IDEAS home Printed from https://ideas.repec.org/a/gam/jijerp/v17y2020i22p8353-d443507.html
   My bibliography  Save this article

INFERENCE: An Evidence-Based Approach for Medicolegal Causal Analyses

Author

Listed:
  • Putri Dianita Ika Meilia

    (Care and Public Health Research Institute (CAPHRI), Faculty of Health, Medicine and Life Sciences, Maastricht University Medical Center+, Universiteitssingel 40, 6229 ER Maastricht, The Netherlands)

  • Maurice P. Zeegers

    (Care and Public Health Research Institute (CAPHRI), Faculty of Health, Medicine and Life Sciences, Maastricht University Medical Center+, Universiteitssingel 40, 6229 ER Maastricht, The Netherlands)

  • Herkutanto

    (Department of Forensic Medicine and Medicolegal Studies, Faculty of Medicine, University of Indonesia, Jl. Salemba Raya No. 4, Salemba, Jakarta Pusat 10430, Indonesia)

  • Michael Freeman

    (Care and Public Health Research Institute (CAPHRI), Faculty of Health, Medicine and Life Sciences, Maastricht University Medical Center+, Universiteitssingel 40, 6229 ER Maastricht, The Netherlands)

Abstract

A fundamental purpose of forensic medical, or medicolegal, analysis is to provide legal factfinders with an opinion regarding the causal relationship between an alleged unlawful or negligent action and a medically observed adverse outcome, which is needed to establish legal liability. At present, there are no universally established standards for medicolegal causal analysis, although several different approaches to causation exist, with varying strengths and weaknesses and degrees of practical utility. These approaches can be categorized as intuitive or probabilistic, which are distributed along a spectrum of increasing case complexity. This paper proposes a systematic approach to evidence-based assessment of causation in forensic medicine, called the INtegration of Forensic Epidemiology and the Rigorous EvaluatioN of Causation Elements (INFERENCE) approach. The INFERENCE approach is an evolution of existing causal analysis methods and consists of a stepwise method of increasing complexity. We aimed to develop a probabilistic causal analysis approach that (1) fits the needs of legal factfinders who require an estimate of the probability of causation, and (2) is still sufficiently straightforward to be applied in real-world forensic medical practice. As the INFERENCE approach is most relevant in complex cases, we also propose a process for selecting the most appropriate causal analysis method for any given case. The goal of this approach is to improve the reproducibility and transparency of causal analyses, which will promote evidence-based practice and quality assurance in forensic medicine, resulting in expert opinions that are reliable and objective in legal proceedings.

Suggested Citation

  • Putri Dianita Ika Meilia & Maurice P. Zeegers & Herkutanto & Michael Freeman, 2020. "INFERENCE: An Evidence-Based Approach for Medicolegal Causal Analyses," IJERPH, MDPI, vol. 17(22), pages 1-16, November.
  • Handle: RePEc:gam:jijerp:v:17:y:2020:i:22:p:8353-:d:443507
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1660-4601/17/22/8353/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1660-4601/17/22/8353/
    Download Restriction: no
    ---><---

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Michael D. Freeman, 2021. "Principles and Methods for Evidence-Based Quantification of the Effect of Seat Belt Non-Use in Crash-Related Litigation," IJERPH, MDPI, vol. 18(18), pages 1-14, September.
    2. Putri Dianita Ika Meilia & Maurice P. Zeegers & Herkutanto & Michael D. Freeman, 2021. "Medicolegal Causation Investigation of Bacterial Endocarditis Associated with an Oral Surgery Practice Using the INFERENCE Approach," IJERPH, MDPI, vol. 18(14), pages 1-9, July.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jijerp:v:17:y:2020:i:22:p:8353-:d:443507. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.