Safe Patient Diagnosis – An All Time Priority

Dr Rinu J George* (ORCID - 0000-0002-2932-5648)

TMM College of Nursing, Thiruvalla, Kerala, India.

*Corresponding author

*Dr Rinu J George, TMM College of Nursing, Thiruvalla, Kerala, India.

Even though safe patient diagnosis is an essential component of high-quality healthcare, it continues to be a source of concern due to the considerable number of diagnostic errors that occur. There are several variables that must be considered in order to guarantee a safe diagnosis. These include effective communication, the utilization of cutting-edge diagnostic techniques, teamwork among medical specialists, and comprehensive follow-up treatment. In addition to this, it is highly dependent on the cognitive and technical abilities of physicians, in addition to the active participation of patients.1, 2, 3 Diagnostic errors, which can originate from a variety of sources, such as cognitive biases, insufficient patient histories, and poor access to resources, are one of the most significant obstacles that must be overcome in order to provide a safe diagnosis.

Studies show that diagnostic errors contribute to approximately 10% of patient deaths and account for 6-17% of adverse hospital events. Because a sizeable portion of these errors can be avoided, one of the most important concerns in the field of medicine is the protection of patients. patients and providers need to communicate effectively with one another. Incomplete information is frequently the result of misunderstandings in communication or a lack of patient participation, which can lead to a delayed diagnosis or an inaccurate diagnosis.4,5 To make more accurate diagnoses, it is vital to have an open discussion with patients, according to a study conducted by the Institute of Medicine.

This dialogue should include the collection of all pertinent symptoms and medical history.6,7 Artificial intelligence (AI) and machine learning (ML) are two examples of technological breakthroughs that show promise in terms of enhancing diagnostic accuracy. Artificial intelligence (AI) systems can analyze enormous volumes of data in a short amount of time. They can also provide assistance to medical professionals by recognizing patterns or anomalies that may not be immediately obvious to human eyes. As a result of this support, doctors may experience less cognitive strain, which may result in a reduction in error rates.8
Collaboration between different fields of study is another essential component.

To guarantee that all possible reasons are considered, complex diagnoses frequently require input from various medical specialities. The utilization of a team-based approach has the potential to cultivate a more all-encompassing perspective on the patient's condition, hence reducing the likelihood of improper or missed diagnosis.9,10 In conclusion, the provision of follow-up care is an essential component of safe diagnosis. A timely re-evaluation of a patient's condition is crucial, particularly in cases when symptoms continue to develop.

The failure to alter treatment plans in response to new information or the failure to miss follow-up appointments can result in diagnostic delays, which can have a detrimental impact on the outcomes for patients. It is important to note that arriving at a safe diagnosis is a multi-step process that necessitates careful attention to communication, the utilization of technology, collaboration between professionals from different fields, and continuous patient evaluation. Healthcare systems can improve patient safety outcomes and reduce diagnostic errors if they dedicate their attention to these areas.

References

  1. Singh H, Graber ML, Hofer TP. Measures to Improve Diagnostic Safety in Clinical Practice. J Patient Saf. 2019 Dec;15(4):311-316. doi: 10.1097/PTS.0000000000000338. PMID: 27768655; PMCID: PMC5398940.
  2. Olson, A. P. J., Linzer, M., & Schiff, G. D. (2021). Measuring and Improving Diagnostic Safety in Primary Care: Addressing the "Twin" Pandemics of Diagnostic Error and Clinician Burnout. Journal of general internal medicine, 36(5), 1404–1406. https://doi.org/10.1007/s11606-021-06611-0
  3. Mark L. Graber and others, "Cognitive interventions to reduce diagnostic error: a narrative review", BMJ Quality & Safety, vol. 21, No. 7 (July 2012), pp. 535–557. Available at https://qualitysafety.bmj.com/content/21/7/535.
  4. Committee on Diagnostic Error in Health Care; Board on Health Care Services; Institute of Medicine; The National Academies of Sciences, Engineering, and Medicine; Balogh EP, Miller BT, Ball JR, editors. Improving Diagnosis in Health Care. Washington (DC): National Academies Press (US); 2015 Dec 29. 3, Overview of Diagnostic Error in Health Care. Available from: https://www.ncbi.nlm.nih.gov/books/NBK338594/
  5. Vally, Z. I., Khammissa, R. A. G., Feller, G., Ballyram, R., Beetge, M., & Feller, L. (2023). Errors in clinical diagnosis: a narrative review. The Journal of International Medical Research, 51(8), 3000605231162798. https://doi.org/10.1177/03000605231162798
  6. O’Daniel M, Rosenstein AH. Professional Communication and Team Collaboration. In: Hughes RG, editor. Patient Safety and Quality: An Evidence-Based Handbook for Nurses. Rockville (MD): Agency for Healthcare Research and Quality (US); 2008 Apr. Chapter 33. Available from: https://www.ncbi.nlm.nih.gov/books/NBK2637/
  7. Tiwary, A., Rimal, A., Paudyal, B., Sigdel, K. R., & Basnyat, B. (2019). Poor communication by health care professionals may lead to life-threatening complications: examples from two case reports. Wellcome open research, 4, 7. https://doi.org/10.12688/wellcomeopenres.15042.1
  8. Alowais, S. A., Alghamdi, S. S., Alsuhebany, N., Alqahtani, T., Alshaya, A. I., Almohareb, S. N., Aldairem, A., Alrashed, M., Bin Saleh, K., Badreldin, H. A., Al Yami, M. S., Al Harbi, S., & Albekairy, A. M. (2023). Revolutionizing healthcare: the role of artificial intelligence in clinical practice. BMC medical education, 23(1), 689. https://doi.org/10.1186/s12909-023-04698-z
  9. Bendowska, A., & Baum, E. (2023). The Significance of Cooperation in Interdisciplinary Health Care Teams as Perceived by Polish Medical Students. International journal of environmental research and public health, 20(2), 954. https://doi.org/10.3390/ijerph20020954
  10. Kozlowski, S. W. J., & Ilgen, D. R. (2006). Enhancing the Effectiveness of Work Groups and Teams. Psychological Science in the Public Interest, 7(3), 77-124. https://doi.org/10.1111/j.1529-1006.2006.00030.x
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