency and strict adherence to privacy regulations such as HIPAA.

For my project, I selected the integration and impact of telehealth services in primary care. This topic is particularly relevant because it aligns with current healthcare trends toward digital health solutions, especially in response to the COVID-19 pandemic. My interest lies in understanding how telehealth influences patient engagement, care quality, and the operational efficiency of clinics. This project is crucial for my academic growth and future professional practice as healthcare increasingly adopts remote care modalities.

The theory of Information Processing, outlined by Coiera (2015), complements my project by emphasizing how technological systems influence clinician decision-making and workflow. Coiera’s framework highlights how interface design, cognitive load, and data accessibility directly affect clinical performance. Applying this theory helps explain how effective telehealth platforms need to be user-friendly and integrated seamlessly into clinical routines to support optimal patient outcomes. Recognizing these interactions is vital to designing telehealth strategies that enhance rather than hinder clinical practice, thereby contributing to improved healthcare delivery.

References

• Coiera, E. (2015). Guide to health informatics (3rd ed.). CRC Press.
• Fitzgerald, M. A., et al. (2020). Impact of user-centered design on clinical documentation quality. Journal of Medical Systems, 44(4), 67.
• Hersh, W. R., et al. (2018). Security and privacy in electronic health records. Journal of the American Medical Informatics Association, 25(8), 934–943.
• Hebda, T., Hunter, K., & Czar, P. (2019). Handbook of informatics for nurses & healthcare professionals (6th ed.). Pearson.
• McGraw, R., et al. (2019). Patient privacy and data security in telehealth. Telemedicine and e-Health, 25(9), 798–804.
• Fitzgerald, M. A., et al. (2020). Impact of user-centered design on clinical documentation quality. Journal of Medical Systems, 44(4), 67.
• Hersh, W. R., et al. (2018). Security and privacy in electronic health records. Journal of the American Medical Informatics Association, 25(8), 934–943.
• Hebda, T., Hunter, K., & Czar, P. (2019). Handbook of informatics for nurses & healthcare professionals (6th ed.). Pearson.
• McGraw, R., et al. (2019). Patient privacy and data security in telehealth. Telemedicine and e-Health, 25(9), 798–804.
• Coiera, E. (2015). Guide to health informatics (3rd ed.). CRC Press.