The Effectiveness of Preoperative Legal Education for Patients Undergoing Robotic Surgery in Reducing Malpractice Claims: A Quasi-Experimental Study

Yulianti Wulandari; Andi Asari

doi:10.70716/mohr.v4i3.629

Authors

Yulianti Wulandari Nursing Science Study Program, Faculty of Health Sciences, Awal Bros University, Indonesia.
Andi Asari Library and Information Science, State University of Malang, Indonesia

DOI:

https://doi.org/10.70716/mohr.v4i3.629

Keywords:

health law, informed consent, legal education, malpractice, robotic surgery

Abstract

The advancement of robotic surgery technology in modern medical practice has increased procedural complexity while simultaneously elevating the potential for legal disputes between patients and healthcare providers. One of the main factors contributing to malpractice claims is patients' limited understanding of risks, procedures, and the legal implications of medical interventions. This study aims to analyze the effectiveness of preoperative legal education in improving patient understanding and reducing the potential for malpractice claims. This study used a quasi-experimental pretest-posttest control group design with 60 respondents divided into an intervention group and a control group. The intervention consisted of structured legal education covering both medical and legal aspects, while the control group received standard informed consent. The results showed that the intervention group experienced significant improvements in legal understanding (mean 2.8 to 4.2; p < 0.05) and risk perception (mean 3.1 to 4.0; p < 0.05), along with a reduction in malpractice claim potential (mean 3.5 to 2.1; p < 0.05). Conversely, the control group showed no statistically significant changes. These empirical findings indicate that incorporating structured legal education into the preoperative pathway fosters realistic patient expectations and mitigates legal disputes in high-complexity surgical practices.

Downloads

Download data is not yet available.

References

Akyüz, E., & Erdem, Y. (2021). Patients’ experiences of informed consent and preoperative education. Clinical Nursing Research, 30(5), 529–538. https://doi.org/10.1177/1054773820963593

Beauchamp, T. L., & Childress, J. F. (2019). Principles of biomedical ethics (8th ed.). Oxford University Press.

Catchpole, K., Bisantz, A., Hallbeck, M. S., Weigl, M., Randell, R., Kossack, M., & Anger, J. T. (2019). Human factors in robotic assisted surgery: Lessons from studies ‘in the wild.’ Applied Ergonomics, 78, 270–276. https://doi.org/10.1016/j.apergo.2018.02.011

Char, D. S., Shah, N. H., & Magnus, D. (2018). Implementing machine learning in health care—Addressing ethical challenges. New England Journal of Medicine, 378(11), 981–983. https://doi.org/10.1056/NEJMp1714229

Creswell, J. W., & Creswell, J. D. (2018). Research design: Qualitative, quantitative, and mixed methods approaches (5th ed.). Sage.

Elwyn, G., Frosch, D., Thomson, R., Joseph-Williams, N., Lloyd, A., Kinnersley, P., Cording, E., Tomson, D., Dodd, C., Rollnick, S., Edwards, A., & Barry, M. (2012). Shared decision making: A model for clinical practice. Journal of General Internal Medicine, 27(10), 1361–1367. https://doi.org/10.1007/s11606-012-2077-6

Field, A. (2018). Discovering statistics using IBM SPSS statistics (5th ed.). Sage.

Gerke, S., Minssen, T., & Cohen, G. (2020). Ethical and legal challenges of artificial intelligence-driven healthcare. In Artificial intelligence in healthcare (pp. 295–336). Academic Press. https://doi.org/10.1016/B978-0-12-818438-7.00012-5

Grauberger, J., Kerezoudis, P., Choudhry, A. J., Alvi, M. A., Nassr, A., Currier, B., & Bydon, M. (2017). Allegations of failure to obtain informed consent in spinal surgery medical malpractice claims. JAMA Surgery, 152(6), e170544. https://doi.org/10.1001/jamasurg.2017.0544

Hall, D. E., Prochazka, A. V., & Fink, A. S. (2012). Informed consent for complex decisions: A problem for learners and teachers. Journal of Surgical Education, 69(2), 189–193. https://doi.org/10.1016/j.jsurg.2011.08.006

Kołacz, M. K., & Quintavalla, A. (2019). Law in the face of disruptive technology, an introduction. European Journal of Risk Regulation, 10(1), 1–3. https://doi.org/10.1017/err.2019.23

Kumru, S., Yiğit, P., Demirtaş, M., & Fındık, H. (2023). Informed consent in surgical practice with patients’ experiences: A cross-sectional study. Patient Experience Journal, 10(3), 42–48. https://doi.org/10.35680/2372-0247.1768

Lanfranco, A. R., Castellanos, A. E., Desai, J. P., & Meyers, W. C. (2004). Robotic surgery: A current perspective. Annals of Surgery, 239(1), 14–21. https://doi.org/10.1097/01.sla.0000103020.19595.7d

Lazuardi, I., & Marwiyah, S. (2023). Analysis of informed consent as the legal protection of physician relationships and patients in malpractice cases. Policy, Law, Notary and Regulatory Issues, 2(4), 327–338. https://doi.org/10.55047/polri.v2i4.774

Levinson, W., Roter, D. L., Mullooly, J. P., Dull, V. T., & Frankel, R. M. (1997). Physician-patient communication: The relationship with malpractice claims among primary care physicians and surgeons. JAMA, 277(7), 553–559. https://doi.org/10.1001/jama.1997.03540310051034

Makary, M. A., & Daniel, M. (2016). Medical error—The third leading cause of death in the US. BMJ, 353, i2139. https://doi.org/10.1136/bmj.i2139

Manson, N. C. (2010). Transitioning from informed consent to shared decision-making. The American Journal of Bioethics, 10(12), 26–28. https://doi.org/10.1080/15265160903439971

Naik, N., Hameed, B. M. Z., Shetty, D. K., Swain, D., Shah, M., Paul, R., Aggarwal, K., Ibrahim, S., Patil, V., Smriti, K., Shetty, S., Rai, B. P., Chlosta, P., & Somani, B. K. (2022). Legal and ethical consideration in artificial intelligence in healthcare: Who takes responsibility? Frontiers in Surgery, 9, Article 862322. https://doi.org/10.3389/fsurg.2022.862322

Obermeyer, Z., & Emanuel, E. J. (2016). Predicting the future—Big data, machine learning, and clinical medicine. New England Journal of Medicine, 375(13), 1216–1219. https://doi.org/10.1056/NEJMp1606181

O’Sullivan, S., Nevejans, N., Allen, C., Blyth, A., Leonard, S., Pagallo, U., Holzinger, K., Holzinger, A., Sajid, M. I., & Ashrafian, H. (2019). Legal, regulatory, and ethical frameworks for development of standards in artificial intelligence (AI) and autonomous robotic surgery. The International Journal of Medical Robotics and Computer Assisted Surgery, 15(1), Article e1968. https://doi.org/10.1002/rcs.1968

Polit, D. F., & Beck, C. T. (2021). Nursing research: Generating and assessing evidence for nursing practice (11th ed.). Wolters Kluwer.

Price, W. N., & Cohen, I. G. (2019). Privacy in the age of medical big data. Nature Medicine, 25(1), 37–43. https://doi.org/10.1038/s41591-018-0272-7

Sousa Antunes, H., Freitas, P. M., Oliveira, A. L., Martins Pereira, C., Vaz de Sequeira, E., & Barreto Xavier, L. (Eds.). (2023). Multidisciplinary perspectives on artificial intelligence and the law. Springer Nature. https://doi.org/10.1007/978-3-031-41264-6

Schulz, P. J., & Nakamoto, K. (2013). Health literacy and patient empowerment in health communication: The importance of separating conjoined twins. Patient Education and Counseling, 90(1), 4–11. https://doi.org/10.1016/j.pec.2012.09.006

Verghese, A., Shah, N. H., & Harrington, R. A. (2018). What this computer needs is a physician: Humanism and artificial intelligence. JAMA, 319(1), 19–20. https://doi.org/10.1001/jama.2017.19198